Abstract
The purpose of the present study was to explain land-use/cover changes in Coimbatore City Corporation using Landsat ETM+ and Landsat 8 Operational Land Imager (OLI) and Thermal Infrared Sensor (TIRS) data for the period of 2003–2014. Two Landsat images from years 2003 and 2014 were downloaded from USGS Earth Explorer. Maximum likelihood method was used to classify the images into five classes: urban fabric, vegetation, water bodies, agriculture lands, and barren lands. Overall kappa accuracy measure is about to 87.60 and 86.15% for the years 2003 and 2014, respectively. The change detection analysis has been performed for years 2003 and 2014 postclassified images. The results of the study have indicated that Coimbatore City has experienced rapid modifications in LULC, particularly in terms of urban/built-up area. Over the past 11 years, urban/built-up areas have increased by 94.5 km2, resulting in a significant drop in the area of agricultural land and vegetation cover. It is found that (1) urban areas are increased 200% due to population growth cum rapid economic progress. (2) Vegetation cover decreased 38.76% due to conversion into urban features. (3) Water bodies in area increased to 15.78% due to eradication of encroachment. (4) There is loss of 1.89% of agricultural lands due to demand for construction activities. (5) About 85.24% of barren lands were converted into other uses, particularly 57.33% to urban areas. (6) Urban growth has accelerated towards north-eastern, northern, and eastern parts, where national highways exist. The built-up areas were dropped from 85.32 to 22.28%, within 5-km distance from the city center.
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References
Billa, M. A. L. (2013). Modelling urban growth evolution and land-use changes using GIS based cellular automata and SLEUTH models: The case of Sana’ a metropolitan city, Yemen. Environmental Earth Sciences, 70(1), 425–437.
Bolca, M., Turkyilmaz, B., Kurucu, Y., Altinbas, U., Esetlili, M., & Gulgun, B. (2007). Determination of impact of urbanization on agricultural land and wetland land use in Balçovas’ Delta by remote sensing and GIS technique. Environmental Monitoring and Assessment, 131(1–3), 409–419.
Chowdhury, P. K., & Maithani, S. (2010). Monitoring growth of built-up areas in indo-Gangetic plain using multi-sensor remote sensing data. Journal of the Indian Society of Remote Sensing, 38, 291–300.
Congalton, R. G. (1991). A review of assessing the accuracy of classifications of remotely sensed data. Remote Sensing of Environment, 37, 35–46.
Deng, J. S., Wang, K., Hong, Y., & Qi, J. G. (2009). Spatio-temporal dynamics and evolution of land use change and landscape pattern in response to rapid urbanization. Landscape and Urban Planning, 92, 187–198.
Dewan, A. M., & Yamaguchi, Y. (2009). Land use and land cover change in greater Dhaka, Bangladesh: Using remote sensing to promote sustainable urbanization. Applied Geography, 29(3), 390–401.
Landis, J.R. and Koch, G.G. (1977). The Measurement of Observer Agreement for Categorical Data. Biometric, 33, 159–174.
Mundia, C. N., & Aniya, M. (2005). Analysis of land use/cover changes and urban expansion in Nairobi city using remote sensing and GIS. International Journal of Remote Sensing, 26, 2831–2849.
Ma, Y., & Xu, R. (2010). Remote sensing monitoring and driving force analysis of urban expansion in Guangzhou City, China. Habitat International, 34(2), 228–235.
Rahman, A., Kumar, S., Fazal, S., & Siddiqui, M. (2012). Assessment of land use/land covers change in the north-West District of Delhi using remote sensing and GIS techniques. Journal of the Indian Society of Remote Sensing, 40(4), 689–697.
Ramachandra, T. V., Bharath, H. A., & Sowmyashree, M. V. (2013). Analysis of spatial patterns of urbanisation using Geoinformatics and spatial metrics. Theoretical and Empirical Researches in Urban Management, 8(4), 5–25.
Rawat, J. S., Biswas, V., & Kumar, M. (2013). Changes in land use/cover using geospatial techniques : A case study of Ramnagar town area, district Nainital, Uttarakhand, India. The Egyptian Journal of Remote Sensing and Space Sciences, 16(1), 111–117.
Rosenfield, G. H., & Fitzpatrick, K. (1986). A coefficient of agreement as a measure of thematic classification accuracy. Photogrammetric Engineering and Remote Sensing, 52, 223–227.
Sun, Z., Ma, Æ. R., & Wang, Æ. Y. (2009). Using Landsat data to determine land use changes in Datong basin, China. Environmental Geology, 57(8), 1825–1837.
Tan, K., Lim, H., Mat Jafri, M., & Abdullah, K. (2010). Landsat data to evaluate urban expansion and determine land use/land cover changes in Penang Island, Malaysia. Environmental Earth Sciences, 60(7), 1509–1521.
Vitousek, P. M., Mooney, H. A., Lubchenco, J., & Melillo, J. M. (1997). Land use change under conditions of high population pressure: The case of java. Global Environmental Change, 9, 303–312.
Wakode, H. B., Baier, K., & Jha, R. (2014). Analysis of urban growth using Landsat TM/ETM data and GIS — A case study of Hyderabad, India. Arabian Journal of Geosciences, 7, 109–121.
Weng, Q. (2001). A remote sensing – GIS evaluation of urban expansion and its impact on surface temperature in the Zhujiang Delta, China. International Journal of Remote Sensing, 22(10), 1999–2014.
Yin, J., Yin, Z., Zhong, H., Xu, S., Hu, X., Wang, J., & Wu, J. (2011). Monitoring urban expansion and land use/land cover changes of shanghai metropolitan area during the transitional economy (1979-2009) in China. Environmental Monitoring and Assessment, 177(1–4), 609–621.
Yueliang Ma, Ruisong Xu. (2010). Remote sensing monitoring and driving force analysis of urban expansion in Guangzhou City, China. Habitat International, 34(2), 228–235.
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Prabu, P., Dar, M.A. Land-use/cover change in Coimbatore urban area (Tamil Nadu, India)—a remote sensing and GIS-based study. Environ Monit Assess 190, 445 (2018). https://doi.org/10.1007/s10661-018-6807-z
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DOI: https://doi.org/10.1007/s10661-018-6807-z