首页> 外文OA文献 >Remote sensing of vegetation dynamics in drylands: Evaluating vegetation optical depth (VOD) using AVHRR NDVI and in situ green biomass data over West African Sahel
【2h】

Remote sensing of vegetation dynamics in drylands: Evaluating vegetation optical depth (VOD) using AVHRR NDVI and in situ green biomass data over West African Sahel

机译:遥感干旱地区的植被动态:使用AVHRR NDVI和西非萨赫勒地区的原地绿色生物量数据评估植被光学深度(VOD)

代理获取
本网站仅为用户提供外文OA文献查询和代理获取服务,本网站没有原文。下单后我们将采用程序或人工为您竭诚获取高质量的原文,但由于OA文献来源多样且变更频繁,仍可能出现获取不到、文献不完整或与标题不符等情况,如果获取不到我们将提供退款服务。请知悉。

摘要

Monitoring long-term biomass dynamics in drylands is of great importance for many environmental applications including land degradation and global carbon cycle modeling. Biomass has extensively been estimated based on the normalized difference vegetation index (NDVI) as a measure of the vegetation greenness. The vegetation optical depth (VOD) derived from satellite passive microwave observations is mainly sensitive to the water content in total aboveground vegetation layer. VOD therefore provides a complementary data source to NDVI for monitoring biomass dynamics in drylands, yet further evaluations based on ground measurements are needed for an improved understanding of the potential advantages. In this study, we assess the capability of a long-term VOD dataset (1992–2011) to capture the temporal and spatial variability of in situ measured green biomass (herbaceous mass and woody plant foliage mass) in the semi-arid Senegalese Sahel. Results show that the magnitude and peak time of VOD are sensitive to the woody plant foliage whereas NDVI seasonality is primarily governed by the green herbaceous vegetation stratum in the study area. Moreover, VOD is found to be more robust against typical NDVI drawbacks of saturation effect and dependence on plant structure (herbaceous and woody compositions) across the study area when used as a proxy for vegetation productivity. Finally, both VOD and NDVI well reflect the spatial and inter-annual dynamics of the in situ green biomass data; however, the seasonal metrics showing the highest degree of explained variance differ between the two data sources. While the observations in October (period of in situ data collection) perform best for VOD (r2 = 0.88), the small growing season integral (sensitive to recurrent vegetation) have the highest correlations for NDVI (r2 = 0.90). Overall, in spite of the coarse resolution, the study shows that VOD is an efficient proxy for estimating green biomass of the entire vegetation stratum in the semi-arid Sahel and likely also in other dryland areas.
机译:对于许多环境应用(包括土地退化和全球碳循环模型),监测干旱地区的长期生物量动态至关重要。根据归一化差异植被指数(NDVI)作为植被绿度的度量,已经对生物量进行了广泛的估算。来自卫星被动微波观测的植被光学深度(VOD)主要对地上总植被层中的水分敏感。因此,VOD提供了NDVI的补充数据源,用于监测干旱地区的生物量动态,但仍需要基于地面测量值进行进一步评估,以更好地了解潜在优势。在这项研究中,我们评估了一个长期VOD数据集(1992-2011年)捕获半干旱塞内加尔萨赫勒地区原位测量的绿色生物量(草皮质量和木本植物叶子质量)的时空变化的能力。结果表明,VOD的大小和峰值时间对木本植物的叶子敏感,而NDVI的季节性主要受研究区域中绿色草本植物地层的控制。此外,在用作研究植被生产力的代用物时,发现VOD对整个研究区域的典型NDVI缺点(饱和效应和对植物结构(草皮和木质成分)的依赖性)具有更强的抵抗力。最后,VOD和NDVI都很好地反映了原地绿色生物量数据的空间和年际动态。但是,两个数据源之间的季节性指标显示出最高的解释方差。尽管十月份的观测结果(就地数据收集周期)对VOD的效果最好(r2 = 0.88),但小生长期积分(对轮回植被敏感)与NDVI的相关性最高(r2 = 0.90)。总体而言,尽管分辨率很低,但研究表明,VOD是估算半干旱萨赫勒地区以及其他干旱地区的整个植被层绿色生物量的有效代理。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
代理获取

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