• 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>Fresenius Environmental Bulletin >LONG-TERM TIME SERIES OF VEGETATION VARIATIONS AND ITS RELATIONSHIP WITH CLIMATE FACTORS BY INTEGRATING AVHRR GIMMS AND TERRA MODIS DATA
【24h】

LONG-TERM TIME SERIES OF VEGETATION VARIATIONS AND ITS RELATIONSHIP WITH CLIMATE FACTORS BY INTEGRATING AVHRR GIMMS AND TERRA MODIS DATA

机译：结合AVHRR GIMMS和TERRA MODIS数据进行植被变化的长期时间序列及其与气候因子的关系。

获取原文
获取原文并翻译 | 示例
           
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

Long-term time series of Normalized Difference Vegetation Index datasets is key for the monitoring of land surface dynamics and vegetation change. We evaluated the Advanced Very High Resolution Radiometer (AVHRR) Global Inventory Modeling and Mapping Studies (GIMMS) NDVI and the Moderate Resolution Imaging Spectroradiometer (MODIS) ND'VI for the same time period from 2000 to 2006 for a comparative analysis. Prior to use, both datasets have been processed using the Savitzky-Golay filter to reduce the effects of clouds, atmosphere, sensor properties and behaviour and the surface Bidirectional Distribution Reflectance Function (BDRF). The average Normalized Difference Vegetation Index, monthly Coefficient of Variation and trends of GIMMS and MODIS datasets are typically in alignment. A high correlation of 98.1% pixels (r >= 0.9, P<0.05) are observed between the GIMMS and MODIS datasets. The correlation coefficient, intercept and slope parameters using the two datasets have been calculated to derive a new GIMMS dataset (1982-2006). A long-term series dataset (1982 to 2013) was subsequently produced at 8 km spatial resolution for the Northeast of China by integrating the new MEWS (1982-2000) and MODIS (2001-2013) datasets. The expanded Normalized Difference Vegetation Index dataset passed consistency tests based on the linear regression for each pixel and was utilized for the 1982-2013 long-term series analysis. Significant correlations were detected between the monthly Normalized Difference Vegetation Index trends and regional climatic change.
机译：标准化差异植被指数数据集的长期时间序列是监测土地表面动态和植被变化的关键。我们对2000年至2006年同期的先进超高分辨率辐射计（AVHRR）全球清单建模和制图研究（GIMMS）NDVI和中分辨率成像光谱仪（MODIS）ND'VI进行了评估，以进行比较分析。在使用之前，两个数据集均已使用Savitzky-Golay滤波器进行了处理，以减少云，大气，传感器属性和行为以及表面双向分布反射函数（BDRF）的影响。 GIMMS和MODIS数据集的平均归一化植被指数，月变化系数和趋势通常是一致的。在GIMMS和MODIS数据集之间观察到98.1％像素的高度相关性（r> = 0.9，P <0.05）。已经使用这两个数据集计算了相关系数，截距和斜率参数，以得出一个新的GIMMS数据集（1982-2006）。随后，通过整合新的MEWS（1982-2000）和MODIS（2001-2013）数据集，在中国东北以8 km的空间分辨率生成了一个长期序​​列数据集（1982年至2013年）。扩展后的标准化差异植被指数数据集通过了基于每个像素的线性回归的一致性测试，并用于1982-2013年长期序列分析。在月均归一化植被指数趋势和区域气候变化之间发现了显着的相关性。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号