Spatial Exploration of Multiple Cropping Efficiency in China Based on Time Series Remote Sensing Data and Econometric Model

This study explored spatial explicit multiple cropping efficiency (MCE) of China in 2005 by coupling time series remote sensing data with an econometric model – stochastic frontier analysis (SFA). We firstly extracted multiple cropping index (MCI) on the basis of the close relationship between crop...

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Bibliographic Details
Main Authors: Li-jun ZUO, Xiao WANG, Fang LIU, Ling YI
Format: Article
Language:English
Published: Elsevier 2013-05-01
Series:Journal of Integrative Agriculture
Subjects:
Online Access:http://www.sciencedirect.com/science/article/pii/S2095311913603081
Description
Summary:This study explored spatial explicit multiple cropping efficiency (MCE) of China in 2005 by coupling time series remote sensing data with an econometric model – stochastic frontier analysis (SFA). We firstly extracted multiple cropping index (MCI) on the basis of the close relationship between crop phenologies and moderate-resolution imaging spectroradiometer (MODIS) enhanced vegetation index (EVI) value. Then, SFA model was employed to calculate MCE, by considering several indicators of meteorological conditions as inputs of multiple cropping systems and the extracted MCI was the output. The result showed that 46% of the cultivated land in China in 2005 was multiple cropped, including 39% double-cropped land and 7% triple-cropped land. Most of the multiple cropped land was distributed in the south of Great Wall. The total efficiency of multiple cropping in China was 87.61% in 2005. Southwestern China, Ganxin Region, the middle and lower reaches of Yangtze River and Huanghuaihai Plain were the four agricultural zones with the largest rooms for increasing MCI and improving MCE. Fragmental terrain, soil salinization, deficiency of water resources, and loss of labor force were the obstacles for MCE promotion in different zones. The method proposed in this paper is theoretically reliable for MCE extraction, whereas further studies are need to be done to investigate the most proper indicators of meteorological conditions as the inputs of multiple cropping systems.
ISSN:2095-3119