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DeepGeo aims to improve urban soil contamination assessment using advanced statistical methods. By developing deep Gaussian processes, the project seeks to model pollution more accurately and provide an open-source software library for broader application in geostatistics.
Urban soil contamination resulting from former land-use is important but challenging to measure.
Direct measurements are expensive and time-consuming to acquire, making a city-wide assessment impossible.
Current statistical methods for modelling the distribution of pollution in urban environments, such as kriging, often fail to do so properly, since the contamination is highly local and uncorrelated with the surroundings.
The problems can be mitigated by using multi-output models, such as co-kri…
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