Geographical Information System - Essay Example

Geographical Information System xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx Name xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx Course xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx Lecturer xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx Date submitted Since its growth in the 1960’s GIS has evidently evolved both in practical expressions and its capabilities. Formative years of GIS provided the platform for the basic organization of the company’s processing structures and database which are still in use in the modern GIS. Initially, GIS focused mainly on technology and less on its application as is the case with majority of technological innovations. Currently, GIS is considered as the most effective way of handling voluminous geographical data and is also reliable in spatial analysis capabilities. In the early 1970’s, computer mapping technology gave birth to a new technology of drafting maps. Areas, points and lines defining a geographical area could now be represented on a well organized Cartesian plane with X, Y coordinates. This automated cartography assisted map drawers in plotting of maps due to its capability of making connections at a variety of scales, colors and projections. Majority of concepts and procedures applied in modern GIS technology rely heavily on the pioneering efforts in automated map drafting. A major advantage that came along with computer mapping was the ability to alter the position of a map and rapidly redraft the area. It is now easy to determine updates of resource maps for instance in the incidence of a forest fire, the starting point can be instantly determined. Mapped data format has radically changed from the previous analog inked lines on paper to storage of data on disks (Ghose 2001). During the early years of 1980’s changes in mapped data computer environment and format was utilized to develop a new technology. This was the spatial database management system (SDBM) which linked management capabilities from traditional database and those of computer mapping capabilities. In this system, geographical features are assigned identification numbers such that user can instantly obtain all the information about the feature once they point the number on the map. There were two alternatives to encoding maps; vector and raster data models which raised disagreements on the most appropriate one. However, in the mid-1980’s, GIS came to the consensus that appropriateness of data structure depends on the processing desired and nature of data. This era of computer mapping heightened the demand for mapped data as there was increasing need to for data availability, standards and accuracy and data structure issues as well. In addition, automated scanners were developed as hardware vendors used manual digitizing tablets to modify digitizing equipment (Ghose 2001). GIS new technology also facilitated emergence of a new industry for database design and map encoding and expansion of the marketplace for the sale of products of digital maps. This period was a milestone for GIS database development as its operations expanded from individual projects to corporate resources. As technological development of GIS advanced prescriptive analysis of mapped data was adapted from the former descriptive “geo-query” database method. Formative years of GIS were focused on automating mapping practices that were traditionally used. The systems were programmed with analogous procedures and mathematical functions which made it easier for users. Automation of the repetitive and tedious operations was a competitive ground for GIS as many people preferred to use the system due to its cost effectiveness. Knowledge of geo-query operations became overwhelmingly widened by mid-1980 and this initiated the theory of partial analysis. The sticking feature of partial analysis theory is numerical representation of data opposed to the traditional analog fashion like the use of inked lines on maps (David 2001). Traditional analog analysis methods were limited in quantitative processing as it utilized manual analytical techniques. On the other hand, digital representation makes it possible for both quantitative and qualitative processing. The application has evolved over the years and takes two forms; spatial analysis and spatial statistics. In the recent years, spatial statistics had moved from descriptive to predictive and finally to optimization models. The application is being utilized in precision farming to determine the spatial relationship between soil nutrients and crop yield and to relate mapped variables using spatial statistics. Spatial analysis on the other hand is extensively used by forest managers, wildlife managers and soil scientists to characterize variable factors in their operations. Since conception of GIS in the 1960’s, its technologies have undergone revolution in different disciplines. As described above, earlier applications emphasized on spatial database management and mapping but this has subsequently changed as more emphasis is placed on developing models that determine the interrelationships among mapped variables. It is quite evident that there are tremendous changes in the roles of database technology within GIS over the last twenty years. Currently, there are emerging procedures and concepts supporting special reasoning or dialogue and GIS modeling. The current roles are aimed at fully realizing GIS potential in decision making especially through inheriting complexity in today’s developing technology (De Smith et al 2007).Applications have moved from computer mapping to map modeling and finally to multimedia mapping. Multimedia mapping took a full cycle in 2010 and was ranked among the three 21st century “mega technologies” by the US department of Labor. Using the application, flagship GIS systems can be heralded as toolboxes which allow development of tailored application solutions and websites. Websites are now being made with sets of map layers that can be used by users to match and mix their desired custom views. Another powerful characteristic of the new application fully globally positioned, fully integrated and remote sensing imagery GIS system. Digital maps and GPS have made it easy for users to determine geographical positioning at place at any time. Automated data collection procedures, on-the-fly procedures and ancillary systems such as robotics have been enabled by multimedia mapping. In addition, display of