Geographic Information Systems Application in Environmental Science - Literature review Example

GIS APPLICATION IN ENVIRONMENTAL SCIENCE (Student Name) (Course No.) (Lecturer) (University) (Date) Introduction “GIS is a powerful software technology that allows a virtually unlimited amount of information to be linked to a geographic location. It can include a digital map which will enable a user to vividly see locations, events, features and any environmental changes showing layer upon layer of information such as soil stability, pesticide use, migration corridors, hazardous wastes, lake remediation efforts among other unlimited uses” (ESRI 2016: p.2). Geographic Information System (GIS) is hugely applicable in environmental science because it aids in mapping environmental management strategies, digitalizing data from field, enhancing data collection and its analysis afterward. Kyriakidis et al. (1999), argue that most GIS application software allow for geostatistics to be used as an analytical tool on sampled field data. Geo-statistics according to Goovaerts (1999) is a subset of statistics specializing in analysis and interpretation of geographically referenced data; it comprises statistical techniques that are adjusted to spatial data which are mostly used in environmental studies especially in pollution cases by quantifying noise in images and spatial variations in remote sensing data enabling an ecosystem’s degradation analysis. The advancements in computer mapping was gradual, according to Brown (1949) early 1970’s saw computer mapping being automated during map drafting process. This was aided by points, lines and areas defining geographic features on a map are represented as a set of X, Y coordinates which were then drawn by a pen plotter using different colors, scales, and projection resulting into a map. According to Abler et al. (1971) work achieved during this time still make underlying concepts and procedures of modern GIS technology. Discussion Joseph (2000) argues that, “environment management is inherently a spatial endeavor. Its data are particularly complex as they require two descriptors; namely a precise location of what is being described as well as a clear description of its physical characteristics. For hundreds of years, explorers produced manually drafted maps which served to link the ‘where is what’ descriptors. ” Today with complex environmental issues on the rise and the need for accurate information, modern mapping systems with its own in-built decision-making process has resulted in radically different approaches for addressing complex environmental issues which could not have been possible using earlier maps. Mason (2016), points out that Geographic Information System is a very important tool useful in environmental sciences. According to the author, GIS is not just an evolutionary digital advancement from the use of cartography to using an Information Technology enabled geographic data and digital mapping because it offers wide applications to researchers, engineers. Mason (2016), “GIS is useful in the private and public sector it gives decision makers the benefit of streamlining an operation using more information more readily and quick. It is used in town planning and waste disposal, in clean-up operations for oil spills, in building new road networks and planning infrastructure for those roads and in natural disaster relief.” According to GIS Geography (2016), “data consists of observations we make from seeing the real world. Spatial data is made up of observations with locations. Spatial data identifies features and positions on the earth’s surface. Spatial data is how we put our observations on the map. Vector and raster data are the two primary data types used in GIS; both these types have spatial referencing systems. These are latitudes and longitudes pinpointing the earth position.” In vector, model features are stored as points through a series of X Y coordinates to create a shape. Vector data is made up of pixels while vector graphics are composed of vertices and paths or lines. Symbol type for vector data are mainly three; points, lines, and polygons. Points are simple XY coordinates and represents features which are too small to be represented as a shape. An example is given of a city appearing to be a shape, but if the scale is increased to global scale, then it appears as a single point. Vector lines connect vertices with paths. A vector line connects dots (points) in a given order. In most cases it represents features that are linear and different thicknesses can be used to show difference in size of a given feature. Vector line features are points connected by a line in a given order. Polygons are a set of vertices joined in a certain order and closed to form a shape to become a vector polygon feature. This feature is characterized by the first coordinate acting as the last coordinate too. Polygons are a representation of features with two dimensions (GIS Geography 2016). According to Maribeth (2006), the following are some of the advantages of this data type, “ it provides precise location of features, stores more attributes, more flexible for cartography, compact in storage of information and it is ideally suited for certain types of analysis especially areas, lengths, and connections. On the other hand raster, data types are mostly made of evenly spaced and square pixels, with each pixel representing a value. For example in a digital photograph, each pixel value represents red, green and blue values. In the case of an elevation model then a pixel will represent height or spectral value. Raster models can be categorized into either discrete raster or continuous raster (GIS Geography 2016). According to GIS Geography (2016), “discrete raster have definable boundaries and are often referred as thematic or categorical raster data, for example, one grid cell represents a land cover class. In a discrete raster land cover a user can distinguish each thematic class because they are discretely defined. Discrete data usually consists of integers representing classes for example value 1 representing urban areas.” Continuous data, on the other hand, are grid cells with gradual changing data for example elevation, temperature or aerial photographs. This type of raster data may be derived from a fixed registration point for instance in a digital elevation model each cell represents height above or below sea level (GIS Geography 2016). According to Maribeth (2006), “raster is the best way to store continuously changing values such as elevation, analysis is faster and more flexible than in vector in many applications and some analysis are only possible using raster.” From this, it can be deduced that the best data type to use is raster because as pointed out by Maribeth some analysis are only possible with raster and it best for continuously changing variables; majority of environmental variable are spatial such as rate of deforestation, pollution changes and even rate of reforestation. One example of GIS is Integrated Land and Water Information