gis for environmental problem solving

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Home > Books > Sustainable Development - Authoritative and Leading Edge Content for Environmental Management

GIS for Environmental Problem Solving

Submitted: 14 December 2011 Published: 01 August 2012

DOI: 10.5772/50098

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Sustainable Development - Authoritative and Leading Edge Content for Environmental Management

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Author Information

Koushen douglas loh.

Department of Ecosystem Science and Management, Texas A&M University, USA

Sasathorn Tapaneeyakul

*Address all correspondence to:

1. Introduction

The authors are affiliated with the Laboratory of Systems Technology Applications in Renewable Resources (The STARR LAB) at Texas A&M University. The purpose of this chapter is to provide a synopsis of the cumulative research and teaching work for the past twenty years from the STARR LAB. The aim of chapter is to demonstrate holistic understandings of what key environmental issues and problems people are facing and how their concerns may be addressed with the help of geographic information systems (GIS).

We are the environments, and the environments are us. There are many environmental issues and problems the society is facing. Some major categories include environmental disasters, ecological services, and perceptions of environments by people, just to name a few. In terms of environmental disasters, hurricanes, earthquake and wildfires are some examples that exert enormous direct impacts on people’s lives. Their increasing recurrences have elevated public awareness on the vulnerability and risks of the environments we live in. An awareness of environmental issues leads to an increase in people’s perceptions regarding the surrounding environments. There are many factors contributing to such perceptions. Combined considerations of pertinent factors result in an overall perception. One plausible combined index is called quality of life (QOL). QOL is a practical measurement of the state of an environment. Environmental awareness also raises people’s concerns on the sustainability of the ecological services. Ecological services refer to public goods, tangible or intangible, rendered to us by environments and ecosystems. Air, water, food, fiber, and fuel we consume are good examples. Sustaining these services is of great importance to all environmental stakeholders.

There are many ways to help stakeholders gain insights to environmental issues and problems. One handy approach is the use of GIS. GIS are systems of hardware, software, data, people, organizations and institutional arrangements for collecting, storing, analyzing and disseminating information about areas of the Earth [ 1 ]. Such technologies enable analyses of spatial-temporal patterns for a geographic span of interest and generations of easy-to-comprehend reports such as maps and images. GIS are maturing and proliferating rapidly in parallel to the quantum leap of personal computer (PC) platforms. It greatly enhances people’s ability to know about their environments. Given the advantages, GIS have emerged as a popular subject matter among interested learners on college campuses as well as in environmental fields. A good indicator of this assertion is the sustaining popularity of Environmental GIS courses the authors teach at Texas A&M University. Other institutions are reporting a similar phenomenon.

All things considered, it is timely to provide a rundown of GIS for Environmental Problem-Solving as a chapter of this book. Main thrusts of our presentation consist of four parts. They are: 1) Introduction (this section); 2) Research method; 3) Illustrations of GIS for environmental problem solving applications; and 4) Concluding remarks.

2. Research method

Systems approach is a key research method to incorporate GIS into problem-solving process in addressing environmental issues and problems. The essence of this approach is to envision and to enact relevant endeavors into a cohesive sequence of steps. The whole process is called developing and implementing a GIS project. A typical sequence of steps in a GIS project includes framing the problem, defining a project area, identifying and acquiring data, extracting and preparing data, editing spatial data, geospatial analysis, and generating maps and reports.

2.1. Framing the problem

The first step in solving any problem is to frame the problem. The purpose of this step is to help narrow down the scope and identify the problem to make it easier to solve. This helps address the questions you want to answer. Specifically, what do you want to accomplish from looking at this problem? What are the goal and objectives you are planning to address from the problem?

Then, the next question is what is the potential information associated with the problem? Pertinent information includes:

Scope: To lay out tasks, data, and time frame to solve a problem, a scope needs to be defined so that you know how much information you are dealing with. The scope varies depending upon the nature and objectives of the problem. Questions on whether the problem is looking at a specific region, a particular group of population, or a particular phenomenon are worth investigating. Also, is the problem asking for information, maps, or more in-depth analysis of the problem?

Scale: Is the problem focusing on an institutional scale (individual, family, municipal, state, national, or international) and/or ecological scale (plant, plot, ecosystem, landscape, biome, or global)? As addressed in [ 2 ], stakeholders at different spatial scales can (and should) assign different values to environment and ecosystem under interest.

Type of information: two distinctive types of information are quantitative and qualitative. You need to specify if the problem is looking for quantitative and/or qualitative information. Quantitative information focuses on some sort of value or measurable information. Number of population affected by a hurricane or the amount of oil spilled into an ocean are quantifiable. Qualitative information, on the other hand, represents some sort of status that needs to be stated. Wildlife species affected by a hurricane or types of chemical released into a river are some of the examples.

It is also helpful to construct an outline or diagram of the problem so that it is easy for you and/or stakeholders to determine necessary steps, to better organize the tasks, and to be able to comprehend the problem at hand.

Consider the following real world examples using the above criteria:

Example 1: The 2005 Hurricane Katrina

The scope is the Hurricane Katrina in New Orleans, Louisiana. This pertains to the Greater New Orleans Region. Information of interest includes population affected, infrastructural damage, hazardous materials, and situations that might arise afterward. Given this information, one possible answer is the number of population affected as the quantitative information. Quantitative information includes, but not limited to, current stage of hazardous waste, groups of population, animal species, and housing.

Example 2: Bastrop County Complex Fire

The scope is a major wildfire in Bastrop County, Texas in 2011. Information of interest is effects on both human and animal, economics losses, effects on land and environments, and infrastructural damage. With the defined information, possible answers include the number of affected people and animals, income losses from the incident, and the loss of species’ habitats, which are accounted as quantitative information. Households and habitats affected by the fire, problem of land degradation and fragmentation, time frame for recovering, and preventive plans are some of the qualitative information that seeks answers.

Example 3: West Nile Virus in Brazos County

Brazos County, Texas and the surrounding areas is the scope of interest. Became widespread in the recent years (with the highest number of 7 severe cases in human being accounted for in 2006 [ 3 ]), West Nile virus has been under surveillance for residents in the County. Critical information that needs to be asked include: What causes the West Nile virus?; How can you track the spread of the West Nile virus?; and Where has West Nile virus been found in this location? Quantitative answers are the current number of infected individuals and the past records. Possible locations and trends that may be associated with the spread of the West Nile virus serve as the qualitative answer to the problem.

2.2. Defining a project area

With an identified problem, you can proceed to define a project area. This step delineates a confined boundary of an area of interest. The information from Step 2.1 helps specify the proper location where the problem occurred and address the possible questions and answers under interest. The process pinpoints the focus of the problem while eliminate unnecessary areas or secondary scope of interest from the picture. Not only that this can help save time, but it also allows you to pay closer attention to the essence of the project. At this stage, the conceptual project area should be carefully thought out before attempting to acquire data, i.e., map layers, in the next step.

ArcGIS is a registered trade mark of Environmental System Research Institute (ESRI), Inc.

For example, one may select an administrative boundary of a local jurisdiction from a base map layer as the project area as in the cases of Bastrop County Complex Fire and West Nile Virus in Brazos County. One may also “union” multiple local jurisdictions into a broader geographic span for addressing issues that are of cross-boundary nature. The project boundary resulted from one way or another serves as the “cookie cutter” for clipping data from relevant layers and tables in the ensuing steps to expedite problem-solving. As in the case of Hurricane Katrina, at least five parishes (Louisiana’s equivalent of counties in other states) should be included as the project area of the Hurricane analysis.

2.3. Identifying and acquiring data

Once the project area is defined, the next step is to locate and acquire needed data. Before looking for data, the methodology needs to be analyzed to establish what data is needed. The most important question that needs to be answered is: Why do I need this data? If the data is truly needed, then this question is easily answered. If not, then the data is most likely not necessary to solve the problem.

To be able to work with data in GIS, you need to understand the nature and procedural steps of working with data in GIS as follows:

2.3.1. GIS datasets formats

Typical formats of datasets, which allow you to conveniently work with multiple information or map layers, include spatial and attribute data.

Spatial data comes in the forms of raster and vector and is generally organized into so-called layers or thematic maps.

Raster data is digital image composed by rectangular grids or cells that contain numeric information from a defined range to characterize geographic features. Digital Elevation Model or DEM is a form of raster data important in depicting a terrain. It provides crucial information on the topologies of a geographic span.

Vector or shapefile data is constructed as points, lines, and polygons to represent geographical features.

Attribute data is information used to describe characteristics of a locale. The data is organized in a table containing information linked to a spatial feature by a common identifier. This gives you details or certain types of information associated with each specific feature.

2.3.2. GIS data sources

See http://geo.data.gov/geoportal/ for more information.
See http://www.tnris.org/get-data/ for more information.

2.3.3. Map projections and coordinate systems

Each map layer contains a coordinate system, which allows one to identify the location of the map and to be able to display, manipulate, and integrate the map layer with other layers for further applications and analysis. It is therefore imperative to understand the fundamentals of map projections and coordinate systems.

