D4.6 Example of Jupyter Notebook for LiDAR- or drone-derived habitat condition metrics

This document illustrates several examples of deploying a workflow (with Jupyter Notebooks) on a compute cluster for deriving a consistent set of habitat condition metrics from LiDAR for EU habitat monitoring.

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Published
2026-08-20
DOI
https://doi.org/10.3897/arphapreprints.e212264
Primary Topic
Remote Sensing and LiDAR Applications
Type
preprint

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preprint

D4.6 Example of Jupyter Notebook for LiDAR- or drone-derived habitat condition metrics

Wilm Daniel Kissling, Wessel Mulder, Yifang Shi, Jinhu Wang
Remote Sensing and LiDAR Applications
preprint

D4.6 Example of Jupyter Notebook for LiDAR- or drone-derived habitat condition metrics

Wilm Daniel Kissling, Wessel Mulder, Yifang Shi, Jinhu Wang
preprint en

Abstract

This document illustrates several examples of deploying a workflow (with Jupyter Notebooks) on a compute cluster for deriving a consistent set of habitat condition metrics from LiDAR for EU habitat monitoring.

Amsterdam University of the Arts (NL), University of Amsterdam (NL)
Netherlands eScience Center, European Commission
Life in Land
Remote Sensing and LiDAR Applications
DOIOpen Access PDFOpenAlex
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D4.6 Example of Jupyter Notebook for LiDAR- or drone-derived habitat condition metrics — Wilm Daniel Kissling, Wessel Mulder, et al. · (2026) | TGRS Research Map | TGRS