Sen-2 LULC

Published: 22 December 2023| Version 3 | DOI: 10.17632/f4ky6ks248.3
Suraj Sawant,
, Shrayank Mistry


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 ( 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 (,(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, ]



Indian Institute of Technology Roorkee


Image Segmentation, Land Cover Analysis, Land Use, Deep Learning, Transfer Learning