干旱区生态环境知识资源中心(Arid): Spatio-temporal evolution and future scenario prediction of karst rocky desertification based on CA-Markov model

Arid

DOI	10.1007/s12517-021-07584-4
	Spatio-temporal evolution and future scenario prediction of karst rocky desertification based on CA-Markov model
	Chen, Fei; Wang, Shijie; Bai, Xiaoyong; Liu, Fang; Tian, Yichao; Luo, Guangjie; Li, Qin; Wang, Jingfeng; Wu, Luhua; Cao, Yue; Li, Huiwen; Deng, Yuanhong; Li, Chaojun; Yang, Yujie; Tian, Shiqi; Lu, Qian; Hu, Zheyin; Xi, Huipeng
通讯作者	Bai, XY (corresponding author), Guizhou Univ, Coll Resources & Environm Engn, Guiyang 550025, Peoples R China. ; Bai, XY (corresponding author), Chinese Acad Sci, Inst Geochem, State Key Lab Environm Geochem, 99 Lincheng West Rd, Guiyang 550081, Guizhou, Peoples R China. ; Bai, XY (corresponding author), Chinese Acad Sci, Puding Karst Ecosyst Observat & Res Stn, Puding 562100, Guizhou, Peoples R China.
来源期刊	ARABIAN JOURNAL OF GEOSCIENCES
ISSN	1866-7511
EISSN	1866-7538
出版年	2021
卷号	14 期号:13
英文摘要	Although the cellular automata (CA) model has been extensively applied in the simulation of ground cover changes, but it is rarely applied in the simulation of the driving forces of karst rock desertification (KRD). KRD has become one of the most serious ecological disasters in southwest China. Thus, it is necessary to accurately identify the driving factors affecting the occurrence and development of KRD. Accurately predicting the future development trend of KRD has great significance for quantitative evaluation of ecological environment governance and restoration in karst areas. We used the actual interpretation of KRD data in 2011 and 2016, based on the geographical detector to select the driving factors for the occurrence and development of KRD, and used the CA model to simulate the spatial and temporal changes of KRD. Results show that (1) the kappa verification accuracy for all types of KRD was above 0.5 when the CA model was used for the simulation of the spatial distribution of KRD and thus the theoretical requirements for accurate identification of the distribution of KRD were met. (2) Driving factors can be accurately screened by using the geodetector model to analyze the driving factors of KRD. The strengths of the factors follow the order lithology (0.35) > population density (0.30) > slope (0.21) > soil erosion (0.16) > altitude (0.05). (3)The combination of geodetector and the CA-Markov model results in the accurate prediction of the evolution of KRD and reduction in the arbitrariness of artificial subjective selection factors and the possibility of misjudgement. (4) From 2011 to 2021, the total area of KRD in the study area decreased at a rate of 29.96 km(2).a(-1), and KRD land indicated an overall trend of improvement. (5) Under the trend of overall improvement of KRD, some areas remain in which KRD increased and worsened. In the process of governance and protection, the impact of such deterioration on ecological environment must be considered.
英文关键词	Karst rocky desertification Geodetector Cellular automata Markov Spatial evolution
类型	Article
语种	英语
收录类别	SCI-E
WOS记录号	WOS:000677560900030
WOS关键词	CELLULAR-AUTOMATON MODEL ; GUIZHOU PROVINCE ; LAND ; FIRE ; DESIGN ; CARBON ; CHINA
WOS类目	Geosciences, Multidisciplinary
WOS研究方向	Geology
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/362535
作者单位	[Chen, Fei; Bai, Xiaoyong; Liu, Fang; Wang, Jingfeng; Lu, Qian] Guizhou Univ, Coll Resources & Environm Engn, Guiyang 550025, Peoples R China; [Chen, Fei; Wang, Shijie; Bai, Xiaoyong; Tian, Yichao; Li, Qin; Wang, Jingfeng; Wu, Luhua; Cao, Yue; Li, Huiwen; Deng, Yuanhong; Li, Chaojun; Yang, Yujie; Tian, Shiqi; Lu, Qian; Hu, Zheyin; Xi, Huipeng] Chinese Acad Sci, Inst Geochem, State Key Lab Environm Geochem, 99 Lincheng West Rd, Guiyang 550081, Guizhou, Peoples R China; [Chen, Fei; Wang, Shijie; Bai, Xiaoyong; Tian, Yichao; Li, Qin; Wang, Jingfeng; Wu, Luhua; Cao, Yue; Li, Huiwen; Deng, Yuanhong; Li, Chaojun; Yang, Yujie; Tian, Shiqi; Lu, Qian; Hu, Zheyin; Xi, Huipeng] Chinese Acad Sci, Puding Karst Ecosyst Observat & Res Stn, Puding 562100, Guizhou, Peoples R China; [Luo, Guangjie] Guizhou Educ Univ, Guizhou Prov Key Lab Geog State Monitoring Waters, Guiyang 550018, Guizhou, Peoples R China
推荐引用方式 GB/T 7714	Chen, Fei,Wang, Shijie,Bai, Xiaoyong,et al. Spatio-temporal evolution and future scenario prediction of karst rocky desertification based on CA-Markov model[J],2021,14(13).
APA	Chen, Fei.,Wang, Shijie.,Bai, Xiaoyong.,Liu, Fang.,Tian, Yichao.,...&Xi, Huipeng.(2021).Spatio-temporal evolution and future scenario prediction of karst rocky desertification based on CA-Markov model.ARABIAN JOURNAL OF GEOSCIENCES,14(13).
MLA	Chen, Fei,et al."Spatio-temporal evolution and future scenario prediction of karst rocky desertification based on CA-Markov model".ARABIAN JOURNAL OF GEOSCIENCES 14.13(2021).