license: mit
task_categories:
- image-segmentation
- image-feature-extraction
tags:
- Geoinformatics
- Bi-Temporal
- Satellite
- Sentinel-2
- Sentinel2
pretty_name: Sentinel-2 Dataset New Delhi
size_categories:
- 1K<n<10K
Sentinel-2 Dataset – New Delhi Region
Dataset Description
This dataset comprises multispectral satellite imagery acquired by the mission over the metropolitan region. Sentinel-2 is part of the Copernicus Programme of the European Space Agency (ESA) and is designed for high-resolution monitoring of land surfaces, urban areas, and environmental processes.
The dataset is intended for geospatial analysis tasks such as image segmentation, feature extraction, and bi-temporal change detection in dense urban and peri-urban environments.
Spatial Coverage
The dataset covers New Delhi and its surrounding areas, capturing a diverse range of land-cover types including dense built-up regions, transportation networks, vegetation, water bodies, and agricultural land. This spatial diversity makes the dataset suitable for urban mapping and environmental monitoring applications.
Spectral Characteristics
Sentinel-2 provides imagery across 13 spectral bands in the visible (VIS), near-infrared (NIR), and shortwave infrared (SWIR) regions. The bands are available at spatial resolutions of 10 m, 20 m, and 60 m, allowing both fine-scale urban analysis and broader environmental assessments.
Key spectral capabilities include:
- High-resolution visible and NIR bands for urban and vegetation analysis
- SWIR bands for moisture, soil, and built-up area characterization
- Atmospheric bands supporting radiometric correction
Temporal Resolution
The dataset benefits from Sentinel-2’s high revisit frequency of approximately 5 days using the combined Sentinel-2A and Sentinel-2B satellites. This enables bi-temporal and multi-temporal analysis for monitoring urban expansion, seasonal vegetation changes, and environmental dynamics.
Data Products
The imagery is typically provided as:
- Level-1C: Top-of-Atmosphere (TOA) reflectance
- Level-2A: Bottom-of-Atmosphere (BOA) surface reflectance
Data are distributed in a tiled format using the UTM/WGS-84 coordinate reference system and are compatible with common geospatial and remote sensing software tools.
Intended Use
This dataset is suitable for:
- Image segmentation of urban and natural features
- Feature extraction for geospatial machine learning models
- Land-use and land-cover (LULC) classification
- Bi-temporal change detection
- Urban growth and environmental monitoring
License
This dataset is released under the MIT License, allowing free use, modification, and distribution with attribution.