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UK firm launches Satellite Land Use Mapping Service

The UK-based company 4 Earth Intelligence (4EI) launched a land cover mapping service, which is based on an advanced machine learning. The service can help in providing large area base maps along with regular updating of land cover change. The earth observation company also helps in sharing details interaction between human activity and nature. This include better understanding of the importance of green infrastructure – vital inputs for solving urban and climatic challenges.

According to Donna Lyndsay, Commercial Director, 4 Earth Intelligence, “Land Cover mapping has many applications and can inform decision making at different levels.”

“With standard classifications ranging from ‘artificial surfaces’, ‘agricultural areas’ and ‘water bodies’ all the way down to specific categories such as ‘vineyards’, ‘airports’ and ‘peat bogs’, it is very easy to get an understanding of current land use and how this is changing,” he further said.

Among applications of the company’s Satellite Derived Land Cover data include description of habitats that could be in danger due to urban sprawl, working on compliance with planning policies, creating corporate mitigation strategies and proofs of Corporate Social Responsibility (CSR) objectives. The firm is also working un coordination with government and commercial companies worldwide to deliver base line maps and updates.

“Each individual satellite footprint can cover an area as large as 10,000 kilometres squared and outputs can be repeated at regular intervals, in some cases as frequently as monthly. It is these characteristics that contribute to a robust, repeatable and automated production methodology delivering results that are both consistent and objective,” Lyndsay continued.

4EI, may also consider satellite pictures or mosaic images so as to share Satellite Derived Land Cover data. The NDVI (normalized difference vegetation index) and SAVI (soil-adjusted vegetation index) are calculated automatically and stacked up alongside spectral bands from the satellite pictures, before categorisation of different indexes.