A coordinate system is a grid that may be used to define where a particular location is. Two common types of coordinate system are:

Geographic Coordinate System: This uses 3D spherical surface to define locations. Often incorrectly referred to as datum, geographic coordinate system includes not only datum, but also angular unit of measure and prime meridian. Points on Earth’s surface are referenced by latitude and longitude, while angles are measured by degree.

Projected Coordinate System: Commonly referred to as map projections, projected coordinate system is defined on flat, 2D surface with constant lengths, angles, and area. X, Y coordinates are presented on grid. It is based on geographic coordinate system.

See [ 4 ] for further explanations on coordinate systems

2.4. Extracting and manipulating data

The fourth step is data extraction and manipulation. In this step, one is to extract data from a conceivably larger original source file. Reduction of the size of datasets and their consolidation expedite the ensuing data management and processing. The project area defined at the onset (the cookie cutter) dictates the extent and size of data to be extracted and prepared.

Typically, data acquired may exist in various forms and shapes, e.g. different coordinate systems and file formats. It is a MUST to prepare and consolidate all datasets into a commonly operable format. GIS have a database management system component to support the proper management of both spatial and attribute data. It also enables convenient linking and relating of various data records by their locations on a common coordinate system. Some common tasks you will encounter during the data extraction and manipulation steps are as follows:

Re-projecting data: This is a basic essential step in any analysis using GIS. The purpose is to convert a particular piece of data from one coordinate system to another. Working with GIS employs more than one map layer, therefore acquired datasets may contain different projections. Different data projections lead to distortion of data and inaccuracy in the analysis.

For example, in Figure 1 , a residential area polygon (in blue) is projected to Geographic Coordinate System: GCS_North_American_1983. The same residential area polygon (in yellow) is in Projected Coordinate System: NAD_1927_UTM_Zone_16N. As shown in Figure, there are some discrepancies in the map layers with different coordinate systems. If this re-projection step is not taken, any analysis preformed will be inaccurate leading to much larger problem in subsequent analysis with multiple layers.

Conversion of raster to vector: Not only data comes in different coordinate systems, the file formats can also be varied; most commonly in the forms of raster or vector (shapefile). Especially with the growing use of GIS, datasets in shapefile have become more available. Shapefile data usually comes embedded with attribute data, which allows user to easily select and manipulate the information of interest. Therefore, converting a raster file to vector enables user to intersect other data with the available vector data. Suppose you have acquired and managed shapefile layers of affected area by Hurricane Katrina and population layer in the Greater New Orleans Region, by intersecting these two layers, you can extract the areas in which population were affected by the Hurricane.

Reclassification: To extract specific data from a raster, i.e., specific elevation data, reclassification is performed. Given the Hurricane problem, flooding can be assessed as one major result of the incident. In order to extract only the flooded area resulted from the Hurricane, reclassification is utilized to distinguish a specific range of elevation in which flooding occurred from others. This will allow you to analyze the effects pertaining to the flooded area.

Selecting by attributes: The purpose is to extract desired attribute data for analysis. This can be done through conditional statement imposed in attribute data table to select only specific information of interest. Considering an attribute table of chemical sites located within the Hurricane flooding zone, one can select only specific sites containing particular chemicals of interest for further analysis and map report.

Exporting data: To make a temporary layer permanent in a current map, data resulted from steps such as that of above need to be exported and saved in a current working folder. Otherwise, the file may be lost or difficult to locate when you want to revisit and work on it.

Same layer file with different coordinate systems resulting in 20-meter difference on the map.

2.5. Editing spatial data

Oftentimes, acquired data might not be in the most suitable shape or boundary for problem under consideration. Options to edit spatial data in GIS allow one to manage the data in such a way that is more manageable and ready to be analyzed.

Typical editing tools consist of creating new features, cutting polygons, modifying features, and extending the basic skills to other tasks such as clipping a feature to a desired shape and area.

Creating new features: When creating a new feature, a blank data set is being defined by the editor. A blank data set is like an empty pie shell, while creating a new feature is like filling the pie shell. This task is only used if a new feature is desired or a single part feature is to be converted into a multi-part feature when the second part of the feature does not already exist.

Cutting polygon features: This process is a shortcut to creating a multi-part feature from a single part feature. Simply put, this process is used like a set of scissors to cut an existing feature into multiple parts.

Modifying features: This task is used when an existing feature does not cover the area that is desired. The attribute data will remain the same, while the feature will be modified to suit one’s need.

Clipping features: Clipping is a process that is like using a “cookie cutter” to remove a portion of a feature permanently. The attribute data will also be changed due to a permanent removal of the feature.

2.6. Geospatial analysis

Upon data readiness, a project may move on to the sixth step of spatial-temporal analyses. There are many useful procedures for these endeavors. Especially with the versatilities of GIS software, one can utilize extended range of applications available. Some common tools that one should be familiar with and were used specifically for the ensuing applications in this chapter include:

Distance analysis: A suite of tools to produce distance maps are commonly available in GIS. In ArcGIS, distance tools are available under Spatial Analyst option. Euclidean distance tool measures straight-line distance from the center of cell to the nearest object of interest, i.e., your source. Another alternative is the cost distance tool, which incorporates travel cost from different paths into the analysis. The products from these tools are distance maps in raster representing proximity maps with a range of distance values from the source. For instance, one can find proximities from pollution sources at defined interval to any locales within a defined area map.

Map algebra: Another useful application, which you will encounter at certain point of analysis, is map algebra. This can be used for computations of raster data to create spatial patterns that depict locales of a particular concern or interest. Raster calculator, a Spatial Analyst application, allows for this useful procedure by inputting specified mathematical functions and expressions in the calculator. The result will be raster values and layer corresponding to the specified function.

The use of analytic procedures mentioned above and other tools in a proper order results in useful information for a problem under study.

2.7. Generating maps and reports

The final major step is to generate maps and reports. One picture is better than a thousand words. To this end, GIS come handy in presenting information in maps, images, 3D graphs, tables, and other forms. It also expedites the import and export of these presentations between GIS and other software environments, e.g. a word or a graphic processor. With the acceleration of PC powers, the sky is the limit to GIS’ capability of generating maps and reports. It is worth noting that you should understand what the readers are looking for when creating the maps and write ups, i.e., what is the focus or message that you want to communicate to others? This should align with the proposed information of interest.

Diagram of problem-solving steps

3. Illustration of GIS for environmental problem solving applications

To illustrate how GIS are used to help address environmental issues and problems, two cases are described herewith in this section. The first one is on flood assessment, and the second is a QOL analysis. The applications help prepare for the building framework of spatial appraisal and valuation of environment and ecosystems (SAVEE), which will be discussed in the following section, tremendously.

3.1. Flood assessment

Considered one of the costliest [ 5 ] and most destructive natural disasters in the history of the United States, Hurricane Katrina provides a number of opportunity to understand the risk of nature, and how one could expect to understand and learn from such disastrous effects. The aforementioned problem-solving steps allow us to contemplate the steps as follows:

Step 1: Framing the problem

An analysis of the scenario indicated that Hurricane Katrina occurred in the Greater New Orleans Area. Field measurements and distributions on the majority of victims indicated that roughly those under 1 meter in elevation were initially affected by the flooding [ 6 ]. Given this information, the scenario was that every location below 1 meter in elevation was affected and any location that is above this level was unaffected by the flood water. This particular area of impact needed to be delineated. The information of interest included area and population affected by the Hurricane. Additional scenarios of water-rise were then set for 5, 10, and 15 meters to emulate different levels of flooding.

Step 2: Defining the project area

In this case, the City of New Orleans and its five neighboring parishes suffered by the storm were identified as the study area.

Step 3: Identifying and acquiring data

The best type of data for delineating the affected area is the elevation data (DEM). DEMs, Satellite Imagery, and Census datasets were collected from Atlas, the GIS data central from the State of Louisiana [ 7 ]. This included DEM, jurisdiction boundaries, street maps of the study area, and Census data.

Step 4: Extracting and preparing data

Initially, the DEM and Census data came projected as GCS_North_American_1983. By assigning a projected coordinate system to the data, further analysis could be proceeded. Given the information, we projected the data to NAD_1927_UTM_Zone_16N. Hillshades of the DEMs were also generated to visually inspect different elevations in the data. Sink holes pervaded in the DEMs were also been filled to prevent erroneous and prepare for proper flow direction process.

Then, the second crucial step was to extract the flooded area from the total area. This employed the reclassification process in which the elevation value was changed to 1 meter to separate the flooded area from the non-flooded area (elevation above 1 meter). In short, the reclassification divided the elevation data into the flooded area and the non-flooded area. The rest of the water-rise scenarios then followed using the same reclassification step as well as the ensuing steps.

Next, this flooded elevation data was converted into vector to prepare for further analysis. The converted flooded layer was the result of the conversion process as well as exporting the data into a new permanent flooded area layer.

In terms of the Census data, the parishes were merged into one layer so that it was more convenient to work with in the subsequent steps for analyzing the total effect on population.

