Mapping Fine-Scale Crown Scorch in 3D with Remotely Piloted Aircraft Systems
Mapping Fine-Scale Crown Scorch in 3D with Remotely Piloted Aircraft Systems
复制标题
使用遥控飞机系统以 3D 方式绘制精细的冠层烧焦图
作者：
C. J. Moran;Valentijn Hoff;R. Parsons;L. Queen;C. Seielstad
遥控飞机系统（RPAS）为火灾遥感提供了新的视角。一个机会是绘制火灾后树冠烧焦的地图，这可以支持科学和管理。这一概念验证表明，在由低成本RGB和校准的RGB-NIR相机以高分辨率（厘米级）获得的点云中，树冠烧焦与未受伤的树冠是可以区分的。归一化植被指数提供了最具鉴别力的光谱数据，但低成本的RGB相机也提供了有用的数据。焦烧高度从点云密切匹配的平均绝对误差为0.52米（n = 29）的现场测量。以简单的阈值NDVI分类为例，对点云进行体素化处理，提供了一个值得应用和进一步研究的数据集。现场测量的焦烧高度也显示出与RPAS-热摄像机衍生的火灾辐射能量密度（FRED）估计值的关系，斯皮尔曼等级相关性为0.43，但仍有许多问题需要解决之前，强大的推理是可能的。使用RPAS和SfM摄影测量法在3D中绘制精细尺度烧焦是一种可行的低成本选择，可以支持相关的科学和管理。
Remotely piloted aircraft systems (RPAS) are providing fresh perspectives for the remote sensing of fire. One opportunity is mapping tree crown scorch following fires, which can support science and management. This proof-of-concept shows that crown scorch is distinguishable from uninjured canopy in point clouds derived from low-cost RGB and calibrated RGB-NIR cameras at fine resolutions (centimeter level). The Normalized Difference Vegetation Index (NDVI) provided the most discriminatory spectral data, but a low-cost RGB camera provided useful data as well. Scorch heights from the point cloud closely matched field measurements with a mean absolute error of 0.52 m (n = 29). Voxelization of the point cloud, using a simple threshold NDVI classification as an example, provides a suitable dataset worthy of application and further research. Field-measured scorch heights also showed a relationship to RPAS-thermal-camera-derived fire radiative energy density (FRED) estimates with a Spearman rank correlation of 0.43, but there are many issues still to resolve before robust inference is possible. Mapping fine-scale scorch in 3D with RPAS and SfM photogrammetry is a viable, low-cost option that can support related science and management.