Optimization of spatial statistical approaches to identify land use/land cover change hot spots of Pune region of Maharashtra using remote sensing and GIS techniques. Issue 7 (3rd July 2017)

• Record Type: Journal Article
• Authors: Ganguly, Kuntal; Kumar, Rajiv; Mruthyunjaya Reddy, K.; Jagadeeswara Rao, P.; Raj Saxena, Manoj; Ravi Shankar, G.
• Is Part Of: Geocarto international. Volume 32:Issue 7(2017)
• Page Start: 777
• Page End: 796
• Publication Date: 2017-07-03
• Subjects: Land use/land cover -- LULCC -- hot spot -- spatial statistics -- remote sensing -- Getis-Ord Gi*; Remote sensing -- Periodicals; Geographic information systems -- Periodicals; Geology -- Periodicals; Cartography -- Periodicals; 621.3678
• DOI: 10.1080/10106049.2016.1178813
• Languages: English
• ISSNs: 1010-6049

Abstract

Abstract: This study investigated land use/land cover change (LULCC) dynamics using temporal satellite images and spatial statistical cluster analysis approaches in order to identify potential LULCC hot spots in the Pune region. LULCC hot spot classes defined as new, progressive and non-progressive were derived from Gi* scores. Results indicate that progressive hot spots have experienced high growth in terms of urban built-up areas (20.67% in 1972–1992 and 19.44% in 1992–2012), industrial areas (0.73% in 1972–1992 and 3.46% in 1992–2012) and fallow lands (4.35% in 1972–1992 and −6.38% in 1992–2012). It was also noticed that about 28.26% of areas near the city were identified as new hot spots after 1992. Hence, non-significant change areas were identified as non-progressive after 1992. The study demonstrated that LULCC hot spot mapping through the integrated spatial statistical approach was an effective approach for analysing the direction, rate, spatial pattern and spatial relationship of LULCC.