全球30m空间分辨率耕地遥感制图研究
发布时间：2018-11-21 19:06
【摘要】：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.
[Abstract]:Cultivated land is one of the most important land cover types in global land cover mapping. The change of cultivated land affects the development of human society and economy, food security and ecological environment protection. The existing global cultivated land mapping products have coarse spatial resolution and lack of global cultivated land data products with high spatial resolution. In this study, we used Landsat TM/ETM (HJ-1), MODIS 250m spatial resolution NDVI time series data and various reference data) in the global 2000 / 2010 two periods of 30m spatial resolution remote sensing image data, aiming at the difficulty of cropland extraction in 30m image of global scale. A method of farmland extraction based on pixel, object and knowledge is proposed, which is based on multi-feature optimization of pixel scale, automatic discrimination of cultivated land based on object and interactive object processing based on information service and prior knowledge. Two periods of remote sensing mapping of 30m cultivated land have been completed, and the global cultivated land area and other information have been statistically analyzed. The results show that the total cultivated land area in 2000 and 2010 is 1.903 billion ha and 1.96 billion ha., respectively. The results of precision evaluation show that the overall accuracy of the global remote sensing mapping of 30m cultivated land in the two periods is over 92%. The global cultivated land remote sensing data products developed in 2000 / 2010 are superior in spatial resolution and classification accuracy to similar products in the world, so they are global food security. The study of ecological environment monitoring and global change provides important basic data.
【作者单位】： 北京师范大学地表过程与资源生态国家重点实验室;国家基础地理信息中心;安徽理工大学测绘学院;
【基金】：国家高技术研究发展计划项目(编号:2009AA122001) 北京师范大学地表过程与资源生态国家重点实验室项目(编号:2013-RC-02) 国家自然科学基金项目(批准号:41301352)资助
【分类号】：S127;F323.211
本文编号：2348017
[Abstract]:Cultivated land is one of the most important land cover types in global land cover mapping. The change of cultivated land affects the development of human society and economy, food security and ecological environment protection. The existing global cultivated land mapping products have coarse spatial resolution and lack of global cultivated land data products with high spatial resolution. In this study, we used Landsat TM/ETM (HJ-1), MODIS 250m spatial resolution NDVI time series data and various reference data) in the global 2000 / 2010 two periods of 30m spatial resolution remote sensing image data, aiming at the difficulty of cropland extraction in 30m image of global scale. A method of farmland extraction based on pixel, object and knowledge is proposed, which is based on multi-feature optimization of pixel scale, automatic discrimination of cultivated land based on object and interactive object processing based on information service and prior knowledge. Two periods of remote sensing mapping of 30m cultivated land have been completed, and the global cultivated land area and other information have been statistically analyzed. The results show that the total cultivated land area in 2000 and 2010 is 1.903 billion ha and 1.96 billion ha., respectively. The results of precision evaluation show that the overall accuracy of the global remote sensing mapping of 30m cultivated land in the two periods is over 92%. The global cultivated land remote sensing data products developed in 2000 / 2010 are superior in spatial resolution and classification accuracy to similar products in the world, so they are global food security. The study of ecological environment monitoring and global change provides important basic data.
【作者单位】： 北京师范大学地表过程与资源生态国家重点实验室;国家基础地理信息中心;安徽理工大学测绘学院;
【基金】：国家高技术研究发展计划项目(编号:2009AA122001) 北京师范大学地表过程与资源生态国家重点实验室项目(编号:2013-RC-02) 国家自然科学基金项目(批准号:41301352)资助
【分类号】：S127;F323.211
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