Estimation of moisture content of sandy beaches from X-band synthetic aperture radar

IF 11.4 1区 地球科学 Q1 ENVIRONMENTAL SCIENCES
Julie Paprocki , Nina Stark , Hans C. Graber , Heidi Wadman , Jesse E. McNinch
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Abstract

Moisture content is a critical parameter for estimating the strength of partially saturated sand for engineering challenges such as beach trafficability. A framework for estimating the volumetric moisture content of sandy beaches using satellite-based HH-polarized X-band synthetic aperture radar imagery is presented and used to test the applicability of three theoretical scattering models: Oh, Dubois, and the Integral Equation Model (IEM). The developed framework relies on the measured backscatter coefficient, soil surface root-mean square (RMS) height, and the geometric characteristics of the image. Models for estimating the RMS height were developed based on field measurements for two distinct sites composed of predominately quartz sand and approximately uniform beach slopes: Duck, North Carolina and Cannon Beach in Yakutat, Alaska. The models were developed and tested for incidence angles of 23.3°-54.2° using data obtained from the Cosmo-SkyMED and TerraSAR-X satellites. Four sets of RMS height models were tested: Oh with moisture contents greater than 0 %, Oh with moisture contents greater than a very dry threshold, Dubois, and the IEM. Unique RMS height models, specific to a moisture content model, were developed for incidence angles ranging from a single incidence angle to a range of consecutive incidence angles. Applying the RMS height models, the root mean square error (RMSE) of moisture content was 0.7–6.9 %. Images with incidence angles of 30°- 46° and 40°-50° resulted in the best estimates of moisture content when compared to other ranges of incidence angles for the models tested. Deviations generally represented underestimates of the moisture content (0.1 %–1.3 %), with greater underestimates observed for the IEM. Spatial estimates of moisture content resulted in two distinct zones, one with low moisture contents and a second with slightly elevated moisture contents for all models except the IEM. Challenges associated with differences in scattering mechanisms, a lack of data with high moisture content, and sensitivity of models to small changes in RMS height are discussed.
用x波段合成孔径雷达估算沙滩含水率
水分含量是估算部分饱和砂强度的关键参数,适用于沙滩交通等工程挑战。提出了一种基于卫星hh偏振x波段合成孔径雷达图像估算沙滩体积含水量的框架,并用于测试三种理论散射模型的适用性:Oh, Dubois和积分方程模型(IEM)。开发的框架依赖于测量的后向散射系数、土壤表面均方根(RMS)高度和图像的几何特征。估算均方根高度的模型是基于两个不同地点的现场测量开发的,这些地点主要由石英砂和近似均匀的海滩斜坡组成:北卡罗来纳州的Duck和阿拉斯加州的Yakutat的Cannon海滩。利用Cosmo-SkyMED和TerraSAR-X卫星获得的数据,开发并测试了入射角为23.3°-54.2°的模型。测试了四组RMS高度模型:含水率大于0%的Oh、含水率大于极干阈值的Oh、Dubois和IEM。独特的RMS高度模型,特定于含水量模型,开发了从单一入射角到一系列连续入射角的入射角。采用均方根高度模型,水分含量的均方根误差(RMSE)为0.7 ~ 6.9%。与测试模型的其他入射角范围相比,入射角为30°- 46°和40°-50°的图像产生了最佳的水分含量估计。偏差通常表示水分含量的低估(0.1% - 1.3%),在IEM中观察到更大的低估。水分含量的空间估算结果显示,除IEM外,所有模式的水分含量都有两个明显的区,一个是低水分含量区,另一个是略高水分含量区。讨论了与散射机制差异、缺乏高含水量数据以及模型对均方根高度微小变化的敏感性相关的挑战。
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来源期刊
Remote Sensing of Environment
Remote Sensing of Environment 环境科学-成像科学与照相技术
CiteScore
25.10
自引率
8.90%
发文量
455
审稿时长
53 days
期刊介绍: Remote Sensing of Environment (RSE) serves the Earth observation community by disseminating results on the theory, science, applications, and technology that contribute to advancing the field of remote sensing. With a thoroughly interdisciplinary approach, RSE encompasses terrestrial, oceanic, and atmospheric sensing. The journal emphasizes biophysical and quantitative approaches to remote sensing at local to global scales, covering a diverse range of applications and techniques. RSE serves as a vital platform for the exchange of knowledge and advancements in the dynamic field of remote sensing.
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