Cross-Site: Spatio-temporal Dynamics of Canopy and Soil Moisture: Linking Synthetic Aperture Radar Image Phenomenology with Ecosystem Processes

跨站点：冠层和土壤湿度的时空动力学：将合成孔径雷达图像现象学与生态系统过程联系起来

• 批准号: 9527108
• 负责人: Alan Knapp
• 金额: $ 15.13万
• 依托单位: Kansas State University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 1995
• 资助国家: 美国
• 起止时间: 1995-10-01 至 1998-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=9527108&HistoricalAwards=false
• 关键词: Cross; Site; Spatio; temporal; Dynamics

Soil moisture is a key controlling factor for numerous ecological and biophysical processes. While diverse techniques are available to make point estimates of soil moisture, spatially extensive surveys can be logistically difficult and fraught with problems of interpolation. Remote sensing of soil moisture offers the possibility of exhaustive spatial sampling. The efficacy of microwave sensors (both active and passive) in measuring soil moisture is well-studied. However, little research has focused on patterns of radar imagery of natural landscapes. Yet, there is a distinct need to assess the potential of Synthetic Aperture Radar (SAR) for routine environmental monitoring of land surface processes. Environmental monitoring of vegetated landscapes will increase during the next decade as data from spaceborne SAR platforms become more readily available. The project involves the use of SAR data from the European, Canadian, and Japanese orbital platforms to address the variation in canopy and soil moisture and its ecological consequences. These data augment current investigatio ns at two NSF Long Term Ecological Research (LTER) sites, Konza prairie Research Natural Area in the northeast Kansas and Sevilleta National Wildlife Refuge in central New Mexico. Both LTER sites are located within ecological transitional zones (ecotones) in which soil moisture is a major determinant of plant productivity and species composition. The primary products are site-specific time series of soil moisture and canopy change maps. These data will then be used to link remote sensing and groundtruth data with ecological processes.

土壤水分是许多生态和生物物理过程的关键控制因素。 虽然不同的技术，使土壤水分的点估计，空间广泛的调查可能是后勤困难，充满了插值问题。 土壤湿度遥感提供了详尽的空间取样的可能性。 微波传感器（有源和无源）在测量土壤水分的功效得到了充分的研究。 然而，很少有研究集中在自然景观的雷达图像的模式。 然而，有一个明确的需要，以评估合成孔径雷达（SAR）的陆面过程的例行环境监测的潜力。 随着来自星载合成孔径雷达平台的数据越来越容易获得，今后十年将增加对植被景观的环境监测。 该项目涉及使用来自欧洲、加拿大和日本轨道平台的合成孔径雷达数据，以研究冠层和土壤湿度的变化及其生态后果。 这些数据增强了目前在两个NSF长期生态研究（LTER）站点的调查，即堪萨斯东北部的Konza草原研究自然区和新墨西哥州中部的Sevilleta国家野生动物保护区。 这两个LTER站点都位于生态过渡区（生态交错区），其中土壤水分是植物生产力和物种组成的主要决定因素。 主要产品是特定地点的土壤湿度和树冠变化图的时间序列。 这些数据将用于将遥感和地面实况数据与生态过程联系起来。