A Statistical Approach for Predicting Grassland Degradation in Disturbance-Driven Landscapes

ISSN Print: 2152-2197
ISSN Online: 2152-2219
www.scirp.org/journal/jep
E-mail: jep@scirp.org

Citations

"A Statistical Approach for Predicting Grassland Degradation in Disturbance-Driven Landscapes"
written by Anne Jacquin, Michel Goulard, J. M. Shawn Hutchinson, Thomas Devienne, Stacy L. Hutchinson,
published by Journal of Environmental Protection, Vol.7 No.6, 2016

has been cited by the following article(s):

[1]	Overview of Grassland Degradation Research Based on Remote Sensing Monitoring
	Open Journal of Applied …, 2022

[2]	Using Shapley additive explanations to interpret extreme gradient boosting predictions of grassland degradation in Xilingol, China
	2021

[3]	Modelling land use and land cover change on the Mongolian Plateau
	2020

[4]	Phenology-adjusted dynamic curve number for improved hydrologic modeling
	2019

[5]	Quantifying the role of climate change and land use on desertification using remote sensing
	2018

[6]	Detecting dryland degradation using Time Series Segmentation and Residual Trend analysis (TSS-RESTREND)
	Remote Sensing of Environment, 2017

[7]	Time Series Analysis of Phenometrics and Long-Term Vegetation Trends for the Flint Hills Ecoregion using Moderate Resolution Satellite Imagery
	2017

[1]	Partial Order Ranking of the Key Drivers of Grassland Conversion in the Urban–Grassland Interface: A Case Study of the Hohhot–Baotou–Ordos Region Applied Sciences, 2025 DOI:10.3390/app15115906

[2]	Using Shapley additive explanations to interpret extreme gradient boosting predictions of grassland degradation in Xilingol, China Geoscientific Model Development, 2021 DOI:10.5194/gmd-14-1493-2021

[3]	Phenology-adjusted dynamic curve number for improved hydrologic modeling Journal of Environmental Management, 2019 DOI:10.1016/j.jenvman.2018.12.115

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