SAR-SIAD-2025:Pond/Water Body Detection from Satellite Image.

Published: 31 August 2025| Version 1 | DOI: 10.17632/5gyngmzhzv.1
Contributors:
,
, Md Ashikur Rahman, Jubair Ahmed

Description

This dataset contains a satellite image focused on aquaculture ponds and water bodies, along with corresponding ,annotation files in CSV format. The dataset is designed for research in pond/water body detection, image segmentation, and land-use classification. The annotations provide labeled information to distinguish between Water Bodies (ponds, reservoirs) and Non-Water Areas (agriculture, vegetation, and built-up regions), making it suitable for training and evaluating computer vision models. File Information - Total Files/Size: 36.3 MB - Image(s):Total: 930 images, PNG format (satellite image(s) of ponds and surroundings) - Annotation(s): CSV format - Columns: image_id, x_min, y_min, x_max, y_max, label - Labels: -1 = Water Body (ponds, reservoirs) - 0 = Non-Water (fields, vegetation, built-up areas) Applications - Automated pond/water body detection - Image segmentation and classification in remote sensing - Aquaculture monitoring and resource management - Training/testing deep learning models for land-use analysis

Files

Institutions

  • Daffodil International University

Categories

Computer Vision, Environmental Science, Remote Sensing, Aquaculture, Machine Learning, Geospatial Data Repository, Deep Learning

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