Satellite & Imagery

Work with satellite, aerial and drone imagery.

8 tools

Build an imagery workflow from discovery to display

Separate finding imagery, analysing its pixels and delivering a map to users. The right workflow depends on your area of interest, acquisition dates, spectral bands and acceptable cloud cover. A viewer or processing library does not automatically include an imagery archive or rights to redistribute the data.

Jump to all tools

Explore Earth Engine data

geemap brings interactive Earth Engine analysis and visualization into Python workflows. Use it to explore collections and inspect results, while accounting separately for Earth Engine access and the datasets you choose.

Process raster pixels

Rasterio reads and writes geospatial raster data through Python arrays. Consider it for a pipeline you control, with explicit handling of projections, nodata, band selection and output resolution.

Present results in context

CesiumJS can place imagery within a 3D globe or scene. Choose delivery formats and zoom behaviour around the questions users need to answer; retain access to analytical values when a rendered image is insufficient.

Before you choose

Check acquisition date, resolution, bands and cloud masking before comparing scenes.
Record projection, resampling and nodata decisions so results can be reproduced.
Plan storage and delivery for both original data and derived products.