The grain production potential assessment with multiple cropping index (MCI) in China

  • Zhiqiang Gao*
  • , Jicai Ning
  • , Wei Gao
  • *Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Scopus citations

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.

Original languageEnglish
Title of host publicationRemote Sensing and Modeling of Ecosystems for Sustainability XI
EditorsJinnian Wang, Ni-Bin Chang, Wei Gao
PublisherSPIE
ISBN (Electronic)9781628412482
DOIs
StatePublished - 2014
Externally publishedYes
EventRemote Sensing and Modeling of Ecosystems for Sustainability XI - San Diego, United States
Duration: 18 Aug 201420 Aug 2014

Publication series

NameProceedings of SPIE - The International Society for Optical Engineering
Volume9221
ISSN (Print)0277-786X
ISSN (Electronic)1996-756X

Conference

ConferenceRemote Sensing and Modeling of Ecosystems for Sustainability XI
Country/TerritoryUnited States
CitySan Diego
Period18/08/1420/08/14

Keywords

  • Change of cropland
  • China
  • Grain production potential
  • MCI
  • Time series data

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