Mapping the global supply and demand structure of rice |
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Authors: | Kan-ichiro Matsumura Rover J Hijmans Yann Chemin Christopher D Elvidge Kenji Sugimoto Wenbin Wu Yang-won Lee Ryosuke Shibasaki |
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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 |
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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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