Remote Sensing and GIS technology was applied by Radhakrishnan, Erni, and Kumar (2014) to the city of Tiruchirappalli, India in order to analyze urban sprawl patterns occurring between the years of 1998 and 2009, and predict future sprawl patterns. Imagery and data collected to demonstrate different sections of the city as well as transportation patterns within the city are depicted below.
Further, various “land-use cover” (Radhakrishnan et al., 2014, 3) was classified using “digital image processing based on visual representation.” Radhakrishnan et. al then compared land-use between the years of 1998, 2006, and 2009 using software such as ERDAS, Maximum likelihood Classifier, and ArcGIS. These researchers performed an“accuracy assessment” (Radhakrishnan et.al 5) of the data extracted from these programs using “GPS, false color remotely sensed data, and Google Earth”producing the below images.
From the accumulated data, Radhakrishnan et. al identified ribbon sprawl, “development that follows major transportation corridors” (2014, 5) along highways and roads of the city as well as “low-density sprawl” caused by unplanned expansion outside of city corridors due to various levels of urban expansion and industrialization. Shannon’s Entropy, a mathematical tool used to “measure the degree of spatial concentration and dispersion exhibited by geographic variable” (Radhakrishnan et.al, 2014, 6) was then used to track future patterns of urban sprawl. Factors of population change and variances in land-use were also analyzed to predict sprawl.
The overall conclusions of Radhakrishnan et. al research was that the expansion of development and intrusion into agricultural lands is exceeding the rate of population increase. Combined with GIS and population data, it was observed that between 1998 and 2009, the land developed experienced a 40% increase while the population of the city only grew by 12%, and was dispersed across the city.Within the built up region of the land which centered around transportation portals, approximate 55% increase in sprawl is predicted to occur in the year of 2031. This type of GIS centered research is necessary in detecting past and future urban growth patterns so that more economically, socially, and environmentally sustainable cities can be planned and successfully executed.
Radhakrishnan, N., Eerni, S., & Kumar, S. (2014). Analysis of Urban Sprawl Pattern in Tiruchirappalli City Using Applications of Remote Sensing and GIS. Arabian Journal For Science & Engineering (Springer Science & Business Media B.V. ), 39(7), 5555-5563. doi:10.1007/s13369-014-1099-2
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