The International Journal of Informatics, Media and Communication Technology (Jun 2024)
Assessing and Regenerating Proposed GIS Grid-based Geospatial Modeling Algorithms
Abstract
This research is a new attempt to purify the modeling concepts from some misleading geographical published papers and unpublished M.A. theses & Ph.D. dissertations that dealt with grid-based spatial modeling irrationally. Recently, it was noticed that there is a conceptual confusion among many researchers concerning the GIS-based modeling environment. The confusion was detected from several perspectives. Firstly, there is a vague thinking among researchers in differentiating between GISystems (GISs) and GIScience (GISc) modeling approaches and between the rightful definitions of GIS-analysts and GIS-modelers. Secondly, differentiating between types of GIS-based models especially between "Ready-to-Use", "Programming-Modified", and "Programming Stand-Alone" models. Thirdly, the vigorously methodological misuse of the modeling procedures in which GIS-modelers should strictly follow. In this respect, this research shed lights on grid modeling algorithms of GIS Spatial Modeling -also called GIS-based Geospatial Modeling-. Three algorithms are chosen such as; Cartographic Modeling (CM), Surface Modeling Technique (SMT), and Impedance Surface Modeling (ISM). Empirically, modeling settlement/urban growth change is chosen to be applicable to all selected and proposed modeling algorithms. Furthermore, it aims to offer a perusable study of these algorithms. Objectifying to study the concepts, characteristics, designs, structures, conditions, conceptual designed methodology, and procedures of both conventional and suggested modified algorithms. Furthermore, it focuses on producing critical assessment for traditional algorithm and then generating and proposing new modifications concerning the chosen application for each modeling approach. Finally, the study offers new geospatial modeling modifications to overcome the existing modeling algorithms' obstacles, limited usage, locality, performance deficiencies, and other modeling disadvantages.
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