Effects of cutline density and land-cover heterogeneity on landscape metrics in western Alberta
Effects of cutline density and land-cover heterogeneity on landscape metrics in western Alberta
复制标题
地缘线密度和土地覆盖异质性对艾伯塔省西部景观指标的影响
DOI：
10.5589/m08-034
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发表时间：
2008
期刊：
影响因子：
--
通讯作者：
G. Stenhouse
中科院分区：
文献类型：
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作者：
J. Linke;S. Franklin;M. Hall;G. Stenhouse
森林分割线是在地球物理测量中创建的狭窄的线状要素。在加拿大的许多地区，使用相对较粗的空间分辨率土地覆盖图，例如由陆地卫星专题地图(TM)分类生成的地图，并不能始终如一地探测森林砍伐线。然而，这些特征在某些野生动物管理应用中可能很重要，包括那些需要在不同尺度上评估景观结构或森林碎片化的应用。从L卫星的陆地观测(SPOT)和印度遥感系统(IRS)等平台上的传感器获得的更高空间分辨率的卫星图像可用于绘制这些应用的森林砍伐线图。本研究以艾伯塔省西部基于TM的土地覆盖图为研究对象，利用TM-IRS融合影像绘制的森林切割线图，量化了切割线密度的增加对灰熊栖息地评价中常用的5种景观指标的影响。融合图像解译的准确率为88%。首先对模拟景观进行测试，将研究区划分为104个六边形景观样本，每个样本直径约6公里。在这些样本景观中，切割密度和初始景观异质性是解释三个度量变化的重要参数，即边缘密度、平均斑块大小和斑块上下文(表示为平均最近邻距离)。斑块大小的可变性(表示为平均斑块大小的变异系数)和斑块的分散度(表示为平均最近邻距离的变异系数)需要关于割线定位的额外信息。总体而言，引入的割线网络的密度和割线前的度量值可靠地预测和量化了灰熊生物学家感兴趣的景观度量的反应。这项研究表明了绘制森林砍伐线在改变景观结构量化中的作用的重要性，并指出了当负责景观转换的特征太小而不能可靠地出现在基于TM的普通分类图像中时，使用额外的遥感数据的必要性。
Forest cutlines are narrow, linear features created in geophysical surveys. In many areas of Canada, forest cutlines are not consistently detected using relatively coarse spatial resolution land-cover maps, such as those produced by classification of Landsat Thematic Mapper (TM) imagery. However, such features may be important in certain wildlife management applications, including those which require an assessment of landscape structure, or forest fragmentation, at various scales. Higher spatial resolution satellite imagery obtained from sensors on platforms such as Satellite Pour l’Observation de la Terre (SPOT) and the Indian Remote Sensing (IRS) system may be used to map forest cutlines for these applications. In this study, a TM-based land-cover map of western Alberta is analyzed with forest cutlines mapped from a TM-IRS fusion image, and the effect of increasing cutline density is quantified on five commonly used landscape metrics used to characterize landscape structure in grizzly bear habitat assessment. The accuracy of the fusion image interpretation was determined to be 88%. Simulated landscapes were tested first, and the study area was divided into 104 hexagon-shaped sample landscapes of about 6 km diameter each. Across these sample landscapes, cutline density and initial landscape heterogeneity were significant parameters in explaining change in three metrics, namely edge density, mean patch size, and patch context (expressed as mean nearest-neighbour distance). Patch size variability (expressed as the coefficient of variation of mean patch size) and patch dispersion (expressed as the coefficient of variation of mean nearest-neighbour distance) required additional information on cutline positioning. Overall, the density of the introduced cutline network and the pre-cutline metric value reliably predicted and quantified the response of landscape metrics of interest to grizzly bear biologists. This study shows the importance of mapping forest cutlines regarding their role in changing landscape structure quantification and points out the necessity of using additional remotely sensed data when the feature responsible for the landscape transformation is of too small a size to appear reliably in common TM-based classified imagery.