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首页> 外文期刊>Journal of Remote Sensing & GIS >Detection of the Dry Trees Result of Oak Borer Beetle Attack Using Worldview-2 Satellite and UAV Imagery an Object-Oriented Approach
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Detection of the Dry Trees Result of Oak Borer Beetle Attack Using Worldview-2 Satellite and UAV Imagery an Object-Oriented Approach

机译：使用Worldview-2卫星和无人机图像的面向对象方法检测橡树甲虫袭击的枯树结果

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In Iran, forest inventory information has been essential with respect to land management because 10% of Iran is composed of forests. Therefore, accurate forest information such as tree counts, height, DBH, and volume are critical for forest management. While such data traditionally have required labor intensive and time consuming field measurement, new technologies such as remote sensing have supplemented and supplanted some of these field measurements. Although different types of sensors have been used to extract individual trees information, WorldView-2 (WV-2) has been used recently to extract surface information because WV-2 have high spatial and spectral resolution. In this study, object base classifiers (with KNN way) were used to classify WV-2 satellite and do assessment accuracy with UAV image in study sites. the study indicate that the classification accuracy of Objectbased algorithm was best for extraction of dry trees. This study is conducted to evaluate the possibility of WV-2 data to extract forest characteristics from identifying and measuring individual trees. Our results demonstrate that WV-2 data, NDVI with object-based classification can be used to detect tree mortality resulting from numerous causes and in several forest cover types.
机译：在伊朗，森林清查信息对于土地管理至关重要，因为伊朗10％的森林是森林。因此，准确的森林信息（例如树木数量，高度，DBH和体积）对于森林管理至关重要。传统上，此类数据需要耗费大量人力和时间的野外测量，而诸如遥感之类的新技术已补充并取代了其中的一些野外测量。尽管已使用不同类型的传感器来提取单个树木的信息，但由于WV-2具有较高的空间和光谱分辨率，因此最近已使用WorldView-2（WV-2）来提取表面信息。在这项研究中，基于对象的分类器（采用KNN方法）被用于对WV-2卫星进行分类，并在研究地点对无人机图像进行评估准确性。研究表明，基于对象的算法的分类精度最适合于枯树的提取。进行这项研究是为了评估WV-2数据从识别和测量单个树木中提取森林特征的可能性。我们的结果表明，基于对象分类的WV-2数据，NDVI可用于检测由多种原因和几种森林覆盖类型引起的树木死亡率。

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