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Use of remote sensing to estimate soil salinity and evapotranspiration in agricultural fields.

机译:利用遥感估算农田中的盐分和蒸散量。

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摘要

In recent years, methods for detecting soil salinity have improved greatly. This research describes methods to detect soil salinity levels in agricultural lands based on crop conditions and evapotranspiration (ET) using satellite imagery.; Elevated levels of soil salinity affect the growth of most crops as well as their appearance. For this research, satellite images of the study area, the Arkansas River Basin in Colorado, are used to classify the condition of the crops being grown in fields according to their different reflectance values. Using spatially referenced ground data collected in the study area, each class in the satellite image is related to a level of soil salinity. These classes are then used to create a signature file to classify other areas within the same image having the same crop.; For the purpose of detecting soil salinity in this study, two satellite scenes were used: a multi-spectral Ikonos image from July 27, 2001 and a Landsat 7 image from July 8, 2001. While the Ikonos image provides more details, the results of this study indicate that the Landsat imagery also performed remarkably well.; Evapotranspiration (ET) is one of the processes that are affected by soil salinity. Reliable estimates of evapotranspiration from vegetation are needed for investigations of the relationship between soil salinity and ET. Satellite-derived information has been found useful for estimation of aerial ET. For this purpose, a surface energy balance-based model (RESET) was developed using remotely sensed data from satellite imagery. The RESET model takes into consideration the spatial variability in weather. Moreover, the model implements a spatiotemporal interpolation methodology in order to obtain ET information between satellite scenes.; The RESET model was applied to estimate ET values in the study area. A geographic information system (GIS) was used to spatially relate the ET values to soil salinity data. The ET values were regressed against the spatially corresponding soil salinity values to develop a relationship between ET and soil salinity. The ET values were found to correlate well with the soil salinity levels in the study area, with correlation coefficients of up to 0.92.
机译:近年来,检测土壤盐分的方法有了很大的进步。这项研究描述了使用卫星图像根据作物状况和蒸散量(ET)检测农田土壤盐分水平的方法。土壤盐分水平升高会影响大多数农作物的生长及其外观。在这项研究中,使用研究区域(位于科罗拉多州的阿肯色州河流域)的卫星图像,根据其不同的反射率值对田间作物的生长状况进行分类。使用研究区域收集的空间参考地面数据,卫星图像中的每个类别都与土壤盐分水平相关。然后使用这些类来创建签名文件,以对同一图像中具有相同裁剪的其他区域进行分类。为了检测本研究中的土壤盐分,使用了两个卫星场景:2001年7月27日的多光谱Ikonos图像和2001年7月8日的Landsat 7图像。虽然Ikonos图像提供了更多细节,但这项研究表明,Landsat影像的表现也非常出色。蒸散(ET)是受土壤盐度影响的过程之一。要研究土壤盐度与ET之间的关系,需要可靠地估算出植被的蒸散量。已发现卫星衍生信息可用于估算空中ET。为此,使用了来自卫星图像的遥感数据,开发了基于表面能平衡的模型(RESET)。 RESET模型考虑了天气的空间变异性。此外,该模型实现了时空内插方法,以获取卫星场景之间的ET信息。 RESET模型用于估计研究区域的ET值。地理信息系统(GIS)用于将ET值与土壤盐分数据进行空间关联。将ET值相对于空间上对应的土壤盐分值进行回归,以建立ET与土壤盐分之间的关​​系。发现ET值与研究区域的土壤盐分水平高度相关,相关系数最高为0.92。

著录项

  • 作者

    Elhaddad, Aymn.;

  • 作者单位

    Colorado State University.;

  • 授予单位 Colorado State University.;
  • 学科 Agriculture Soil Science.; Engineering Agricultural.; Remote Sensing.
  • 学位 Ph.D.
  • 年度 2007
  • 页码 111 p.
  • 总页数 111
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 土壤学;农业工程;遥感技术;
  • 关键词

  • 入库时间 2022-08-17 11:39:49

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