Step 5: Editing spatial data

The acquired data contained certain parts that were irrelevant to the analysis. Lake Ponchartran, for instance, should not be counted toward the flooded area. Therefore, by editing the data, some unnecessary information of interest were taken out. Pertinent steps of editing the lake included: 1) Creating a new blank shapefile; 2) Using the blank shapefile as the base for editing tools to create a new feature around the lake area; and 3) Using the newly created feature as a cookie cutter to clip off the lake area from the flooded area layer. The result was the flooded area without the lake that was ready to be incorporated into other analysis.

Step 6: Geospatial analysis

At this stage, socio-economic analyses were conducted to assess the damage and impact on the livelihoods of residents of the affected areas. Census data developed was used directly for this purpose. Combining census data with the emulated flooded areas, patterns of suffering by which racial stakeholders and by what economic classes were clearly displayed.

Based on the flooded area layer in Step 5 , we proceeded to calculate the area under the layer’s attribute table. Visual Basic Code to calculate the area (available from [ 8 ]) or a Calculate Geometry option, an automated tool in ArcGIS, derived the numbers of area affected by the Hurricane. Mathematical formula imposed helped convert the numbers into desirable units such as acres.

Benefited from the above numbers, the population affected was conveniently calculated. Census data contains racial information that represents groups of population in different parishes. By intersecting the flooded area layer with the merged parishes layer, representing population profile in the areas, affected population was extracted. The overall statistics in the attribute table identified the total population affected by the flooding. Figure 3 demonstrates map layers resulting from the above problem-solving steps.

Step 7: Generating maps and report

Upon generating desired information and analysis, each pertinent map was composed as a map report containing a map title, legend (showing values of the map layer), north arrow, and scale bar. Then, the map reports were exported as image files to be included in a report. The report addressed the finding results of effects from the Hurricane as illustrated by the maps and relevant discussions of further applications and analysis that can later be applied based on this project.

Illustrations of selected problem-solving steps for flood assessment in reference to the 2005 Hurricane Katrina flooding in the Greater New Orleans Region.

3.2. Quality of life assessment

QOL is emerging as a major indicator to monitor citizen’s livelihood and wellbeing at the grassroots level. By virtue of its focuses, QOL helps inform local people and organizations of their living environment and optimize the allocations of resources to improve the community development. Canada is perhaps more aggressive in setting up a national framework for QOL [ 9 ]. In the U.S., states such as Utah [ 10 ]; cities such as San Francisco, California [ 11 ]; and organizations, including nonprofit organizations such as the Quality of Life Foundation [ 12 ] have been vigorously promoting such term as one of their agendas.

Categories of data to support the development of QOL indicators range from education, environment, economics, social, and justice to transportation/mobility. However, the use of GIS to track QOL progress is still at its infancy stage. City of College Station, Texas, with its advanced GIS installation and rich collection of data, stands to gain a lead role in this area and to provide even superior services to its residents when it embarks on this path.

There are three issues and opportunities in the development of QOL indicators. They are:

Combining subjective values with objective measurements to create consensus and develop common ground to accommodate multiple perspectives of stakeholders.

Combining the use of both spatial and attribute information to develop base layer and indices in environment, crimes, recreation, etc. For example:

Overlay of census blocks with subdivisions or other neighborhood entities (e.g. apartment complex) to establish the baseline reference (population, its composition, income level, education level, and number of household of an entity)

Overlay of crime type, frequency, and location data with entities on the base layer

Developing a composite score (ranking) of QOL for each neighborhood entity on the base layer

As you set forth to do your research, as in the case of QOL assessment, you are most likely facing with three puzzling situations:

1. Pertinent data/information comes in a variety of forms

It is plausible that the data/information you are facing and plan to collect exists in at least two forms. They are categorical and numeric. Examples of categorical information include “Yes” or “No” on whether a city (or any local jurisdiction) has a neighborhood improvement in place or not program; “Very Good,” “Good,” “Fair,” and “Bad” on how such a program is being regarded by the communities; and “Highly favorable,” “Favorable,” and “Least Favorable” on how service rendered by the program is perceived by the beneficiaries.

Quite often, information of categorical nature is derived from one’s “gut feeling.” It may also be convenient to summarize some judgments based on historical data, on some kinds of trends, or on some opinion surveys/polls.

There are two types of numeric information: discrete and continuous. Population of an ethnic group residing in a particular Census unit is an example of discrete type. Example of continuous type is the percentage of an ethnic group versus the total population in such a unit.

2.How to “add” “oranges” and “apples”

When one has data and information of various types in hand, he/she will ask this question:

“How do I add them together?” Indeed, you cannot add oranges and apples together at their original forms. The trick is to convert and normalize all of them into the same numerical scale, say between -1 and +1.

So, what is normalization? Normalization is the act of taking many sets of data that have no clear correlation and placing them under the same quantitative scale. Essentially, normalization allows us to compare apples and oranges. Some decisions must be made prior to normalizing any type of data. The questions include:

What are the important factors?

Which factors are positive and which factors are negative?

How much should each of these factors count in relation to the overall project?

For categorical type of information, what you do is to fix the “best” and the “worst” at +1 and -1 respectively. This is plausible as +1 can represent the best case and -1 the worst. When both ends are fixed, one may logically deduce that a numeric value of “0” represents “Inconclusive.” Furthermore, one may come up with a scheme saying that “+0.25” is “somewhat better”, “+0.5” is “better” and “+0.75” is “much better.” One can also say that “-0.25” is “somewhat worse”, “-0.5” is “worse”, and “-0.75” is “much worse.” As a result, you are converting and normalizing categorical or qualitative data into numeric or quantitative information as illustrated in Figure 4 .

Illustration of the qualitative – quantitative information conversion scheme.

For numeric information, the conversion and normalization is less complicated. Say you deem the ratio of white population in a Census unit at 50% is the best mix (most favorable), in terms of quality of life; 100% or 0% is least favorable. For the best mix, you believe it should be given a score of +1 and for the least favorable a 0. Given this range, you may apply the following equations to convert and normalize the percentage into values in the range (0,+1)

where E is the expected (best value of x)

Another method is to convert distance to an object from such measurements as miles to the uniform score between (-1 and +1). For example, one may decide that the presence of oil well is bad for quality of life. Evidently, the household right at the oil well would have absolutely unfavorable score of -1. The negative effect most likely would tap off as the distance reaches certain threshold, e.g. 1 mile or 5,280 feet. The tapering effect can then be described by a negative exponential equation as:

where x is the distance to oil well(s)

The normalization equation for strictly negative attribute based on the negative exponential equation above becomes:

The translation of the equation is “If Condition < X, True, False.” This means if an input value (distance value) falls under the condition (less than X), then the output is negative value. Otherwise, the output is zero. It might be helpful to put this in the oil well scenario above:

The above equation is set so that if the distance to an oil well is less than 1 mile, then the output is negative. As the locales get closer to the actual oil wells path, the more negative they will become (with the minimum at -1). At a distance of 1 mile or greater all the output values are set to zero as shown in Figure 5 .

Negative decay graph showing the more negative values as the locales get closer to oil wells.

At any rate, once you have all factors converted and normalized into the scheme of (-1, +1), then the values can be “operated” on to add up their contributions to the overall quality of life assessment of a city. This is done by applying the following formula:

The method is derived from an expert system algorithm called Emycin [ 13 ]. The operations utilize map algebra calculation to integrate two values at a time, i.e., pair-wise calculation, while avoiding the problem of double-counting. The calculations are performed iteratively until all normalized layers are exhausted. As illustrated in Figure 6 , the operation calculates the values of two attributes at a time to derive the final score, which is the integration of the values in all attributes. Through fuzzy logic operations, two QOLs (different factor contributing to QOL) can be integrated at a time until all QOLs are exhausted. Iteration 1 integrates QOL 1 and QOL 2 so that only the overlapping portion of both factors values remains. By taking this portion to integrate with another QOL, QOL 3 , the final result is the overlapping portion among three factors; QOL 1 , QOL 2 , and QOL 3 .The results can be color-coded as a gradient map of integrated and locale-specific QOL in the range of (-1, +1).

The nicety of the Emycin formula is that:

Regardless of the number of factors being used, you always “operate” on two of them in each iteration. This is called pair-wise calculation.

Depending on the score values of the two factors, there will be only one of the equations that is applicable.

Unlike many “ordinary” algorithms, this formula allows both positive and negative contributions from factors under considerations, which is more realistic.

Regardless of the number of factors being considered and operated on, the resulted score will always be bounded between -1 and +1.

Regardless of the sequence each factor is put into pair-wise calculation, the result is always the same.

Once all factors are exhausted in the calculation, one can always convert the result back to the qualitative scheme to make it more comprehensive to lay persons or people one intend to interpret the results to.

A word of caution: Both -1 and +1 are “singular” points. In other words, if you come up with a score on the contribution of a factor to be either -1 or +1, then other factors’ contributions will not matter anymore. This is not a surprise or unreasonable. Because -1 means absolutely “bad” and +1 means absolutely “good.” When you have a factor that determines the quality of life to be absolutely bad, then indeed why bother to waste time to assess other factors?

