Hyperspectral database prediction of ecological characteristics for grass species of alpine grasslands

doi:10.1071/RJ17084

CORC > 成都山地灾害与环境研究所 > 中国科学院水利部成都山地灾害与环境研究所 > 数字山地与遥感应用中心

	Hyperspectral database prediction of ecological characteristics for grass species of alpine grasslands
	Yu, Huan 1,6; Kong, Bo2 ; Wang, Guangxing 3; Sun, Hua 4; Wang, Lu5
刊名	RANGELAND JOURNAL
	2018
卷号	40 期号:1 页码:19-29
关键词	dominant species ecosystem monitoring prediction
ISSN号	1036-9872
DOI	10.1071/RJ17084
英文摘要	Alpine grasslands are being degraded because of human activities and associated global climate change. Mapping the spatial distributions and ecological characteristics of grass species is essential for scientific management of grasslands. However, traditional field-survey methods are costly or even impossible owing to poor accessibility. Hyperspectral remote sensing provides solutions for the purpose. This study was conducted in Shenzha County of the Qiangtang Plateau, north-western Qinghai-Tibet Plateau, to examine the potential of using hyperspectral data for identifying the grass species and predicting their ecological characteristics in the alpine grasslands dominated by Stipa purpurea with coexisting species Leontopodium nanum and Oxytropis microphylla. Hyperspectral data were collected in 106 sample quadrats and the ecological characteristics of each quadrat (number and height of plants, vegetation cover, etc.) were measured. The results of spectral data analysis and regression modelling showed the following. (i) The near-and middle-infrared region was more appropriate than the visible region for discriminating the grass species. (ii) The enhanced spectral variables had much higher correlations with the ecological characteristics than the original bands. (iii) Most of the 23 derived enhanced spectral variables were significantly correlated with the number and height of the dominant species plants within the quadrats. (iv) The vegetation cover could be accurately predicted by using the models based on the enhanced spectral variables of the fieldcollected hyperspectral data with the relativeRMSEvalues < 28%. (v) The ecological characteristics of the dominant species could be more accurately estimated than of co-existing species. Overall, this study suggests that the hyperspectral database method provided great potential to predict the ecological characteristics of grass species in alpine grasslands.
语种	英语
出版者	CSIRO PUBLISHING
WOS记录号	WOS:000428045400003
内容类型	期刊论文
源URL	[http://ir.imde.ac.cn/handle/131551/22844]
专题	成都山地灾害与环境研究所_数字山地与遥感应用中心
通讯作者	Yu, Huan
作者单位	1.Chengdu Univ Technol, Coll Earth Sci, Chengdu 610059, Sichuan, Peoples R China 2.Chinese Acad Sci, Inst Mt Hazards & Environm, Chengdu 610041, Sichuan, Peoples R China 3.Southern Illinois Univ, Dept Geog & Environm Resources, Carbondale, IL 62901 USA 4.Cent South Univ Forestry & Technol, Res Ctr Forestry Remote Sensing & Informat Engn, Changsha 410004, Hunan, Peoples R China 5.South China Agr Univ, Coll Nat Resources & Environm, Guangzhou 510642, Guangdong, Peoples R China 6.Minist Land & Resources, Key Lab Geosci Spatial Informat Technol, Chengdu 610059, Sichuan, Peoples R China
推荐引用方式 GB/T 7714	Yu, Huan,Kong, Bo,Wang, Guangxing,et al. Hyperspectral database prediction of ecological characteristics for grass species of alpine grasslands[J]. RANGELAND JOURNAL,2018,40(1):19-29.
APA	Yu, Huan,Kong, Bo,Wang, Guangxing,Sun, Hua,&Wang, Lu.(2018).Hyperspectral database prediction of ecological characteristics for grass species of alpine grasslands.RANGELAND JOURNAL,40(1),19-29.
MLA	Yu, Huan,et al."Hyperspectral database prediction of ecological characteristics for grass species of alpine grasslands".RANGELAND JOURNAL 40.1(2018):19-29.