Doherty Kyle, Gurinas Max, Samsoe Erik, Casper Charles, Larkin Beau, Ramsey Philip, Trabucco Brandon, Salakhutdinov Ruslan
MPG Ranch, Aerial Survey Program, Missoula, MT, USA.
University of Chicago Laboratory Schools, Chicago, IL, USA.
Sci Data. 2025 May 6;12(1):746. doi: 10.1038/s41597-025-05094-6.
This dataset comprises 1.3 cm resolution aerial images of grasslands in western Montana, USA, captured by a commercial drone. Many scenes contain leafy spurge (Euphorbia esula), introduced to North America, now widespread in rangeland ecosystems, which is highly invasive and damaging to crop production and biodiversity. Technicians surveyed 1000 points in the study area, noting spurge presence or absence, and recorded each point's position with precision global navigation satellite systems. We cropped tiles from an orthomosaic image at these locations. We publicly release these images and metadata as a Hugging Face Dataset, accessible in one line of code. Our aim is to invite the research community to develop classifiers as early warning systems for spurge invasion. We tested classification performance for two contemporary vision models and achieved 0.85 test accuracy. This demonstrates the feasibility yet difficulty of this classification task.
该数据集包含美国蒙大拿州西部草原的1.3厘米分辨率航空图像，由商用无人机拍摄。许多场景中含有引入北美、现已在牧场生态系统中广泛分布的乳浆大戟，它具有高度入侵性，会损害作物生产和生物多样性。技术人员在研究区域内调查了1000个点，记录乳浆大戟的有无情况，并使用精密全球导航卫星系统记录每个点的位置。我们在这些位置从正射镶嵌图像中裁剪出图像块。我们将这些图像和元数据作为一个Hugging Face数据集公开发布，通过一行代码即可访问。我们的目标是邀请研究界开发分类器，作为乳浆大戟入侵的预警系统。我们测试了两种当代视觉模型的分类性能，测试准确率达到了0.85。这证明了这项分类任务的可行性和难度。