To this end, one may want to adjust or shift the score from a factor that is somewhat different from the absolute values of -1 or +1 so that the pair-wise calculation may proceed logically. Again, this is not unreasonable as there is hardly anything that one can claim that is absolutely good or bad.

Illustration of pair-wise calculations.

3. Incomplete information

An additional nicety to the above approach is that one can proceed to conduct studies under incomplete information. The condition of incomplete information actually happens quite often in real life. With the kind of flexibility boasted by Emycin, you “add” the contributions from whatever data you are able to get your hand on for a city in determining its quality of life. In the case of comparing multiple cities, you may get this and that for one jurisdiction while not the same categories for all of them. By nature of the conversion, normalization, and pair-wise calculation, you would be able to derive scores on the same scheme and will be able to make comparisons.

With better understanding on the assessment framework, it is time to put such theory into real application.

The information of interest for this case is the factors contributing to the QOL of a city/community. Relevant questions include:

What defines a high quality of life?: This depends on who the target audience is: elderly community, students, or married couples.

What factors can contribute to the QOL?:

Distance to: hospitals, schools, university, parks, landfill, oil wells, etc.

Census Data Analysis: racial mix, relative income of a population, and number of children per household

In the case of the QOL assessment, the project area was the City of College Station, Texas.

Step 3: Identify and acquiring data

Acquiring data from the City’s GIS Department is crucial. From the rich collection of datasets rendered by the City [ 14 ], a number of data layers were selected for the ensuing analysis endeavor. They included census data, roads and streets, railroads, parks and green spaces, residence subdivisions, landfills, oil wells, schools, hospitals, flood plains, crime statistics, and many more.

DEMs for College Station were acquired and converted into raster. This represented the base map of College Station for the following steps. Selecting only the areas pertaining to College Station attribute was also another important preparation step since we were looking at the QOL in College Station and nothing else.

Basemap that contains areas beyond College Station were clipped off, and only the College Station boundary was left for the analysis.

Based on the identified QOL factors, proximities to parks, green spaces, schools, hospitals, and some other geographic features were regarded as positive contributing factors. On the other hand, closeness to such factors as landfills, oil wells, railroads, crime occurrences, and flood plains were considered to have negative impacts. The contributions of these factors, positive or negative, were mathematically formulated as distance functions from objects on corresponding data layers. In the ensuing steps, proximity maps encoded with distance functions were generated. The results from each factor layer were then combined with fuzzy logic calculation to form an integrated index between (-1, 1). Any number greater than 0 indicated a good QOL with anything below 0 representing bad index. The index was coded in a color scheme with a gradient from red to green. The color-coded QOL maps displayed clearly the patterns of QOL of the City at every specific neighborhood and locale.

To better illustrate this, four QOL factors, QOL 1 , QOL 2 , QOL 3 , and QOL 4 , were used as an example for the calculation (see Figure 7) . The first fuzzy operation employed two QOLs, QOL 1 and QOL 2 , to derive QOL 12 . The locales within defined proximity to QOL 1 were color-coded in green representing high QOL with the values approaching 1. On the other hand, those in red represented low QOL with the values approaching -1. Next, QOL 12 was integrated with QOL 3 resulting in QOL 123 . The last operation was QOL 123 and QOL 4 as shown in the final integrated map of QOL 1234 . The map results in the color gradient reflecting more green in the portion where high QOLs overlap (in the middle of the map) while the outer portion becomes more yellow to orange as a result of integrated low QOLs.

At this stage, twenty sample residential addresses were selected and tabulated in a table. By linking this table to the Address Locator tool in ArcGIS, the residential addresses were shown as a point shapefile on the map. To pinpoint the QOL of each selected address, Identify Tool was used to indicate the QOL index associated with such address.

Map reports of this project were individually created to reflect normalized layer of each factor contributing to QOL. The normalized values (within -1 to 1 range) were shown in the legend to reflect the results from the analysis. The combined layers resulted from Emycin algorithms were exported into a group of combined layer of strictly positive factors, combined layer of strictly negative factors, and combined layer of the combination of positive and negative factors. The report concludes how QOL assessment was made possible with useful applications of GIS. Future development of applications from the QOL assessment such as the linkage to SAVEE framework was also discussed.

The QOL index illustrated in the above example sheds light on the shape of things to come with SAVEE. First of all, one may acquire the land price and/or real estate information from local authority of a jurisdiction. Using the SAVEE methodology, such information can be converted into the (0, 1) range for services provided by specific environments and ecosystems in an area. Similarly, the QOL index above may also be computed in the same range. Spatial statistical analyses can then be conducted to determine correlation between land prices and QOL. Useful information may be thus generated to pave way for “spatial acres of an environment or ecosystem”.

4. Concluding remarks

The chapter depicts the natures and categories of environmental issues people are facing and how GIS can be deployed to help address them. In the context of environmental problem-solving, the systems approach for applying GIS is presented; and a few practical cases are illustrated. This organization casts a holistic view for readers to gain better comprehension of the subject matter.

Iteration of map algebra to incorporate fuzzy logic to compute contributions of relevant factors to locale-specific QOL in College Station, Texas.

Problem-solving starts with shaping a mental model on to formulate a solution to the issue at hand. Steps of the solution process are then implemented through the use of appropriate data and tools enabled by GIS. Skills and knowledge to facilitate these endeavors can be best advanced by hands-on practices. For this purpose, interested readers may access the full set of documentation of learning modules at http://starr.tamu.edu/gis2012a/. The materials are from a senior course the authors teach at Texas A&M University. It bears the same title as this chapter, “GIS for Environmental Problem-Solving.” First conceived in the 1990s, the course has gained and maintained its popularity among the student bodies. The learning modules include well-organized step-by-step instructions of applications in ArcGIS presented in this chapter. Being offered online since 2006, this course has proven to be easy yet comprehensive for self-learning, even among students with no prior GIS background.

It is worthwhile mentioning that the approach mentioned above is for a typical GIS project for environment. There is, however, usually one step short. That is asserting monetary values associated with the environment. This issue is emerging as a priority matter in the environmental research community. For example, the monetary losses from the BP Oil Spill in the Gulf of Mexico are yet to be more plausibly determined. Taking on this issue, the authors here at the STARR LAB are developing a new research methodology called Spatial Appraisal and Valuation of Environment and Ecosystems (SAVEE). The aim of this effort is to define “spatial acre” that attaches monetary values to a geographic span of interest.

One main thrust of SAVEE is to cross-reference economic development and ecological sustainability in the framework of Sustainable Development declared in the 1992 Earth Summit and being enhanced continuously ever since. Economic development is tangible and comes with a price tag. It is plausible to assume that the intensity of development of a locale of interest can be reflected in its real estate value, which is generally available. Sampling some locales of their real estate values leads to a price list of real estate values. This price list is then converted into a uniform range between 0 and 1, a well-behaved index representing the intensity of development of locales. On the other hand, ecological sustainability of an area of interest normally does not come with a price tag. However, one may systematically incorporate pertinent ecological services it renders into consideration and develop an index that has the same range of (0, 1). The numbers approaching 1 represent higher sustainability, and the opposites represent lower indices. On the basis of equitability between development and environment, the two index systems may then be mapped. The mapping leads to assigning monetary values associated with development sites to ecological locales with comparable index numbers.

Learning is a life-long process; so are the advances of knowledge and technologies. On the environmental GIS front, asserting monetary values to a system under study has become an imperative. The authors are hopeful that the general framework stipulated in SAVEE shall be advanced to explore this new territory. Only labeling it with dollar signs would make stakeholders appreciate more of our environment of its values. After all, without such dollar values, it is difficult for stakeholders and authorities to understand the magnitude of the environmental problems at hand. It is contended that SAVEE and other similar effort will make a significant contribution to environmental sectors in general and the advancement of GIS.

