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Regional-scale soil moisture monitoring using NOAA/AVHRR data.

机译：使用NOAA / AVHRR数据进行区域规模的土壤湿度监测。

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摘要

Regional-scale soil moisture is important information in the areas of agriculture, hydrology, climatic modeling, and global environmental change. The problems with conventional techniques, such as field surveys and meteorological methods, for monitoring soil moisture include the inability to detect subtle differences in surface "wetness" across geographic space and the lack of moisture data in a timely fashion.;The purpose of the research was to develop a means of measuring the regional-scale root-zone soil moisture content using remote-sensing techniques. To accomplish this goal, a methodology was established and software was developed which make use of both thermal and visible channels of NOAA/AVHRR data in conjunction with the ground meteorological data to infer the regional-scale root-zone soil moisture content and other moisture-related surface physical quantities. The software development occurred within the context of a Geographic Information System (GIS).;The research results indicated that AVHRR data can be used to detect and measure both temporal and spatial changes in root-zone soil moisture and certain other surface physical quantities such as daily evapotranspiration, canopy temperature, diurnal heat capacity, and net radiation, and that this can be done on a regional scale in an operational mode. In addition, the research concluded that, theoretically, the Normalized Vegetation Index (NVI or NDVI) is equal to the foilage shielding factor, and that NVI is not a spatially extendable indicator of soil moisture condition. The research demonstrated that only a thermal image, either day or night, is necessary to obtain soil moisture information. The work also suggested that, with a given ground meteorological condition, soil moisture information is functionally related to the day or night surface temperature, foliage shielding factor, and incoming solar radiation. A second order regression model was used to describe the relationship. The Palmer Drought Severity Index (PDSI) correlated well with daily evapotranspiration, while the Crop Moisture Index (CMI) varied with both the root-zone moisture content and canopy temperature.
机译：区域尺度的土壤湿度是农业，水文学，气候模拟和全球环境变化领域的重要信息。用于监测土壤水分的常规技术（例如野外调查和气象方法）存在的问题包括无法检测到整个地理空间的表面“湿度”的细微差异以及缺乏及时的水分数据。旨在开发一种使用遥感技术测量区域尺度根际土壤水分含量的方法。为了实现这一目标，建立了一种方法并开发了软件，该软件利用NOAA / AVHRR数据的热通道和可见通道以及地面气象数据来推断区域尺度的根区土壤水分含量和其他水分含量。相关的表面物理量。软件开发是在地理信息系统（GIS）的背景下进行的；研究结果表明，AVHRR数据可用于检测和测量根区土壤水分和某些其他表面物理量（例如，每天的蒸散量，冠层温度，日热容和净辐射，可以在运行模式下在区域范围内完成。此外，研究得出的结论是，从理论上说，归一化植被指数（NVI或NDVI）等于the草屏蔽因子，并且NVI并不是土壤湿度条件的空间可扩展指标。研究表明，仅白天或晚上的热图像就可以获取土壤水分信息。这项工作还表明，在给定的地面气象条件下，土壤湿度信息在功能上与白天或夜晚的表面温度，树叶遮蔽因子和太阳辐射有关。使用二阶回归模型来描述这种关系。帕尔默干旱严重度指数（PDSI）与日蒸散量相关性很好，而作物水分指数（CMI）则随根区含水量和冠层温度的变化而变化。

著录项

  • 作者

    Di, Liping.;

  • 作者单位

    The University of Nebraska - Lincoln.;

  • 授予单位 The University of Nebraska - Lincoln.;
  • 学科 Geography.;Remote Sensing.
  • 学位 Ph.D.
  • 年度 1991
  • 页码 415 p.
  • 总页数 415
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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