干旱区生态环境知识资源中心(Arid): Extracting Information on Rocky Desertification from Satellite Images: A Comparative Study

Arid

DOI	10.3390/rs13132497
	Extracting Information on Rocky Desertification from Satellite Images: A Comparative Study
	Pu, Junwei; Zhao, Xiaoqing; Dong, Pinliang; Wang, Qian; Yue, Qifa
通讯作者	Zhao, XQ (corresponding author), Yunnan Univ, Sch Earth Sci, Kunming 650500, Yunnan, Peoples R China.
来源期刊	REMOTE SENSING
EISSN	2072-4292
出版年	2021
卷号	13 期号:13
英文摘要	Rocky desertification occurs in many karst terrains of the world and poses major challenges for regional sustainable development. Remotely sensed data can provide important information on rocky desertification. In this study, three common open-access satellite image datasets (Sentinel-2B, Landsat-8, and Gaofen-6) were used for extracting information on rocky desertification in a typical karst region (Guangnan County, Yunnan) of southwest China, using three machine-learning algorithms implemented in the Python programming language: random forest (RF), bagged decision tree (BDT), and extremely randomized trees (ERT). Comparative analyses of the three data sources and three algorithms show that: (1) The Sentinel-2B image has the best capability for extracting rocky desertification information, with an overall accuracy (OA) of 85.21% using the ERT method. This can be attributed to the higher spatial resolution of the Sentinel-2B image than that of Landsat-8 and Gaofen-6 images and Gaofen-6's lack of the shortwave infrared (SWIR) bands suitable for mapping carbonate rocks. (2) The ERT method has the best classification results of rocky desertification. Compared with the RF and BDT methods, the ERT method has stronger randomness in modeling and can effectively identify important feature factors for extracting information on rocky desertification. (3) The combination of the Sentinel-2B images and the ERT method provides an effective, efficient, and free approach to information extraction for mapping rocky desertification. The study can provide a useful reference for effective mapping of rocky desertification in similar karst environments of the world, in terms of both satellite image sources and classification algorithms. It also provides important information on the total area and spatial distribution of different levels of rocky desertification in the study area to support decision making by local governments for sustainable development.
英文关键词	rocky desertification open-access satellite image information extraction machine-learning algorithms southwest China
类型	Article
语种	英语
开放获取类型	Green Published, gold
收录类别	SCI-E
WOS记录号	WOS:000672010800001
WOS关键词	ECOSYSTEM SERVICES ; NORTHWEST GUANGXI ; EXPOSED BEDROCK ; KARST AREAS ; VEGETATION ; PROJECTS ; PROVINCE ; REGION ; COVER ; CHINA
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/2XILL650/351542
作者单位	[Pu, Junwei; Zhao, Xiaoqing; Wang, Qian; Yue, Qifa] Yunnan Univ, Sch Earth Sci, Kunming 650500, Yunnan, Peoples R China; [Pu, Junwei] Yunnan Univ, Inst Int Rivers & Ecosecur, Kunming 650500, Yunnan, Peoples R China; [Dong, Pinliang] Univ North Texas, Dept Geog & Environm, Denton, TX 76203 USA
推荐引用方式 GB/T 7714	Pu, Junwei,Zhao, Xiaoqing,Dong, Pinliang,et al. Extracting Information on Rocky Desertification from Satellite Images: A Comparative Study[J],2021,13(13).
APA	Pu, Junwei,Zhao, Xiaoqing,Dong, Pinliang,Wang, Qian,&Yue, Qifa.(2021).Extracting Information on Rocky Desertification from Satellite Images: A Comparative Study.REMOTE SENSING,13(13).
MLA	Pu, Junwei,et al."Extracting Information on Rocky Desertification from Satellite Images: A Comparative Study".REMOTE SENSING 13.13(2021).