干旱区生态环境知识资源中心(Arid): Using Landsat observations (1988-2017) and Google Earth Engine to detect vegetation cover changes in rangelands - A first step towards identifying degraded lands for conservation

Arid

DOI	10.1016/j.rse.2019.111317
	Using Landsat observations (1988-2017) and Google Earth Engine to detect vegetation cover changes in rangelands - A first step towards identifying degraded lands for conservation
	Xie, Zunyi 1,2,3; Phinn, Stuart R.3; Game, Edward T.4; Pannell, David J.5; Hobbs, Richard J.6; Briggs, Peter R.7; McDonald-Madden, Eve 2
通讯作者	Xie, Zunyi
来源期刊	REMOTE SENSING OF ENVIRONMENT
ISSN	0034-4257
EISSN	1879-0704
出版年	2019
卷号	232
英文摘要	Globally, the area of agricultural land is shrinking in part due to environmental degradation. Acquisition and restoration of degraded lands no longer used for agriculture may present a major conservation opportunity with minimal social and political opposition. The ability to efficiently and accurately identify these lands from regional to global scales will aid conservation management, ultimately enhancing the global prospects of achieving the Sustainable Development Goals (SDGs). Remote Sensing provides a potential tool to identify areas where surface property changes can be mapped and linked with land degradation. In this study, we begin to tackle a small section of this challenge by presenting novel approach to mapping changes in vegetation cover amounts at the pixel level (30 m), using Google Earth Engine (GEE). We illustrate our approach across large-scale rangelands in Queensland Australia, using three decades of Landsat satellite imagery (1988-2017) along with field observations of land condition scores for validation. The approach used an existing method for dynamic reference cover to remove the rainfall variability and focused on the human management effects on the vegetation cover changes. Results showed the identified vegetation cover changes could be categorized into five classes of decrease, increase or stable cover compared with a set reference level, which was obtained from locations of the most persistent ground cover across all dry years. In total, vegetation cover decrease was observed in 20% of our study area, with similar portion of lands recovering and the rest (similar to 60%) staying stable. The lands with decrease in vegetation cover, covering a considerable area of similar to 2 x 10(5) km(2), exhibited a markedly reduced resilience to droughts. The accuracy assessment yielded an overall classification accuracy of 82.6% (+/- 3.32 standard error) with 75.0% (+/- 5.16%) and 70.0% (+/- 4.13%) producer's and user's accuracy for areas experiencing a significant decrease in vegetation cover, respectively. Identifying areas of degraded land will require multiple stages of spatial data analysis and this work provided the first stage for identifying vegetation cover changes in large-scale rangeland environment, and provides a platform for future research and development to identify degraded lands and their utility for achieving conservation endeavours.
英文关键词	Vegetation cover Rangelands SDGs Big data Landsat Google Earth Engine
类型	Article
语种	英语
国家	Peoples R China ; Australia
开放获取类型	Green Submitted
收录类别	SCI-E
WOS记录号	WOS:000486355300042
WOS关键词	TREND ANALYSIS ; SURFACE-WATER ; DEGRADATION ; CLASSIFICATION ; ACCURACY ; RAINFALL ; DROUGHT ; INDEX ; AREA ; DESERTIFICATION
WOS类目	Environmental Sciences ; Remote Sensing ; Imaging Science & Photographic Technology
WOS研究方向	Environmental Sciences & Ecology ; Remote Sensing ; Imaging Science & Photographic Technology
来源机构	Commonwealth Scientific and Industrial Research Organisation ; University of Western Australia
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/218433
作者单位	1.Henan Univ, Minist Educ, Key Lab Geospatial Technol Middle & Lower Yellow, Kaifeng 475004, Peoples R China; 2.Univ Queensland, Ctr Biodivers & Conservat Sci, Sch Earth & Environm Sci, Brisbane, Qld 4072, Australia; 3.Univ Queensland, Remote Sensing Res Ctr, Sch Earth & Environm Sci, Brisbane, Qld 4072, Australia; 4.Nature Conservancy, South Brisbane, Qld 4101, Australia; 5.Univ Western Australia, Sch Agr & Environm, Crawley, WA 6009, Australia; 6.Univ Western Australia, Sch Biol Sci, Crawley, WA 6009, Australia; 7.CSIRO Oceans & Atmosphere, Canberra, ACT 2601, Australia
推荐引用方式 GB/T 7714	Xie, Zunyi,Phinn, Stuart R.,Game, Edward T.,et al. Using Landsat observations (1988-2017) and Google Earth Engine to detect vegetation cover changes in rangelands - A first step towards identifying degraded lands for conservation[J]. Commonwealth Scientific and Industrial Research Organisation, University of Western Australia,2019,232.
APA	Xie, Zunyi.,Phinn, Stuart R..,Game, Edward T..,Pannell, David J..,Hobbs, Richard J..,...&McDonald-Madden, Eve.(2019).Using Landsat observations (1988-2017) and Google Earth Engine to detect vegetation cover changes in rangelands - A first step towards identifying degraded lands for conservation.REMOTE SENSING OF ENVIRONMENT,232.
MLA	Xie, Zunyi,et al."Using Landsat observations (1988-2017) and Google Earth Engine to detect vegetation cover changes in rangelands - A first step towards identifying degraded lands for conservation".REMOTE SENSING OF ENVIRONMENT 232(2019).