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GIS for environmental application provides a practical introduction to the principles, methods, techniques and tools in GIS for spatial data management, analysis modeling and visualization and their applications in environmental problem solving and decision making. The emphasis is placed on application of the concepts and techniques of GIS through examples with step-by-step instructions and numerous unnoted screen shots .This volume weaves theory and practice together, assimilates the most current GIS knowledge and tools. It will be an indispensable resource for any student taking a module for

I. Introduction

 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.

 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. 

All things considered, it is timely to provide a rundown of GIS for Environmental Problem Solving as a topic. Main thrusts of our presentation consist of four parts. They are: 

2) Research method; 3) Illustrations of GIS for environmental problem solving applications; and 4) Concluding remarks.

2. Research method (METHODOLOGY)

 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)?  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 is 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.

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.

GIS enable a variety of ways for convenient delineation of a project’s boundary that might not be made possible with other applications. ArcGIS®1, worldwide used GIS software, allows users to work with geographic information data by inputting and manipulating map layers in a comprehensive manner.  We use ArcGIS for all GIS applications in this topic.

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 shape file 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

 GIS data is vastly available from many sources, including those in public domains at local, state and federal agencies; international non-governmental organizations or NGOs; and private sector providers. 

Each agency supplies relevant datasets pertaining to their line of work which contains a wide range of attributes detailed to the block level.

 With increasing demand for GIS in solving various problems, many counties and cities have initiated GIS departments, which oversee and provide relevant geographic data to inquirers.

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.

 Often, input maps will be in different projections, requiring transformation of one or all maps to make coordinates compatible. Since monitor screens are analogous to a flat sheet of paper, there is a need to provide transformations from the curved surface to the plane for displaying data.

 In order to do so, mathematical formulas to relate spherical coordinates to planar coordinates are required. Some distortions in the shape, area, distance or direction of data can occur during the transformation; different projections cause different distortions. Therefore, careful consideration of the appropriate map projection is crucial. Proper map projection must consider: the map’s subject and purpose; the subject area’s size, shape, and location; the audience and general attractiveness; size and shape of page; and appearance of the graticule.

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 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. 
  • 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 (shape file). Especially with the growing use of GIS, datasets in shape file have become more available. Shape file 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.
  • Reclassification: To extract specific data from a raster, i.e., specific elevation data, reclassification is performed. The natural disaster i.e. floods can be assessed as one major result of the incident. In order to extract only the flooded area resulted from the natural disaster, 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 a given affected 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.

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.

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 and most destructive natural disasters in the history of the United States, Hurricane Katrina provides a number of opportunities to understand the risk of nature, and how one could expect to understand and learn from such disastrous effects. We apply the methodology above.

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. In the U.S., states such as Utah; cities such as San Francisco, California; and organizations, including nonprofit organizations such as the Quality of Life Foundation 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