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Disaggregation Of Passive Microwave Soil Moisture For Use In Watershed Hydrology Applications.

机译:分水岭水文应用中的被动微波土壤水分分解。

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摘要

In recent years the passive microwave remote sensing has been providing soil moisture products using instruments on board satellite/airborne platforms. Spatial resolution has been restricted by the diameter of antenna which is inversely proportional to resolution. As a result, typical products have a spatial resolution of tens of kilometers, which is not compatible for some hydrological research applications. For this reason, the dissertation explores three disaggregation algorithms that estimate L-band passive microwave soil moisture at the subpixel level by using high spatial resolution remote sensing products from other optical and radar instruments were proposed and implemented in this investigation. The first technique utilized a thermal inertia theory to establish a relationship between daily temperature change and average soil moisture modulated by the vegetation condition was developed by using NLDAS, AVHRR, SPOT and MODIS data were applied to disaggregate the 25 km AMSR-E soil moisture to 1 km in Oklahoma. The second algorithm was built on semi empirical physical models (NP89 and LP92) derived from numerical experiments between soil evaporation efficiency and soil moisture over the surface skin sensing depth (a few millimeters) by using simulated soil temperature derived from MODIS and NLDAS as well as AMSR-E soil moisture at 25 km to disaggregate the coarse resolution soil moisture to 1 km in Oklahoma. The third algorithm modeled the relationship between the change in co-polarized radar backscatter and the remotely sensed microwave change in soil moisture retrievals and assumed that change in soil moisture was a function of only the canopy opacity. The change detection algorithm was implemented using aircraft based the remote sensing data from PALS and UAVSAR that were collected in SMPAVEX12 in southern Manitoba, Canada. The PALS L-band h-polarization radiometer soil moisture retrievals were disaggregated by combining them with the PALS and UAVSAR L-band hh-polarization radar spatial resolutions of 1500 m and 5 m/800 m, respectively. All three algorithms were validated using ground measurements from network in situ stations or handheld hydra probes. The validation results demonstrate the practicability on coarse resolution passive microwave soil moisture products.
机译:近年来,无源微波遥感已经使用卫星/机载平台上的仪器提供土壤水分产品。空间分辨率受到天线直径的限制,而天线直径与分辨率成反比。结果,典型产品的空间分辨率为几十公里,这与某些水文研究应用程序不兼容。为此,本文提出并实现了三种分解算法,该算法利用其他光学和雷达仪器的高分辨率遥感产品在亚像素水平上估算L波段无源微波土壤水分。利用NLDAS,AVHRR,SPOT和MODIS数据开发了第一种技术,利用热惯性理论建立了每日温度变化与植被条件调节的平均土壤水分之间的关​​系,将25 km AMSR-E土壤水分分解为俄克拉荷马州1公里。第二种算法是基于半经验物理模型(NP89和LP92)建立的,该模型是通过使用基于MODIS和NLDAS的模拟土壤温度以及土壤表皮感应深度(几毫米)上土壤蒸发效率和土壤水分之间的数值实验得出的,以及25公里处的AMSR-E土壤湿度将粗分辨率土壤湿度分解为俄克拉荷马州的1公里。第三种算法模拟了同极化雷达反向散射的变化与土壤水分反演中的遥感微波变化之间的关系,并假设土壤水分的变化仅是冠层不透明度的函数。更改检测算法是使用飞机实施的,该飞机基于来自加拿大曼尼托巴南部SMPAVEX12的PALS和UAVSAR遥感数据。通过将其分别与1500 m和5 m / 800 m的PALS和UAVSAR L波段hh极化雷达的空间分辨率相结合,将PALS L波段h极化辐射计的土壤水分反演分类。使用来自网络现场站或手持水力探头的地面测量结果验证了这三种算法。验证结果证明了在粗分辨率被动微波土壤水分产品上的实用性。

著录项

  • 作者

    Fang, Bin.;

  • 作者单位

    University of South Carolina.;

  • 授予单位 University of South Carolina.;
  • 学科 Remote sensing.;Geology.;Hydrologic sciences.
  • 学位 Ph.D.
  • 年度 2015
  • 页码 185 p.
  • 总页数 185
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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