title: Comparability of red/near-infrared reflectance and NDVI based on the spectral response function between MODIS and 30 other satellite sensors using rice canopy spectra.
abstract: Long-term monitoring of regional and global environment changes often depends on the combined use of multi-source sensor data. The most widely used vegetation index is the normalized difference vegetation index (NDVI), which is a function of the red and near-infrared (NIR) spectral bands. The reflectance and NDVI data sets derived from different satellite sensor systems will not be directly comparable due to different spectral response functions (SRF), which has been recognized as one of the most important sources of uncertainty in the multi-sensor data analysis. This study quantified the influence of SRFs on the red and NIR reflectances and NDVI derived from 31 Earth observation satellite sensors. For this purpose, spectroradiometric measurements were performed for paddy rice grown under varied nitrogen levels and at different growth stages. The rice canopy reflectances were convoluted with the spectral response functions of various satellite instruments to simulate sensor-specific reflectances in the red and NIR channels. NDVI values were then calculated using the simulated red and NIR reflectances. The results showed that as compared to the Terra MODIS, the mean relative percentage difference (RPD) ranged from -12.67% to 36.30% for the red reflectance, -8.52% to -0.23% for the NIR reflectance, and -9.32% to 3.10% for the NDVI. The mean absolute percentage difference (APD) compared to the Terra MODIS ranged from 1.28% to 36.30% for the red reflectance, 0.84% to 8.71% for the NIR reflectance, and 0.59% to 9.32% for the NDVI. The lowest APD between MODIS and the other 30 satellite sensors was observed for Landsat5 TM for the red reflectance, CBERS02B CCD for the NIR reflectance and Landsat4 TM for the NDVI. In addition, the largest APD between MODIS and the other 30 satellite sensors was observed for IKONOS for the red reflectance, AVHRR1 onboard NOAA8 for the NIR reflectance and IKONOS for the NDVI. The results also indicated that AVHRRs onboard NOAA7-17 showed higher differences than did the other sensors with respect to MODIS. A series of optimum models were presented for remote sensing data assimilation between MODIS and other sensors.
authors.affiliation: College of Southeast Land Management, Zhejiang University, Hangzhou, 310029, China. hjf@zju.edu.cn.
authors.forename: Weijiao
authors.initials: W
authors.lastname: Huang
authors.forename: Jingfeng
authors.initials: J
authors.lastname: Huang
authors.forename: Xiuzhen
authors.initials: X
authors.lastname: Wang
authors.forename: Fumin
authors.initials: F
authors.lastname: Wang
authors.forename: Jingjing
authors.initials: J
authors.lastname: Shi
mesh_terms: D000465:Algorithms; D004784:Environmental Monitoring / Q000295:instrumentation* / Q000379:methods*; D012275:Oryza / Q000254:growth & development*; D017215:Satellite Communications / Q000295:instrumentation*; D019265:Spectroscopy, Near-Infrared / Q000295:instrumentation* / Q000379:methods*