contemporary maps has taken a new form contrary to the former 2D planimetric paper map. According De Smith et al (2007), it is clear that future build on cognitive basis not forgetting databases of GIS technology. Clearly, information systems are at a brink which is pushing well beyond management, modeling mapping and modeling to what is known as special reasoning and dialogue. Twenty years ago, analytical models widely focused on management yet there is another set of perspectives that can be considered. This new wave or roles concentrate on GIS modeling which widely employs advance analytical operation as well as special statistics. The application can be categorized into three namely; data mining, predictive modeling and dynamic stimulations (De Smith et al 2007). Data mining mainly uses GIS to discover relationship that exists in mapped variables. For instance, a map of fir parcels can be compared statistically to map driving variables such as soil type, slope aspect, depth to bedrock and elevation. De Smith et al (2007) asserts that, if special correlation is identified within a combination of certain driving variables then, this information become useful in directly managing actions to area of living fir under harmful conditions. Another new role displayed in data mining is defined within the derivation of empirical models. Here, a good example is in the geographical distribution of lead concentration in an aquifer which can be interpolated from water samples taken at local wells as described earlier. Further, high concentration area can be eliminated. If maps of area of high concentration are animated and time series of samples are considered, contamination normally appears to move through aquifer thus forming what is known as the empirical ground water model. The role in data visualization and investigation increasingly extend beyond earlier perspectives of map renderings. National Research Council of the National Academies (2006) maintains that, predictive modeling is currently considered to be non spatial. Here, environmental data is collected through sampling larger areas. Thereafter, data is used to solve a mathematical model like a regression equation, creating of equation linking the variable as a way of obtaining other variables. The mathematical model is obtained by way of collecting data on driving variables for a certain period of time or another area which is then followed by reducing measurements to typical values as well as evaluating the established prediction equation. Earlier non special approach is seen to ignore geographical distribution on varied data collected by highly assuming that “average tree on average terrain” is everywhere (National Research Council of the National Academies 2006). The prediction here was based on a single level of breakage for complete area that is usually extended within a range of standard deviation. Within a given mathematical sense, non spatial approach assumes that variables are uniformly and randomly distributed thorough a given project area and that variable present are spatially independent. Clearly, direct considerations of given spatial coincidence and pattern among data that is mapped will increase proper refine environmental management and prediction making them more responsive to current unique conditions. National Research Council of the National Academies (2006) maintains that, dynamic simulation allows user interaction with GIS model. If model parameters are analytically modified and induced changes within the map tracked the behavior displayed within the model can be investigated. The roles changes here in that relative importance of each mapped variable within unique geographical concept setting is widely applied. The adaptation use of dynamic simulation will widely involve decision makers in GIS analysis phase of environmental administration and policy. Queries experienced within dynamic stimulation will be addressed which in result may provide insight into sensitive systems (Grimshaw 2000). Grimshaw (2000) maintains that, with clear observation, emerging applications of predictive modeling, data mining and dynamic simulation is known to have technological cart in front of scientific horse. GIS stores tremendous descriptive data and overlay a myriad of maps for their described coincidence. The changing roles are important since they possess powerful tools used in expressing special interactions among mapped variables. This therefore creates a chasm between applied science and GIS technology. The new defined tool characterizes special relationship known as cart where understanding of its various expressions within complex systems which is the horse becomes unnecessary (Grimshaw 2000). Clearly, the new roles characterize the changes within GIS in relation to amount of edge in a given landscape by way of computing a set of fractal dimensional maps. This therefore establishes a holistic approach in both modeling and mapping within GIS. Evidently, as the future of GIS unfolds mapping will be viewed less as just a static description of a landscape and more as an active process which accounts for inherent variability in spatial descriptors as well as perception. In conclusion, it is important the environmental administration and policymakers to obtain more information. Clearly, earlier information systems highly relied on manual processing and physical data storage. It is important for them to adapt the current changing roles within GIS for information processing to become more qualitative. These new roles will actively develop links between mix of management action as well as descriptive data of landscape thus maximizing on set objectives. Clearly, the new roles push GIS which is seen to go beyond cute icons and graphical user. References David, B, 2001, GIS: a visual approach, Albany: Delmar Thomson Learning. De Smith, M, Goodchild, M. and Longley, P. 2007. Geospatial Analysis: A Comprehensive Guide to Principles, Techniques, and Software Tools. Leicester: Winchelsea Press Ghose, R, 2001, Use of Information Technology for Community Empowerment: Transforming Geographic Information Systems into Community Information Systems, Transactions in GIS, volume 5: 141–163.  Grimshaw, D, 2000, Bringing Geographical Information Systems Into Business, 2nd Edition. Wiley: New York. National Research Council of the National Academies ,2006, Beyond Mapping: Meeting National Needs through Enhanced Geographic Information Science. Washington D.C: National Academies Press Read More