Earth observation company 4 Earth Intelligence (4EI) has launched a new land cover mapping service based on advanced machine learning. Created from satellite imagery the 4EI service can automatically provide large area base maps together with regular updates of land cover change. Offering a better understanding of changing landscape and vegetation patterns the 4EI Land Cover data also provides insight into the interaction between human activity and nature including improved understanding of the importance of green infrastructure – essential ingredients for solving urban and climatic challenges.
“Land Cover mapping has many applications and can inform decision making at different levels,” commented Donna Lyndsay, Commercial Director at 4 Earth Intelligence. “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.”
Applications of 4EI’s Satellite Derived Land Cover data include the identification of habitats which could be vulnerable due to urban sprawl, understanding and demonstrating compliance with planning policies, creation of corporate mitigation strategies and evidence of Corporate Social Responsibility (CSR) objectives. 4EI has already worked with government and commercial organisations around the world to deliver base line maps and updates.
“Satellite imagery as a source for wide scale land cover mapping offers many advantages,” continued Lyndsay. “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.”
In order to produce Satellite Derived Land Cover data 4EI can consider individual satellite images or mosaics of images that are close in date. Before classification different indexes, for example NDVI (normalized difference vegetation index) and SAVI (soil-adjusted vegetation index) are automatically calculated and stacked up along with the spectral bands from the satellite images. This is then processed using machine learnt algorithms before post classification quality control is undertaken.
The 4EI schema used to classify land use is adapted from the CORINE (Coordination of Information on the Environment) programme. Originally initiated by the European Commission and latterly administrated by the European Environment Agency the CORINE land cover project defines 44 classifications of land cover and presents results as a cartographic product.
About 4 Earth Intelligence (4EI)
4 Earth Intelligence (4EI) is a specialist in earth observation intelligence and data services. Built on decades of earth observation excellence, geospatial expertise and data analytics experience, 4EI creates data products, services and insights that enable organisations to manage risk and make informed decisions to improve outcomes.
With a focus on customer need 4EI designs solutions to solve core problems while ensuring data quality is proven, consistent and repeatable. 4EI has worked with government and commercial organisations, and leading academic institutions, to complete a range of projects including a new Global Air quality index, wide-scale habitat mapping and the use of machine learning for urban heat mapping.
4EI will focus on new sectors and technical innovations using machine learning and Artificial Intelligence to provide smart data for global environmental challenges such as climate change, pollution and population pressure.
For more information, visit www.4earthintelligence.com.
What Is Earth Observation?
Earth observation is the collection of information about the physical, chemical and biological systems of the planet via remote sensing techniques; in other words measurement or information gathering from a distance. Earth observation includes monitoring and assessing the status of, and changes in the natural and man-made environments. Techniques and technologies used for earth observation can range from floating buoys used to monitor ocean currents, temperature and salinity right up to sophisticated satellite sensors.
It is currently estimated there are in the region of 2,000 artificial satellites orbiting the earth designated into separate categories or roles; including communications, navigation and Global Positioning Satellites (GPS). This classification also includes the overarching definition of remote sensing satellite which can itself include a wide variety of sensors, and therefore data captured, including imagery, radar and non-imaging sensors such as infra-red and hyperspectral.
Recent estimates suggest that there are around 700 earth observation satellites, a staggering growth of 250 percent in just four years, which allows for the globe’s entire landmass to be imaged, in its entirety, every day!
