TY - JOUR
T1 - A risk-based model for grassland management using MODIS data
T2 - The case of Gannan region, China
AU - Liu, Ying
AU - Feng, Qisheng
AU - Wang, Chenggang
AU - Tang, Zeng
N1 - Publisher Copyright:
© 2018 Elsevier Ltd
Copyright:
Copyright 2018 Elsevier B.V., All rights reserved.
PY - 2018/3
Y1 - 2018/3
N2 - The grassland classification management model is considered to be a sustainable approach for grassland resources use. However, it is difficult to accurately calculate the index of classification management of grasslands (ICG) due to high variability of grassland productivity and livestock prices. Inaccurate ICG indices may lead to adoption of unreliable grassland management strategies. To overcome the problem, this article introduces a risk-based ICG model accounting for sheep prices, grassland productivity, and their variability. In this model, grassland forage dry biomass and coverage from 2001 to 2016 were estimated with enhanced vegetation index (EVI) of each pixel in MODIS using the power model and logarithmic model, respectively. A simple linear regression model was employed to estimate sheep prices. Finally, the ICGm was estimated by variability of grassland productivity and sheep prices derived from the models. A test of the performance of the model showed that the area of conservative and moderately productive grassland predicted with the risk-based model fits very well with the observed area. This risk-based ICG model thus provides a reliable tool for classification management of grassland.
AB - The grassland classification management model is considered to be a sustainable approach for grassland resources use. However, it is difficult to accurately calculate the index of classification management of grasslands (ICG) due to high variability of grassland productivity and livestock prices. Inaccurate ICG indices may lead to adoption of unreliable grassland management strategies. To overcome the problem, this article introduces a risk-based ICG model accounting for sheep prices, grassland productivity, and their variability. In this model, grassland forage dry biomass and coverage from 2001 to 2016 were estimated with enhanced vegetation index (EVI) of each pixel in MODIS using the power model and logarithmic model, respectively. A simple linear regression model was employed to estimate sheep prices. Finally, the ICGm was estimated by variability of grassland productivity and sheep prices derived from the models. A test of the performance of the model showed that the area of conservative and moderately productive grassland predicted with the risk-based model fits very well with the observed area. This risk-based ICG model thus provides a reliable tool for classification management of grassland.
KW - Ecological value
KW - Grassland management
KW - Livestock production
KW - Remote sensing
KW - Risk aversion behaviors
KW - Sustainability
UR - http://www.scopus.com/inward/record.url?scp=85041403894&partnerID=8YFLogxK
U2 - 10.1016/j.landusepol.2018.01.015
DO - 10.1016/j.landusepol.2018.01.015
M3 - Article
AN - SCOPUS:85041403894
VL - 72
SP - 461
EP - 469
JO - Land Use Policy
JF - Land Use Policy
SN - 0264-8377
ER -