Dissertation > Industrial Technology > Automation technology,computer technology > Remote sensing technology > The application of remote sensing technology

The Remote Monitoring for Multiple Cropping Index of Arable Land in East China Monsoon Area

Author WuYan
Tutor LiuShouDong;HuangJingFeng
School Nanjing University of Information Engineering
Course Applied Meteorology
Keywords multiple cropping index MODIS-NDVI five-points weighted average method potential multiple cropping index
Type Master's thesis
Year 2008
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Multiple cropping index is a basic indicator in agricultural statistic in China, which represents the degree of intensive arable land use effectively. Because the multiple cropping index calculated on the base of statistic data is not ensured, there will be some deviation in policy-making. With the continuous development of remote sensing technology, satellite remote sensing has become the most effective method to survey the large-scale land cover pattern. Based on the MODIS-NDVI (normalized difference vegetation index) data from NASA in America, this dissertation monitors the multiple cropping index of arable land in east China monsoon area using five-points weighted average method for 2001. According to the results of multiple cropping capacity estimated, this paper has analyzed the multiple cropping capacity can be further exploited for different regions.The main conclusions are as following:(1) Analyzed the crop growth and the corresponding pixel’s time series of NDVI, the research concludes that the curve of time series of NDVI is the record of dynamics of crops cultivated in the arable land. The peaks and troughs of the time series of NDVI are related to crop growth. The fluctuate of time series of NDVI represent the performance of sequential cropping and the multiple cropping index is equal to the number of peaks of time series of NDVI.(2) This research has analyzed a lot of pixel’s time series of NDVI and used five-points weighted average method to smooth the time series of NDVI. There is a methodology extracting peaks had been designed to extracting the multiple cropping index. The methodology for smoothing and extracting peaks is accurate and has high rate of speed calculation, it is also more in line with the biological significance of crops. The statistical validation of multiple cropping index shows that the relative errors of 2/3 of the provinces in east China monsoon area are less than 15% so the result can be used for study of multiple cropping index.(3) Based on the MODIS-NDVI data the result of the multiple cropping index shows that there is a obvious geographical distribution of the multiple cropping index in east China monsoon area. The multiple cropping index gradually increases from the northeast to west, south. The multiple cropping index in northeast area of China is the smallest and about 100%. And the index in south China is largest and about 250%. The geographical distribution of the multiple cropping index is consistent to the climate change in east China monsoon area. Under the same climate condition the multiple cropping indexes of economically developed regions are bigger than the indexes of the cities underdeveloped. (4) According to multiple cropping capacity estimated by climate condition, there have little potential multiple cropping to be exploited in Northeast. There have 30~40% potential multiple cropping to be exploited in region of Huanghuaihai and loess plateau area except Shaanxi Province and 50~80% in the middle - lower Yangtze area except Anhui Province. The multiple cropping capacity further exploited in Fujian Province is about 80% and the other is from 30% to 50%. The multiple cropping capacity further exploited has 20~45% in southwest China.

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