干旱区生态环境知识资源中心(Arid): Investigation of Multi-Frequency SAR Data to Retrieve the Soil Moisture within a Drip Irrigation Context Using Modified Water Cloud Model

Arid

DOI	10.3390/s22020580
	Investigation of Multi-Frequency SAR Data to Retrieve the Soil Moisture within a Drip Irrigation Context Using Modified Water Cloud Model
	Ayari, Emna; Kassouk, Zeineb; Lili-Chabaane, Zohra; Baghdadi, Nicolas; Zribi, Mehrez
通讯作者	Zribi, M
来源期刊	SENSORS
EISSN	1424-8220
出版年	2022
卷号	22 期号:2
英文摘要	The objective of this paper was to estimate soil moisture in pepper crops with drip irrigation in a semi-arid area in the center of Tunisia using synthetic aperture radar (SAR) data. Within this context, the sensitivity of L-band (ALOS-2) in horizontal-horizontal (HH) and horizontal-vertical (HV) polarizations and C-band (Sentinel-1) data in vertical-vertical (VV) and vertical-horizontal (VH) polarizations is examined as a function of soil moisture and vegetation properties using statistical correlations. SAR signals scattered by pepper-covered fields are simulated with a modified version of the water cloud model using L-HH and C-VV data. In spatially heterogeneous soil moisture cases, the total backscattering is the sum of the bare soil contribution weighted by the proportion of bare soil (one-cover fraction) and the vegetation fraction cover contribution. The vegetation fraction contribution is calculated as the volume scattering contribution of the vegetation and underlying soil components attenuated by the vegetation cover. The underlying soil is divided into irrigated and non-irrigated parts owing to the presence of drip irrigation, thus generating different levels of moisture underneath vegetation. Based on signal sensitivity results, the potential of L-HH data to retrieve soil moisture is demonstrated. L-HV data exhibit a higher potential to retrieve vegetation properties regarding a lower potential for soil moisture estimation. After calibration and validation of the proposed model, various simulations are performed to assess the model behavior patterns under different conditions of soil moisture and pepper biophysical properties. The results highlight the potential of the proposed model to simulate a radar signal over heterogeneous soil moisture fields using L-HH and C-VV data.
英文关键词	ALOS-2 Sentinel-1 soilmoisture rowvegetation modifiedwater cloudmodel drip irrigation
类型	Article
语种	英语
开放获取类型	gold, Green Published
收录类别	SCI-E
WOS记录号	WOS:000920072100008
WOS关键词	INTEGRAL-EQUATION MODEL ; C-BAND ; SEMIEMPIRICAL CALIBRATION ; RADAR DATA ; BACKSCATTERING COEFFICIENT ; TERRASAR-X ; VEGETATION ; PARAMETERS ; SURFACE ; SENTINEL-1
WOS类目	Chemistry, Analytical ; Engineering, Electrical & Electronic ; Instruments & Instrumentation
WOS研究方向	Chemistry ; Engineering ; Instruments & Instrumentation
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/394479
推荐引用方式 GB/T 7714	Ayari, Emna,Kassouk, Zeineb,Lili-Chabaane, Zohra,et al. Investigation of Multi-Frequency SAR Data to Retrieve the Soil Moisture within a Drip Irrigation Context Using Modified Water Cloud Model[J],2022,22(2).
APA	Ayari, Emna,Kassouk, Zeineb,Lili-Chabaane, Zohra,Baghdadi, Nicolas,&Zribi, Mehrez.(2022).Investigation of Multi-Frequency SAR Data to Retrieve the Soil Moisture within a Drip Irrigation Context Using Modified Water Cloud Model.SENSORS,22(2).
MLA	Ayari, Emna,et al."Investigation of Multi-Frequency SAR Data to Retrieve the Soil Moisture within a Drip Irrigation Context Using Modified Water Cloud Model".SENSORS 22.2(2022).