A new temporal prediction method of grazing pressure based on normalized difference vegetation index and precipitation using nonlinear autoregressive with exogenous input networks-Reference-Cited by-同舟云学术

A new temporal prediction method of grazing pressure based on normalized difference vegetation index and precipitation using nonlinear autoregressive with exogenous input networks

Published:2019-10-09 Issue:2 Volume:66 Page:116-123
ISSN:1744-6961
Container-title:Grassland Science
language:en
Short-container-title:Grassl Sci

Author:

Wu Taosuo¹²³,Feng Feng⁴^ORCID,Lin Qian⁵,Bai Hongmei¹³

Affiliation:

1. School of Microelectronics Tianjin University Tianjin China

2. School of Physics and Electronic Information Hulunbuir College Hulunbuir China

3. Tianjin Key Laboratory of Imaging and Sensing Microelectronic Technology Tianjin University Tianjin China

4. Department of Electronics Carleton University Ottawa ON Canada

5. College of Physics and Electronic Information Engineer Qinghai Nationalities University Xining China

Funder

Qingdao National Laboratory for Marine Science and Technology

Publisher

Wiley

Subject

Plant Science,Agronomy and Crop Science,Ecology, Evolution, Behavior and Systematics

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1111/grs.12262

Reference37 articles.

1. Grassland degradation in China: Methods of monitoring, management and restoration

2. An international terminology for grazing lands and grazing animals

3. The Influence of Recent Grazing Pressure and Landscape Position on Grass Recruitment in a Semi-Arid Woodland of Eastern Australia.

4. Regional estimation of groundwater arsenic concentrations through systematical dynamic-neural modeling

5. Spatial and seasonal variation of climate on steppe slopes of the northern Mongolian mountain taiga

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