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Disaggregation of LST over India: comparative analysis of different vegetation indices

Eswar, R and Sekhar, M and Bhattacharya, BK (2016) Disaggregation of LST over India: comparative analysis of different vegetation indices. In: INTERNATIONAL JOURNAL OF REMOTE SENSING, 37 (5). pp. 1035-1054.

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Official URL: http://dx.doi.org/10.1080/01431161.2016.1145363

Abstract

The non-availability of high-spatial-resolution thermal data from satellites on a consistent basis led to the development of different models for sharpening coarse-spatial-resolution thermal data. Thermal sharpening models that are based on the relationship between land-surface temperature (LST) and a vegetation index (VI) such as the normalized difference vegetation index (NDVI) or fraction vegetation cover (FVC) have gained much attention due to their simplicity, physical basis, and operational capability. However, there are hardly any studies in the literature examining comprehensively various VIs apart from NDVI and FVC, which may be better suited for thermal sharpening over agricultural and natural landscapes. The aim of this study is to compare the relative performance of five different VIs, namely NDVI, FVC, the normalized difference water index (NDWI), soil adjusted vegetation index (SAVI), and modified soil adjusted vegetation index (MSAVI), for thermal sharpening using the DisTrad thermal sharpening model over agricultural and natural landscapes in India. Multi-temporal LST data from Landsat-7 Enhanced Thematic Mapper Plus (ETM+) and Moderate Resolution Imaging Spectroradiometer (MODIS) sensors obtained over two different agro-climatic grids in India were disaggregated from 960 m to 120 m spatial resolution. The sharpened LST was compared with the reference LST estimated from the Landsat data at 120 m spatial resolution. In addition to this, MODIS LST was disaggregated from 960 m to 480 m and compared with ground measurements at five sites in India. It was found that NDVI and FVC performed better only under wet conditions, whereas under drier conditions, the performance of NDWI was superior to other indices and produced accurate results. SAVI and MSAVI always produced poorer results compared with NDVI/FVC and NDWI for wet and dry cases, respectively.

Item Type: Journal Article
Publication: INTERNATIONAL JOURNAL OF REMOTE SENSING
Publisher: TAYLOR & FRANCIS LTD
Additional Information: Copy right for this article belongs to the TAYLOR & FRANCIS LTD, 4 PARK SQUARE, MILTON PARK, ABINGDON OX14 4RN, OXON, ENGLAND
Department/Centre: Division of Interdisciplinary Sciences > Interdisciplinary Centre for Water Research
Division of Mechanical Sciences > Civil Engineering
Date Deposited: 23 Apr 2016 07:01
Last Modified: 18 Oct 2018 13:27
URI: http://eprints.iisc.ac.in/id/eprint/53689

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