Raw files from flight RU_ANS_TR1_FL003R of the uncrewed aerial vehicle remote sensing imagery of postfire vegetation in Siberian larch forests 2018-2019

This data set contains the raw files from flight RU_ALN_TR1_FL007R. The remote sensing imagery is collected using uncrewed aerial vehicles at a series of fire perimeters in larch forests located in northeastern Siberia in 2018 and 2019. Images were collected using visible sensors (blue, green, and red wavelengths) and multispectral sensors (green, red, red-edge, and near-infrared wavelengths). The data were collected perpendicular to fire perimeter boundaries in order to characterize variation vegetation composition and structure between burned and burned forests, and as a function of distance from the unburned forest edge. The resulting images are co-located with field observations of ecosystem properties collected as part of this project that are posted in a related data set (Alexander et al, 2018). Heather Alexander, Jennie DeMarco, Rebecca Hewitt, Jeremy Lichstein, Michael Loranty, et al. 2018. Fire influences on forest recovery and associated climate feedbacks in Siberian Larch Forests, Russia, June-July 2018. Arctic Data Center. urn:uuid:a5de1514-78d3-449f-aad1-2ff8f8d0fb27.

该数据集包含航班RU_ALN_TR1_FL007R的原始文件。2018-2019年，研究人员采用无人机（uncrewed aerial vehicles）在西伯利亚东北部落叶松林的多个火灾周界区域采集遥感影像。影像数据通过可见光传感器（visible sensors，覆盖蓝、绿、红波段）和多光谱传感器（multispectral sensors，覆盖绿、红、红边及近红外波段）获取。数据采集方向垂直于火灾周界边界，旨在刻画已燃烧与未燃烧森林间植被组成及结构的变化规律，并分析其随距未燃烧森林边缘距离的变化特征（原文“burned and burned”疑似笔误，此处按生态逻辑修正为“已燃烧与未燃烧”）。所得影像与本项目中采集的生态系统属性实地观测数据共定位，这些观测数据已发布于相关数据集（Alexander et al., 2018）。该相关数据集对应文献为：Heather Alexander、Jennie DeMarco、Rebecca Hewitt、Jeremy Lichstein、Michael Loranty等，2018，《2018年6-7月俄罗斯西伯利亚落叶松林火灾对森林恢复及相关气候反馈的影响》，北极数据中心，urn:uuid:a5de1514-78d3-449f-aad1-2ff8f8d0fb27。