3. West Nile Virus Activity in Brazos County [Internet]. College Station (TX): AgriLIFE Extension; Agricultural and Environmental Safety; 2012 cited 2012 April 21]. Available from: http://www-aes.tamu.edu/public-health-vector-and-mosquito-control/brazos-county-mosquito-borne-disease-surveillance/west-nile-virus-activity-in-brazos-county/
4. Maling D.H 1991 Coordinate Systems and Map Projections for GIS. In: Maguire D.J, Goodchild M.F, Rhind D.W, editors. Geographical Information Systems: Principles and Applications. London: Longman Group UK. 1 135 146
5. Knabb R.D, Rhome J.R, Brown D.P 2006 Tropical Cyclone Report: Hurricane Katrina: 23 30 August 2005. National Hurricane Center.
7. Atlas: The Louisiana Statewide GIS [Internet]. Baton Rouge (LA): Louisiana State University CADGIS Research Laboratory; 2009 cited 2012 April 23]. Available from: http://atlas.lsu.edu/
8. ArcGIS Desktop 9.3 Help [Internet]. Redland (CA): Environmental Systems Research Institute; 2008 cited 2012 April 23]. Available from: http://webhelp.esri.com/arcgisdesktop/9.3/index.cfm?TopicName=Sample_VBA_code
9. Atlas of Canada Quality of Life [Internet]. Place unknown]: National Resources Canada; 2009 cited 2012 April 23]. Available from: http://atlas.nrcan.gc.ca/auth/english/maps/peopleandsociety/QOL
10. The Utah Foundation Quality of Life Index: First Biennial Survey Reveals Strengths, Weaknesses [Internet]. Salt Lake City (UT): Utah Foundation; 2011 cited 2012 April 27]. Available from: http://www.utahfoundation.org/img/pdfs/rr703.pdf
11. City and County of San Francisco as Successor to the Redevelopment Agency [Internet]. San Francisco: San Francisco Redevelopment Agency; 2012 cited 2012 April 27]. Available from: http://www.sfredevelopment.org/
12. The Quality of Life Foundation [Internet]. San Francisco: The Quality of Life Foundation; [Date unknown] [cited 2012 April 27]. Available from: http://www.qualityoflifefoundation.org/
14. GIS- Geographic Information Services [Internet]. College Station (TX): City of College Station GIS; 2001 cited 2012 April 29]. Available from: http://www.cstx.gov/index.aspx?page=3683
See [4] for further explanations on coordinate systems

© 2012 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution 3.0 License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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GIS for Environmental Applications - A Practical Approach

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Research output : Book/Report › Book › Other › peer-review

GIS (geographic information system)
Environmental Science
Remote sensing

This output contributes to the following UN Sustainable Development Goals (SDGs)

T1 - GIS for Environmental Applications - A Practical Approach

AU - Zhu, Xuan

PY - 2016/6

Y1 - 2016/6

N2 - GIS for Environmental Applications provides a practical introduction to the principles, methods, techniques and tools in GIS for spatial data management, analysis, modelling and visualisation, and their applications in environmental problem solving and decision making. It covers the fundamental concepts, principles and techniques in spatial data, spatial data management, spatial analysis and modelling, spatial visualisation, spatial interpolation, spatial statistics, and remote sensing data analysis, as well as demonstrates the typical environmental applications of GIS, including terrain analysis, hydrological modelling, land use analysis and modelling, ecological modelling, and ecosystem service valuation. Case studies are used in the text to contextualise these subjects in the real world, examples and detailed tutorials are provided in each chapter to show how the GIS techniques and tools introduced in the chapter can be implemented using ESRI ArcGIS (a popular GIS software system for environmental applications) and other third party extensions to ArcGIS to address.

AB - GIS for Environmental Applications provides a practical introduction to the principles, methods, techniques and tools in GIS for spatial data management, analysis, modelling and visualisation, and their applications in environmental problem solving and decision making. It covers the fundamental concepts, principles and techniques in spatial data, spatial data management, spatial analysis and modelling, spatial visualisation, spatial interpolation, spatial statistics, and remote sensing data analysis, as well as demonstrates the typical environmental applications of GIS, including terrain analysis, hydrological modelling, land use analysis and modelling, ecological modelling, and ecosystem service valuation. Case studies are used in the text to contextualise these subjects in the real world, examples and detailed tutorials are provided in each chapter to show how the GIS techniques and tools introduced in the chapter can be implemented using ESRI ArcGIS (a popular GIS software system for environmental applications) and other third party extensions to ArcGIS to address.

KW - GIS (geographic information system)

KW - Environmental Science

KW - Remote sensing

SN - 9780415829069

SN - 9780415829076

BT - GIS for Environmental Applications - A Practical Approach

PB - Routledge

CY - London and New York

Principles and Applications of Geographic Information Systems (GIS)

Use of GIS has seen unprecedented growth in the last ten years. With the powerful technology getting cheaper and system memories expanding, meaning that we can handle much bigger sets of data, some say that GIS is in a golden age. It was once the preserve of the cartographer - few outside would have used it or needed it, yet recently GIS has become a core part of modern environmental science degrees . Geology, climatology, geography, statisticians, archaeology, oceanography, conservation based qualification and most other environmental sciences (1) now offer a module at undergraduate level. In the last five years, most universities have offered masters degrees specifically in GIS, or post-graduate certificates and diplomas with a prerequisite of environmental undergraduate degree.

It is surprising to many that this technology has been around for over fifty years (2) because to people outside of the relevant fields, and to some within fields who are just starting to learn about applications and potential for their work, it is still relatively new and exciting with endless possibilities. GIS is something that will make many jobs easier and faster and allow them to do more things in the same space of time with the click of a button. No longer are maps the exclusive preserve of the cartographer, now urban and rural developers, medical resource planners, conservation professionals, environment agency staff (to track and measure floodplains and the spread of protected species) archaeologists and utilities providers are just some of the environmentalist careers that can benefit from digital mapping.

How Does GIS Work?

The questions in the previous section rely heavily on geographic data and it is estimated that the vast majority of data handled by computers these days has and requires specific geographic parameters (5). Taking the example of the two restaurants as a starting point, they may look at different data sets:

The fast food joint may look at maximising their catchment area and accessibility: they will look at busiest roads, the best junction to place at, close to leisure areas such as shopping malls or other non-exclusive entertainment issues - efficiency and maximisation of profit.
The exclusive restaurant will look primarily at desirability and facilities that best reflect their image. Even though they too will be concerned with maximising their profit, they are less concerned with numbers and more concerned with image. They may appear near other exclusive restaurants, near theatres and other high-class leisure facilities.

Both may use GIS to find the ideal location and can access any number of websites to collect relevant data for their business plan. This information makes it easier to manage what we know and to extrapolate that which is most useful to us based on the widest variety of relevant data (3: p11) . In this respect, GIS is problem solving using geographic means and its co-operative method of sharing pure and unbiased raw data (3: 22) has made it the ideal candidate for everything that affects our environment or how our environment might affect us.

It helps better decision making and as most people prefer visual medium, there is no better visual communication medium than a map (4) so long as you are making it clear what the person is looking at. Maps are immediately identifiable and engaging, and a flexible and universal method of communication within a discipline, between disciplines and to the public as a whole. How it is compiled comes in four elements (1) which are data acquisition, storage & retrieval, transformation & analysis (which may include statistics and the production of models) and reporting (which will include the maps, tables and any associated reports) of data that may previously have been unrelated but will serve a useful function to someone, somewhere (5) . Not everyone will be involved in all of these processes but most GIS technicians are charged with locating data that is collected by others and need to know how to acquire and manipulate the data as well as produce maps that are useful. It is a co-operative system limited (1) only by the technology of the day.

History of GIS

There is some debate over when true GIS really started, thanks to the disparate technologies that came together to give us GIS as we understand it today (1) , but effectively it has been around since the early 1960s. Advocates claim that it was truly born in 1962 with the first CLI conference (Canadian Land Inventory) that set out to produce masses of data of maps of Canada covering a large number of potential uses and data sets (2) . The conference produced these maps using the old methods but it was first theorised here that in future, such data could be produced using the developing computing technology as data got bigger and potential to explore it became more and more complex (8) .

The next few decades saw the technology strictly limited to those who had the resources: the hardware and the software were both expenses that had to be justified for the business or the industry, hence that fossil fuel companies represent some of the earliest groups to take up the technology. The 1980s when home computing was increasingly the norm and IT technology began to spread its wings, the business ESRI was formed. Today they are famous for the popular package ARCGIS; the second most popular package in the world today is MapInfo and the corporation was also formed in the same decade (10) . But it would be some time before their software - as popular and as useful as it was - would be anything more than a niche interest.

Today, most organisations that collect and use data make information available to almost anyone. Though confidential data may require that the user register on a site and sign a non-disclosure agreement, the nature of Big Data coupled with the exponential growth of Web 2.0 and how that data is used means that anyone can produce useful maps (3: 24-25) . In the early days, GIS was concerned with how the world looks but less concerned with how it works. This is a result of the growth of technology, decreasing price of the technology and the fact that we can do more things with more data (3: 44-45) .

Real World Example Applications of GIS

Disaster management.

Hurricane Katrina is seen by many as the first time that GIS was used a disaster management tool. Thanks to newly available technology, the first responders on the ground shared a great deal of data about street plans - particularly which streets were and were not accessible and the extent of the flooding. Despite that FEMA and the government came in for criticism, many agree that the efforts of data transmission both prior to and during initial relief efforts were vital to relief efforts (3: 5-6) .

2014 was a terrible year for drought for the SW United States. Increasingly, GIS is being used to manage environmental problems and specifically in disaster relief. Environmental experts have plotted the reporting of official droughts in most of these areas and shape files are now available (9) of the affected region.

Crime Statistics

GIS is now vital to law enforcement and planning in terms of crime statistics. Though most police forces in the USA have used them for a long time, automated and digital mapping of reported crime has made the process much easier, especially when looking at different types of crime from different departments in larger cities. The ability to share maps and look for correlations between different types of crime can give police a much better idea of an overall picture of a wider region (11) . The study cited here also permitted community leaders and the police to get a better understanding of each other, facilitating two-way dialogue.

