干旱区生态环境知识资源中心(Arid): Shortwave infrared vegetation index-based modelling for aboveground vegetation biomass assessment in the arid steppes of Algeria

Arid

DOI	10.2989/10220119.2021.1882575
	Shortwave infrared vegetation index-based modelling for aboveground vegetation biomass assessment in the arid steppes of Algeria
	Benseghir, Louai; Bachari, Nour El Islam
通讯作者	Benseghir, L (corresponding author), Univ Mhamed Bougara, Lab Biodivers Biotechnol Environm & Dev Durable, Fac Sci, Dept Biol, Boumerdes, Algeria.
来源期刊	AFRICAN JOURNAL OF RANGE & FORAGE SCIENCE
ISSN	1022-0119
EISSN	1727-9380
出版年	2021-03
英文摘要	Selecting the appropriate vegetation index for accurate biomass estimation is a prerequisite before and during the ecosystem management project. This study, aims to compare Vegetation Indices (VIs) that are combining both Visible and Near Infrared OLI bands (VNIR-VIs), Visible and Short Wave Infrared OLI bands and also NIR and Short Wave Infrared OLI bands (SWIR-VIs) in order to accurately model the Aboveground Biomass (AGB) of three widely-located study sites over the arid steppe lands in Algeria. The Simple Linear Model (SLM) and Support Vector Machine (SVM) were utilised as statistical learning techniques on data; firstly, from each study site separately, and secondly, from all study sites (pooled data). In all study sites, SVM improves R-2 with a mean of 4.5% and decreases the Root Mean Squared Error (RMSE) and Percentage of Error (PE), respectively, with 15.50 (kg DM ha(-1)) and 1.33% on average. In all cases, the SWIR-VIs outperforms the VNIR-VIs with an improvement rate of 40% of R-2 and an average reduction of 362.36 kg DM ha(-1) and 25% of RMSE and PE, respectively. The principal main improvement was found to involve the pooled data-based model utilising normalised difference VI form, which combines OLI2(0.452-0.512 mu m) with OLI7(2.107-2.294 mu m), (R-2 = 0.840, p < 0.0005).
英文关键词	cross-validation Landsat 8 OLI machine learning Stipa tenacissima L
类型	Article ; Early Access
语种	英语
收录类别	SCI-E
WOS记录号	WOS:000630935800001
WOS类目	Ecology ; Environmental Sciences
WOS研究方向	Environmental Sciences & Ecology
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/367502
作者单位	[Benseghir, Louai] Univ Mhamed Bougara, Lab Biodivers Biotechnol Environm & Dev Durable, Fac Sci, Dept Biol, Boumerdes, Algeria; [Bachari, Nour El Islam] Univ Sci & Technol, Fac Sci Biol, Lab Oceanog Biol & Environm Marin LOBEM, Houari Boumediene, Alger, Algeria
推荐引用方式 GB/T 7714	Benseghir, Louai,Bachari, Nour El Islam. Shortwave infrared vegetation index-based modelling for aboveground vegetation biomass assessment in the arid steppes of Algeria[J],2021.
APA	Benseghir, Louai,&Bachari, Nour El Islam.(2021).Shortwave infrared vegetation index-based modelling for aboveground vegetation biomass assessment in the arid steppes of Algeria.AFRICAN JOURNAL OF RANGE & FORAGE SCIENCE.
MLA	Benseghir, Louai,et al."Shortwave infrared vegetation index-based modelling for aboveground vegetation biomass assessment in the arid steppes of Algeria".AFRICAN JOURNAL OF RANGE & FORAGE SCIENCE (2021).