---
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.

---