Archaeology

GIS is now critical to many elements of archaeology as it takes on more elements and characteristics of an environmental science. There are many applications in the field of historical research but none has been more beneficial than the prediction of historic site location (12) . Several US universities recently plotted an area to the south of the Caucasus to identify prehistoric sites and areas that may have potential for future on-the-ground research, most notably of the migration route out of Africa in antiquity. The project successfully identified a number of potential new sites for future investigation.

Civic Planning

GIS has been a superb tool for rural and urban planning for the last few decades, working out local tax rates, planning desirability and mapping social deprivation, where new roads could go or which should be prioritised for repair. It is now a vital part of our green future too (13) . As with regular and previous methods of planning utilities, using the landscape is far more critical to planning. Cascade in Montana is a prime site for wind farms and there is a website that uses GIS data to plot wind speeds over the course of a year in order to best site the wind farms.

Health / Medical Resource Management

GIS is vital to the proper planning and analysis of the provision of cancer services for the UK socialised healthcare system, the NHS (National Health Service) (14) . The package is used to plan and examine a number of issues including catchment areas for GP surgeries. A study recently found that there was greater provision for cancer treatment in the midlands than the actual population. Such maps are used to better manage resources of the NHS.

One of the biggest public works in the UK right now is the planned High Speed 2 (HS2) rail connection between London and Manchester and then later beyond that. It plans to upgrade and revolutionise the rail network in the UK, arguably starved of much-needed modernisation since privatisation in the 1980s. Because of the massive amount of planning involved, including that many agencies have input into the project, it would have been a logistical problem with the massive amounts of data available and collected on a dedicated GIS site in order that the best decisions are made while respecting local infrastructures and the environment (15) .

This above list is only a small selection of examples of GIS' functionality. Any industry or area of resource management where there may be a geographical element may benefit from the advantages of using GIS. It is increasingly vital in many jobs today.

Additional GIS Content Regarding Environmental Science:

Agricultural Science & GIS
Climate Science & GIS
Environmental Biology & GIS
Environmental Engineering & GIS
Environmental Microbiology & GIS
Environmental Planning & GIS

How Sustainability Uses GIS

http://www.esri.com/news/arcnews/fall12articles/the-fiftieth-anniversary-of-gis.html
Longley, P.A., Goodchild, M.F., Maguire, D.J. & Rhind D.W. 2011: Geographic Information Systems & Science (Third Edition) . Wiley: Hoboken, New Jersey
http://www.esri.com/what-is-gis
http://www.mapcruzin.com/what-is-gis.htm
http://www.geostore.com/environment-agency/
http://webarchive.nationalarchives.gov.uk/20130402151656/http://archive.defra.gov.uk/environment/climate/documents/adapt-reports/06road-rail/network-rail.pdf
http://gisandscience.files.wordpress.com/2012/08/4-computermapping.pdf
http://mapcruzin.blogspot.co.uk/2014/09/drought-maps-and-charts-updated-weekly.html
http://wiki.osgeo.org/wiki/Open_Source_GIS_History
http://www.esri.com/news/arcnews/winter1112articles/predicting-prehistoric-site-location-in-the-southern-caucasus.html
http://www.esri.com/library/brochures/pdfs/gis-for-green-government.pdf
https://www.wmciu.org.uk/
http://webarchive.nationalarchives.gov.uk/20141027142236/http://www.hs2.org.uk/news-resources/hs2-gis-information
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GIS for Resource Management (ESSM 351/651) and GIS for Environmental Problem-Solving (RENR 405) are undergraduate- and graduate-level courses offered for academic credit by the Department of Ecosystem Science & Management at Texas A&M University.

Offered both on-campus and online year round, the courses help students learn a holistic approach to solving problems using ArcGIS™ software and real world spatial, satellite and census data. The overall goal is to enhance students’ spatial information literacy in a knowledge-based economy of the emerging and ever changing information age.

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In This Article Expand or collapse the "in this article" section Use of GIS in Environmental Science

Introduction.

Spatial Data
Spatial Analysis
Public Health and Epidemiology
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Climate Change
Environmental Modeling
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Other Technologies: Remote Sensing, Global Positioning Systems, and Virtual Globes
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Use of GIS in Environmental Science by Karam Ahmad , Melinda Laituri LAST REVIEWED: 27 September 2017 LAST MODIFIED: 27 September 2017 DOI: 10.1093/obo/9780199363445-0081

The use of geographic information systems (GIS) in environmental science is a complex, multifaceted, and amorphous topic. Environmental science is a multidisciplinary field that integrates the biological, social, and physical sciences to address the seemingly intractable environmental problems humans face. Increasingly, GIS is the tool used to organize, analyze, manage, and visualize geospatial data that links models to derive outputs from environmental analysis and modeling. Coupled, the fields of GIS and environmental science cover a multitude of topics and approaches scattered across a broad bibliographic landscape. The environmental movement of the 1960s and 1970s fueled the development of environmental science as a disciplinary field closely related to ecology, geography, and hydrology. In the 1980s, GIS became a more accessible tool for researchers through such programs as GRASS, Intergraph, and ESRI’s ArcInfo to characterize and analyze complex environmental problems. During the 1990s, approaches to environmental science focused on risk management, pollution, and monitoring. The coincidence of Internet development, data accessibility, visualization, and software modeling tools have created a perfect storm for the adoption of an integrated approach—environmental science with an integrated technology (GIS)—to address environmental issues. There has been a virtual explosion of applications and research utilizing GIS that cover a broad range of issues: water resources, climate change, urban planning, environmental justice, vulnerability studies, etc. This bibliography provides an entrée to the complex landscape of GIS applications for environmental science. It is not an exhaustive bibliography, but one that highlights some of the main avenues of GIS applications. Utilizing the Web of Science, Academic Search Premier, and Google Scholar, key articles on GIS and environmental science were accessed and organized around various thematic areas, including Disasters , Ecology , Pollution , Public Health and Epidemiology , and Water Resources Analysis . There are numerous other areas of this topic, but selecting these areas presents the reader with an overview of the field. Many of the articles in this bibliography provide a jumping off point to explore other topic areas that are not included in this bibliography.

General Overviews

The works in this section provide several general overviews of the breadth and depth of GIS and the sciences. These articles track the increasing sophistication of topics, techniques, and tools which have broadened the application of environmental sciences that utilize a geospatial approach. Goodchild 2003 provides an overview of the advances made in GIS analysis and modeling for environmental research. Goodchild’s discussion is a continuation of assessments that have tracked the advancement of GIS and environmental scientific research since 1993 (see Goodchild, et al. 1993 ). Burrough 1999 discusses the importance of geostatistics in enriching the tools for spatial analysis, generalization, and assessing spatial patterns. Emerging technological approaches include open source GIS applications for addressing big data, changing climate, and citizen science ( Sui 2014 ); the utilization of 3D geo-databases for interdisciplinary research ( Breunig and Zlatanova 2011 ); and the integration of remotely sensed data for studying the relationship of human societies and their biophysical environment ( Turner 2003 ). Overview articles also include specific thematic areas, including natural resource management ( Wright, et al. 2009 ), public health research ( Jerrett, et al. 2010 ), and marine environment research ( Palumbi, et al. 2003 ). These demonstrate the broad application of GIS and the environmental sciences.

Breunig, M., and S. Zlatanova. 2011. 3D geo-database research: Retrospective and future directions. Computers & Geosciences 37:781–803.

DOI: 10.1016/j.cageo.2010.04.016

Provides an examination of twenty-five years of geo-database research, including modeling, standards, and indexing. Describes the potential to use 3D geo-databases for urban planning, environmental monitoring, infrastructure management, and early warning or disaster management and response.

Burrough, P. A. 1999. GIS and geostatistics: Essential partners for spatial analysis. Environmental and Ecological Statistics 8 (April): 361–377.

DOI: 10.1023/A:1012734519752

An early summary of the integration of geostatistics with GIS analysis. Describes the fundamentals of spatial sampling and pattern analysis. Discusses the conceptual basis of interpolation methods, error analysis, and generalization techniques to be used in environmental modeling.

Goodchild, M. F. 2003. Geographic information science and systems for environmental management. Annual Review of Environment and Resources 28:493–519.

DOI: 10.1146/annurev.energy.28.050302.105521

In-depth review of trends in environmental research and management. Included are definitions of GIS terminology with overviews of GIS analysis/modeling, sources of geographic data, software design, and representation in GIS. This paper reveals GIS technology’s rapid changes and the author’s prescient view identifying many trends that have since come to fruition.

Goodchild, M. F., B. O. Parks, and L. T. Steyaert, eds. 1993. Environmental modeling with GIS . New York: Oxford Univ. Press.

The result of a conference on environmental modeling and crosscutting themes, this text provides an early look at the links between computer modeling and environmental science through a conceptual discussion and a series of case studies.

Jerrett, Michael, Sara Gale, and Caitlin Kontgis. 2010. Spatial modeling in environmental and public health research. International Journal of Environmental Research and Public Health 7.4 (April): 1302–1329.

DOI: 10.3390/ijerph7041302

Comprehensive summary of GIS methods used for environmental and public health research. Reviews public health research using such methods. The paper has two aims: (1) to summarize various geographic information science methods, and (2) to provide a review of studies utilizing such methods. It describes the field of spatial epidemiology.

