Exploring the Chile wildfires with Landsat and Sentinel-2 imagery

Yesterday we had a look at some DigitalGlobe imagery of Chile showing the damage caused by wildfires in late January and early February this year.

We thought it would be interesting to explore the region with Landsat and Sentinel-2 imagery.

Landsat imagery. Credit: USGS/NASA Landsat

Sentinel-2 Imagery. Credit: Copernicus Sentinel data, 2017.

The wildfires extended far beyond the area covered by DigitalGlobe imagery (red outlines in the first two images) and almost certainly there were more fires outside the areas shown above, but we did not have time to gather imagery for the whole country. The southernmost Sentinel-2 image was captured earlier than the others and shows at least two wildfires still in progress. Both Landsat and Sentinel-2 imagery clearly show the areas affected by the wildfires and we have outlined them below.

Unfortunately the imagery above is too large for us to share as a KML on this blog.

To obtain the imagery, we started with our KMLs that show previews of Landsat and Sentinel-2 imagery. Once we have selected a suitable image that covers the region of interest in the right date range and without excessive cloud cover, we download the key files from Amazon AWS. For Landsat imagery you need bands 2, 3, 4 and 8 and for Sentinel-2 just bands 2, 3 and 4. We then used GeoSage’s ‘Spectral Discovery’ tools (Landsat Sentinel-2) to process the imagery. An alternative method is to use GIMP or any other suitable image processing tool. GeoSage’s tools certainly make the process much easier, but one downside is the colour processing is automatic, which resulted in significantly different colours for the three Sentinel images.

Obtaining and processing Landsat and Sentinel-2 imagery has certainly become easier over time, with both AWS and Google Cloud hosting the imagery archives. However, what is sorely needed is for a provider to pre-process the imagery and even better would be to then provide it in tiled format. Doing so would change the two public sources of imagery from a niche product mostly used by GIS professionals to a public resource readily available to all.