Analysis of Landsat-8 OLI Imagery for Estimating Exposed Bedrock Fractions in Typical Karst Regions of Southwest China Using a Karst Bare-Rock Index

doi:10.3390/rs10091321

	Analysis of Landsat-8 OLI Imagery for Estimating Exposed Bedrock Fractions in Typical Karst Regions of Southwest China Using a Karst Bare-Rock Index
	Pei, Jie 1,2; Wang, Li 1; Huang, Ni 1; Geng, Jing 2,3; Cao, Jianhua 4,5; Niu, Zheng 1,2
刊名	REMOTE SENSING
	2018-09-01
卷号	10 期号:9 页码:19
关键词	karst bare-rock index Landsat-8 remote sensing exposed bedrock fractions southwest China
ISSN号	2072-4292
DOI	10.3390/rs10091321
通讯作者	Wang, Li(wangli@radi.ac.cn) ; Niu, Zheng(niuzheng@radi.ac.cn)
英文摘要	Karst rocky desertification (KRD) has become the primary ecoenvironmental problem in the karst regions of southwest China. The rapid and efficient acquisition of exposed bedrock fractions (EBF) is crucial for the monitoring and assessment of KRD degree and distribution within the highly heterogeneous landscapes. Remote-sensing indices provide a useful method for the quick mapping of the EBF at large scales. The currently available rock indices, however, are faced with insensitivity to bedrock change characteristics, which greatly limits their performances and suitability. To address this problem, we proposed a novel karst bare-rock index (KBRI) that applies shortwave-infrared (SWIR) and near-infrared (NIR) bands from Landsat-8 OLI imagery to maximally distinguish between exposed bedrock and other land cover types in southwest China. A linear regression model was thus established between KBRI and the EBF derived from in situ measurements. The model developed here was then validated with an independent experiment and applied over a large geographic area to produce regional maps of EBF in southwest China. Experimental results showed good performance on root mean square error (5.59%), mean absolute error (4.63%), root mean absolute percentage error (13.59%), and coefficient of determination (0.72), respectively. The advantages of the proposed method are reflected in its simplicity and minimal requirements for auxiliary data while still achieving comparatively better accuracy than existing related indices. Thus, the KBRI has the great potential for the application in other regions around the world with the similar geological backgrounds, thereby helping to address the similar or other related environmental issues. Results of this study provide baseline data for the KRD assessment and karst-ecosystem management in southwest China.
资助项目	National Key Research and Development Project[2016YFC0502501] ; National Natural Science Foundation of China[41771465] ; National Natural Science Foundation of China[41871347]
WOS关键词	SPECTRAL MIXTURE ANALYSIS ; ESTIMATING ECOLOGICAL INDICATORS ; RESTORATION PROJECTS ; VEGETATION INDEXES ; BUILT-UP ; DESERTIFICATION ; COVER ; LAND ; AREAS ; LANDSCAPES
WOS研究方向	Remote Sensing
语种	英语
出版者	MDPI
WOS记录号	WOS:000449993800001
资助机构	National Key Research and Development Project ; National Natural Science Foundation of China
内容类型	期刊论文
源URL	[http://ir.igsnrr.ac.cn/handle/311030/52538]
专题	中国科学院地理科学与资源研究所
通讯作者	Wang, Li; Niu, Zheng
作者单位	1.Chinese Acad Sci, Inst Remote Sensing & Digital Earth, State Key Lab Remote Sensing Sci, POB 9718,Datun Rd, Beijing 100101, Peoples R China 2.Univ Chinese Acad Sci, Yuquan Rd 19, Beijing 100049, Peoples R China 3.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Key Lab Ecosyst Network Observat & Modeling, Datun Rd, Beijing 100101, Peoples R China 4.Chinese Acad Geol Sci, Inst Karst Geol, Key Lab Karst Dynam, Qixing Rd, Guilin 541004, Peoples R China 5.UNESCO, Int Res Ctr Karst, Qixing Rd, Guilin 541004, Peoples R China
推荐引用方式 GB/T 7714	Pei, Jie,Wang, Li,Huang, Ni,et al. Analysis of Landsat-8 OLI Imagery for Estimating Exposed Bedrock Fractions in Typical Karst Regions of Southwest China Using a Karst Bare-Rock Index[J]. REMOTE SENSING,2018,10(9):19.
APA	Pei, Jie,Wang, Li,Huang, Ni,Geng, Jing,Cao, Jianhua,&Niu, Zheng.(2018).Analysis of Landsat-8 OLI Imagery for Estimating Exposed Bedrock Fractions in Typical Karst Regions of Southwest China Using a Karst Bare-Rock Index.REMOTE SENSING,10(9),19.
MLA	Pei, Jie,et al."Analysis of Landsat-8 OLI Imagery for Estimating Exposed Bedrock Fractions in Typical Karst Regions of Southwest China Using a Karst Bare-Rock Index".REMOTE SENSING 10.9(2018):19.