Palumbi, S. R., S. D. Gaines, H. Leslie, and R. R. Warner. 2003. New wave: High-tech tools to help marine reserve research. Frontiers in Ecology and the Environment 1 (March): 73–79.

DOI: 10.2307/3868033

Describes new tools for understanding marine ecology and management of these complex areas. Mapping population movements and species dispersal provides monitoring mechanisms for protected and unprotected areas. These approaches provide lessons for other areas of conservation and ecosystem management of a terrestrial nature, including decision-making tools for multiple stakeholders.

Sui, D. 2014. Opportunities and impediments for open GIS. Transactions in GIS 18.1 (February): 1–24.

DOI: 10.1111/tgis.12075

Describes the potential for open GIS based upon open science with respect to data, environmental change, citizen science, and education. A visionary discussion on the future of GIS and science.

Turner, M. D. 2003. Methodological reflections on the use of remote sensing and geographic information science in human ecological research. Human Ecology 31.2 (June): 255–279.

DOI: 10.1023/A:1023984813957

Focusing on the Sahel, this paper discusses the applications of remote sensing and GIS as applied to environmental science. The author provides a critique of such approaches and the need to integrate human, cultural, and political ecologies into such research frameworks.

Wright, D. J., S. L. Duncan, and D. Lach. 2009. Social power and GIS technology: A review and assessment of approaches for natural resource management. Annals of the Association of American Geographers 99.2: 252–274.

DOI: 10.1080/00045600802686299

An examination of the role of GIS in environmental decision making, using a case study approach. Focusing on forestry management in western Oregon, this case study demonstrates the link between science, decisions, and power. A thoughtful piece when considering implementation of GIS for contentious environmental issues.

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Managing the environment using GIS

Perhaps the most important concern for all of us today is protecting the environment we live and breathe in. Climate change issues are creating havoc with erratic weather patterns affecting everything from crop production to untimely melting of ice glaciers. There is a lot to worry about and immediate action is definitely required. It’s not that the world has not geared up to take corrective actions, but we need to do more, and GIS can help us achieve that. GIS is a powerful tool. It is enabling every sector to perform better and the environment is no exception.

How GIS can help

Human activities and global warming are rapidly contributing to environmental degradation, decreasing glacier area, growth in glacial lake size, unprecedented rainfall, changes in land use and land cover, forest degradation, floods and glacial lake outburst floods, landslides, and shortfalls in agricultural crop production are among the many problems brought on by environmental changes. These issues need timely monitoring and supervision. Effective monitoring of the environment and an improved understanding of the same requires valuable information and data that can be extracted through application of geospatial technologies such as remote sensing and GIS .

GIS can be used most effectively for environmental data analysis and planning. It allows better viewing and understanding physical features and the relationships that influence in a given critical environmental condition. Factors, such as steepness of slopes, aspects, and vegetation, can be viewed and overlaid to determine various environmental parameters and impact analysis.

GIS can also display and analyze aerial photographs. Digital information can be overlaid on photographs to provide environmental data analysts with more familiar views of landscapes and associated data. GIS can provide a quick, comparative view of hazards (highly prone areas) and risks (areas of high risk which may occur) and areas to be safeguarded.

On completion of data analysis, GIS can help in effective planning and managing the environmental hazards and risks. In order to plan and monitor the environmental problems, the assessment of hazards and risks becomes the foundation for planning decisions and for mitigation activities. GIS supports activities in environmental assessment, monitoring, and mitigation and can also be used for generating environmental models.

GIS can aid in hazard mitigation and future planning, air pollution & control, disaster management, forest fires management, managing natural resources, wastewater management, oil spills and its remedial actions etc.

GIS in disaster management

In the recent past, India has made great strides in the disaster alert systems – be it cyclone alerts, regional tsunami warnings or heavy rainfall/flood alert system. The Indian Tsunami Early Warning Centre based in Hyderabad has been successful in delivering accurate alerts. Due to timely predictions, preparations have been better, even leading to timely evacuations and thus no loss of lives.

GIS in air quality monitoring

GIS in forest fire management

GIS in managing natural resources

GIS helps in identifying the impact of human behavior on natural resources and leads to more effective utilization of the same. Data about natural resources could be collected through remote sensing , aerial photography or satellite imagery and then they are mapped using GIS technology. The major application of GIS in natural resource management is in confronting environmental issues like a flood, landslide, soil erosions, drought, earthquake etc. It also addresses the current problems of climate change , habitat loss, population growth, pollution etc. and provides information about land area change between time periods. The information obtained from GIS help to study specific areas and monitoring can be done in and around those areas. It provides relevant information about the environmental condition and policy, including conservation programs. Maps in GIS provide the information of location and current resources.

Along with the aforementioned applications, GIS can effectively aid in wastewater management, oil spilling, sewage treatment etc. Spatial information leads to better outcomes in almost every industry and GIS provides invaluable location information that makes decision-making superior and extremely productive. The benefits that GIS can yield are only limited by human’s capability to innovate and harness. We all must dedicate ourselves towards preserving our environment and technologies like GIS can be our best friends for the purpose.

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How Can We Use GIS for Environmental Preservation?

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The environment is a crucial part of our lives. Our climate is changing, and we are experiencing horrible weather patterns. Crops are dying because we cannot predict the weather. Ice glaciers are melting. The world has worked hard to address these problems, but there is still more to do. We can do more if we use GIS technology. GIS, or Geographic Information System, makes it easy for organizations to create better strategies for preserving the environment. Read on to find out what role GIS can play in environmental preservation and management.

What is the importance of GIS?

GIS is a powerful tool that helps organizations to collect, analyse and distribute information. As a result, organizations can update their resource management plans and save money. Several research agencies use GIS technology to manage and plan their projects. You can read more about how GIS is used in conservation efforts here.

GIS and Environment Preservation

GIS, together with other tools such as satellite images and documentation, helps organizations to save more trees and control the distribution of forests. For example, GIS makes it easy to observe the distribution of forests using satellite images. Organizations can use this information to allocate funds for tree planting. This helps to sustain the forests.

The technology is also used to manage conservation areas in order to help preserve the environment. An organization can use GIS mapping to map forest areas that are near their facilities and their locations along the coastline. This allows them to develop a conservation strategy.

It's also important to note that GIS can be used for gathering data about water resources . Using GIS technology, organizations can observe the level of pollution in water bodies. They can also track the movement of water in order to know where the water is flowing to. They can use this information to solve water issues.

Lastly, GIS technology is crucial for creating an inventory of our animals and plants. This will help us to assess the factors that are threatening their population. We can also use GIS technology to track the animals and plants in order to monitor their growth.

Use of GIS in Conservation Biology

Wildlife, particularly those classified as rare, threatened, or endangered, are increasingly suffering the effects of habitat loss and fragmentation as people continue to modify the environment at a rapid pace. Scientists have agreed that habitat loss has been the primary cause of species extinction worldwide for a long time.

As a result, it is becoming more apparent that our current species conservation methods are insufficient for maintaining biodiversity and naturally functioning ecosystems. Geographic Information Systems (GIS) are essential instruments in accelerating efforts to preserve species diversity . Here are some of the ways GIS is causing a stir in the conservation world. 1. Using GIS to Predict Wildlife Movement

Wildlife is unconcerned with the limits constructed by humans. When highways are built across the habitats of large, free-ranging animals, such as bears, it frequently results in numerous fatalities.

In this situation, GIS is critical to identifying a workable solution. GIS software has been used to create suitability maps identifying the places animals were most likely to select as crossing points.

Animal movement data may also be used to develop and evaluate models that anticipate the most likely connection sites utilized by bears, lowering construction costs and reducing road-kill.

This sort of study emphasizes the practical use of GIS models over manual and time-consuming data collection methods. 2. Monitoring the Progress/Status of Conservation Efforts

Users may utilize GIS to define conservation targets, create conservation goals for specific places, and track how these actions progress over time.

It is critical to design our towns and maintain natural spaces and protected areas for a healthy environment and sustainable life as our population rises. GIS helps in tracking the current state of an area as well as predicting or planning future requirements.

Consider the following scenario on a smaller scale: you discover an area of your land that appears to be a suitable bird habitat. Using GIS, you can create a map showing birds' most frequented places over several days. Later, you may use this knowledge to place bird feeders in high-traffic locations or areas where you want to see more birds. 3. Mapping Species Populations and Distribution

The distribution of threatened and common animal populations, native plant distribution, and invasive or alien vegetation occurrences are all plotted over time and across regional areas.

Property managers can use GIS to conserve vulnerable environments and populations in the middle of development, such as on recreational grounds (e.g., golf courses).

Species invasions can also be studied by simulating the rate of population increase and displaying species distribution data across time.

The Importance of GIS in Environment Preservation

Lack of technology is a major reason why many organizations fail their projects. They fail because they cannot collect accurate data. They cannot distribute information to all concerned parties. They cannot achieve their objectives because they were not well planned. GIS makes it easier for organizations to plan and manage projects concerning the environment.

