Sen-2 LULC
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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）"是一款包含213750余张经过预处理的10米分辨率影像的数据集，涵盖7类不同的土地利用与土地覆盖（Land Use Land Cover，LULC）类别。该7个类别分别为：水体、茂密森林、疏林、裸地、建成区、农用地与休耕地。单张影像可同时包含多个类别。 该数据集的哨兵-2（Sentinel-2）影像取自印度中部区域，来源于哥白尼公开获取枢纽（Copernicus Open Access Hub，https://scihub.copernicus.eu/），影像云覆盖率介于0%至0.5%之间。影像由B4、B3、B2三个波段组合而成，分别对应红、绿、蓝波段，空间分辨率为10米。所有影像采集于2021年2月至3月期间，且均属于哨兵-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).）。 该数据集配套包含等量的掩码影像，共包含6个文件夹，分别对应训练、测试与验证集的影像，以及训练、测试与验证集的掩码。本数据集可用于印度区域的土地利用与土地覆盖分类任务以构建深度学习模型，对土地利用与土地覆盖分类研究具有重要应用价值。 [相关论文可参阅：Sen-2 LULC：面向深度学习方法的土地利用与土地覆盖数据集。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. ]
