
Proceedings Paper
The grain production potential assessment with multiple cropping index (MCI) in ChinaFormat | Member Price | Non-Member Price |
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Paper Abstract
This paper retrieved the information of cropland and MCI (Multiple Cropping Index) of China in 2000 and 2009 with SPOT NDVI time series data and utilized meteorological data and statistical data released by the state to calculate potential MCI and statistical MCI. Then, the MCI potential of China and grain production potential based on MCI were calculated in order to analyze the potential spatial distribution characteristics of MCI and the potential spatial pattern characteristics. The national mean MCI potentials in 2000 and 2009 are 0.485 and 0.506 respectively calculated with the remote sensing method and statistical method. And the grain productivity potentials of China based on MCI are 51% and 53% respectively. The improvement of MCI potential not only increases hydrothermal utilization rate and the utilization rate of cropland but also enormously enhances the food security degree of China and provides more available cropland area for the economic development.
Paper Details
Date Published: 8 October 2014
PDF: 5 pages
Proc. SPIE 9221, Remote Sensing and Modeling of Ecosystems for Sustainability XI, 922116 (8 October 2014); doi: 10.1117/12.2058304
Published in SPIE Proceedings Vol. 9221:
Remote Sensing and Modeling of Ecosystems for Sustainability XI
Wei Gao; Ni-Bin Chang; Jinnian Wang, Editor(s)
PDF: 5 pages
Proc. SPIE 9221, Remote Sensing and Modeling of Ecosystems for Sustainability XI, 922116 (8 October 2014); doi: 10.1117/12.2058304
Show Author Affiliations
Zhiqiang Gao, Yantai Institute of Coastal Zone Research (China)
Colorado State Univ. (China)
Jicai Ning, Yantai Institute of Coastal Zone Research (China)
Colorado State Univ. (China)
Jicai Ning, Yantai Institute of Coastal Zone Research (China)
Wei Gao, Colorado State Univ. (United States)
Published in SPIE Proceedings Vol. 9221:
Remote Sensing and Modeling of Ecosystems for Sustainability XI
Wei Gao; Ni-Bin Chang; Jinnian Wang, Editor(s)
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