In this case, GIS technology helped gather the data needed to make these decisions. They used the available map data to collect information about the available resources. They used the data to decide where to plant trees. They then used the data to plant trees in the most strategic locations.

GIS makes it easy to monitor the environment using satellite images. Satellite images help monitor the natural resources, soil, and habitat of different species. With the help of GIS, an organization can observe the distribution of different species and use this information to allocate funds for the species. This helps conservationists search for endangered species and do something to help preserve them.

Utilize the Effectiveness of GIS for Environment Preservation

The environment needs our protection. We need to do something to make sure that the world is habitable for future generations. GIS technology is a critical part of conservation efforts and will become quite useful in mapping out our forests and observing the distribution of the resources. In the long run, this very tool can lead us to the conservation of our environment.

If you’re looking for a collaborative mapping solution that’s optimized for sharing and selling geospatial content, then Ellipsis Drive has the answer. We make ingestion, integration, and collaboration of geospatial data seamless by offering you and other groups simultaneous access via the tools of your choice. Interested in what Ellipsis Drive has to offer? Contact us today to learn more about what we do.

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Natural Resource Management using GIS Technology

Technology has long been an important management tool used to preserve natural resources. Many technologies have been developed over the years to suit various needs. In some cases, management practice

COMMENTS

GIS for Environmental Problem Solving
Illustration of GIS for environmental problem solving applications. To illustrate how GIS are used to help address environmental issues and problems, two cases are described herewith in this section. The first one is on flood assessment, and the second is a QOL analysis. The applications help prepare for the building framework of spatial ...
GIS for Environmental Applications
GIS for Environmental Applications provides a practical introduction to the principles, methods, techniques and tools in GIS for spatial data management, analysis, modelling and visualisation, and their applications in environmental problem solving and decision making.It covers the fundamental concepts, principles and techniques in spatial data, spatial data management, spatial analysis and ...
GIS for Environmental Applications
Abstract. GIS for Environmental Applications provides a practical introduction to the principles, methods, techniques and tools in GIS for spatial data management, analysis, modelling and visualisation, and their applications in environmental problem solving and decision making. It covers the fundamental concepts, principles and techniques in ...
Geographic Information Systems (GIS) Principles and Applications
In this respect, GIS is problem solving using geographic means and its co-operative method of sharing pure and unbiased raw data (3: 22) has made it the ideal candidate for everything that affects our environment or how our environment might affect us.
GIS for Environmental Applications : A practical approach
Xuan Zhu. Routledge, May 26, 2016 - Science - 490 pages. GIS for Environmental Applications provides a practical introduction to the principles, methods, techniques and tools in GIS for spatial data management, analysis, modelling and visualisation, and their applications in environmental problem solving and decision making.
PDF GIS Best Practices Environmental Management
GIS technology is an effective tool for studying the environment, reporting on environmental phenomena, and modeling how the environment is responding to natural and man-made factors. Environmental managers, scientists, regulators, planners, and many others use GIS to visualize data about. Natural resources.
GIS for Environmental Applications
Xuan Zhu. Routledge, May 26, 2016 - Science - 490 pages. GIS for Environmental Applications provides a practical introduction to the principles, methods, techniques and tools in GIS for spatial data management, analysis, modelling and visualisation, and their applications in environmental problem solving and decision making.
GIS for Resource Management & GIS for Environmental Problem-Solving
GIS for Resource Management (ESSM 351/651) and GIS for Environmental Problem-Solving (RENR 405) are undergraduate- and graduate-level courses offered for academic credit by the Department of Ecosystem Science & Management at Texas A&M University. ... Offered both on-campus and online year round, the courses help students learn a holistic ...
GIS for Environmental Applications
An important aspect of the application of GISs is solving environmental problems, including terrain analysis, hydrological modelling, land use analysis and modelling, ecological modelling, and ...
Use of GIS in Environmental Science
The use of geographic information systems (GIS) in environmental science is a complex, multifaceted, and amorphous topic. Environmental science is a multidisciplinary field that integrates the biological, social, and physical sciences to address the seemingly intractable environmental problems humans face. Increasingly, GIS is the tool used to ...
PDF GIS Best Practices for Environmental Health
GIS technology allows you to identify at-risk communities who are subject to greater health disparities. Applying a geographic approach gives you access to demographic data, tools that identify unequal resource allocation, and insight into communities who are exposed to greater environmental threats. Mapping and analysis can expose the ...
A new and complete Environmental GIS Course
Purpose: The purpose of this course is to lay a firm foundation for the successful use of GIS by introducing students to the ways that digital maps from GIS can be created, symbolized, and used in visualizations to solve problems and serve as communication tools in environmental science and beyond.
Mapping The Way Forward: GIS Is Powering Solutions To Global ...
Around the globe, scientists, schools, businesses, governments, and countless others are leveraging GIS capabilities to understand and solve 21st century challenges, from Covid-19 to climate change.
GIS for Environmental Problem Solving
Koushen Douglas Loh & Sasathorn Tapaneeyakul, 2012. "GIS for Environmental Problem Solving," Chapters, in: Sime Curkovic (ed.), Sustainable Development - Authoritative and Leading Edge Content for Environmental Management, IntechOpen. Handle: RePEc:ito:pchaps:80552 DOI: 10.5772/50098
GIS Trends for Environmental Consulting
Environmental science is a multidisciplinary field that integrates the biological, social, and physical sciences to solve the environmental problems we face every day. Environmental scientists examine the interaction between humans and the environment to characterize and analyze complex environmental problems. ... Panel Discussion on GIS Use in ...
Remote Sensing and GIS in Environmental Monitoring
Figure 1 summarizes the published papers on remote sensing for environmental monitoring and on GIS for environmental monitoring in the last two decades based on data from worldwidescience.org (last access on 26 July 2022) [ 1 ]. From Figure 1, we can see that GIS and remote sensing for environmental monitoring grew in population almost equally.
Managing the environment using GIS
The major application of GIS in natural resource management is in confronting environmental issues like a flood, landslide, soil erosions, drought, earthquake etc. It also addresses the current problems of climate change , habitat loss, population growth, pollution etc. and provides information about land area change between time periods.
Integrating GIS into an Environmental Science Program
GIS provides theoretical foundations and practical applications for social and ecological problem-solving. One approach to integrating GIS into an environmental program at a university is through a course I developed and taught through the Au Sable Institute. Through a series of readings, videos, and hands-on exercises covering a variety of ...
Harness GIS for Environmental Problem-Solving Skills
To utilize GIS for addressing environmental issues, start by defining clear goals. Identify the specific environmental problems you aim to solve or analyze using GIS technology.
Environmental Modeling with GIS
Environmental Modeling with GIS. Michael F. Goodchild, Bradley O. Parks, Louis T. Steyaert. Oxford University Press, 1993 - Computers - 488 pages. Six introduction perspectives. Environmental research: what we must do. The state of GIS for environmental problem-solving. A perspective on the state of environmental simulation modeling.
How Can We Use GIS for Environmental Preservation?
Using GIS technology, organizations can observe the level of pollution in water bodies. They can also track the movement of water in order to know where the water is flowing to. They can use this information to solve water issues. Lastly, GIS technology is crucial for creating an inventory of our animals and plants.
My ten years with Environment and Planning B
Semantic Scholar extracted view of "My ten years with Environment and Planning B" by Linda See. ... A View on the GIS Crisis in Geography, or, Using GIS to Put Humpty-Dumpty Back Together Again ... A Monte Carlo Simulation Approach to Solving Multicriteria Optimisation Problems Related to Planmaking, Evaluation, and Monitoring in Local Planning.
Meeting challenges with the tech of where
For decades, organizations have been using GIS to solve an increasing number of the most pressing problems their organizations face. Articles in this issue highlight how organizations use GIS to cut through complexity, identify solutions, and take action. The HALO Trust, a humanitarian nongovernment organization, featured in this issue, is an ...

GIS for Environmental Problem Solving

Sustainable Development - Authoritative and Leading Edge Content for Environmental Management

Author Information

Sasathorn Tapaneeyakul

1. Introduction

2. Research method

2.1. Framing the problem

2.2. Defining a project area

2.3. Identifying and acquiring data

2.3.1. GIS datasets formats

2.3.2. GIS data sources

2.3.3. Map projections and coordinate systems

2.4. Extracting and manipulating data

2.5. Editing spatial data

2.6. Geospatial analysis

2.7. Generating maps and reports

3. Illustration of GIS for environmental problem solving applications

3.1. Flood assessment

3.2. Quality of life assessment

4. Concluding remarks

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Use of GIS in Environmental Science by Karam Ahmad , Melinda Laituri LAST REVIEWED: 27 September 2017 LAST MODIFIED: 27 September 2017 DOI: 10.1093/obo/9780199363445-0081

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References to this book

How Can We Use GIS for Environmental Preservation?

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What is the importance of GIS?

GIS and Environment Preservation

Use of GIS in Conservation Biology

The Importance of GIS in Environment Preservation

Utilize the Effectiveness of GIS for Environment Preservation

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