...
首页> 外文期刊>Remote Sensing of Environment: An Interdisciplinary Journal >Quantification of aboveground rangeland productivity and anthropogenic degradation on the Arabian Peninsula using Landsat imagery and field inventory data
【24h】

Quantification of aboveground rangeland productivity and anthropogenic degradation on the Arabian Peninsula using Landsat imagery and field inventory data

机译:使用Landsat影像和现场清单数据量化阿拉伯半岛上的地上土地生产力和人为退化

获取原文
获取原文并翻译 | 示例
           

摘要

The productivity of semi-arid rangelands on the Arabian Peninsula is spatially and temporally highly variable, and increasing grazing pressure as well as the likely effects of climatic change further threatens vegetation resources. Using the Al Jabal al Akhdar mountains in northern Oman as an example, our objectives were to analyse the availability and spatial distribution of aboveground net primary production (ANPP) and the extent and causes of vegetation changes during the last decades with a remote sensing approach. A combination of destructive and non-destructive biomass measurements by life-form specific allometric equations was used to identify the ANPP of the ground vegetation (<50cm) and the leaf and twig biomass of phanerophytes. The ANPP differed significantly among the life forms and the different plant communities, and the biomass of the sparsely vegetated ground was more than 50 times lower (mean=0.22tDMha~(-1)) than the biomass of phanerophytes (mean=12.3tDMha~(-1)). Among the different vegetation indices calculated NDVI proved to be the best predictor for rangeland biomass. Temporal trend analysis of Landsat satellite images from 1986 to 2009 was conducted using a pixel-based least square regression with the annual maximum Normalized Differenced Vegetation Index (NDVI_(max)) as a dependent variable. Additionally, linear relationships of NDVI_(max) and annual rainfall along the time series were calculated. The extent of human-induced changes was analysed using the residual trends method. A strongly significant negative biomass trend detected for 83% of the study area reflected a decrease in annual rainfall but even without clear evidence of deforestation of trees and shrubs, human-induced vegetation degradation due to settlement activities were also important.
机译:阿拉伯半岛半干旱牧场的生产力在空间和时间上高度可变,放牧压力的增加以及气候变化的可能影响进一步威胁了植被资源。以阿曼北部的Al Jabal al Akhdar山区为例,我们的目标是使用遥感方法分析近几十年来地上净初级生产力(ANPP)的可用性和空间分布以及植被变化的程度和原因。通过特定于生命形式的异速方程将破坏性和非破坏性生物量测量相结合,可用于识别地面植被(<50cm)的ANPP以及旱生植物的叶片和树枝生物量。在不同的生命形式和不同的植物群落中,ANPP差异显着,稀疏植被地的生物量(比平均生物量(平均= 12.3tDMha〜)低50倍以上(平均值= 0.22tDMha〜(-1))。 (-1))。在不同的植被指数中,计算得出的NDVI被证明是牧场生物量的最佳预测指标。 1986年至2009年Landsat卫星图像的时间趋势分析是使用基于像素的最小二乘回归法进行的,该回归法以年最大归一化差异植被指数(NDVI_(max))为因变量。此外,还计算了NDVI_(max)与年降雨量在时间序列上的线性关系。使用残留趋势法分析了人为变化的程度。在研究区域的83%处检测到的强烈的负生物量趋势非常明显,这反映了年降水量的减少,但即使没有明显的树木和灌木丛砍伐的证据,由于定居活动而导致的人为植被退化也很重要。

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