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Land use/land cover and land surface temperature analysis in Wayanad district, India, using satellite imagery
J. John, G. Bindu, , A. Wadhwa, P. Rajan
Published in Taylor and Francis Ltd.
2020
Volume: 26
   
Issue: 4
Pages: 343 - 360
Abstract
This paper assesses Land Use/Land Cover (LULC) classification and Land Surface Temperature (LST) in Wayanad district during the years 2004 and 2018. The LULC classification of Wayanad district is identified using IRS P6 (Linear Imaging Self Scanner) LISS- III, and LST using thermal band of (Enhanced Thematic Mapper Plus) ETM+ imageries. Maximum likelihood classification (MLC) technique is opted to categorize six land-use features: water body, paddy field, forest, dense, agricultural crops and built-up. From 2004 to 2018, impacts of changes in features are correlated with the raised LST. Overall vegetation cover shows an increasing pattern during the study period. The water bodies in Wayanad district improved from 4.30 to 32.68 sq.km due to construction of two dams: Banasurasagar and Karappuzha. However, agricultural crops and paddy field area have decreased by 4.7% in last 14 years. Decreasing rate of agricultural crops can be directly linked to population growth, thereby developing various built-up zones for basic needs. Forest and dense vegetated cover area are increased nearly 2.3 and 3.0%, respectively, during the study period, while bamboo degradation has also been witnessed from 2008 to 2013. The built-up class shows growth from 1.48 to 5.69% of total land area during 2004 and 2018. LULC have noticeable influences on LST with a negative correlation between vegetation cover and LST with a decrease of 1.75oC. The study findings can help the local authorities to implement urban planning regulations for public awareness and policy makers for a sustainable planning and management in forthcoming years. © 2020 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group, on behalf of Nanjing Normal University.
About the journal
JournalData powered by TypesetAnnals of GIS
PublisherData powered by TypesetTaylor and Francis Ltd.
ISSN19475683