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Temporal patterns of road network development in the Brazilian Amazon

机译：巴西亚马逊地区道路网络发展的时间模式

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The Brazilian Amazon is a globally important ecosystem that is undergoing rapid development and land-use change. Roads are a key spatial determinant of land-use conversion and strongly influence the rates and patterns of habitat loss and represent a key component of models that attempt to predict the spatio-temporal patterns of Amazonian land-use change and the consequences of such changes. However, the spatio-temporal patterns of road network development are poorly understood and seldom quantified. Here, we used manually digitised satellite imagery at multiple temporal and spatial scales across the Brazilian Amazon to quantify and model the rate at which road networks are proliferating. We found that the road network grew by almost 17,000 km per year between 2004 and 2007. There was large spatial variation in road network density, with some municipalities having road densities as high as 0.5 km/km~2, and road network growth rates were highest in municipalities with an intermediate road network density. Simulations indicated that road network development within municipalities follows a logistic growth pattern through time, with most of the development occurring within a 39-year time period. This time period is similar to those of other boom and bust development dynamics observed in the Brazilian Amazon. Understanding the temporal patterns of road development will aid the development of better predictive land-use change models for the Amazon, given the key importance of roads as a predictor of deforestation in many existing models.
机译：巴西亚马逊河是全球重要的生态系统，正在经历快速发展和土地利用变化。道路是土地利用转化的关键空间决定因素，并且强烈影响着栖息地丧失的速度和方式，并且代表了模型的关键组成部分，这些模型试图预测亚马逊土地利用变化的时空格局及其变化的后果。但是，对道路网络发展的时空格局了解甚少，很少量化。在这里，我们使用了横跨巴西亚马逊的多个时空尺度的手动数字化卫星图像，以量化和建模道路网络的扩散速度。我们发现，路网在2004年至2007年之间每年增长近17,000 km。路网密度的空间变化很大，一些城市的路密度高达0.5 km / km〜2，路网增长率为在中等道路网密度的城市中最高。模拟表明，市政当局内的道路网络发展遵循逻辑增长模式，其中大部分发展发生在39年内。此时间段类似于在巴西亚马逊地区观察到的其他繁荣和萧条发展动态。考虑到在许多现有模型中道路作为森林砍伐预测因子的关键意义，了解道路发展的时间模式将有助于为亚马逊开发更好的土地利用预测模型。

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