首页> 外文会议>International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery >Detection of Vegetation Patch Growth by Absorption Feature Analysis on Tasseled Cap Brightness of Transects from Landsat 7 ETM+ Images
【24h】

Detection of Vegetation Patch Growth by Absorption Feature Analysis on Tasseled Cap Brightness of Transects from Landsat 7 ETM+ Images

机译:通过覆盖覆盖覆盖覆盖覆盖亮度的吸收特征分析检测植被补丁增长覆盖覆盖率7 ETM +图像

获取原文

摘要

Vegetation patches are worldwide distributed in arid and semi-arid ecosystems. Mapping vegetation patch dynamics provides valuable information for regional vegetation recovery and re-establishment. The high spatial resolution images may be powerful for the decametric-scale vegetation patch detection. However, the dense and long time series of fine spatial resolution (better than 2.5 m) imagery were not available for large regions until recently due to design considerations on satellite and sensors, satellite data transmission, satellite life and revisited period, and further effects like atmospheric absorption and cloud. For multispectral images (less than 10 m), it was often a challenge for detecting these vegetation patches through visual interpretation and the common image classifications. In this paper, our proposed method based on analysis of absorption features of tasseled cap brightness of Landsat 7 Enhanced Thematic Mapper Plus (ETM+) images along transect provided the acceptable results for vegetation patch recovery detection, which represented a efficient, economical and straightforward procedures for local vegetation management in the Yellow River Delta, China and other similar landscapes.
机译:植被补丁是在干旱和半干旱生态系统中分布的全球范围内。映射植被补丁动力学为区域植被恢复和重新建立提供了有价值的信息。高空间分辨率图像对于欺骗级植被补丁检测可能是强大的。然而,大型地区的密集和长时间的精细空间分辨率(优长而不是2.5米)的图像,直到最近由于卫星和传感器的设计考虑,卫星数据传输,卫星寿命和重新审查,以及进一步的效果大气吸收和云。对于多光谱图像(小于10米),通过视觉解释和常见图像分类检测这些植被斑块通常是挑战。在本文中,我们的提出方法基于Landsat 7增强专题Mapper Plus(ETM +)图像的流苏帽亮度的吸收特征分析提供了植被补丁恢复检测的可接受结果,这代表了一种有效,经济和直接的程序当地植被管理在黄河三角洲,中国等类似风景。

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