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Forest big data, deep learning- Session 1

Tracks
Breakout 2
Wednesday, September 11, 2024
10:00 AM - 11:30 AM
WSP Room

Speaker

Dr Johannes Rahlf
Research Scientist
Norwegian Institute Of Bioeconomy Research (nibio)

Leveraging Deep Learning and NFI Data for Forest Attribute Mapping from Orthophotos

10:00 AM - 10:15 AM

Abstract

Biography

Johannes Rahlf is aresearcher at the Norwegian National Forest Inventory (NFI), with a PhD from the Norwegian University of Life Sciences. He specializes in remote sensing and large-scale mapping of forest resources using both airborne and satellite 3D and optical data. Johannes is particularly interested in incorporating artificial intelligence into remote and proximal sensing for forestry and forest monitoring. As part of NIBIOs SmartForest center, he oversees the project's cloud service, ForestSens.com, facilitating the application of AI algorithms for sensor data processing.
Mr Christopher Schiller
Phd Candidate
Freie Universität Berlin

Spaceborne Forest Disturbance Detection in Central Europe using Transformers

10:15 AM - 10:30 AM

Abstract

Biography

Christopher Schiller studied Geoecology at Karlsruhe Institute of Technology (KIT) in Karlsruhe, Germany. Afterwards, he started his PhD at Free University Berlin in the Remote Sensing and Geoinformatics working group, led by Prof. Fabian Fassnacht. There, his topic is Deep Learning-based Forest Disturbance Monitoring using Sentinel-2 time series.
Ms Pratima Khatri-Chhetri
Graduate Student
University of Washington

Mapping forest type combining field plot and high-resolution data with machine learning in the boreal forest of Interior Alaska

10:30 AM - 10:45 AM

Abstract

Biography

Pratima Khatri-Chhetri is a PhD Candidate at the Forest Resilience Lab, the University of Washington. Her research is focused on developing deep learning models for monitoring the impact of climate change in various forest ecosystems including boreal and mixed conifer. She has recently published high-resolution remote sensing benchmark data and deep learning models for mapping individual tree mortality for mixed-conifer forest ecosystem. Her research interests include large scale ecological modeling using high resolution remote sensing data and deep learning models.
Mr Rylan Boothman
Phd Candidate
Mcgill University

Mapping Forest Insect Infestations with Earth Observation Foundation Models

10:45 AM - 11:00 AM

Abstract

Biography

Rylan is a PhD candidate in the Department of Natural Resource Sciences at McGill University, supervised by Dr. Jeffrey Cardille. He has a BSc in Computer Science from the University of Victoria. His research focuses on using machine learning to interpret remote sensing imagery with a focus on forests.
Ms Melanie Palmer
Data Analyst
Scion

ForestInsights: Mapping New Zealand's forests through deep learning and data-centric AI

11:00 AM - 11:15 AM

Abstract

Biography

Melanie is a data analyst specialising in geospatial and computer vision at Scion. Melanie has a background in geography and geospatial science with an interest in the intersection between the physical and social sciences. Melanie's research at Scion revolves around the use of remote sensing, GIS, and AI for a wide range of forestry applications.
Ms Amandine Debus
PhD Student
University of Cambridge

Identifying deforestation drivers in Cameroon using deep learning and Earth observation data

11:15 AM - 11:30 AM

Abstract

Biography

Amandine is a PhD student in the Department of Geography at the University of Cambridge and a member of the Cambridge Centre for Earth Observation. She graduated from the French Engineering School CentraleSupélec with an MSc in Engineering, and Imperial College London with an MSc in Environmental Engineering and Business Management. Before joining the University of Cambridge, she worked as a Young Graduate Trainee at the European Space Agency Centre for Earth Observation in Italy. She has also worked as a consultant for the environmental law NGO ClientEarth; been part of the Environmental Monitoring Project Team with the Alan Turing Institute, the UK's national institute for data science and artificial intelligence; and is a Teaching Assistant for classes on statistics, cartography, and 'Nature-based solutions to Climate Change' at the University of Cambridge. She is interested in using Earth Observation to inform policy in the broad area of Sustainable Development Goals.
Dr Jonathan Batchelor
Postdoctoral Scholar
University Of Washington

Chairperson

Biography

Ms Pratima Khatri-Chhetri
Graduate Student
University of Washington

Chairperson

Biography

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