Sen-2 LULC

The "Sen-2 LULC Dataset" is a collection of 2,13,750+ pre-processed 10 m resolution images representing 7 distinct classes of Land Use Land Cover. The 7 classes are water, Dense forest, Sparse forest, Barren land, Built up, Agriculture land and Fallow land. Multiple classes are present in the single image of the dataset. The Sentinel-2 images of Central India are taken from Copernicus Open Access Hub (https://scihub.copernicus.eu/) with cloud clover percentage ranging from 0 to 0.5%. The images are combination of bands B4, B3 and B2 constituting the red, green and blue bands with spectral resolution of 10m. The images are taken within the months of February and March 2021. The images used in the dataset belongs to Sentinel-2 Level-2A product (https://sentinels.copernicus.eu/web/sentinel/user-guides/sentinel-2-msi/product-types/level-2a#:~:text=The%20Level%2D2A%20product%20provides,(UTM%2FWGS84%20projection).). The dataset contains equal number of mask images. The dataset contains 6 folders with train, test and validate images and train, test and validate masks. This dataset can be used for Land Use Land Cover Classification (LULC) of Indian region to build the deep learning models. This dataset is beneficial for LULC classification research. [The related article is available at: Sen-2 LULC: Land use land cover dataset for deep learning approaches. Cite the article as : Sawant, S., Garg, R. D., Meshram, V., & Mistry, S. (2023). Sen-2 LULC: Land use land cover dataset for deep learning approaches. Data in Brief, 51, 109724, https://doi.org/10.1016/j.dib.2023.109724. ]

Sen-2 LULC 数据集（Sen-2 LULC Dataset）收录了超过213750张经过预处理的10米分辨率影像，涵盖7类不同的土地利用/土地覆盖（Land Use Land Cover, LULC）类别，分别为水体、茂密森林、稀疏森林、裸地、建成区、农用地与休耕地。该数据集中的单张影像可包含多个类别。印度中部地区的Sentinel-2影像取自哥白尼开放获取中心（Copernicus Open Access Hub，https://scihub.copernicus.eu/），其云覆盖百分比介于0至0.5%之间。影像由B4、B3、B2波段组合而成，对应红、绿、蓝波段，光谱分辨率为10米。影像采集时间为2021年2月至3月，所用影像均属于Sentinel-2 Level-2A级产品（https://sentinels.copernicus.eu/web/sentinel/user-guides/sentinel-2-msi/product-types/level-2a#:~:text=The%20Level%2D2A%20product%20provides,(UTM%2FWGS84%20projection).）。本数据集配套了等量的掩码影像，共包含6个文件夹，分别存储训练、测试与验证集的影像及对应的训练、测试、验证掩码。该数据集可用于印度区域的土地利用/土地覆盖分类任务，以构建深度学习模型，对LULC分类研究具有重要应用价值。相关研究论文可参阅：《Sen-2 LULC: Land use land cover dataset for deep learning approaches》，引用格式为：Sawant, S., Garg, R. D., Meshram, V., & Mistry, S. (2023). Sen-2 LULC: Land use land cover dataset for deep learning approaches. Data in Brief, 51, 109724, https://doi.org/10.1016/j.dib.2023.109724.

搜集汇总

背景与挑战

背景概述

Sen-2 LULC数据集是一个包含213,750多张10米分辨率图像的数据集，覆盖7种土地利用和土地覆盖类别，适用于深度学习模型的构建和土地利用土地覆盖分类研究。图像来自Sentinel-2 Level-2A产品，拍摄于2021年2月至3月，覆盖印度中部地区。