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首页> 外文会议>ACRS 2011;Asian conference on remote sensing >MERGING LANDSAT IMAGE INFORMATION WITH GEOREFERENCED BIOPHYSICAL AND SOCIO-ECONOMICAL DATASETS TO DESCRIBE FOREST COVER CHANGE IN A PHILIPPINE PROVINCE
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MERGING LANDSAT IMAGE INFORMATION WITH GEOREFERENCED BIOPHYSICAL AND SOCIO-ECONOMICAL DATASETS TO DESCRIBE FOREST COVER CHANGE IN A PHILIPPINE PROVINCE

机译：结合地球物理和社会经济数据集结合LandSAT图像信息，以描述菲律宾省的森林覆盖率变化

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This paper describes a combined remote sensing-GIS-logistic regression approach of merging extracted information from Landsat images with georeferenced biophysical and socio-economic datasets in the detection and analysis of the driving forces of forest cover change in Agusan del Norte (ADN) in Mindanao Island, Philippines, a province where forest resource use have been historically extensive. Year 1976 Landsat 2 MSS and year 2001 Landsat ETM+ images were independently classified using Support Vector Machines (SVM) to produce land cover maps with overall classification accuracies of 95% and 98%, respectively. Changes in forest cover and other types of land-cover change in the 25-year period were then detected from these maps through post-classification comparison in a GIS. To investigate what has driven these conversions, the associations between these changes and a selection of biophysical and socio-economical variables were explored through logistic regression analysis. The results show that while both the biophysical and socio-economical variables were significantly associated with the occurrences of forest cover change, the models containing only the socio-economical variables predict better the occurrences of change than those containing only the biophysical variables. This implies that most of the forest cover change detected in the year 2001 in ADN is much more a socio-economical matter, and is less forced by biophysical limitations. With these results, this study demonstrated the usefulness of RS, GIS and statistical analysis as exploratory tools in understanding the underlying processes and identification of driving forces of forest cover change, especially in areas of extensive forest resource use.
机译：本文描述了一种结合遥感-GIS-逻辑回归的方法，该方法将Landsat影像中提取的信息与地理参考生物物理和社会经济数据集相结合，以检测和分析棉兰老岛阿古桑·德尔诺特（ADN）森林覆盖率变化的驱动力菲律宾岛是历史上森林资源广泛使用的省份。使用支持向量机（SVM）对1976年的Landsat 2 MSS和2001年的Landsat ETM +图像进行独立分类，以生成总体覆盖率分别为95％和98％的土地覆盖图。然后通过GIS中的分类后比较从这些地图中检测出25年期间的森林覆盖率变化和其他类型的土地覆被变化。为了研究驱动这些转换的因素，通过逻辑回归分析探索了这些变化与生物物理和社会经济变量选择之间的关联。结果表明，虽然生物物理和社会经济变量都与森林覆盖变化的发生显着相关，但是仅包含社会经济变量的模型比仅包含生物物理变量的模型预测的发生更好。这意味着，在2001年ADN中发现的大多数森林覆盖变化都是一种社会经济问题，并且受到生物物理限制的压力较小。有了这些结果，这项研究证明了RS，GIS和统计分析作为探索性工具在理解森林覆盖变化的基本过程和识别驱动力方面的有用性，特别是在广泛使用森林资源的地区。

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