干旱区生态环境知识资源中心(Arid): A new temporal prediction method of grazing pressure based on normalized difference vegetation index and precipitation using nonlinear autoregressive with exogenous input networks

Arid

DOI	10.1111/grs.12262
	A new temporal prediction method of grazing pressure based on normalized difference vegetation index and precipitation using nonlinear autoregressive with exogenous input networks
	Wu, Taosuo 1,2,3; Feng, Feng 4; Lin, Qian 5; Bai, Hongmei 1,3
通讯作者	Feng, Feng
来源期刊	GRASSLAND SCIENCE
ISSN	1744-6961
EISSN	1744-697X
出版年	2020
卷号	66 期号:2 页码:116-123
英文摘要	Restoration of natural vegetation in arid and semi-arid grasslands is facing severe challenges. The vegetation is easy to lose their vitality, resulting in the loss of the cover in natural grasslands under the high grazing pressure. To address this situation, this paper proposes a novel method for accurately predicting the grazing pressure using the nonlinear autoregressive with exogenous input (NARX) network based on the remote sensing data of normalized difference vegetation index (NDVI) and precipitation. The proposed method uses the NARX networks to predict the temporal variations of the NDVI with respect to the precipitation. The grazing pressure can be thus calculated using the predicted values of the NDVI. For practical application, this study investigated an arid and semi-arid grassland with heavy grazing pressure in Hulunbuir, China. The results demonstrate that the proposed method can provide an accurate prediction of the grazing pressure (mean absolute error 0.103, root-mean-square error 0.122, mean absolute percentage error 8.36% and coefficient of determination 0.899 at the confidence interval of 95%). In addition, the predicted values of the grazing pressure in the study area during the years from 2016 to 2020 can be obtained using the proposed method. The proposed method can obtain a good prediction of the grazing pressure, which can be further used as a guidance for the rangeland managers to reduce the occurrence of the overgrazing.
英文关键词	grazing pressure NARX network NDVI precipitation prediction
类型	Article
语种	英语
国家	Peoples R China ; Canada
收录类别	SCI-E
WOS记录号	WOS:000489242100001
WOS关键词	INNER-MONGOLIA ; NEURAL-NETWORK ; GRASSLAND ; RANGELAND ; EROSION ; STEPPE ; CHINA
WOS类目	Agriculture, Multidisciplinary ; Agronomy
WOS研究方向	Agriculture
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/216109
作者单位	1.Tianjin Univ, Sch Microelect, Tianjin, Peoples R China; 2.Hulunbuir Coll, Sch Phys & Elect Informat, Hulunbuir, Peoples R China; 3.Tianjin Univ, Tianjin Key Lab Imaging & Sensing Microelect Tech, Tianjin, Peoples R China; 4.Carleton Univ, Dept Elect, 1125 Colonel By Dr, Ottawa, ON K1S 5B6, Canada; 5.Qinghai Nationalities Univ, Xining, Qinghai, Peoples R China
推荐引用方式 GB/T 7714	Wu, Taosuo,Feng, Feng,Lin, Qian,et al. A new temporal prediction method of grazing pressure based on normalized difference vegetation index and precipitation using nonlinear autoregressive with exogenous input networks[J],2020,66(2):116-123.
APA	Wu, Taosuo,Feng, Feng,Lin, Qian,&Bai, Hongmei.(2020).A new temporal prediction method of grazing pressure based on normalized difference vegetation index and precipitation using nonlinear autoregressive with exogenous input networks.GRASSLAND SCIENCE,66(2),116-123.
MLA	Wu, Taosuo,et al."A new temporal prediction method of grazing pressure based on normalized difference vegetation index and precipitation using nonlinear autoregressive with exogenous input networks".GRASSLAND SCIENCE 66.2(2020):116-123.