干旱区生态环境知识资源中心(Arid): A data-mining-based approach for aeolian desertification susceptibility assessment: A case-study from Northern China

Arid

DOI	10.1002/ldr.3393
	A data-mining-based approach for aeolian desertification susceptibility assessment: A case-study from Northern China
	Yue Yaojie 1,2; Min, Li 2; Lin, Wang 2; Zhu A-Xing 3,4,5
通讯作者	Zhu A-Xing
来源期刊	LAND DEGRADATION & DEVELOPMENT
ISSN	1085-3278
EISSN	1099-145X
出版年	2019
卷号	30 期号:16 页码:1968-1983
英文摘要	Desertification is a grave threat to the environment and livelihoods. Desertification susceptibility assessment (DSA) plays a critical role in reasonable desertification prevention planning by mapping the extent, intensity, and classification of desertification. Numerous desertification maps have been produced using various DSA methods. However, the method of rapid desertification mapping by objectively discovering valuable DSA knowledge from experienced experts stored in such maps has rarely been explored. We propose a data-mining-based approach to mapping aeolian desertification that applies the decision tree (DT) C5.0 (C5) algorithm as a knowledge discovery tool to the reference map and corresponding environmental variables. The results of our case-study in Northern China show that the overall accuracy of aeolian desertification classification based on C5 is 86.69%, and the predicted map is highly consistent with the reference map. The DT algorithm outperforms the artificial neural network and naive Bayes approaches. Our results highlight the importance of selecting more representative training samples across where interleaved distributions of multiple aeolian desertification land exist when applying the DT algorithm. The findings of the present study are valuable for highlighting the significance of the data mining approach in DSA, with the growth of desertification maps. Given that aeolian desertification is a complex process coupling natural and human factors, and there are significant regional and scale differences in Northern China, further studies at a fine-scale regarding human factors deserve more attention.
英文关键词	aeolian desertification susceptibility data mining DT algorithm environmental indicators Northern China
类型	Article
语种	英语
国家	Peoples R China ; USA
开放获取类型	hybrid
收录类别	SCI-E ; SSCI
WOS记录号	WOS:000478243900001
WOS关键词	LAND DEGRADATION ; DECISION TREE ; QUANTITATIVE ASSESSMENT ; KNOWLEDGE DISCOVERY ; WIND EROSION ; SOIL MAP ; SENSITIVITY ; SCALE ; SOUTH ; ENVIRONMENT
WOS类目	Environmental Sciences ; Soil Science
WOS研究方向	Environmental Sciences & Ecology ; Agriculture
来源机构	北京师范大学
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/217480
作者单位	1.Beijing Normal Univ, Key Lab Environm Change & Nat Disaster, Minist Educ, Beijing 100875, Peoples R China; 2.Beijing Normal Univ, Sch Geog, Fac Geog Sci, Beijing 100875, Peoples R China; 3.Nanjing Normal Univ, Jiangsu Ctr Collaborat Innovat Geog Informat Reso, Nanjing 210023, Jiangsu, Peoples R China; 4.Nanjing Normal Univ, Sch Geog, Nanjing 210023, Jiangsu, Peoples R China; 5.Univ Wisconsin, Dept Geog, Madison, WI 53706 USA
推荐引用方式 GB/T 7714	Yue Yaojie,Min, Li,Lin, Wang,et al. A data-mining-based approach for aeolian desertification susceptibility assessment: A case-study from Northern China[J]. 北京师范大学,2019,30(16):1968-1983.
APA	Yue Yaojie,Min, Li,Lin, Wang,&Zhu A-Xing.(2019).A data-mining-based approach for aeolian desertification susceptibility assessment: A case-study from Northern China.LAND DEGRADATION & DEVELOPMENT,30(16),1968-1983.
MLA	Yue Yaojie,et al."A data-mining-based approach for aeolian desertification susceptibility assessment: A case-study from Northern China".LAND DEGRADATION & DEVELOPMENT 30.16(2019):1968-1983.