Evaluating the Physical-Spatial Indices in Determination of Urban Sprawl Patterns Using Remote Sensing (Case Study: City of Kerman)

Over the past decades, the increase of world’s urban population has resulted in uncontrolled urban expansions and especially sprawl of the major cities. Accordingly, analysis of such phenomena and determining urban development and sprawl patterns should be taken into consideration as a necessity. This research aims at evaluating 28 physical-spatial indices divided into 4 distinctive groups (Area-Edge, Shape, Aggregation, and Diversity) and 3 levels (Patch, Class, Landscape) in determination of urban sprawl patterns of the city of Kerman using remote sensing data from the period of 1984 to 2018. For this purpose, 8 temporal satellite images were selected with an acquisition date interval of 5 years. Pre-processing, Processing and classification methods were applied to the RS images using ENVI software. Output data from ENVI were imported to ArcGIS software for further preparation of GeoTIFF file. Afterwards, The GeoTIFF file were imported to Fragstats software in order to calculate the 28 indices of this research. Setting weights to the matrix of indices by Shannon’s Entropy Method and application of MATLAB, we calculated the sprawl of the case study for the years of interest. The findings demonstrates that in the year 1984, the city of Kerman had shown the most proportion of sprawl, and in contrary, in the year 2018, the amount of sprawl was at its minimum extent. In the final stage, Friedman’s test were conducted via SPSS software, resulting in calculation of the Mean-Ranks of 4 group-indices where they illustrate that sprawl pattern of the city of Kerman is mainly resultant of Area-Edge indices.