Heating season means pollution season

Bad air quality is one of the most serious threat to public health. Starting in autumn it becomes even more dangerous. Power consumption related to the heating system and road traffic is increasing, which leads to the increase of air pollution as well. What is more, lower temperatures are favorable conditions to keep air quality poor. This article presents how NO2 pollution changes from September to November in respect of temperature.

Timeliness and frequency of Sentinel products explained

Sentinel satellite missions, as part of the Copernicus programme, generate a wide portfolio of Earth Observation (EO) products which are generated with different frequency and timeliness. This is sometimes problematic for users to comprehend, thus this article provides an executive summary of observation scenarios of Sentinel satellite missions and timeliness.

Monitoring floods using Python and Sentinel-2 satellite imagery

In the last decade, the number of extreme natural phenomena has dramatically increased, causing damage to people all around the world. According to statistics, the number of natural catastrophes is correlated with global warming. The rise in air temperature not only leads to droughts and global fires but also triggers extreme storms and large-scale floods. […]

Monitoring droughts with Earth observation data

Back to the list According to the European Centre for Medium-Range Weather Forecasts (ECMWF) and the Copernicus Climate Change Service (C3S), July 2023 has set a new record as the warmest month ever recorded globally, with an average temperature of 16.95 degrees Celsius. This temperature surge is attributed to massive heatwaves that affected Europe, Asia, […]

Traceability Service in Copernicus Data Space Ecosystem 

Traceability in satellite imagery is a fundamental concept that holds significant value and utility in various applications related to remote sensing and geospatial analysis. It refers to the ability to trace and track the source and processing history of satellite data, enabling users to understand the data's origin, quality, and reliability.

Running Science/EO application stack on Kubernetes in CloudFerro Cloud

Technologies based on containers have revolutionized the way that applications and workflows get deployed. They greatly reduce overheads linked to system configuration and promote use of micro-services for delivering clean, maintainable software.

Processing Sentinel-5P data using HARP and Python

Air quality is a crucial factor that impacts public health. Thanks to the satellite observations provided by TROPOMI onboard Senitnel-5P, hotspots of nitrogen dioxide (NO2) can be detected over the Earth every day. However, Sentinel-5P data needs to be prepared in a proper way to be useful for further analysis.

EO Data Access (R)evolution

Earth Observation (EO) produces a massive amount of data (34 PB available on CREODIAS) that needs to be archived and made accessible to end-users. Operational costs of maintaining Immediately Available Data (IAD) were cumbersome for many data platforms operating at a large scale such as the Copernicus Open Access Hub. Consequently, the rolling data policy has been implemented whereby, after a certain time, the EO products are moved from the costly IAD to the less expensive Long Term Archive (LTA). Within the LTA, data is stored on magnetic tape, which is the cheapest storage solution, but requires additional cartridge handling (either manual or more efficient automatic handling). Either way, restoring data from the tape LTA to IAD requires a lot of time, so a user must wait hours, days, or even weeks to get immediate access to data.

Land cover classification using remote sensing and AI/ML technology

Although the terms “land usage” and “land cover” are frequently used interchangeably, each term has a distinct definition. The term “land cover” describes a material that covers the surface of the ground, such as vegetation, urban infrastructure, water, bare soil, etc. Land cover identification creates the baseline data for tasks like thematic mapping and change detection analyses. The term “land use” describes the function that a piece of land performs, such as agriculture, wildlife habitat, or recreation.