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首页> 外文会议>Conference on Biological Quality and Precision Agriculture II, Nov 6-8, 2000, Boston, USA >Analysis of Vegetation Green Wave Change in China Using NOAA AVHRR Data Sets
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Analysis of Vegetation Green Wave Change in China Using NOAA AVHRR Data Sets

机译：基于NOAA AVHRR数据集的中国植被绿波变化分析

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摘要

NOAA-AVHRR data have a daily coverage, synoptic overview, data volume, and low cost, so the global change scientific community has identified the AVHRR data set as an important database for land and vegetation cover mapping and land processes modeling at continental and global scales (IGBP 1992). In this study, a series of 12 monthly average NDVI data is used to analysis vegetation cover change from January 1990 ― December 1990 for whole China. The result indicates that the vegetation cover change is different along the longitude and latitude during a year. Along the same longitude, vegetation index change is closely corresponded to the seasonal change law. Especially in the eastern agriculture area, there is one peak NDVI value in North East Plain, two peak NDVI value in North China Plain, and three Peak NDVI value in Pear River Plain over a year respectively, which is closely related to crop harvest times during a year. Along the same latitude the vegetation index change is closely related to precipitation change. Generally, there is a high NDVI value curve in the eastern fores area during the forest-growing season, but NDVI value is simply no change in the Western desert area over a year due to less vegetation there. When greenness classification is completed for each monthly NDVI image, the result shows that there is a quite big NDVI value change between summer and winter. In summer greenness value o grassland, mixed forest, and forest types classes occupy 76.70% of whole china, there is no clear difference in vegetation index between south and north, but in winter this difference is much clear. In winter, the greenness value of desert and little vegetation classes occupy 76.40 % for the total territor due to the monsoon climate effluence. Vegetation cover change is difficult task due to its more dynamic, which is caused by seasonal change as well as long -term climate or land management change. For the further work related to long the study of long-term vegetation cover change and climate retrieval, it requires long-term time series NOAA AVHRR data as well as historical and ground truth data.
机译：NOAA-AVHRR数据每天都有覆盖，摘要，数据量大且成本低廉，因此，全球变化科学界已将AVHRR数据集确定为陆地和植被覆盖图以及大陆和全球范围内土地过程建模的重要数据库（IGBP 1992）。在这项研究中，使用了一系列12个月平均NDVI数据来分析1990年1月至1990年12月整个中国的植被覆盖变化。结果表明，一年中植被覆盖度的变化沿经纬度不同。在相同的经度上，植被指数变化与季节变化规律密切相关。尤其是在东部农业区，一年中东北平原有一个NDVI峰值，华北平原有两个NDVI峰值，而梨河平原有三个NDVI峰值，这与作物收获期的收获时间密切相关。一年。在同一纬度上，植被指数变化与降水变化密切相关。通常，在森林生长季节，东部森林区的NDVI值曲线较高，但由于沙漠中的植被较少，NDVI值在西部沙漠地区一年中根本没有变化。对每个月度NDVI图像完成绿色分类后，结果表明，夏季和冬季之间NDVI值会有很大变化。夏季，草地，混交林和森林类型类别的绿色度值占整个中国的76.70％，南北之间的植被指数没有明显的差异，但是在冬季，这种差异非常明显。在冬季，由于季风性气候影响，沙漠和几乎没有植被的绿化价值占整个领土的76.40％。植被变化是一项艰巨的任务，因为它更具动态性，这是由季节变化以及长期气候或土地管理变化引起的。对于与长期研究长期植被变化和气候恢复有关的进一步工作，它需要长期时间序列NOAA AVHRR数据以及历史和地面真实数据。

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