Gis A Computing Perspective 🎮





 
 
 
 
 
 
 

Gis A Computing Perspective

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gis a computing perspective
GIS a Computing Perspective
GIS Computing Perspective
gis computing perspective
GIS Computing Perspective
gis computing perspective
GIS Computing.
GIS computing
A. Introduction
The computational approach to the processing, storing, searching, and manipulating of spatial data has developed rapidly in the last few decades, commencing with the first use of computers to process remotely sensed satellite images in the 1970s and culminating in the widespread availability of sophisticated hardware and software platforms for a range of different tasks. This approach has contributed to the more than twenty-fold increase in the volume of geospatial data archived in academic and commercial databases.
A result of the increased availability of spatial data on a global scale is the use of these spatial data in a variety of applications, including the management of land, the tracking of people and goods, the tracking of wildlife populations, and the tracking of environmental change such as climate, ecosystems, and water quality, and for virtually any activities that require the collection, management, and analysis of data on a geographic scale.
However, GIS, though widely understood as the integration of spatial data with software, has a much longer history as the use of computers for spatial analysis. Over the past five decades, scientists have been using computers to visualize and analyze data in ways which are impossible to do using a human eye alone. Computers have been vital to the development of Geographic Information Science.
There are at least two good reasons for developing a computational approach to the processing, storing, searching, and manipulating of spatial data. The first is that this approach can provide solutions that are not possible using purely manual methods, or those that require a large investment in time and staff. The second is that the development of such software is comparatively inexpensive, especially in light of the volume of geospatial data that is now available.
With these two driving motivations, we must recognize that the purpose of software development is not to provide easy answers, but to provide tools that allow the expert users to identify the need for expert solutions.
Furthermore, we must recognize that the creation of such tools does not eliminate the human element. Rather than the algorithms themselves becoming the source of wisdom, the human experts (users, programmers, designers, and scientists) must retain the ability to recognize patterns and make sense of what they see. The computational approach is, therefore, best understood as a means of augmenting human expertise.
Similarly, we must recognize that the computational approach has its own limitations. Though powerful in their
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