干旱区生态环境知识资源中心(Arid): Soil Texture Estimation Using Radar and Optical Data from Sentinel-1 and Sentinel-2

Arid

DOI	10.3390/rs11131520
	Soil Texture Estimation Using Radar and Optical Data from Sentinel-1 and Sentinel-2
	Bousbih, Safa 1,2; Zribi, Mehrez 1; Pelletier, Charlotte 3; Gorrab, Azza 2; Lili-Chabaane, Zohra 2; Baghdadi, Nicolas 4; Ben Aissa, Nadhira 2; Mougenot, Bernard 1
通讯作者	Bousbih, Safa
来源期刊	REMOTE SENSING
EISSN	2072-4292
出版年	2019
卷号	11 期号:13
英文摘要	This paper discusses the combined use of remotely sensed optical and radar data for the estimation and mapping of soil texture. The study is based on Sentinel-1 (S-1) and Sentinel-2 (S-2) data acquired between July and early December 2017, on a semi-arid area about 3000 km(2) in central Tunisia. In addition to satellite acquisitions, texture measurement samples were taken in several agricultural fields, characterized by a large range of clay contents (between 13% and 60%). For the period between July and August, various optical indicators of clay content Short-Wave Infrared (SWIR) bands and soil indices) were tested over bare soils. Satellite moisture products, derived from combined S-1 and S-2 data, were also tested as an indicator of soil texture. Algorithms based on the support vector machine (SVM) and random forest (RF) methods are proposed for the classification and mapping of clay content and a three-fold cross-validation is used to evaluate both approaches. The classifications with the best performance are achieved using the soil moisture indicator derived from combined S-1 and S-2 data, with overall accuracy (OA) of 63% and 65% for the SVM and RF classifications, respectively.
英文关键词	Sentinel-1 Sentinel-2 Soil Moisture Texture Clay SVM Random Forest
类型	Article
语种	英语
国家	France ; Tunisia ; Australia
开放获取类型	Green Published, gold
收录类别	SCI-E
WOS记录号	WOS:000477049000013
WOS关键词	MOISTURE ESTIMATION ; TIME-SERIES ; CLAY ; REFLECTANCE ; SURFACE ; COLOR ; CALIBRATION ; PREDICTION ; RESOLUTION ; IMAGES
WOS类目	Environmental Sciences ; Geosciences, Multidisciplinary ; Remote Sensing ; Imaging Science & Photographic Technology
WOS研究方向	Environmental Sciences & Ecology ; Geology ; Remote Sensing ; Imaging Science & Photographic Technology
来源机构	French National Research Institute for Sustainable Development
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/218390
作者单位	1.INRA, CNES, IRD, CNRS,UPS,CESBIO, 18 Ave Edouard Belin, F-31401 Toulouse 9, France; 2.Univ Carthage, INAT, LR GREEN TEAM, 43 Ave Charles Nicolle, Tunis 1082, Tunisia; 3.Monash Univ, Fac Informat Technol, Melbourne, Vic 3800, Australia; 4.Univ Montpellier, UMR TETIS, IRSTEA, F-34093 Montpellier 5, France
推荐引用方式 GB/T 7714	Bousbih, Safa,Zribi, Mehrez,Pelletier, Charlotte,et al. Soil Texture Estimation Using Radar and Optical Data from Sentinel-1 and Sentinel-2[J]. French National Research Institute for Sustainable Development,2019,11(13).
APA	Bousbih, Safa.,Zribi, Mehrez.,Pelletier, Charlotte.,Gorrab, Azza.,Lili-Chabaane, Zohra.,...&Mougenot, Bernard.(2019).Soil Texture Estimation Using Radar and Optical Data from Sentinel-1 and Sentinel-2.REMOTE SENSING,11(13).
MLA	Bousbih, Safa,et al."Soil Texture Estimation Using Radar and Optical Data from Sentinel-1 and Sentinel-2".REMOTE SENSING 11.13(2019).