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首页> 外文学位 >Economic modeling of tropical deforestation in Antioquia (Colombia), 1980--2000: An analysis at a semi-fine scale with spatially explicit data.
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Economic modeling of tropical deforestation in Antioquia (Colombia), 1980--2000: An analysis at a semi-fine scale with spatially explicit data.

机译：1980--2000年，安蒂奥基亚（哥伦比亚）热带森林砍伐的经济模型：使用空间明晰数据的半精细规模分析。

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摘要

This dissertation used land rent theory and an economic model of land-use conversion to examine the main drivers of the deforestation occurred in Antioquia, Colombia, between 1980 and 2000. Land-cover information at a semi-fine scale (1:25,000) obtained largely from aerial photography was employed to calculate deforestation. In addition, free international databases and national georeferenced biophysical information are also used to consolidate a set of potential explanatory variables. Econometric models estimated the clearing probability as a function of the variables: distance from roads, distance from rivers, slope, Gini's index (a measure of land ownership concentration), soil fertility, protected area, and population density.;The robustness of the statistical estimation to the pixel size, the analysis unit used in this dissertation, suggests that a 30 m pixel size model performs better from a statistical viewpoint than models with pixel size from 50 to 300 m. The 30 m pixel size model has the highest values of R 2 and area under the ROC curve, an index used to measure discrimination accuracy in the econometric models. Elasticity magnitudes of all the explanatory variables included in the 30 m pixel size model indicate that the Gini's index, the slope, and the distance from roads are the main drivers of the observed deforestation in Antioquia. The 30 m pixel size model was used in policy analyses in two different ways: (i) to simulate how new roads may influence deforestation, (ii) to identify the areas under greater threat of deforestation.;For the building of new roads a simulated scenario examines the incremental effects on deforestation with respect to a base scenario, after reducing the distance from roads by a fixed percentage of 50%. Simulation results suggest that the building of new roads will induce more deforestation (~1039 hectares) compared to the base scenario. The results of this dissertation were also employed to identify forest areas under greater threat of deforestation. The results indicate that the forests located in the Northwest of Antioquia are under greater threat of conversion most likely because of their accessibility, and that forests located in remote sites may be protected without significant institutional efforts.
机译：本文利用土地租金理论和土地利用转化的经济模型，研究了1980至2000年间哥伦比亚安蒂奥基亚发生的森林砍伐的主要动因。获得了半精细规模的土地覆盖信息（1：25,000）很大程度上是通过航空摄影来计算森林砍伐。此外，还使用免费的国际数据库和国家地理参考的生物物理信息来合并一组潜在的解释变量。计量经济学模型根据以下变量估算清算概率：与道路的距离，与河流的距离，坡度，基尼系数（土地所有权集中度的度量），土壤肥力，保护区和人口密度。;统计的稳健性通过对像素大小的估计，本文的分析单元表明，从统计角度来看，30 m像素大小的模型比像素大小为50至300 m的模型表现更好。 30 m像素大小的模型具有最高的R 2值和ROC曲线下的面积，ROC曲线是衡量计量经济学模型中判别准确性的指标。 30 m像素大小模型中包含的所有解释变量的弹性强度表明，基尼系数，坡度和与道路的距离是观察到的安蒂奥基亚森林砍伐的主要驱动力。 30 m像素大小的模型以两种不同的方式用于政策分析：（i）模拟新道路如何影响毁林，（ii）识别遭受毁林威胁更大的区域。;对于新建道路的模拟情景研究了在与道路的距离减少50％的固定百分比之后，相对于基本情景对毁林的增量影响。仿真结果表明，与基本方案相比，修建新道路将导致更多的森林砍伐（约1039公顷）。本文的结果也被用于识别森林砍伐威胁更大的森林区域。结果表明，位于安蒂奥基亚西北部的森林最有可能由于其可及性而面临更大的转化威胁，而且位于偏远地区的森林无需大量机构努力即可得到保护。

著录项

  • 作者

    Orrego, Sergio.;

  • 作者单位

    Oregon State University.;

  • 授予单位 Oregon State University.;
  • 学科 Agriculture Forestry and Wildlife.;Economics Agricultural.;Natural Resource Management.;Land Use Planning.
  • 学位 Ph.D.
  • 年度 2009
  • 页码 137 p.
  • 总页数 137
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 森林生物学;农业经济;
  • 关键词

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