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首页> 外文会议>ACRS 2011;Asian conference on remote sensing >CHANGE IN HABITAT SELECTION BY JAPANESE MACAQUES AND HABITAT FRAGMENTATION ANALYSIS USING TEMPORAL REMOTELY SENSED DATA IN NIIGATA PREFECTURE, JAPAN
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CHANGE IN HABITAT SELECTION BY JAPANESE MACAQUES AND HABITAT FRAGMENTATION ANALYSIS USING TEMPORAL REMOTELY SENSED DATA IN NIIGATA PREFECTURE, JAPAN

机译：日本新泻县日本猕猴生境选择的变化和生境碎片化分析

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The aim of this study was to evaluate changes in macaque habitat selection during a 29-year period. We focused on the 1970s, when little crop damage was caused by Japanese macaques (Macaca fuscata), and the 2000s, when the damage became remarkable. Landsat/MSS from 1978 and ALOS/AVNIR-2 from 2007 were employed for land-cover mapping. For the 2007 land-cover classification, we applied an object-oriented image classification and a classification and regression tree. The Kappa coefficient of the 2007 land-cover map was 0.89. For the 1978 land-cover classification, change detection using principal component analysis and object-oriented image classification were applied to reduce resolution difference errors. The Kappa coefficient of the 1978 land-cover map was 0.84. We applied a Random Forest model for machine learning and data mining to predict the habitat selection of macaques. Several important environmental factors were identified for macaque habitat selection: the ratio of coniferous forest to farmland, distance to farmland, and maximum snow depth. The Random Forest model was extrapolated to the 1978 land-cover map. Over the 29-year period, coniferous forest changed to broad-leaved forest and/or mixed forest within the macaque habitat area. Coniferous forests were not selected as food resources by Japanese macaques. Furthermore, large-scale patches of farmland were used as food resources over the 29-year period. These changes indicated that habitat selection by Japanese macaques changed over the study period: The results show that the home range of macaques expanded, and macaques may now be distributed over a wider area as a result of changes in landscape configuration. Thus, forest planning, such as sustainable management of artificial conifer forests, is important for reducing crop damage.
机译：这项研究的目的是评估29年期间猕猴栖息地选择的变化。我们的研究重点是1970年代，当时日本猕猴（Macaca fuscata）对农作物造成的破坏很小，而2000年代则是造成极大破坏的时候。 1978年的Landsat / MSS和2007年的ALOS / AVNIR-2被用于土地覆盖制图。对于2007年的土地覆盖分类，我们应用了面向对象的图像分类以及分类和回归树。 2007年土地覆盖图的Kappa系数为0.89。对于1978年的土地覆盖分类，应用了基于主成分分析和面向对象图像分类的变化检测来减少分辨率差异误差。 1978年土地覆盖图的Kappa系数为0.84。我们将随机森林模型应用于机器学习和数据挖掘，以预测猕猴的栖息地选择。确定了猕猴栖息地选择的几个重要环境因素：针叶林与农田的比例，与农田的距离以及最大积雪深度。随机森林模型被外推到1978年的土地覆盖图。在29年的时间里，猕猴栖息地内的针叶林变为阔叶林和/或混交林。日本猕猴没有选择针叶林作为食物资源。此外，在29年期间，大量农田被用作粮食资源。这些变化表明，日本猕猴在研究期内的栖息地选择发生了变化：结果表明，由于景观配置的变化，猕猴的居住范围扩大了，猕猴现在可能分布在更广泛的区域。因此，森林规划，例如人工针叶林的可持续管理，对于减少农作物的损害非常重要。

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