Timber & Oil Palm Consessions
Identifying mismatches in commodity production based on satellite imagery in West Kalimantan, Borneo.
R, Jupyter Notebook
Applied remote sensing, GIS, and machine learning
for forest monitoring and environmental applications.
With a rapidly changing environment, traditional sensing techniques are often unscalable spatially and limited due to data unavailibility. With a passion for preserving various world's ecosystems for future generations, I offer expertise using applied Geo-information Science with a special focus on tropical rainforests and temperate forests. In my career, I have deployed techniques such as RADAR-derived machine learing algorithms for detecting logging routes under dense forest canopies, utilised spectral indices to quanitfy vegetation status spatially, or combined field LiDAR measurements with air/space-borne data to include validation through ground-truth. The possibility of continuously obtaining such data on our Earth's ecosystems allows for informed decision making at a meaningufl extent while there is still time to act.
Recent Work
Biodiversity based on Tree Crown Complexity
Estimating forest biodiversity based on tree crown complexity metrics derived from the AHN6. Reinforcement through web application where users contribute by logging new trees.
JavaScript, PHP, CSS, R
Water Infrastructure
Spatially optimising water pipeline infrastrucure the Maas-Waal area, connecting industries with refinement plant.
ArcGIS Model Builder
LiDAR Forest Inventory
Comparing handheld LiDAR devices to professional MLS/TLS scanners for DBH estimates in Loobos Scotts pine forest.
CloudCompare, 3DFin
Small- vs Large-scale Farming in the Amazon
Comparing the impact of small- vs large-scall farming and their effects on surround tropical rainforest canopy in Brazilian Amazon. Interviews conducted with farmers of compared parcels during my 2024 bachelor's thesis work near Manaus, Amazonas.
QGIS, LECOS, RFC
Last project example
Description of my last visual project example.
Tools used
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