Progresses on microwave remote sensing of land surface parameters

Shi, Jiancheng; Du, Yang; Du, Jinyang; Jiang, Lingmei; Chai, Linna; Mao, Kebiao; Xu, Peng; Ni, Wenjian; Xiong, Chao; Liu, Qiang; Liu, Chenzhou; Guo, Pan; Cui, Qian; Li, Yunqing; Chen, Jing; Wang, Anqi; Luo, Hejia; Wang, YinHui

doi:10.1007/s11430-012-4444-x

Cited by 83 publications

(39 citation statements)

References 171 publications

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“…Both spaceborne and airborne TIR sensors (HCMM, Landsat TM/TM+, AVHRR, MODIS, ASTER, TIMS, ATM, MIVIS) can be used to collect observations on soil humidity. Another opportunity to derive LST is given by passive microwave RS data [71]: this data source is not affected by cloud cover, smoke and aerosol effects, as thermal RS is. On the other hand, further studies are needed to understand how to derive LST on a large scale [72].…”

Section: Thermal Infrared Remote Sensingmentioning

confidence: 99%

“…Therefore, such parameters together with real-time rainfall data are useful for both landslide monitoring and early warning. Both spaceborne and airborne thermal infrared (TIR) sensors (HCMM, Landsat TM/TM+, AVHRR, MODIS, ASTER, TIMS, ATM, MIVIS) can collect observations on soil humidity, as well as passive microwave RS, as discussed in [71]. For instance, [264] employed MODIS land cover information, while in [265] a soil water index (SWI) was derived by the ASCAT (Advanced SCATterometer) sensor onboard the MetOp (Meteorological Operational) satellite.…”

Section: Hydrologymentioning

confidence: 99%

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Remote Sensing for Landslide Investigations: An Overview of Recent Achievements and Perspectives

et al. 2014

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Landslides represent major natural hazards, which cause every year significant loss of lives and damages to buildings, properties and lifelines. In the last decades, a significant increase in landslide frequency took place, in concomitance to climate change and the expansion of urbanized areas. Remote sensing techniques represent a powerful tool for landslide investigation: applications are traditionally divided into three main classes, although this subdivision has some limitations and borders are sometimes fuzzy. The first class comprehends techniques for landslide recognition, i.e., the mapping of past or active slope failures. The second regards landslide monitoring, which entails both ground deformation measurement and the analysis of any other changes along time (e.g., land use, vegetation cover). The third class groups methods for landslide hazard analysis and forecasting. The aim of this paper is to give an overview on the applications of remote-sensing techniques for the three categories of landslide investigations, focusing on the achievements of the last decade, being that previous studies have already been exhaustively reviewed in the existing literature. At the end of the paper, a new classification of remote-sensing techniques that may be pertinently adopted for investigating specific typologies of soil and rock slope failures is proposed.

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Section: Thermal Infrared Remote Sensingmentioning

confidence: 99%

Section: Hydrologymentioning

confidence: 99%

Remote Sensing for Landslide Investigations: An Overview of Recent Achievements and Perspectives

et al. 2014

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“…The accuracy and spatial resolution will improve in the near future [81,82]. The on-going National Aeronautics and Space Administration (NASA) Soil Moisture Active and Passive (SMAP) mission (launched on 31 January 2015) will provide more precise soil moisture data at a higher spatial resolution [83].…”

Section: Discussionmentioning

confidence: 99%

Monitoring of Evapotranspiration in a Semi-Arid Inland River Basin by Combining Microwave and Optical Remote Sensing Observations

2015

Remote Sensing

115

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Abstract:As a typical inland river basin, Heihe River basin has been experiencing severe water resource competition between different land cover types, especially in the middle stream and downstream areas. Terrestrial actual evapotranspiration (ETa), including evaporation from soil and water surfaces, evaporation of rainfall interception, transpiration of vegetation canopy and sublimation of snow and glaciers, is an important component of the water cycle in the Heihe River basin. We developed a hybrid remotely sensed ETa estimation model named ETMonitor to estimate the daily actual evapotranspiration of the Heihe River basin for the years 2009-2011 at a spatial resolution of 1 km. The model was forced by a variety of biophysical parameters derived from microwave and optical remote sensing observations. The estimated ETa was evaluated using eddy covariance (EC) flux observations at local scale and compared with the annual precipitation and the MODIS ETa product (MOD16) at regional scale. The spatial distribution and the seasonal variation of the estimated ETa were analyzed. The results indicate that the estimated ETa shows reasonable spatial and temporal patterns with respect to the diverse cold and arid landscapes in the upstream, middle stream and downstream regions, and is useful for various applications to improve the rational allocation of water resources in the Heihe River basin. OPEN ACCESSRemote Sens. 2015, 7 3057

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“…Examples include reviews on the significance of soil moisture in atmospheric, geomorphic, hydrologic, and biologic cycles [112], local scale soil moisture monitoring techniques [125], large scale soil moisture monitoring techniques [115,126], satellite-based soil moisture products [127], microwave remote sensing of soil moisture [128] and soil moisture downscaling approaches [129]. For more details on soil moisture remote sensing, it is recommended to refer to these review articles.…”

Section: Overview Of Productsmentioning

confidence: 99%

Application of Remote Sensing Data to Constrain Operational Rainfall-Driven Flood Forecasting: A Review

Grimaldi

Walker

et al. 2016

Remote Sensing

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Abstract:Fluvial flooding is one of the most catastrophic natural disasters threatening people's lives and possessions. Flood forecasting systems, which simulate runoff generation and propagation processes, provide information to support flood warning delivery and emergency response. The forecasting models need to be driven by input data and further constrained by historical and real-time observations using batch calibration and/or data assimilation techniques so as to produce relatively accurate and reliable flow forecasts. Traditionally, flood forecasting models are forced, calibrated and updated using in-situ measurements, e.g., gauged precipitation and discharge. The rapid development of hydrologic remote sensing offers a potential to provide additional/alternative forcing and constraint to facilitate timely and reliable forecasts. This has brought increasing interest to exploring the use of remote sensing data for flood forecasting. This paper reviews the recent advances on integration of remotely sensed precipitation and soil moisture with rainfall-runoff models for rainfall-driven flood forecasting. Scientific and operational challenges on the effective and optimal integration of remote sensing data into forecasting models are discussed.

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Progresses on microwave remote sensing of land surface parameters

Cited by 83 publications

References 171 publications

Remote Sensing for Landslide Investigations: An Overview of Recent Achievements and Perspectives

Remote Sensing for Landslide Investigations: An Overview of Recent Achievements and Perspectives

Monitoring of Evapotranspiration in a Semi-Arid Inland River Basin by Combining Microwave and Optical Remote Sensing Observations

Application of Remote Sensing Data to Constrain Operational Rainfall-Driven Flood Forecasting: A Review

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