MLC-BD: Multi-Platform Land Cover Imagery Dataset of Bangladesh

Description

MLC-BD is a large-scale, multi-source satellite image dataset containing 10,683 manually annotated PNG images representing seven major land-cover categories across Bangladesh. The dataset was compiled from three widely used web-based mapping platforms: ArcGIS Map (3,556 images), Bing Maps (3,632 images), and Google Maps (3,495 images). Images were collected through systematic visual exploration of satellite and aerial basemap imagery covering diverse geographic regions of Bangladesh and were manually assigned to one of seven land-cover classes: Agricultural Land, Beaches/Coastline, Built-up Areas, Grasslands/Open Land, Hills/Mountains, Trees/Forests, and Water Bodies. Each image subsequently underwent quality inspection, standardized labeling, and structured curation to ensure dataset consistency. The dataset is well balanced, with 1,509 to 1,547 images per class, and contains images with varying spatial dimensions ranging from 88 to 506 pixels in width and 72 to 540 pixels in height. MLC-BD is designed to support research in computer vision, remote sensing, and geospatial artificial intelligence, including land-cover recognition, transfer learning, cross-source domain generalization, and model robustness evaluation across heterogeneous imagery providers. By focusing exclusively on Bangladesh, a geographically diverse and densely populated South Asian deltaic nation that remains underrepresented in publicly available remote sensing benchmarks, MLC-BD provides a valuable resource for developing and evaluating vision-based geospatial analysis methods in real-world, multi-source environments.

Institutions

• Hajee Mohammad Danesh Science and Technology University

  Rangpur Division, Dinajpur
• Multimedia University

  Melaka, Malacca
• United International University

  Dhaka Division, Dhaka

Categories

Licence