User's Guide FPAR, LAI (ESDT: MOD15A2) 8-day Composite NASA MODIS Land Algorithm
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چکیده
منابع مشابه
Comparison of seasonal and spatial variations of leaf area index and fraction of absorbed photosynthetically active radiation from Moderate Resolution Imaging Spectroradiometer (MODIS) and Common Land Model
[1] This paper compares by land cover type seasonal and spatial variations of MODIS leaf area index (LAI) and fraction of photosynthetically active radiation (0.4–0.7 mm) absorbed by vegetation (FPAR) from 2.5 years with those from the Common Land Model (CLM) and investigates possible reasons for notable differences. The FPAR value is mainly determined by LAI in MODIS and both LAI and stem area...
متن کاملComparing the Dry Season In-Situ Leaf Area Index (LAI) Derived from High-Resolution RapidEye Imagery with MODIS LAI in a Namibian Savanna
The Leaf Area Index (LAI) is one of the most frequently applied measures to characterize vegetation and its dynamics and functions with remote sensing. Satellite missions, such as NASA’s Moderate Resolution Imaging Spectroradiometer (MODIS) operationally produce global datasets of LAI. Due to their role as an input to large-scale modeling activities, evaluation and verification of such datasets...
متن کاملValidation of MODIS and GEOV1 fPAR Products in a Boreal Forest Site in Finland
Remote sensing of the fraction of absorbed Photosynthetically Active Radiation (fPAR) has become a timely option to monitor forest productivity. However, only a few studies have had ground reference fPAR datasets containing both forest canopy and understory fPAR from boreal forests for the validation of satellite products. The aim of this paper was to assess the performance of two currently ava...
متن کاملThe Performances of MODIS-GPP and -ET Products in China and Their Sensitivity to Input Data (FPAR/LAI)
The aims are to validate and assess the performances of MODIS gross primary production (MODIS-GPP) and evapotranspiration (MODIS-ET) products in China’s different land cover types and their sensitivity to remote sensing input data. In this study, MODIS-GPP and -ET are evaluated using flux derived/measured data from eight sites of ChinaFLUX. Results show that MODIS-GPP generally underestimates G...
متن کاملLand cover mapping in support of LAI and FPAR retrievals from EOS-MODIS and MISR: classification methods and sensitivities to errors
Land cover maps are used widely to parameterize the biophysical properties of plant canopies in models that describe terrestrial biogeochemical processes. In this paper, we describe the use of supervised classification algorithms to generate land cover maps that characterize the vegetation types required for Leaf Area Index (LAI) and Fraction of Photosynthetically Active Radiation (FPAR) retrie...
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