The Canyonlands Dataset

Kristen Such Doncey Albin Christoffer Heckman

Dataset: hosted on CU Research Computing (PetaLibrary) and archived with a citable DOI — https://doi.org/10.25810/AB1G-RK08. The Canyonlands and RestoreBot data are released together under this single DOI.

Abstract

Rangelands provide many ecological services including livestock forage, water retention and carbon sequestration making their health integral for soil health and air quality. However, restoration efforts of degraded rangelands have seen little success in recent years. It is thought that subtle ecological features, called microsites, are critical for plant growth outcomes. Autonomous robots offer a solution to indentify and intervene based off these subtle features, but the lack of relevant data in these environments is a limiting factor to getting highly granular, multi-seasonal data necessary for testing ecological hypotheses. In this paper, we introduce the Canyonlands Dataset, a large-scale, multi-modal dataset collected near to Canyonlands National Park in Southeastern Utah using a teleoperated ground vehicle. The dataset includes high-resolution camera imagery, RTK-GPS trajectories, 3D lidar point clouds, and ground-truth vehicle odometry. To support reproducibility and foster research in autonomous environmental monitoring and restoration, we provide detailed documentation, calibration files, and code for dataset interaction.

System and Sensors

The Canyonlands dataset was collected in Canyonlands National Park in Utah, USA. We collected the dataset using a Clearpath Husky platform equiped with a Ouster lidar,

EquipmentModel NameCharacteristicsResolutionFoVSensor Rate
LiDAROuster OS1-64100 m range64v x 1024h33° x 360°20 Hz
RGB-D CameraIntel RealSense D435 (fwd + down)RGB: rolling shutter1280 × 72069° x 42°30 Hz
IMULORD MicroStrain 3DM-GX5-15 (VRU)±8 g300 dps-400 Hz
GPS / RTKTrimble BX922 + AG25 antenna5 cm RTK/RTX (CenterPoint RTX)--~20 Hz
Survey BaseTrimble SPS855 + Zephyr 3----
Main ComputerAMD Ryzen Threadripper 3990X + GTX 165032-core CPU, GPU for real-time inference---

Table 1. Hardware Specifications.

Seasons

The Canyonlands dataset is broken into to separate data collection times: in May 2022 and November 2022.