JIA-2018-09

1925 Yanbo Huang et al. Journal of Integrative Agriculture 2018, 17(9): 1915–1931 With medium-resolution SPOT image analysis, crop (rice, soybean and corn) area change was determined (Chen et al. 2011). Wheat, corn, soybean and rice growth dynamics were monitored through analysis of high temporal resolution data by the integration of ground observation, agronomic models and low-resolution MODIS remote sensing imagery. Rice growth was monitored through analysis of MODIS imagery (Huang et al. 2012). Soil moisture of farm land in China was monitored through analysis of MODIS imagery (Chen et al. 2011). Crop yields were estimated through integration of remote sensing analysis with crop growth models, agricultural meteorological models and yield trend models (Ren et al. 2008, 2011). Remote sensing data analysis of MODIS imagery was conducted for drought, flood, snow and wild fire monitoring and loss assessment. Remote sensing data analysis was conducted for pest management in crop production in farm land of north and northeast of China. Remote sensing-based dynamical Type? Broadband Narrowband Images RGB CIR Thermal Hyperspectral cube Multispectral images Geometric and radiometric corrections Field 1 Field 2 Field n Image fusion? Image mosaic Image resolution improvement Image time series Analysis Sensitivity analysis and band selection VI/Classification Biophysical & biochemical parameter inversion Assimilation with crop models Results and products distribution No Yes Narrowband Hyperspectral … … … Image coverage clustering Fig. 3 Remote sensing image processing, analysis and management flow for supporting precision agriculture. RGB, red, green and blue; CIR, color infrared; VI, vegetation index.