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首页> 外文期刊>ISPRS Journal of Photogrammetry and Remote Sensing >A practical approach for deriving all-weather soil moisture content using combined satellite and meteorological data
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A practical approach for deriving all-weather soil moisture content using combined satellite and meteorological data

机译:结合卫星和气象数据得出全天候土壤水分含量的实用方法

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摘要

Soil moisture has long been recognized as one of the essential variables in the water cycle and energy budget between Earth's surface and atmosphere. The present study develops a practical approach for deriving all-weather soil moisture using combined satellite images and gridded meteorological products. In this approach, soil moisture over the Moderate Resolution Imaging Spectroradiometer (MODIS) clear sky pixels are estimated from the Vegetation Index/Temperature (VIT) trapezoid scheme in which theoretical dry and wet edges were determined pixel to pixel by China Meteorological Administration Land Data Assimilation System (CLDAS) meteorological products, including air temperature, solar radiation, wind speed and specific humidity. For cloudy pixels, soil moisture values are derived by the calculation of surface and aerodynamic resistances from wind speed. The approach is capable of filling the soil moisture gaps over remaining cloudy pixels by traditional optical/thermal infrared methods, allowing for a spatially complete soil moisture map over large areas. Evaluation over agricultural fields indicates that the proposed approach can produce an overall generally reasonable distribution of all-weather soil moisture. An acceptable accuracy between the estimated all-weather soil moisture and in-situ measurements at different depths could be found with an Root Mean Square Error (RMSE) varying from 0.067 m(3)/m(3) to 0.079 m(3)/m(3) and a slight bias ranging from 0.004 m(3)/m(3) to 0.011 m(3)/m(3). The proposed approach reveals significant potential to derive all-weather soil moisture using currently available satellite images and meteorological products at a regional or global scale in future developments. (C) 2017 International Society for Photogrammetry and Remote Sensing, Inc. (ISPRS). Published by Elsevier B.V. All rights reserved.
机译:长期以来,人们一直认为土壤水分是地球表面与大气之间水循环和能量收支的基本变量之一。本研究开发了一种实用的方法,可以结合使用卫星图像和栅格化气象产品来获取全天候土壤湿度。通过这种方法,根据植被指数/温度(VIT)梯形方案估算了中分辨率成像光谱仪(MODIS)晴朗天空像素上的土壤水分,其中,中国气象局土地数据同化确定了理论上的干湿边缘系统(CLDAS)气象产品,包括气温,太阳辐射,风速和比湿。对于多云像素,土壤湿度值是根据风速通过计算表面阻力和空气动力学阻力得出的。该方法能够通过传统的光学/热红外方法填补剩余的浑浊像素上的土壤水分缺口,从而在大范围内获得空间完整的土壤水分图。对农业领域的评估表明,该方法可以产生全天候土壤水分的总体合理分布。估计的全天候土壤湿度和不同深度的原位测量之间的可接受精度可以在0.067 m(3)/ m(3)至0.079 m(3)/的均方根误差(RMSE)之间找到m(3)和从0.004 m(3)/ m(3)到0.011 m(3)/ m(3)的轻微偏差。拟议的方法显示出在未来发展中使用区域或全球范围内的现有卫星图像和气象产品获得全天候土壤水分的巨大潜力。 (C)2017国际摄影测量与遥感学会(ISPRS)。由Elsevier B.V.发布。保留所有权利。

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  • 作者单位

    Chinese Acad Agr Sci, Minist Agr, Key Lab Agr Remote Sensing, Inst Agr Resources & Reg Planning, Beijing 100081, Peoples R China;

    Chinese Acad Agr Sci, Minist Agr, Key Lab Agr Remote Sensing, Inst Agr Resources & Reg Planning, Beijing 100081, Peoples R China|Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, State Key Lab Resources & Environm Informat Syst, Beijing 100101, Peoples R China;

    Chinese Acad Agr Sci, Minist Agr, Key Lab Agr Remote Sensing, Inst Agr Resources & Reg Planning, Beijing 100081, Peoples R China;

    Chinese Acad Agr Sci, Minist Agr, Key Lab Agr Remote Sensing, Inst Agr Resources & Reg Planning, Beijing 100081, Peoples R China;

    Chinese Acad Agr Sci, Minist Agr, Key Lab Agr Remote Sensing, Inst Agr Resources & Reg Planning, Beijing 100081, Peoples R China;

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  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Soil moisture; All-weather; VIT trapezoid; MODIS; CLDAS meteorological products;

    机译:土壤水分;全天候;VIT梯形;MODIS;CLDAS气象产品;

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