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Upscaling of leaf area index in Terai forest plantations using fine- and moderate-resolution satellite data

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Ecophysiological variables, such as leaf area index (LAI), play a key role in the functioning of ecosystem processes and are thus a useful determinant of primary production, evapotranspiration, and biogeochemical cycling. In the present study, upscaling of LAI was carried out by applying a transfer function from field LAI measurements to fine-resolution LISS III images and subsequently to coarse resolution Moderate Resolution Imaging Spectroradiometer (MODIS) data using a photosynthetically active radiation (PAR)/LAI ceptometer (AccuPAR model LP-80). Field data were collected from differently aged forest plantation types in the Terai Central Forest Division of Nainital district in Uttarakhand, India. The upscaling was done by establishing an empirical exponential relationship between normalized difference vegetation index (NDVI) and LAI. Results reveal a significant relationship (p < 0.01) between NDVI and LAI for each of the studied plantation types, i.e. teak, poplar, eucalyptus, and mixed plantation. The LAI was mapped at 23.5 m resolution by applying a plantation-specific LAI versus NDVI relationship derived from IRS Linear Imaging Self-Scanning Sensor images. The LAI maps were upscaled by using a simple linear averaging within nonoverlapping windows to match with Terra–MODIS 250 m resolution NDVI images. The upscaled time series of LAI was compared with representative field-measured LAI measurements and also with MODIS LAI at a resolution of 1000 m. Upscaled LAI was found to be significantly related to the field-measured LAI with a value of 0.69 for coefficient of determination and with a root mean square error of 0.77. On the other hand, upscaled LAI has less agreement with the MODIS LAI product (R 2 = 0.5 and root mean square error = 0.70).
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Document Type: Research Article

Affiliations: 1: CORAL, Indian Institute of Technology, Kharagpur, 721302, India 2: Agriculture and Soil Department, Indian Institute of Remote Sensing, Dehradun, 248001, India

Publication date: November 17, 2014

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