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Investigations of fire dynamics in seasonally dry regions of the Amazon rainforest (Brazil).

机译:对亚马逊雨林(巴西)季节性干旱地区火灾动态的调查。

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Forests in seasonally dry regions of the Brazilian Amazon have been burning at an increasing rate in recent years, and much of this increase has been due to the disturbance of forest canopy through selective logging. In this thesis, the results of field studies on fire and edge effects are extrapolated to landscape and regional scales through the use of remote sensing data and simulation modeling. A scale relation formalism is used to clarify the spatial and temporal components of this process. Remote sensing data are used to analyze land cover, fire counts and precipitation over a decade, and spatiotemporal characteristics of active fires in 1998. A simulation model of fire growth on gridded artificial landscapes at a 30 m resolution incorporates a model of flammability edge effects implemented with integrative spatial filters. The model reveals that there may be specific thresholds of canopy gap probabilities above which the contiguity of flammable fuel allows for the indefinite spatial spread of any single surface fire in the fuel bed. This condition can be described in terms of a critical percolation. The model is applied to landscapes derived from Landsat data, but the resolution of the 30 m data and model are shown to be problematic. The model resolution is improved to 6 m, and the possible use of IKONOS data is investigated. The fire spread model at the 6 m resolution is used to examine artificial landscapes with gaps of various sizes, from 36 to 4356 m2, and critical percolation thresholds are established. Scale relations and scale dependencies, including the shadowing of smaller gaps, are considered analytically. Finally, canopy gap size distributions are considered in the context of self-organized criticality, and critical percolation thresholds are established for a range of such distributions.; This study indicates that selective logging may dramatically increase the flammability of a forest if it removes more than ten to sixteen percent of the canopy on a random basis, and that certain distributions of gap sizes may attenuate this problem on an areal basis.
机译:近年来,巴西亚马逊地区季节性干旱地区的森林正在以越来越快的速度燃烧,其中大部分是由于选择性伐木对森林冠层的干扰。本文利用遥感数据和模拟模型,将火灾和边缘效应的野外研究结果外推至景观和区域尺度。比例关系形式主义用于阐明此过程的时空成分。遥感数据用于分析十年来的土地覆盖,火灾计数和降水以及1998年发生的主动火灾的时空特征。在30 m分辨率下的网格化人工景观上的火灾增长模拟模型采用了可燃性边缘效应模型与集成的空间过滤器。该模型表明,可能存在特定的树冠间隙概率阈值,高于该阈值时,可燃燃料的连续性允许燃料床中任何单个表面火的不确定空间扩散。这种情况可以用临界渗滤来描述。该模型适用于从Landsat数据得出的景观,但是30 m数据和模型的分辨率显示有问题。模型分辨率提高到6 m,并研究了IKONOS数据的可能用途。以6 m分辨率的火势蔓延模型研究了具有36到4356 m 2 各种尺寸间隙的人工景观,并建立了临界渗透阈值。解析关系认为尺度关系和尺度依存关系,包括较小间隙的阴影。最后,在自组织临界状态下考虑了树冠间隙大小分布,并为一系列此类分布确定了临界渗透阈值。这项研究表明,选择性伐木如果随机清除超过百分之十到百分之十六的树冠,可能会大大增加森林的可燃性,并且间隙尺寸的某些分布可能会在面积上减轻这个问题。

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