| Research Abstract |
The principal contents of this study as follows,
(1) Data Base Constnsction on Global Environment
principal date base made in this study as foIIows,
- Land Use Cover Change Map in 1960's by digitizing Atlas of Agriculture
- Potential distribution of arable land by the method of Cramer and Solomon
- Population , GDP, food Productivity, food consumption, energy consumption, fire wood consumption and round wood consumption per country.
(2) Estimation of Amount of Global Land Resources Considering Trade off Development, Resources and Environment
(3) Estimation of Land Use Cover Change Considering Change of Life Style
Using GIS and socio-economical data the relationship between human activities and global environmental change is Analysed from the view point of food productivity and C02 emission. Under the assumption that the population problem, the food problem and global warming due to energy consumption can be stabilized through managing land use, impacts of human activities such as consumption o
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f food, energy and timber on global environment changes, and global population capacity are Analysed using developed system dynamics model in the research. In the model the world is divided into two groups : OECD countries and the others. Used global land use data set is land cover map derived from satellite data, and potential distribution of arable land is estimated by the method of Cramer and Solomon which takes into consideration spatial distribution of climate data such as precipitation and evapotranspiration. In addition, impacts of C02 emission from human activities on food production through global warming are included in the model as a feedback.
The results of the analysis for BaU scenario and Toronto Conference scenario are similar to the results of existing models. From the result of this study, the human habitability in 2020 is 8 billion people, and C02 emission in 2020 based on BaU Scenario and on Toronto Scenario is 1.7 and 1.2 times more than the 1986's respectively. Improving spatial resolution of the model by using global data to distribute the environmental variables and sauce-economical indices is left for flurther studies. Less
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