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耕地是全球地表覆盖制图中重要的地表覆盖类型之一,其变化影响着人类社会经济发展、粮食安全与生态环境保护.现有全球耕地制图产品空间分辨率较粗,缺乏高空间分辨率的全球耕地数据产品.本研究利用全球2000/2010两期30m空间分辨率遥感影像数据集(Landsat TM/ETM+、HJ-1)、MODIS 250m空间分辨率NDVI时间序列数据及多种参考资料,针对全球尺度30m影像中耕地提取的难点,提出基于像元、对象和知识3个层次的耕地提取方法,即基于像元尺度多特征优化的耕地分类提取、基于对象的耕地自动判别以及基于信息服务和先验知识的交互式对象处理,完成了全球两期30m耕地遥感制图,并对全球耕地的面积等信息进行统计分析.结果表明,全球2000年和2010年耕地总面积分别为19.03亿ha和19.60亿ha.精度评价结果表明,两期全球30m耕地遥感制图总体精度均达到92%以上.本研究研制的2000/2010两期的全球耕地遥感数据产品,在空间分辨率和分类精度上均优于国际上同类产品,为全球粮食安全、生态环境监测和全球变化等研究提供了重要基础数据.
Cultivated land is one of the most important types of land cover in the world’s surface coverage mapping, and its changes affect the social and economic development of humankind, food security and ecological environment protection.Currently, the global spatial resolution of cultivated land mapping products is rather coarse and lacks global spatial resolution Cultivated land data product.This study used the global 2000/2010 30m spatial resolution remote sensing image dataset (Landsat TM / ETM +, HJ-1), MODIS 250m spatial resolution NDVI time series data and a variety of reference materials for the global scale Aiming at the difficulty of extracting cultivated land from 30m images, a method of cropland extraction based on pixel, object and knowledge is put forward, which is cropland classification extraction based on multi-feature optimization of pixel scale, object-based automatic discrimination of cultivated land and information service and priori Knowledge and interactive object processing, completed the global 30m remote sensing mapping of cultivated land and conducted statistical analysis on the information such as the area of cultivated land in the world.The results showed that the total cultivated area in the world in 2000 and 2010 were 1.903 billion ha and 1.96 billion ha respectively The results of precision evaluation showed that the overall accuracy of remote sensing mapping of 30m cultivated land in two phases reached over 92% in 2000. The 2000/2010 Of the global arable land remote sensing data products, on the classification accuracy and spatial resolution are better than the similar products, provide important basic data for the study of food security, environmental monitoring and global change the world.