2024-10-02, 12:00–12:45, Raiffa Room (IIASA)
The workshop aims to exchange on recent policy requirements, progress in providing EO-based data and products and equip participants with better knowledge and skills to analyze the drivers of deforestation and associated carbon emissions using remote sensing and Machine learning. The workshop aligns with recent European Union(EU) regulations to curb the EU market’s impact on global deforestation and provides valuable information for monitoring land use following deforestation, crucial for environmental initiatives and carbon neutrality goals.
Part 1: Guest Speaker
Introduction to Deforestation and EUDR requirements (JRC - F. Achard team)
● Definition and significance of deforestation
● Relevant policy initiatives; in particular EUDR and implications for monitoring
● Requirements
Part 2: Mapping Drivers of Deforestation (R. Masolele)
Section 1: Mapping Land Use and Change Detection
● Change detection methods using remote sensing data
● Monitoring deforestation over time
● Techniques for land use classification
Section 2: Identifying Deforestation Drivers
● Understanding direct drivers of deforestation
● Applying machine learning techniques to identify deforestation drivers
● Case studies on driver identification
Part 3: Estimating and Mapping Carbon Emissions Associated with Deforestation (Camilo Zamora, Arnan Araza)
Session 1: Carbon Emissions Estimation
● Introduction to carbon emissions modeling
● Using remote sensing for above-ground biomass estimation
● Quantifying carbon emissions from deforestation drivers
Additional Components:
Open Discussion and Q&A:
Dedicated time for participants to discuss challenges, share experiences, and seek guidance on specific issues.
Workshop Outcome:
Participants will leave the workshop with practical knowledge in mapping deforestation drivers and estimating associated carbon emissions using remote sensing and machine learning. They will gain insights into the interdisciplinary nature of deforestation analysis and the application of machine learning for informed decision-making.
Open-Earth-Monitor Cyberinfrastructure (Grant agreement ID: 101059548)
Dr. Robert Masolele is a post-doctoral researcher renowned for his work at the intersection of artificial intelligence and remote sensing, particularly in the field of classifying land use changes with a specific emphasis on commodity crops. His innovative research has contributed significantly to our understanding of how agricultural expansion, particularly in the cultivation of commodity crops, impacts global landscapes.
Education and Early Career:
Dr. Masolele earned his Ph.D. in Remote sensing and Machine learning from Wageningen University, where his passion for harnessing cutting-edge technologies to address pressing environmental challenges first took root. His early career saw him working on various projects related to satellite imagery analysis and machine learning applications, laying the foundation for his expertise in the intricate field of land use classification.
Expertise in AI and Satellite Imagery:
Specializing in the fusion of artificial intelligence and high-resolution satellite imagery, Dr. Masolele has developed advanced models and algorithms that excel in classifying land use changes with high accuracy. His research focuses on monitoring the expansion of commodity crops such as cacao, oil palm, rubber, coffee, avocado, pasture, and soy, providing valuable insights into the environmental repercussions of large-scale agricultural practices.
Notable Contributions:
One of Dr. Masolele's most notable contributions includes the development of a novel convolutional neural network (CNN) architecture tailored to handle the complexities of commodity crop identification. His work has led to breakthroughs in mapping the spatial distribution of land use following deforestation, understanding the dynamics of deforestation, and quantifying the ecological impact of crop expansion.
Collaborations and Impact:
Dr. Masolele is a sought-after collaborator in interdisciplinary research endeavors, fostering partnerships between environmental scientists, ecologists, and computer scientists. His work has had a tangible impact on sustainable land management practices and has been influential in shaping conservation policies in regions vulnerable to agricultural encroachment.
Publications:
In recognition of his outstanding contributions, Dr. Robert Masolele's work has been published in leading academic journals, media outlets, and he frequently presents his findings at international conferences.
As Dr. Masolele continues to push the boundaries of knowledge in his field, his dedication to leveraging artificial intelligence and satellite imagery for the betterment of global ecosystems remains a beacon of inspiration for the scientific community.