干旱区生态环境知识资源中心(Arid): Validation and Comparison of Physical Models for Soil Salinity Mapping over an Arid Landscape Using Spectral Reflectance Measurements and Landsat-OLI Data

Arid

DOI	10.3390/rs13030494
	Validation and Comparison of Physical Models for Soil Salinity Mapping over an Arid Landscape Using Spectral Reflectance Measurements and Landsat-OLI Data
	Al-Ali, Z. M.; Bannari, A.; Rhinane, H.; El-Battay, A.; Shahid, S. A.; Hameid, N.
通讯作者	Bannari, A (corresponding author), Arabian Gulf Univ, Dept Geoinformat, Coll Grad Studies, Manama 26671, Bahrain.
来源期刊	REMOTE SENSING
EISSN	2072-4292
出版年	2021
卷号	13 期号:3
英文摘要	The present study focuses on the validation and comparison of eight different physical models for soil salinity mapping in an arid landscape using two independent Landsat-Operational Land Imager (OLI) datasets: simulated and image data. The examined and compared models were previously developed for different semi-arid and arid geographic regions around the world, i.e., Latino-America, the Middle East, North and East Africa and Asia. These models integrate different spectral bands and unlike mathematical functions in their conceptualization. To achieve the objectives of the study, four main steps were completed. For simulated data, a field survey was organized, and 100 soil samples were collected with various degrees of salinity levels. The bidirectional reflectance factor was measured above each soil sample in a goniometric laboratory using an analytical spectral device (ASD) FieldSpec-4 Hi-Res spectroradiometer. These measurements were resampled and convolved in the solar-reflective bands of the Operational Land Imager (OLI) sensor using a radiative transfer code and the relative spectral response profiles characterizing the filters of the OLI sensor. Then, they were converted in terms of the considered models. Moreover, the OLI image acquired simultaneously with the field survey was radiometrically preprocessed, and the models were implemented to derive soil salinity maps. The laboratory analyses were performed to derive electrical conductivity (EC-Lab) from each soil sample for validation and comparison purposes. These steps were undertaken between predicted salinity (EC-Predicted) and the measured ground truth (EC-Lab) in the same way for simulated and image data using regression analysis (p < 0.05), coefficient of determination (R-2), and root mean square error (RMSE). Moreover, the derived maps were visually interpreted and validated by comparison with observations from the field visit, ancillary data (soil, geology, geomorphology and water table maps) and soil laboratory analyses. Regardless of data sources (simulated or image) or the validation mode, the results obtained show that the predictive models based on visible- and near-infrared (VNIR) bands and vegetation indices are inadequate for soil salinity prediction in an arid landscape due to serious signals confusion between the salt crust and soil optical properties in these spectral bands. The statistical tests revealed insignificant fits (R-2 <= 0.41) with very high prediction errors (RMSE >= 0.65), while the model based on the second-order polynomial function and integrating the shortwave infrared (SWIR) bands provided the results of best fit, with the field observations (EC-Lab), yielding an R-2 of 0.97 and a low overall RMSE of 0.13. These findings were corroborated by visual interpretation of derived maps and their validation by comparison with the ground truthing.
英文关键词	soil salinity salinity models remote sensing spectral reflectance simulation Landsat-OLI image electrical conductivity validation
类型	Article
语种	英语
开放获取类型	gold
收录类别	SCI-E
WOS记录号	WOS:000615466500001
WOS关键词	VEGETATION INDEXES ; SATELLITE ; SENSOR ; SPECTROSCOPY ; MESOPOTAMIA ; CALIBRATION ; SALT
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
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/348134
作者单位	[Al-Ali, Z. M.] Arabian Gulf Univ, Dept Nat Resources & Environm, Coll Grad Studies, Manama 26671, Bahrain; [Bannari, A.; Hameid, N.] Arabian Gulf Univ, Dept Geoinformat, Coll Grad Studies, Manama 26671, Bahrain; [Rhinane, H.] Univ Hassan 2, Fac Sci Ain Chock, Casablanca 20100, Morocco; [El-Battay, A.] Int Ctr Biosaline Agr ICBA, Dubai 14660, U Arab Emirates; [Shahid, S. A.] Kuwait Inst Sci Res, Safat 13109, Kuwait
推荐引用方式 GB/T 7714	Al-Ali, Z. M.,Bannari, A.,Rhinane, H.,et al. Validation and Comparison of Physical Models for Soil Salinity Mapping over an Arid Landscape Using Spectral Reflectance Measurements and Landsat-OLI Data[J],2021,13(3).
APA	Al-Ali, Z. M.,Bannari, A.,Rhinane, H.,El-Battay, A.,Shahid, S. A.,&Hameid, N..(2021).Validation and Comparison of Physical Models for Soil Salinity Mapping over an Arid Landscape Using Spectral Reflectance Measurements and Landsat-OLI Data.REMOTE SENSING,13(3).
MLA	Al-Ali, Z. M.,et al."Validation and Comparison of Physical Models for Soil Salinity Mapping over an Arid Landscape Using Spectral Reflectance Measurements and Landsat-OLI Data".REMOTE SENSING 13.3(2021).