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.

本数据集包含飞行任务RU_ALN_TR1_FL007R的原始文件。2018至2019年，研究团队利用无人飞行器（Uncrewed Aerial Vehicles）在西伯利亚东北部落叶松林的多处火灾边界采集遥感影像（Remote Sensing Imagery）。影像采集采用可见光传感器（覆盖蓝、绿、红光波段）与多光谱传感器（覆盖绿、红、红边（red-edge）及近红外（near-infrared）波段）。数据采集方向垂直于火灾边界，旨在表征过火与未过火森林间的植被组成、结构差异，以及该差异随距未燃森林边缘距离的变化规律。所获影像与本项目配套采集的生态系统属性野外观测数据空间配准一致，相关野外观测数据已上传至关联数据集（Alexander等，2018）。相关文献信息如下：Heather Alexander、Jennie DeMarco、Rebecca Hewitt、Jeremy Lichstein、Michael Loranty等，2018。《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》，2018年6-7月，北极数据中心（Arctic Data Center），唯一标识符：urn:uuid:a5de1514-78d3-449f-aad1-2ff8f8d0fb27。