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Classification and Validation of Spatio-Temporal Changes in Land Use/Land Cover and Land Surface Temperature of Multitemporal Images

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  • Vimala Kiranmai Ayyala Somayajula

    (School of Electronics & Electrical Engineering (SEEE), Lovely Professional University, Phagwara 144411, India)

  • Deepika Ghai

    (School of Electronics & Electrical Engineering (SEEE), Lovely Professional University, Phagwara 144411, India)

  • Sandeep Kumar

    (Koneru Lakshmaiah Educational Foundation, Vaddeswaram 522302, India)

  • Suman Lata Tripathi

    (School of Electronics & Electrical Engineering (SEEE), Lovely Professional University, Phagwara 144411, India)

  • Chaman Verma

    (Department of Media and Educational Informatics, Faculty of Informatics, Eötvös Loránd University, 1053 Budapest, Hungary)

  • Calin Ovidiu Safirescu

    (Environment Protection Department, Faculty of Agriculture, University of Agricultural Sciences and Veterinary Medicine of Cluj-Napoca, Calea Mănăştur No. 3–5, 400 372 Cluj-Napoca, Romania)

  • Traian Candin Mihaltan

    (Faculty of Building Services, Technical University of Cluj-Napoca, 400 114 Cluj-Napoca, Romania)

Abstract

Land transfiguration is caused by natural as well as phylogenesis-driving forces, and its consequences for the regional environment are a significant issue in understanding the relationship between society and the environment. Land use/land cover plays a crucial part in the determination, preparation, and execution of administrative approaches to fulfilling basic human needs in the present day. In this study, Visakhapatnam, Vijayawada, Tirupati, A.P., India, is considered as a study area to explain the Land use/land cover (LULC) classification, Land Surface Temperature (LST), and the inverse correlation between LST and the NDVI of Temporal Landsat satellite images at intervals of 5 years from 2000 to 2020. We performed easy and thoroughgoing classifications based on vegetation phenology, using an extended LULC field database, a time series of LANDSAT satellite imagery, and a pixel-based classifier. In total, five land-use and land-cover types have been identified: dense vegetation, vegetation, built-up, barren land, and water. Over the period of inquiry, there were notable increases in the area of built-up land, dense vegetation, and vegetation, whereas there was a marked decrease in water bodies and barren land. The diverse effects of land transformation on the natural environment have been assessed using Land Surface Temperature (LST) and the Normalized Difference Vegetation Index (NDVI). The used technique achieved very good levels of accuracy (90–97%) and a strong kappa coefficient (0.89–0.96), with low commission and omission errors. The variation of the land surface temperature was studied using the Mono-Window algorithm. Change detection, and the transition of the natural land cover to man-made land use, were statistically computed for the study area. Results exposed that there had been significant variations in the land use and cover during the tagged eras. In general, two land use and land cover change patterns were confirmed in the study zone: (i) compatible growth of the zone in built-up areas, barren land, plantations, and shrubs; and (ii) continual diminishment in agriculture and water; maximum urban development took place between 2000 to 2020. The results showed drastic changes in urbanization and decrements in vegetation that had environmental consequences.

Suggested Citation

  • Vimala Kiranmai Ayyala Somayajula & Deepika Ghai & Sandeep Kumar & Suman Lata Tripathi & Chaman Verma & Calin Ovidiu Safirescu & Traian Candin Mihaltan, 2022. "Classification and Validation of Spatio-Temporal Changes in Land Use/Land Cover and Land Surface Temperature of Multitemporal Images," Sustainability, MDPI, vol. 14(23), pages 1-35, November.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:23:p:15677-:d:983755
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    References listed on IDEAS

    as
    1. Yan-jun Guo & Jie-jie Han & Xi Zhao & Xiao-yan Dai & Hao Zhang, 2020. "Understanding the Role of Optimized Land Use/Land Cover Components in Mitigating Summertime Intra-Surface Urban Heat Island Effect: A Study on Downtown Shanghai, China," Energies, MDPI, vol. 13(7), pages 1-17, April.
    2. Xinping Zhang & Dexiang Wang & Hongke Hao & Fangfang Zhang & Youning Hu, 2017. "Effects of Land Use/Cover Changes and Urban Forest Configuration on Urban Heat Islands in a Loess Hilly Region: Case Study Based on Yan’an City, China," IJERPH, MDPI, vol. 14(8), pages 1-25, July.
    3. M. Vani & P. Rama Chandra Prasad, 2020. "Assessment of spatio-temporal changes in land use and land cover, urban sprawl, and land surface temperature in and around Vijayawada city, India," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 22(4), pages 3079-3095, April.
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