...
首页> 外文期刊>Remote Sensing of Environment: An Interdisciplinary Journal >Coupling spectral unmixing and trend analysis for monitoring of long-term vegetation dynamics in Mediterranean rangelands
【24h】

Coupling spectral unmixing and trend analysis for monitoring of long-term vegetation dynamics in Mediterranean rangelands

机译:耦合光谱解混和趋势分析,用于监测地中海牧场的长期植被动态

获取原文
获取原文并翻译 | 示例

摘要

The development of vegetation cover is one of the primary indicators for land degradation, stability, or regeneration in regions threatened by overgrazing. This paper addresses the problem how spatially explicit information about degradation processes in European Mediterranean rangelands can be derived from long time series of satellite data. The selected test site in central Crete, Greece, is considered to be representative for the highly heterogeneous character of such landscapes. The monitoring approach comprises the time period between 1977 and 1996, covered by nine Landsat TM and four Landsat MSS images. Special emphasis has hence been put on the evaluation of potentials and drawbacks when coupling Landsat TM and MSS based results. The data sets were geometrically and radiometrically pre-processed in a rigorous fashion, followed by a linear spectral unmixing approach and a time series analysis of vegetation fraction images. Based on the resulting map, the spatio-temporal patterns of vegetation cover changes are explained. Even a test site such as central Crete, with its limited spatial extend, exhibits heterogeneous patterns of change, supporting the hypothesis that long time series of EOS data from Landsat-like sensors are mandatory to identify the relevant changes at landscape level.
机译:植被覆盖的发展是过度放牧威胁地区土地退化,稳定或再生的主要指标之一。本文解决了如何从长时间的卫星数据序列中获得有关欧洲地中海牧场退化过程的空间明确信息的问题。在希腊克里特岛中部选定的测试点被认为是此类景观高度异质性的代表。监测方法包括1977年至1996年的时间段,覆盖了9幅Landsat TM和4幅Landsat MSS图像。因此,在结合使用Landsat TM和MSS的结果时,特别强调了对潜力和缺点的评估。以严格的方式对数据集进行几何和放射学预处理,然后进行线性光谱分解方法和植被分数图像的时间序列分析。根据生成的地图,解释了植被覆盖变化的时空格局。甚至是像克里特岛这样的试验场,其空间扩展都有限,它表现出不同的变化模式,从而支持了这样的假设,即来自Landsat式传感器的EOS数据的长时间序列必须用于识别景观水平的相关变化。

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