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Preservation and RecognItion of Spatial patterns using Machine learning

CORDIS · observation · Publication date unknown

Preservation and RecognItion of Spatial patterns using Machine learning Ecological research necessitates the production of spatial maps representing an array of critical variables such as biodiversity, climate, land cover, and soil carbon storage. While current machine learning methods, such as the well-known random forest (RF), have been effective in generating maps for these variables, they often overlook the intricate spatial patterns inherent in ecological processes. The PRISM project seeks to introduce a novel approach that addresses this limitation by integrating and validating spatial patterns within machine learning models. The project will draw upon insights from various fields, including geography, landscape ecology, statistics, and computer science. To ensure the widespread dissemination and accessibility of its findings, PRISM will adopt a comprehensive open science approach, including manuscript publications, the development of

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recordType

award

status

SIGNED

region

EU

value

189687.36

unit

EUR