Environmental Indices

Environmental Indices API

Compute spectral and environmental indices on-demand. Each endpoint accepts a bounding box and date range, returning pre-computed raster tiles or raw values.

All indices listed below are available as individual endpoints. Additional indices beyond this list are actively being added to the platform.

NDVI

/NDVI

Normalized Difference Vegetation Index

Measures vegetation health and density. Values range from -1 to +1; healthy vegetation yields high positive values.

Applications

Crop monitoring, deforestation tracking, land use classification.

Limitations

Sensitive to soil brightness, saturates in dense canopies.

fetch_ndvi.py
python
import requests

res = requests.get('https://api.velstrom.in/v1/indices/NDVI', params={
    'bbox': [72.8, 18.9, 72.9, 19.0],
    'date': '2026-05-01',
    'api_key': 'YOUR_API_KEY'
})
data = res.json()

NDWI

/NDWI

Normalized Difference Water Index

Detects surface water bodies and measures water content in vegetation.

Applications

Flood mapping, wetland monitoring, irrigation management.

Limitations

Can be confused by built-up areas and certain soil types.

fetch_ndwi.py
python
import requests

res = requests.get('https://api.velstrom.in/v1/indices/NDWI', params={
    'bbox': [72.8, 18.9, 72.9, 19.0],
    'date': '2026-05-01',
    'api_key': 'YOUR_API_KEY'
})
data = res.json()

NBSI

/NBSI

Normalized Bare Soil Index

Highlights bare soil areas by exploiting the reflectance contrast between SWIR and visible green.

Applications

Desertification monitoring, mining site mapping, agricultural bare soil identification.

Limitations

May confuse dry vegetation with bare soil in arid environments.

fetch_nbsi.py
python
import requests

res = requests.get('https://api.velstrom.in/v1/indices/NBSI', params={
    'bbox': [72.8, 18.9, 72.9, 19.0],
    'date': '2026-05-01',
    'api_key': 'YOUR_API_KEY'
})
data = res.json()

NDI7

/NDI7

Normalized Difference Index 7

Uses SWIR2 band to distinguish moisture content in vegetation and soil.

Applications

Drought assessment, fuel moisture estimation, fire risk mapping.

Limitations

Atmospheric correction required for accurate values.

fetch_ndi7.py
python
import requests

res = requests.get('https://api.velstrom.in/v1/indices/NDI7', params={
    'bbox': [72.8, 18.9, 72.9, 19.0],
    'date': '2026-05-01',
    'api_key': 'YOUR_API_KEY'
})
data = res.json()

VIIRS

/VIIRS

Visible Infrared Imaging Radiometer Suite

Provides radiometric data from the VIIRS instrument aboard Suomi-NPP and NOAA-20.

Applications

Nighttime lights, fire detection, ocean color, sea surface temperature.

Limitations

Coarser resolution than Sentinel-2 or Landsat for land applications.

fetch_viirs.py
python
import requests

res = requests.get('https://api.velstrom.in/v1/indices/VIIRS', params={
    'bbox': [72.8, 18.9, 72.9, 19.0],
    'date': '2026-05-01',
    'band': 'DNB',
    'api_key': 'YOUR_API_KEY'
})
data = res.json()

EVI

/EVI

Enhanced Vegetation Index

An optimised vegetation index that corrects for atmospheric and soil background influences.

Applications

Dense canopy monitoring, tropical forests, high-biomass regions.

Limitations

Requires blue band, more complex to compute than NDVI.

fetch_evi.py
python
import requests

res = requests.get('https://api.velstrom.in/v1/indices/EVI', params={
    'bbox': [72.8, 18.9, 72.9, 19.0],
    'date': '2026-05-01',
    'api_key': 'YOUR_API_KEY'
})
data = res.json()

SAVI

/SAVI

Soil Adjusted Vegetation Index

Minimises soil brightness effects in areas with sparse vegetation cover.

Applications

Arid/semi-arid vegetation monitoring, early crop growth.

Limitations

Requires empirical soil brightness correction factor L.

fetch_savi.py
python
import requests

res = requests.get('https://api.velstrom.in/v1/indices/SAVI', params={
    'bbox': [72.8, 18.9, 72.9, 19.0],
    'date': '2026-05-01',
    'api_key': 'YOUR_API_KEY'
})
data = res.json()

NBR2

/NBR2

Normalized Burn Ratio 2

Highlights burned areas by leveraging the difference between two shortwave infrared bands.

Applications

Burn severity mapping, post-fire recovery monitoring.

Limitations

Less effective in regions with high cloud cover or snow.

fetch_nbr2.py
python
import requests

res = requests.get('https://api.velstrom.in/v1/indices/NBR2', params={
    'bbox': [72.8, 18.9, 72.9, 19.0],
    'date': '2026-05-01',
    'api_key': 'YOUR_API_KEY'
})
data = res.json()

Working towards it: Additional spectral indices (MSAVI, GNDVI, ARVI, BSI, MNDWI, and more) are being integrated. The full index catalogue will cover vegetation, water, soil, burn, urban, and atmospheric domains.