首页> 外文期刊>International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences >ASSESSING THE DAMAGE OF FORESTS BURNT IN CENTRAL CHILE BY RELATING INDEX-DERIVED DIFFERENCES TO FIELD DATA
【24h】

ASSESSING THE DAMAGE OF FORESTS BURNT IN CENTRAL CHILE BY RELATING INDEX-DERIVED DIFFERENCES TO FIELD DATA

机译:通过将索引衍生的差异与现场数据的差异相关,评估森林燃烧的损坏

获取原文
           

摘要

To assess the damage produced by wildfires on forest ecosystems is a critical task for their subsequent management and ecological restoration. Satellite-based optical images provide reliable ex-ante and ex-post data about vegetation state, making them suitable for the aforementioned purpose. In this study we assessed the damage produced on two forested lands by the series of wildfires occurred in central Chile during summer 2017. Arithmetic differences from pre- and post-fire NDVI (normalized difference vegetation index), NDWI (normalized difference water index) and NBR (normalized burnt ratio) were retrieved from a Sentinel-2 image set embracing four near-anniversary summer dates: 2016 (ex-ante), 2017, 2018 and 2019 (ex-post). The nine index-derived differences resulting were correlated to CBI (composite burn index) data collected in the field during summer 2019, and a model constructed by a stepwise regression was formulated. Results show that planted forests exhibited a somewhat smaller biomass recovery than native ones, in part due to their post-fire clearing and preparation, deriving in a smaller tree cover. CBI poorly performed because its calculation includes low vegetation strata largely recovered at the time of the field data collection. However, when overstory field data were used alone correlations noticeably increased (r = 0.66–0.74). This was because during the field campaign this stratum was still appreciably damaged, thus better matching with the data provided by the indices-derived differences, intrinsically more representative of uppermost vegetation layers. The burn damage was mapped on both study areas employing the best performing regression model, based on NDWI2016-2019, NDWI2016-2017, NBR2016-2018 and NBR2016-2017 differences (adjusted R2 = 0.72, p  0.005, root mean square error = 0.38). The use of approaches like this one in other areas of central Chile, where wildfires are increasing their frequency and intensity, might contribute to better lead post-fire management and restoration actions on their damaged forest ecosystems.
机译:为了评估森林生态系统上野火产生的损害是他们随后的管理和生态恢复的重要任务。基于卫星的光学图像提供可靠的前蚂蚁和关于植被状态的前后数据,使它们适合上述目的。在这项研究中,我们评估了在2017年夏季智利中部发生的一系列野火的两家森林土地上产生的损害。来自火灾后NDVI(归一化差异植被指数),NDWI(归一化差异水指数)和算术差异从Hentinel-2图像集拥有四个近周年夏季日期:2016年(前赌注),2017,2018和2019(前岗位)中检索到NBR(归一化烧焦比率)。导致的九个指数衍生的差异与2019年夏季在现场收集的CBI(复合烧伤指数)数据相关,并且制定了由逐步回归构成的模型。结果表明,种植的森林表现出比本地物质的较小的生物质回收,部分原因是由于其火灾后清除和制备,源于较小的树木覆盖。 CBI表现不佳,因为它的计算包括在现场数据收集时大部分恢复的低植被地层。然而,当单独使用逾野现场数据时,相关性显着增加(r = 0.66-0.74)。这是因为在现场活动期间,这一层仍然明显地损坏,从而与由指标衍生的差异提供的数据更好地匹配,本质上更大的植被层。基于NDWI2016-2019,NDWI2016-2017,NBR2016-2018和NBR2016-2017差异(调整的R2 = 0.72,P <0.005,均方根误差= 0.38 )。在智利中部地区的其他地区使用这样一个方法,其中野火正在增加其频率和强度,可能有助于更好地导致其损坏的森林生态系统上的火灾后管理和恢复行动。

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