Land-use Change in the Central Highlands of Vietnam
Land-use Change in the Central Highlands of Vietnam
复制标题
越南中部高地的土地利用变化
DOI：
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发表时间：
2003
期刊：
影响因子：
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通讯作者：
D. Müller
中科院分区：
文献类型：
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作者：
D. Müller
本文研究了在过去的25年中，在越南中部高地的达拉克省的两个地区的土地利用变化的地球物理，农业生态和社会经济的决定因素的作用。对这些决定因素的分析有助于评估各种农村发展政策对土地覆被变化的影响。对1975年、1992年和2000年同一种植期的大地遥感卫星图像进行了解释，以检测这两个时期之间的土地覆盖变化。在随机选择的村庄进行的一项调查提供了关于社会经济和政策变量的初步回忆数据，这些变量被假设会影响土地使用的变化。从气象站、数字土壤图和数字高程模型获得了关于降雨量、土壤适宜性和地形的次级数据。所有数据均使用GIS软件进行空间参照。使用可访问性汇流将测量数据与空间显式栅格数据合并，可访问性汇流的设计目的是：基于从每个小区到村庄位置的估计的旅行成本来确定近似的村庄区域。一个简化的形式，多项logit模型是用来估计的影响，假设的决定因素对土地利用和概率，某个像素有五个土地覆盖类在任何两个periodsconsidered.Results结果表明，第一个时期，从1975年至1992年的特点是土地密集型农业扩张和森林转化为草地和农业用地。在第二个时期，自1992年以来，农业部门的快速、劳动和资本密集型增长是由于化肥的引入、农村道路和市场的改善以及灌溉面积的扩大。这些政策，加上在第二个时期实行森林保护区和不鼓励轮垦的政策，减少了对森林的压力，同时提高了农业生产力，增加了人口的收入。在第二个时期，森林覆盖率的增加主要是由于以前用于轮垦的地区的再生，政策模拟模拟了潜在的政策干预对土地使用的影响。政策模拟的土地覆被类别汇总为三类，并绘制了空间样本，以集中分析人为干预影响的变化。这样，模拟的重点是已耕种地区和农业前沿地区的土地使用变化，因为对决策者来说，大多数土地使用变化都发生在这些地区。模拟仅限于1992年至2000年的第二个时期，因为这是可能的政策措施的相关时期，对灌溉设施的低水平和高水平投资、扩大森林保护面积以及灌溉高投资与增加森林保护相结合的四种农村政策情景进行了模拟，这是经常提到的第一最佳政策选择。对这些政策干预措施进行空间上明确的模拟，有助于取得空间上明确的结果，使决策者能够制定和实施针对地理位置的农村发展干预措施。模拟结果表明，适度的土地利用变化的预期方向下的四个情景。对预期变化的位置进行直观评估，可以确定土地覆被转换的可能热点，并可以事先评估拟议的政策干预对土地利用变化幅度的影响。
This dissertation investigates the role of geophysical, agroecological, and socioeconomic determinants of land-use change during the last 25 years in two districts of Dak Lak province in the Central Highlands of Vietnam. The analysis of these determinants allows to assess the influences of various rural development policies on land-cover changes. Landsat satellite images from the same cropping period of the years 1975, 1992 and 2000 are interpreted to detect land-cover change between the two time periods. A survey in randomly selected villages provides primary recall data on socio-economic and policy variables hypothesized to influence land-use change. Secondary data on rainfall, soil suitability, and topography were obtained from meteorological stations, from a digital soil map and a digital elevation model. All data were spatially referenced using GIS software. Survey data is merged with spatially explicit raster data using accessibility catchments, which are designed to a! pproximate village areas based on the estimated travel costs from each cell to the village location. A reduced-form, multinomial logit model is used to estimate the influence of hypothesized determinants on land use and the probabilities that a certain pixel has one of five land-cover classes during either of the two periods under consideration.Results suggest that the first period from 1975 to 1992 was characterized by land-intensive agricultural expansion and the conversion of forest into grass and agricultural land. During the second period, since 1992, the rapid, more labor- and capital-intensive growth in the agricultural sector was enabled by the introduction of fertilizer, improved access to rural roads and markets, and the expansion of irrigated areas. These policies, combined with the introduction of protected forest areas and policies discouraging shifting cultivation during the second period reduced the pressure on forests while at the same time increasing agricultural productivity and incomes for a growing population. Forest cover during the second period mainly increased due to the regeneration of areas formerly used for shifting cultivation.Policy simulations mimic the influences from potential policy interventions on land use. Land-cover categories for the policy simulations are aggregated to three classes and a spatial sample is drawn to concentrate the analysis on changes influenced by anthropogenic interventions. In that way, the focus of the simulations is on land-use changes within already cultivated areas and at the agricultural frontier where most land-use changes relevant for policy makers take place. The simulations are limited to the second period from 1992 to 2000 as this is the relevant period for potential policy measures.The four rural policy scenarios are carried out for low and high levels of investments in irrigation facilities, for an enlarged area under forest protection and for a combination of high investments in irrigation combined with increased forest protection, an often mentioned first-best policy option. Spatially explicit simulations of these policy interventions facilitate spatially explicit results, which can enable decision makers to formulate and implement geographically targeted rural development interventions. Simulation results suggest modest land-use changes in the expected directions under the four scenarios. A visual assessment of the location of the expected changes enables the identification of probable hotspots of land-cover conversions and allows for an ex-ante evaluation of the impacts of proposed policy interventions on the magnitude of land-use change.