System, according to ILWIS (2016), “most packages available in the market provide either vector or raster based programs making it necessary to have at least two programs one using raster and the other using vector. This made GIS and remote sensing to be more difficult and scary for people, however, this problem was sorted by ILWIS. This program combines raster and vector with thematic data operations into one comprehensive integrated software package for the desktop; raster includes satellite images and aerial photos while vector include map. ILWIS is developed by a Dutch training institute making it to be user-friendly. The software offers a range of capabilities such as import/export modules of any software in the market, allows analysis of stereo photographs, digitizing, editing and displaying of data and as well as production of quality maps.” One of the uses of ILWIS is its ability to analyze topography, a process known as Digital Terrain Analysis (Hengl et al2003). According to Hengl et al. (2003:p.2), “the process of quantitatively describing terrain is known as Digital Terrain Analysis (DTA). A digital terrain model which is also known as a Digital Elevation Model (DEM) is a digital representation of earth’s topography. It can be used to derive topographic attributes, geomorphic parameters, morph metric variables or terrain information in general.” The author goes on to point out that since the 90’s, Digital Terrain Analysis has been integrated into many GIS packages with most such as ILWIS being able to run simple filter operations and get for instance aspect, gradient, and map showing hill shading. According to Hengl et al. (2003), there are five common sources of such data. The sources include ground surveys, airborne photogrammetric data capture, existing cartographic surveys, airborne laser scanning and stereoscopic based satellite imagery. A researcher can use any or all of the above sources depending on price of such gadgets, accuracy needed, sampling density of the study and pre-processing requirements. Application of GIS in environmental issues can be noted by looking at ILWIS and its capabilities. For instance using an ILWIS scientist can obtain a Digital Elevation Model and also remote sensing of spatial data. Topography is of great importance to an environmental scientist due to relation between topography and a number of environmental issues, for instance, soil erosion, soil type and depth, water table and type of fauna or flora existing in a given place. According to Hengl et al. (2003:p.10), “traditionally the elevation data is collected by land surveyors from actual ground surveys or by semi-automated digitization using stereo plotters. This is the most accurate but also the most expensive data collection method. The most recent development considers automated stereo-image matching, use of laser scanning and remote sensing imagery either with stereoscopic overlap or interferometric imagery.” Laser scanning seems to be the most accurate method in research where the sample density is high. Laser scanning also provides the option of recording object surface and ground surface creating a Digital Surface Model. As earlier stated ILWIS has many uses however of concern to us in this case is its applicability to environmental issues, one of such abilities is its to analyze topography, a process known as Digital Terrain Analysis (Hengl et al. 2003). According to the same author a mathematical model is generated by ILWIS and because it is raster each pixel has its own values and a different color thereby giving the user varied uses among them characteristics of a given landscape, changes in topology relative to terrain among others. After collection of such data, a scientist is now left with modeling a terrain. A DEM is on most cases modeled and visualized using a rectangular grid or a triangular shaped Irregular Network (TIN).” In order to create catchment area and slope, length maps when using ILWIS such analysis is automated (Hengl et al. 2003:p4 5) and can consists of four steps. The first is the generation of slope length for each diagonal and cardinal direction and their sum, the second step is generation of drainage fraction out of each cell for each direction, the third step is the generation of drainage fraction into each cell and lastly propagation of the total number of contributing cells. The resultant output will be raster images of drainage fraction elements in each direction (Hengl et al. 2003). An environmental scientist could use this output in making an informed decision for example which side of a given hill is more prone to erosion therefore needs most immediate and robust mediation measures such as gabions. One major challenge is the huge amount of data which requires more space to hold, with greater resolutions comes larger sizes. It is important to note that even though ILWIS can be used to generate DEMs, it is not as robust as other stand alone terrain analysis software tools such as one developed by Centre for Resource and Environmental Studies in Canberra (Hengl et al. 2003:p. 4). Conclusion In conclusion, this study used ILWIS as a case study on how GIS software could aid a researcher in relation to environmental issues. From the study it was found that GIS offers vivid maps thus providing a clear description of any phenomenon, it is also one of the few ways used to measure pollution and other spatial data such as change in pollution, GIS also can be used to produce three dimensional models as shown by DEMs thereby improving on accuracy, presentation and reliability of any given data. BIBLIOGRAPHY Abler, R.J., J. Adams, and P. Gould, 1971. Spatial Organization: The Geographer’s View of the World, Prentice Hall, Englewood Cliffs NJ. Brown L.A(1949). The Story of Maps. Little Brown and Company, Boston MA. ESRI (2016). GIS Solutions for Environment Management. Mapping your Environmental Management Strategy. New York Street Redland. 2016. 1-800-447-9778. GIS Geography (2016). GIS Spatial Data Types: Vector vs Raster. Retrieved from http://gisgeography.com/spatial-data-types-vector-raster/ (Accessed: 28 April 2016) Goovaerts, P., 1999. Geostatistics in soil science: State-of-the-art and perspectives. Geoderma 89 (1-2):1–45. ILWIS (2016). Free GIS Intergrated Raster and Vector in the world’s User friendly GIS. Retrieved from http://www.ilwis.org/gis.htm (Accessed: 28 April 2016) Joseph. K (2000). GIS Technology in Environmental Management: A Brief History, Trends and Probable Future. Retrieved from http://www.innovativegis.com/basis (Accessed: 28 April 2016) Kyriakidis, P. C., Journel, A. G., (1999). Geostatistical Space–Time Models: A Review. Mathematical Geology 31 (6): 651–684 Maribeth H.P (2006). Raster and Vector Data. Mason. M (2016). Environmental Engineering. Hoboken, N.J. : Wiley. Retrieved from http://www.environmentalscience.org/environmental-engineering-gis (Accessed: 28 April 2016) T. Hengl, S Gruber and D.P Shrestha (2003). Digital Terrain Analysis in ILWIS. Retrieved from http://www.itc.nl/personal/shrestha/DTA/ (Accessed: 28 April 2016) Read More