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Updated: Feb 7, 2026

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Published on: August 8, 2014
Analyzing urban landscape with City Biodiversity Index for sustainable urban growth
Shubhasmita Sahani1,2, V Raghavaswamy3,4
1Department of Spatial Information Technology, Institute of Science and Technology, Jawaharlal Nehru Technological University, Hyderabad, Telangana, 500072, India. shubhasmita.sahani@gmail.com.
Abstract:
Urbanization process converts natural landscape into an anthropogenic urban landscape. The present paper attempts to understand spatiotemporal urban dynamics of a mid-sized Indian town-Khammam in Telangana-by carrying out Land Use Land Cover Change Analysis for assessing urban growth pattern. A set of metrics of Landscape Analysis available to analyze growth pattern and broadly categorized into two sets-composition and configuration. Principal Component Analysis was used to identify three critical metrics from Landscape Analysis, viz., Number of Patches and Edge Length and Splitting Indexes while two additional metrics of the composition set, viz., Shannon Diversity and Shannon Evenness Indexes, based on expert opinion were added to make the study amenable. Twenty-three indicators of City Biodiversity Index broadly grouped into three core components, viz., Native Biodiversity in City, Ecosystem Services provided, and governance and management of CBI, were analyzed, and five indicators that were amenable to digital interpretation of satellite data pertaining to proportion of park and natural area within city, availability of water or quantum of water for urbanization, extent of natural protected area, extent of parks and natural area, and impact of vegetated area on ambient cooling were studied. Study indicated that in Khammam score of 8 out of a total score of 20 in CBI analysis indicated unsustainable growths, although trends among individual LULC components varied making it essential to study individual patterns. Study highlights need to use such indicators to guide urban development in mid-sized urban towns and cities that could substitute for large metropolitan cities as the growth engine in future.
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