SOURCE-LINKED INTELLIGENCE

Deep learning for Forest Mapping using Point clouds

CORDIS · observation · Publication date unknown

Deep learning for Forest Mapping using Point clouds Over the last decade, the Earth has witnessed significant climate change and global warming, largely as consequences of rapid industrial development. To combat this, the management and preservation of forests have become increasingly essential, given their homeostatic role in regulating the global climate. Point clouds (PCs) obtained from LiDAR mapping offer vast amounts of data, which have proven invaluable for forest mapping. In our research, DeepForMaP, we leverage PC data and utilise advanced deep learning techniques to monitor forest patterns across both space and time. One of the primary challenges in processing PC data arises from its unstructured nature. To address this, we employ recent feature extractors such as Mamba and Kolmogorov Arnold Networks (KANs) to process the data, extracting meaningful and discriminative representa

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recordType

award

status

SIGNED

region

EU

value

226420.56

unit

EUR