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Those are the TOP 3 submissions to the Social Entrepreneurship Challenge. Congratulations to the winning solution!
ArchEO – Democratising AI to Explore the Past
Archaeology is under constant threat from development, agriculture, and climate change. Knowing where sites are located is of key importance for protection and management, yet manual approaches are slow and costly. ArchEO provides AI-derived tools to automatically detect and monitor sites based on EO data.
These tools, which have been tested and researched by two Ph.D students, will provide both commercial organisations and society at large with an accessible way to engage with local and global heritage.
ArchEOwill use Sentinel-2 data at 10-metre resolution to detect very large sites. In addition, data at sub-metre resolution (along with nationally captured LiDAR and other local datasets) will be acquired to map sites of all sizes.
The platform will be free for users who want to engage with open-source data and be subject to a fee for those who require high accuracy (e.g. archaeology firms that offer advice to project developers on selecting more suitable development sites to avoid project delays and have less heritage impact).
Submitted by Iris Kramer
Asbestos Roofing Detection with Sentinel-2 Data
Public authorities face a tremendous task in identifying and certifying the removal of asbestos materials from the roofs of private and public buildings. A test was done using Sentinel-2 multispectral images to evaluate the detection of spatial asbestos distribution and its evolution over time (change detection). Using a combination of trained algorithms, the experiment demonstrated that it is possible to identify land cover and detect changes in asbestos with 70-91% precision.
The procedure uses Sentinel-2 (L1C/L2A) MS images within the visible to SWIR regions (B2-B8A and B11-B12) as its minimum input for spectrum unmixing and supervised classification algorithms in SNAP.
The ground scale to be covered by public authorities to ensure asbestos law compliance is such that using satellite data and image processing techniques for hazardous land cover detection could benefit society, public health, human resources and environmental practices.
Submitted by Pedro Miguel da Silva Pinto
Zuri – An AI-Enabled Platform for Monitoring and Regulating Farm Fires in India
Every year, millions of tonnes of crop waste are burnt to clear agricultural fields in India, which releases significant pollution and GHG emissions. The huge smoke cloud that results then moves across the North Indian plains, inflicting irreversible health damage on 300 million Indians who breathe the hazardous air.
Zuri is an AI-enabled platform that uses satellite data for improved monitoring, supply chain and pricing analysis, and alternative allocation of crop waste to other industries as raw material.
Zuri is built on Copernicus data, including information from Sentinel-2 (RGB) and Sentinel-3 (S7-9, F1-2) for burnt area detection and TROPOMI products for monitoring evolving plumes, as well as on NASA products for fire detection.
The inefficient burning of crop waste costs India 1.7% of its GDP on an annual basis. This same crop waste can be used in electricity generation, green packaging, sustainable textiles, and engineered wood. Zuri enables this transition of crop waste to raw material with data and analytics.
Submitted by Abhilasha Purwar
Participants of this challenge can be non-profit social enterprises, for-profit social enterprises, or hybrid-social enterprises. Submissions to the challenge can range in maturity, from idea through to a completed product or service. Further, the solutions submitted do not need to have a commercial application, but could still clearly provide benefits to society with the realisation of their idea.
Submissions are welcome in any relevant application field, including but not limited to:
Submissions to the Social Entrepreneurship Challenge will be evaluated against the following criteria:
Does the solution provide clear benefits to society?
Does the solution demonstrate a novel application of Earth observation data?
Does the solution use Copernicus data to add value for end-users?
Does the solution apply Copernicus data in a technically feasible way?
AZO is an international networking and branding company for European space programmes, supporting entrepreneurship with more than 500 companies founded in Europe. Over the last 15 years, AZO has established the leading European space cluster innovation network for the satellite downstream market. AZO organises the “Innovation Masters Series”, the most important space-related innovation competitions: Galileo Masters, Copernicus Masters, INNOspace Masters, Space Exploration Masters
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