Trees / NoTrees Sattellite Imagery Dataset

This dataset is derived from Sentinel-2 satellite imagery. The main goal is to employ this dataset to train and classify images into two classes: with trees, and without trees. The structure of the dataset is 2 folders named: "tree" (images containing trees) and "no-trees" (images without presence of trees). Each folder contains 5200 images of this type. References: + M.Ç.Aksoy (2022). Trees in Satellite Imagery [Dataset].https://www.kaggle.com/datasets/mcagriaksoy/trees-in-satellite-imagery + Helber, P., Bischke, B., Dengel, A., & Borth, D. (2019). Eurosat: A novel dataset and deep learning benchmark for land use and land cover classification. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 12(7), 2217-2226.

本数据集源自 Sentinel-2 卫星影像。其核心目标在于利用该数据集对图像进行训练与分类，将其划分为两大类：含树木与不含树木。数据集结构分为两个文件夹：名为“tree”（包含树木的图像）和“no-trees”（不含树木的图像）的文件夹。每个文件夹内均包含5200张此类图像。参考文献：+ M.Ç.Aksoy (2022). Trees in Satellite Imagery [Dataset]. https://www.kaggle.com/datasets/mcagriaksoy/trees-in-satellite-imagery + Helber, P., Bischke, B., Dengel, A., & Borth, D. (2019). Eurosat: A novel dataset and deep learning benchmark for land use and land cover classification. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 12(7), 2217-2226.