Quantifying The Rate Of Spatio-Temporal Urban Growth Pattern Using Remote Sensing And Spatial Metrics: (A Case Of Shashemanne Town)

Abstract

The spatio-temporal patterns and processes of urban growth of Shashemanne town and its drivers were investigated from the year 1990 to 2019 by using remote sensing and spatial metrics by Logistic Regression Model (LRM). Four different land cover maps derived from Landsat TM image of 1990, Landsat ETM+ 2000, 2010 and Landsat OLI/TIR of 2019 were used to evaluate a set of five selected spatial metrics to reveal patterns and dynamics of urban growth in the study area. The computation of spatial metrics was conducted at two spatial scales. First, the summary descriptors of landscape heterogeneity at the town level are evaluated. Secondly, in order to better link the metric analysis to more specific locations, the study area is broken into five smaller individual regions on the basis of administrative boundaries. Then the changing patterns of urban growths over time were linked to the major physical driving forces in the study area with binary logistic regression modeling. Therefore three models were built for 1990-2000, 2000-2010 and 2010-2019 time periods. The growth was prolonging both from urban center to adjoining non-built up areas in all direction, but mainly to the east, north and west direction along major road corridors. The total built-up area in the town has grown from 305 ha in 1990 to 2500 ha in 2019 at an average growth rate of 2.65%, 5.29% and 7.19% per annum during 1990-2000, 2000-2010 and 2010-2019 study periods respectively. The analysis of spatial metrics at the town level revealed that the urban landscape has experienced a process of sprawling and fragmented development pattern particularly in the fringe areas while, the town center under went in fill and edge expansion development processes. The results of binary logistic regression model revealed that proportion of built up cell distance to (major roads, town centers, higher institution, CBD and satellite towns) and slope were the major driving forces of urban growth at different time periods with varying level of significance and correlation.