• 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>Turkish Journal of Agriculture & Forestry >The potential of G?ktürk 2 satellite images for mapping burnt forest areas
【24h】

The potential of G?ktürk 2 satellite images for mapping burnt forest areas

机译：G？Ktürk2卫星图像的潜力，用于绘制焚烧林区

获取原文
           
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

Using remotely sensed data to identify burnt forest areas produces fast, economical, and highly accurate results. Accordingly, in this study we investigate the capabilities of G?ktürk-2, Turkey's national satellite, for mapping burnt forest areas. We compare our results with those obtained from Landsat-8 and Worldview-2 satellite images, which are frequently used for mapping burnt areas. The capabilities of the satellites are compared, in terms of detecting burnt forest areas, using support vector machine (SVM) and rotation forest (RF) classification, which are advanced methods. According to the results of the accuracy analysis, SVM classification gives similar kappa statistics and overall accuracy for G?ktürk-2 and Landsat-8 images, while the performance of Worldview-2 shows greater general accuracy. Although there is no significant difference between the two classification methods forLandsat-8 images, SVM gives better results than RF for both G?ktürk-2 and Worldview-2. The results of our study show that G?ktürk-2 images are an effective source for mapping burnt forest areas.
机译：使用远程感测的数据来识别烧焦的林区，产生快速，经济，高度准确的结果。因此，在本研究中，我们研究了G？Ktürk-2，土耳其国家卫星的能力，用于绘制焚烧森林地区。我们将结果与从Landsat-8和WorldView-2卫星图像获得的结果进行比较，这些图像经常用于绘制烧焦的区域。在使用支持向量机（SVM）和旋转林（RF）分类的燃烧林区域检测烧焦的森林区域，卫星的能力进行比较。根据精度分析的结果，SVM分类为G？Ktürk-2和Landsat-8图像提供了类似的kappa统计和整体准确性，而世界观-2的性能表现出更大的一般准确性。虽然福兰斯-8图像的两个分类方法之间没有显着差异，但SVM为G？Ktürk-2和WorldView-2的RF提供更好的结果。我们的研究结果表明，G？Ktürk-2图像是用于绘制烧毁林区的有效源。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号