干旱区生态环境知识资源中心(Arid): Contribution of predictive factors of land degradation occurrence applying maximum entropy model

Arid

DOI	10.1080/15324982.2023.2298996
	Contribution of predictive factors of land degradation occurrence applying maximum entropy model
	Abolhasani, Azam; Khosravi, Hassan; Zehtabian, Gholamreza; Rahmati, Omid; Alamdarloo, Esmaeil Heydari; D'Odorico, Paolo
通讯作者	Khosravi, H
来源期刊	ARID LAND RESEARCH AND MANAGEMENT
ISSN	1532-4982
EISSN	1532-4990
出版年	2024
卷号	38 期号:3 页码:299-317
英文摘要	Land degradation (LD) is a significant environmental issue that needs to be spatially mapped in different areas. This research provides a framework to prioritize the geo-environmental and anthropogenic factors on LD in a semi-arid region, Qazvin Plain, in Iran based on the maximum entropy model for the first time and also to produce the LD hazard map. The LD inventory map that shows the occurrence points of LD was prepared based on the decreasing trend of net primary productivity (NPP) over 20 years. 120 random points were selected as degraded sites where NPP showed a decreasing trend. Several environmental and anthropogenic factors including temperature, rainfall, land use, normalized difference vegetation index (NDVI), vegetation soil salinity index (VSSI), visible and shortwave infrared drought index (VSDI), electrical conductivity (EC) and sodium adsorption ratio (SAR) of groundwater, groundwater table, annual depletion of groundwater resources, slope, aspect, and altitude were considered as predictive factors of LD and their relative contributions were determined using the maximum entropy model. According to the findings, 49.74% of the region was in the class of low degradation. Also, 22.57%, 17.87%, and 9.82% of the plain were related to the moderate, high, and very high degradation classes, respectively. The model specified altitude as the most significant variable influencing LD followed by land use, slope, and VSSI. The least important variable affecting LD in the study area was the aspect. The results of modeling LD also showed that the areas most sensitive to LD were frequently rangelands which are mostly found on steep slopes and highlands. Based on the UAC value, the model illustrated a very good efficiency with a value of 0.8. According to the results, the maximum entropy model successfully mapped the LD hazard in the Qazvin plain.
英文关键词	Prediction predictive variable sensitivity spatial modeling
类型	Article
语种	英语
收录类别	SCI-E
WOS记录号	WOS:001136786900001
WOS关键词	BACTERIAL COMMUNITY STRUCTURE ; SOIL MICROBIAL BIOMASS ; VULNERABILITY ; SENSITIVITY ; IMPACT
WOS类目	Environmental Sciences ; Soil Science
WOS研究方向	Environmental Sciences & Ecology ; Agriculture
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/402945
推荐引用方式 GB/T 7714	Abolhasani, Azam,Khosravi, Hassan,Zehtabian, Gholamreza,et al. Contribution of predictive factors of land degradation occurrence applying maximum entropy model[J],2024,38(3):299-317.
APA	Abolhasani, Azam,Khosravi, Hassan,Zehtabian, Gholamreza,Rahmati, Omid,Alamdarloo, Esmaeil Heydari,&D'Odorico, Paolo.(2024).Contribution of predictive factors of land degradation occurrence applying maximum entropy model.ARID LAND RESEARCH AND MANAGEMENT,38(3),299-317.
MLA	Abolhasani, Azam,et al."Contribution of predictive factors of land degradation occurrence applying maximum entropy model".ARID LAND RESEARCH AND MANAGEMENT 38.3(2024):299-317.