Presentation on theme: "Experience and Achievement of Remote Sensing Applications in Agriculture Tang Huajun Institute of Agricultural Resources and Regional Planning CAAS, China."— Presentation transcript:
Experience and Achievement of Remote Sensing Applications in Agriculture Tang Huajun Institute of Agricultural Resources and Regional Planning CAAS, China
Remote Sensing in Agriculture Crop Monitoring Agricultural Land Use Changes Disasters Monitoring and Management
Yield Prediction Model Structure The basic idea is the stepwise regression method to set up crop yield estimation models. Firstly, based on the statistical data of crop production, meteorological data, and remotely- sensed NDVI data, set up the yield prediction model clusters for sampled counties.
NATURAL DISASTERS IN CHINA 4-8%GNP Direct damage caused by natural disasters in China from 1989 to 2002 (unit: 1 billion RMB yuan)
1/3 world agricultural land: arid and semi-arid regions year of 206 to 1949: 1086 times severe drought year of 1950 to 2003: 26 times severe drought 25 % of total arable land affected by severe drought/year 33 million kg grain loss/year drought loss: 57 % Drought: occurs more frequently, lasts longer & affects larger area
1954 Flood of Yangtze River Floods: caused direct economic loss 1998 Floods of Yangtze River On the average, about 9 million hectares of farmland are affected annually by floods in the past five decades. Direct economic loss: >12 b $ Direct economic loss: about 18 b $ 1991 Flood of Huaihe River Direct economic loss: 4 b $
DISCUSSION AND CONCLUSION Accurate estimates and quick forecasts early Data acquisition (satellite, weather parameters, social economic statistics and field observations) and multi-data sources Cooperation and information sharing