干旱区生态环境知识资源中心(Arid): EVALUATING LAND SURFACE MOISTURE CONDITIONS BEFORE AND AFTER FLASH-FLOOD STORM FROM OPTICAL AND THERMAL DATA: MODELS COMPARISON AND VALIDATION

Arid

DOI	10.1109/IGARSS39084.2020.9323655
	EVALUATING LAND SURFACE MOISTURE CONDITIONS BEFORE AND AFTER FLASH-FLOOD STORM FROM OPTICAL AND THERMAL DATA: MODELS COMPARISON AND VALIDATION
	Bannari, A.; Bahi, H.; Rhinane, H.
通讯作者	Bannari, A (corresponding author), Arabian Gulf Univ, Coll Grad Studies, Dept Geoinformat, POB 26671, Manama, Bahrain.
会议名称	IEEE International Geoscience and Remote Sensing Symposium (IGARSS)
会议日期	SEP 26-OCT 02, 2020
会议地点	ELECTR NETWORK
英文摘要	Soil moisture (SM) is an important physical parameter for several hydrological and agricultural applications, weather and climate predictions, as well as early warning of natural hazards such as flood and drought. It varies significantly in space and time, and it is a challenge to map its variations accurately at the regional and local scales. The aim of the present study is a comparison and validation of four models such as NDWI, SIWSI, TOTRAM and OPTRAM for SM mapping before and after flash-flood storm in arid land. The used methodology exploits two pairs of images acquired with Landsat-OLI/TIRS sensors over the study area before and after flood. The first pair was acquired two weeks before the flash flood, and the second one was collected eight days after the flood. These images were radiometrically and atmospherically corrected, as well topographically rectified using SRTM DEM. For validation purposes, before and after storm, two independent SM products were used. Both, they were derived from data acquired simultaneously with those recorded by Landsat-OLI/TIRS. The first is derived from SMOS data, and the second is compiled from rainfall data (SM-RFE) delivered by NOAA climate prediction center RFE (Rainfall Estimator) for Africa. The results revealed that TOTRAM and NDWI models converge towards the same conclusions describing accurately the drastic change of SM before and after flash-flood highlighting the impact of inundation and the mud accumulation over the study area. Their results validation against those of SMOS and SM-RFE products shows a significant agreement (R 2 of 0.95). However, in addition to its simplicity and to its easy implementation, the NDWI show a great potential for SM content estimation independently of LST using only optical data such as Landsat-OLI or Sentinel-MSI.
英文关键词	Soil moisture NDWI SIWSI TOTRAM OPTRAM Flash-flood Models Landsat-OLI/TIRS SMOS SM-RFE
来源出版物	IGARSS 2020 - 2020 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM
出版年	2020
页码	5038-5041
ISBN	978-1-7281-6374-1
出版者	IEEE
类型	Proceedings Paper
语种	英语
收录类别	CPCI-S
WOS记录号	WOS:000664335304210
WOS关键词	SOIL-MOISTURE ; RETRIEVAL ; TEMPERATURE ; INDEX ; WATER ; RADAR ; SMOS
WOS类目	Computer Science, Artificial Intelligence ; Environmental Sciences ; Geosciences, Multidisciplinary ; Remote Sensing ; Optics
WOS研究方向	Computer Science ; Environmental Sciences & Ecology ; Geology ; Remote Sensing ; Optics
资源类型	会议论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/365524
作者单位	[Bannari, A.] Arabian Gulf Univ, Coll Grad Studies, Dept Geoinformat, POB 26671, Manama, Bahrain; [Bahi, H.] Mohammed VI Polytech Univ, Sch Architecture Planning & Design, Benguerir, Morocco; [Rhinane, H.] Univ Hassan 2, Fac Sci Ain Chock, Casablanca 20100, Morocco
推荐引用方式 GB/T 7714	Bannari, A.,Bahi, H.,Rhinane, H.. EVALUATING LAND SURFACE MOISTURE CONDITIONS BEFORE AND AFTER FLASH-FLOOD STORM FROM OPTICAL AND THERMAL DATA: MODELS COMPARISON AND VALIDATION[C]:IEEE,2020:5038-5041.