Journal
INTERNATIONAL JOURNAL OF REMOTE SENSING
Volume 36, Issue 19-20, Pages 4864-4878Publisher
TAYLOR & FRANCIS LTD
DOI: 10.1080/01431161.2015.1040132
Keywords
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Funding
- Excellent Young Talent Funds for Kezhen Distinguished Young Scholar in the Institute of Geographic Sciences and Natural Resources Research (IGSNRR) [2012RC101]
- Chinese Academy of Sciences (CAS) [2012RC101]
- National Natural Science Foundation of China [41171287]
- Hi-Tech Research and Development Programme of China [863 Plan Programme] [2012AA12A305, 2012AA12A302]
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This work estimated the land surface emissivities (LSEs) for MODIS thermal infrared channels 29 (8.4-8.7m), 31 (10.78-11.28m), and 32 (11.77-12.27m) using an improved normalized difference vegetation index (NDVI)-based threshold method. The channel LSEs are expressed as functions of atmospherically corrected reflectance from the MODIS visible and near-infrared channels with wavelengths ranging from 0.4 to 2.2m for bare soil. To retain the angular information, the vegetation LSEs were explicitly expressed in the NDVI function. The results exhibited a root mean square error (RMSE) among the estimated LSEs using the improved method, and those calculated using spectral data from Johns Hopkins University (JHU) are below 0.01 for channels 31 and 32. The MODIS land surface temperature/emissivity (LST/E) products, MOD11_L2 with LSE derived via the classification-based method with 1km resolution and MOD11C1 with LSE retrieved via the day/night LST retrieval method at 0.05 degrees resolution, were used to validate the proposed method. The resultant variances and entropies for the LSEs estimated using the proposed method were larger than those extracted from MOD11_L2, which indicates that the proposed method better described the spectral variation for different land covers. In addition, comparing the estimated LSEs to those from MOD11C1 yielded RMSEs of approximately 0.02 for the three channels; however, more than 70% of pixels exhibited LSE differences within 0.01 for channels 31 and 32, which indicates that the proposed method feasibly depicts LSE variation for different land covers.
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