CS-Wild-Places Dataset

CS-Wild-Places is a large-scale lidar dataset for cross-source place recognition between ground and aerial viewpoints in forest environments. The data was collected from four forests in Brisbane, Australia over ten months, with lidar scans captured by a handheld sensor payload (below canopy) and aerial drone (above canopy). CS-Wild-Places builds upon the Wild-Places dataset by introducing geo-registered aerial submaps covering Karawatha and Venman forests, enabling research into place recognition between challenging viewpoints. We further release ground and aerial data captured in two new forest environments: QCAT and Samford Ecological Research Facility. The aerial data spans 370 hectares in total, and we captured two ground sequences with 3.5km of total traversal, producing a total of ~36k high resolution lidar submaps with accurate 6-DoF poses and timestamps. We release the data in three main configurations: raw (submaps randomly downsampled to 500k points max), and post-processed (submaps voxel-downsampled with 0.8m voxels, ground points removed, with and without normalisation).

CS-Wild-Places是一款面向森林环境下地面与空中视角跨源地点识别的大规模激光雷达（lidar）数据集。该数据集于澳大利亚布里斯班的四座森林中历时十个月采集完成，采集设备涵盖冠层下方的手持激光雷达传感器载荷，以及冠层上方的航拍无人机。本数据集基于Wild-Places数据集拓展而来，新增了覆盖Karawatha与Venman森林的地理配准航空子地图，可为挑战性视角下的地点识别研究提供支撑。团队还额外发布了两个全新森林环境中的地面与航空数据：QCAT与萨姆福德生态研究设施（Samford Ecological Research Facility）。本次发布的航空数据总覆盖面积达370公顷，地面采集序列共两条，总遍历里程3.5千米，最终生成约3.6万幅高精度激光雷达子地图，所有子地图均配有精确的6自由度（6-DoF）位姿与时间戳信息。此次发布的数据分为三种主要配置：原始数据（子地图经随机下采样，最大点云量为50万）、后处理数据（子地图采用0.8米体素进行下采样、移除地面点，包含归一化与未归一化两种版本）。