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Mapping the global supply and demand structure of rice
Authors:Kan-ichiro Matsumura  Rover J Hijmans  Yann Chemin  Christopher D Elvidge  Kenji Sugimoto  Wenbin Wu  Yang-won Lee  Ryosuke Shibasaki
Institution:(1) Department of Informatics, School of Policy Studies, Kwansei Gakuin University, Sanda Hyogo, 669-1337, Japan;(2) Geography (GIS) Lab, International Rice Research Institute, Los Banos, Laguna, Philippines;(3) United States Department of Commerce, NOAA National Geophysical Data Center, 325 Broadway, Boulder, CO 80205, USA;(4) Center for Spatial Information Science, The University of Tokyo, 4-6-1 Komaba, Meguro-ku Tokyo, 153-8505, Japan
Abstract: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.
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