The first 19 bands of a moderate-resolution imaging spectrometer (MODIS), covering the visible to short wave infrared spectral wavelength, were simulated by ground-level reflectance spectra. | Q. CHENG, X. WU Research Article Turk J Agric For 35 (2011) 579-589 © TÜBİTAK doi: Mapping paddy rice yield in Zhejiang Province using MODIS spectral index Qian CHENG*, Xiuju WU Department of Environmental Resources Management and City Planning, Zhejiang Gongshang University, Hangzhou, 310035 - CHINA Received: Abstract: The first 19 bands of a moderate-resolution imaging spectrometer (MODIS), covering the visible to shortwave infrared spectral wavelength, were simulated by ground-level reflectance spectra. All spectral indices similar to the normalized difference vegetation index (NDVI) and ratio vegetation index (RVI) formed by every 2 bands were calculated to obtain their determination coefficients, with theoretical and real yield. Results revealed that the combinative nearinfrared (NIR) index (band 2 and band 19, symbol b2 and b19, and other similar ones) and the (b16, b19) of MODIS were strongly correlated with rice yield, especially the correlative coefficient that exceeded significant levels in the maturing stage. However, combinative visible light index was correlated with rice yield strongly in the early stage and poorly in the latter stage. The best spectral indices for predicting rice yield in whole rice growth were the combinations of (b2, b19) and (b16, b19). Based on the 2-band combination of the (b2, b19) of MODIS and the constructed estimating model, the rice yield of Zhejiang Province was estimated and its spatial distribution was mapped. Estimated results based on MODIS images were validated using 8 measured validation sites. Errors in the estimated rice yield ranged from to , with a mean value of . The results indicated that the 2-band combination of the (b2, b19) MODIS index was most suitable for monitoring rice yield. Key words: Estimation, rice yield, MODIS, spectral index Introduction Among the various modern methods for estimating rice yield, remote sensing is of primary importance. This is
