首页> 外文期刊>Mathematical and Computational Forestry & Natural-Resource Sciences >Estimation of forest stand disturbance through implementation of Vegetation Change Tracker algorithm using Landsat time series Stacked imagery in coastal Georgia -- Poster Summary
【24h】

Estimation of forest stand disturbance through implementation of Vegetation Change Tracker algorithm using Landsat time series Stacked imagery in coastal Georgia -- Poster Summary

机译:通过使用Landsat时间序列叠加影像在佐治亚州沿海地区实施植被变化跟踪器算法估算林分扰动-海报摘要

获取原文
获取外文期刊封面目录资料

摘要

Knowledge of forest disturbances is the key information relevant to forest resource management and distribution of forest ecosystem structures. The objective of this research was to identify and date forest disturbances between 1984 and 2016 on 30 meter spatial resolution Landsat images of coastal Georgia through implementation of the modified Vegetation Change Tracker algorithm. First, we created Landsat Time Series Stack (LTSS) by stacking annual Landsat 5 TM and 8 OLI imagery, which cover WRS2- Path 17/Row 38. We calculated the inter-band Forest Z score (IFZ) for each imagery contained in LTSS. IFZ is a vegetation index calculated for each pixel in each year to measure the likelihood that the land use of a pixel is a forest. We have tested an algorithm automatically detecting the specific year of forest disturbance at the pixel level. To detect the disturbance the algorithm considers the time series changes in IFZ value for each pixel. The result of such analysis was summarized in the form of a disturbance year map, in which each pixel is assigned specific year of disturbance as its value. We used this analysis to estimate the areas of forest disturbances in each year. We made an accuracy assessment for the disturbance map using test points determined by a stratified sampling method. The results of this research provide a better age class description of our study area making possible to assess its location-specific information about forest disturbances and age structure.
机译:森林干扰知识是与森林资源管理和森林生态系统结构分布有关的关键信息。这项研究的目的是通过实施改进的“植被变化跟踪器”算法,在乔治亚州沿海地区的30米空间分辨率Landsat图像上识别和记录1984年至2016年之间的森林干扰。首先,我们通过堆叠涵盖WRS2-路径17 /行38的年度Landsat 5 TM和8 OLI图像,创建了Landsat时间序列堆栈(LTSS)。我们为LTSS中包含的每个图像计算了带间森林Z分数(IFZ) 。 IFZ是每年为每个像素计算的植被指数,用于测量像素的土地用途是森林的可能性。我们测试了一种算法,可以自动检测像素级别的特定森林干扰年。为了检测干扰,算法考虑了每个像素的IFZ值的时间序列变化。以干扰年图的形式总结了这种分析的结果,其中为每个像素指定了特定的干扰年作为其值。我们使用此分析来估算每年的森林干扰面积。我们使用分层采样方法确定的测试点对干扰图进行了准确性评估。这项研究的结果为我们的研究区域提供了更好的年龄分类描述,从而有可能评估其有关森林干扰和年龄结构的特定位置信息。

著录项

相似文献

  • 外文文献
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