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UID:pretalx-europython-2026-DWGSFA@programme.europython.eu
DTSTART;TZID=CET:20260716T112500
DTEND;TZID=CET:20260716T115500
DESCRIPTION:Due to climate change\, **large wildfires** continue affecting 
 all continents of the Earth\, leading to forest loss and exacerbating envi
 ronmental impacts. Even more\, current changing weather conditions associa
 ted with global warming will further increase fire danger to a global exte
 nt. Investigating these phenomena in a data-driven manner helps in decisio
 n making in pre-intervention and post-restoration following wildfire event
 s. **Satellites** orbiting Earth can offer critical insights by capturing 
 detailed images of the planet’s surface. Utilizing this data\, environme
 ntal scientists perform detailed assessments to monitor an ecosystem’s l
 oss and post-restoration progress. However\, data from satellites arrive i
 n the form of millions of raw pixels and turning them into analysis ready 
 products is a **time-consuming** task full of **multi-step** and **error-p
 rone** processes.\n\nThis talk introduces an end-to-end Python workflow to
  automate the processing of **Earth Observation (EO) data**. The presentat
 ion walks through pixels to insights showcasing a real example and highlig
 hting both the power of automation in the field of remote sensing and the 
 importance of EO data in **climate change monitoring**. After the session\
 , the audience will understand how utilizing open Python packages such as 
 **Rasterio** and **NumPy** with openly distributed data from the [European
  Space Agency’s Sentinel-2 mission](https://dataspace.copernicus.eu/data
 -collections/copernicus-sentinel-missions/sentinel-2) can lead us quickly 
 into crucial and spatially meaningful information. Although the demonstrat
 ion focuses on wildfire events\, the automated workflow is broadly applica
 ble to other environmental fields such as land cover change detection\, hy
 drological assessments and coastal studies.\n\n**No prior knowledge is req
 uired**! The **goal** is not to delve into complex mathematical equations\
 , but to showcase the power of automation in remote sensing with Python.
DTSTAMP:20260524T121903Z
LOCATION:Theatre Hall (S2)
SUMMARY:From Pixels to Insights: Python for Earth Observation - ELENI TOKMA
 KTSI
URL:https://programme.europython.eu/europython-2026/talk/DWGSFA/
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