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Drought monitoring with remote sensing based land surface phenology applications and validation.

机译：基于遥感的土地表面物候应用和验证进行干旱监测。

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摘要

Droughts are a recurrent part of our climate, and are still considered to be one of the most complex and least understood of all natural hazards in terms of their impact on the environment. In recent years drought has become more common and more severe across the world. For more than a decade, the US southwest has faced extensive and persistent drought conditions that have impacted vegetation communities and local water resources. The focus of this work is achieving a better understanding of the impact of drought on the lands of the Hopi Tribe and Navajo Nation, situated in the Northeastern corner of Arizona. This research explores the application of remote sensing data and geospatial tools in two studies to monitor drought impacts on vegetation productivity. In both studies we used land surface phenometrics as the data tool. In a third related study, I have compared satellite-derived land surface phenology (LSP) to field observations of crop stages at the Maricopa Agricultural Center to achieve a better understanding of the temporal sensitivity of satellite derived phenology of vegetation and understand their accuracy as a tool for monitoring change.;The first study explores long-term vegetation productivity responses to drought. The paper develops a framework for drought monitoring and assessment by integrating land cover, climate, and topographical data with LSP. The objective of the framework is to detect long-term vegetation changes and trends in the Normalized Difference Vegetation Index (NDVI) related productivity.;The second study examines the major driving forces of vegetation dynamics in order to provide valuable spatial information related to inter-annual variability in vegetation productivity for mitigating drought impacts.;The third study tests the accuracy of remote sensing-derived LSP by comparing them to the actual seasonal phases of crop growth. This provides a way to compare and validate the various LSP algorithms, and more crucially, helps to characterize the remote sensing-based metrics that contrast with the actual biological phenophases of the crops.;These studies demonstrate how remote sensing data and simple statistical tools can be used to assess drought effects on vegetation productivity and to inform about land conditions, as well as to better understand the accuracy of satellite derived LSP.
机译：干旱是我们气候中反复出现的一部分，就其对环境的影响而言，仍然被认为是所有自然灾害中最复杂，了解最少的自然灾害之一。近年来，干旱在世界范围内变得更加普遍和严重。十多年来，美国西南部面临着广泛而持续的干旱条件，影响了植被群落和当地水资源。这项工作的重点是使人们更好地了解干旱对位于亚利桑那州东北角的霍皮族和纳瓦霍族土地的影响。这项研究探索了遥感数据和地理空间工具在两项研究中的应用，以监测干旱对植被生产力的影响。在这两项研究中，我们都使用了地表物候计量学作为数据工具。在第三项相关研究中，我将卫星衍生的地表物候（LSP）与马里科帕农业中心的作物生长阶段的实地观测进行了比较，以更好地了解卫星衍生的植物学物候的时间敏感性，并了解它们的准确性。监测变化的工具。；第一项研究探讨了长期植被生产力对干旱的响应。本文通过将土地覆盖，气候和地形数据与LSP集成，为干旱监测和评估开发了一个框架。该框架的目的是检测长期植被变化和归一化植被指数（NDVI）相关生产力的趋势。；第二项研究考察了植被动力学的主要驱动力，以便提供与相互之间相关的有价值的空间信息。减轻干旱影响的植被生产力的年度变化。；第三项研究通过将遥感LSP与作物生长的实际季节相比较来测试其准确性。这提供了一种比较和验证各种LSP算法的方法，更重要的是，它有助于表征与作物的实际生物表相形成对比的基于遥感的指标。这些研究证明了遥感数据和简单的统计工具如何能够用于评估干旱对植被生产力的影响并告知土地状况，以及更好地了解卫星衍生LSP的准确性。

著录项

  • 作者

    El Vilaly, Mohamed Abd salam M.;

  • 作者单位

    The University of Arizona.;

  • 授予单位 The University of Arizona.;
  • 学科 Geodesy.;Climate Change.;Remote Sensing.
  • 学位 Ph.D.
  • 年度 2013
  • 页码 176 p.
  • 总页数 176
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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