干旱区生态环境知识资源中心(Arid): Airborne imaging spectroscopy for assessing land-use effect on soil quality in drylands

Arid

DOI	10.1016/j.isprsjprs.2022.01.018
	Airborne imaging spectroscopy for assessing land-use effect on soil quality in drylands
	Levi, Nathan; Karnieli, Arnon; Paz-Kagan, Tarin
通讯作者	Paz-Kagan, T
来源期刊	ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING
ISSN	0924-2716
EISSN	1872-8235
出版年	2022
卷号	186 页码:34-54
英文摘要	Global population growth has resulted in land-use (LU) changes in many natural ecosystems, causing deterioration in the environmental conditions that affect soil quality. The effect of LU on soil quality is acute in water limited systems that are characterized by insufficient availability of soil organic resources. Thus, the main objective of this study was to assess the effects of human activities (i.e., land-uses as grazing, modern agriculture, and runoff harvesting systems) on soil quality using imaging spectroscopy (IS) in the arid regions of Israel. For this, 12 physical, biological, and chemical soil properties were selected and further integrated into the soil quality index (SQI) as a method to assess the significant effects of LU changes in an arid area in southern Israel. A flight campaign of the AisaFENIX hyperspectral airborne sensor was used to develop an IS prediction model for the SQI on a regional scale. The spectral signatures, extracted from the hyperspectral image itself, were well separable among the four LUs using the partial least squares-discriminant analysis (PLS-DA) classification method (OA = 95.31%, Kc = 0.90). The correlation was performed using multivariate support vector machine regression (SVM-R) models between the spectral data and the measured soil indicators and the overall SQI. The SVM-R models were significantly correlated for several soil properties, including the overall SQI (R(adj)(2)Val = 0.87), with the successful prediction of the regional SQI mapping (R(adj)(2)Pred = 0.78). Seven individual soil properties, including fractional sand and clay, SOM, pH, EC, SAR, and P, were successfully used for developing prediction maps. Applying IS, and statistically integrative methods for comprehensive soil quality assessments enhances the prediction accuracy for monitoring soil health and evaluating degradation processes in arid environments. This study establishes a precise tool for sustainable and efficient land management and could be an example for future potential IS earth-observing space missions for soil quality assessment studies and applications.
英文关键词	Soil quality index Arid environment Support vector machine-regression Runoff harvesting system Agriculture Grazing
类型	Article
语种	英语
开放获取类型	hybrid
收录类别	SCI-E
WOS记录号	WOS:000782587800003
WOS关键词	INFRARED REFLECTANCE SPECTROSCOPY ; MANAGEMENT ASSESSMENT FRAMEWORK ; SUPPORT VECTOR REGRESSION ; SODIUM ADSORPTION RATIO ; ORGANIC-MATTER CONTENT ; DIFFUSE-REFLECTANCE ; SPECTRAL REFLECTANCE ; HYPERSPECTRAL DATA ; INDEX SSQI ; HEALTH
WOS类目	Geography, Physical ; Geosciences, Multidisciplinary ; Remote Sensing ; Imaging Science & Photographic Technology
WOS研究方向	Physical Geography ; 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/2XILL650/393242
推荐引用方式 GB/T 7714	Levi, Nathan,Karnieli, Arnon,Paz-Kagan, Tarin. Airborne imaging spectroscopy for assessing land-use effect on soil quality in drylands[J],2022,186:34-54.
APA	Levi, Nathan,Karnieli, Arnon,&Paz-Kagan, Tarin.(2022).Airborne imaging spectroscopy for assessing land-use effect on soil quality in drylands.ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING,186,34-54.
MLA	Levi, Nathan,et al."Airborne imaging spectroscopy for assessing land-use effect on soil quality in drylands".ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING 186(2022):34-54.