Skip to main content

Mapping the global supply and demand structure of rice


Rice plays a major role in the global supply and demand for sustainable food production. The constraints of maintaining sustainable rice production are closely linked to the relationship between the distribution patterns of human activity on the planet and economic growth. Global patterns of rice production can be mapped by using various criteria linked to domestic income, population patterns, and associated satellite brightness data of rice-producing regions. Prosperous regions have more electric lighting, and there are documented correlations between gross domestic product (GDP) and nighttime light. We chose to examine global rice production patterns on a geographical basis. For the purposes of this study, each country is considered to be made up of regions, and rice production is discussed in terms of regional distribution. A region is delineated by its administrative boundaries; the number of regions where rice is produced is about 13,839. We used gridded spatial population distribution data overlain by nocturnal light imagery derived from satellite imagery. The resultant relationship revealed a correlation between regional income (nominal values of GDP were used) and rice production in the world. The following criteria were used to examine the supply and demand structure of rice. Global rice consumption = “caloric rice consumption per capita per day” multiplied by “regional population values”. Regional rice yields = “country-based production” divided by “harvested area” (multiple harvests are taken into account). Regional rice production = “regional harvested areas” multiplied by “rice yield values”. We compared regional rice consumption and production values according to these methods. Analysis of the data sets generated a map of rice supply and demand. Inter-regional shipping costs were not accounted for. This map can contribute to the understanding of food security issues in rice-producing regions and to estimating potential population values in such regions.

This is a preview of subscription content, access via your institution.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8


  1. DMSP (2008) Defense Meteorological Satellite Program Data Archive, Research, and Products.

  2. Elvidge CD, Sutton PS, Baugh KE, Tuttle BT, Howard AT, Erwin EH, Bhaduri B, Bright E (2006) A global poverty map derived from satellite data.

  3. FAO STAT (2008)

  4. GPCC (2008) Global precipitation climatology centre.

  5. IFS (2009) International Financial Statistics Publications Services CD-ROM. International Monetary Fund, Washington

    Google Scholar 

  6. Imhoff ML, Lawrence WT, Stutzer DC, Elvidge CD (1997) A technique for using composite DMSP/OLS “City lights” satellite data to map urban area. Remote Sensing Environ 61:361–370

  7. IRRI (2008) International Rice Research Institute Statistics Portal.

  8. ISS (2008) Information Sharing System System developed by Y. Shibatsuji, Kwansei Gakuin University. For base scripts refer to

  9. Kawashima H (2008) World food production and biomass energy. The outlook for 2050, University of Tokyo Press

  10. Land Scan (2003)

  11. Nakaya T (2002) A grid-surface projection of urban and rural population in China, 1990–2050. In: Otsubo K (ed) Study on the processes and impact of land-use change in China-final report of the LU/GEC second phase (1998–2000). Centre for Global Environmental Research, Ibaraki, Japan, pp 89–98

  12. USDA (2008) United States Department of Agriculture, Foreign Agricultural Service.

Download references


Night time Image and data processing by NOAA’s National Geophysical Data Center. DMSP data collected by US Air Force Weather Agency. Border data sets and River datasets are provided by ESRI company. Attached to ArcGIS Software.

Author information



Corresponding author

Correspondence to Kan-ichiro Matsumura.

Rights and permissions

Reprints and Permissions

About this article

Cite this article

Matsumura, Ki., Hijmans, R.J., Chemin, Y. et al. Mapping the global supply and demand structure of rice. Sustain Sci 4, 301 (2009).

Download citation


  • Rice consumption
  • Nocturnal lights
  • Gridded population
  • Harvested area