Raw files from flight RU_ALN_TR1_FL008B 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.

本数据集包含航班RU_ALN_TR1_FL007R的原始文件。2018至2019年，研究团队于俄罗斯西伯利亚东北部的落叶松林（Larch Forests）的一系列火边界（Fire Perimeters）处，使用无人机（Uncrewed Aerial Vehicles, UAV）采集遥感影像数据。影像采集采用可见光传感器（Visible Sensors，覆盖蓝、绿、红光波段）与多光谱传感器（Multispectral Sensors，覆盖绿、红、红边及近红外波段）。数据采集方向垂直于火边界，旨在表征火烧与未火烧森林间植被组成与结构的差异，以及植被特征随距未烧森林边缘距离的变化规律。所获取的影像与本项目配套采集的野外生态系统属性观测数据完成了空间配准，该野外观测数据已上传至关联数据集（Alexander等，2018）。Heather Alexander、Jennie DeMarco、Rebecca Hewitt、Jeremy Lichstein、Michael Loranty等人于2018年发布了题为《俄罗斯西伯利亚落叶松林火干扰对森林恢复及相关气候反馈的影响》的数据集，数据采集时间为2018年6-7月，存储于北极数据中心（Arctic Data Center），唯一标识符为urn:uuid:a5de1514-78d3-449f-aad1-2ff8f8d0fb27。