Advancing Nature-based Solutions
with Earth Observation & AI

I am Takayuki Ishikawa — Remote Sensing Specialist at the Food and Agriculture Organization of the United Nations (FAO) in Rome.
I combine deep learning, satellite imagery, and 15+ years of forest policy experience to support global forest monitoring and sustainable land management.

Skills & Expertise

Earth Observation & GIS

Google Earth Engine ArcGIS / QGIS Multispectral SAR (Radar) LiDAR Time-series Analysis Photointerpretation

AI / Machine Learning

Deep Learning PyTorch CNN / ViT Tree Species Classification Land-use Mapping Object Detection

Programming

Python R Java HTML / CSS Linux / Bash Git Slurm (HPC)

Forest & Climate Policy

UNFCCC REDD+ Paris Agreement Art. 6 JCM Carbon Credits National Forest Mgmt Green Climate Fund

Experience

Oct 2025 – Present
Food and Agriculture Organization of the UN — Rome, Italy
Remote Sensing Specialist, Forestry Division
Land-use label collection via satellite photointerpretation for the FAO Forest Resource Assessment (FRA) Remote Sensing Survey. Constructing and evaluating AI models for automated land-use and land-use change classification.
Sep 2023 – Aug 2025
Wageningen University & Research — Wageningen, Netherlands
MSc Geo-information Science
Deep learning for tree species classification (Dutch National Forest Inventory), canopy height modeling, agroforestry crop identification, and historical land-use change detection using multi-source satellite data.
Apr 2021 – Aug 2023
Forest Agency, Japan — Tokyo
Assistant Director, International Forestry Cooperation Office
Japanese REDD+ focal point at COP26, COP27 & SB58. Managed JCM afforestation/reforestation projects in Cambodia. Represented Japan at the World Bank Forest Carbon Partnership Facility.
Apr 2018 – Mar 2021
Consulate General of Japan — Seattle, USA
Consul
Promoted Japan–US AI and technology partnerships. Supported ML-focused meet-up events connecting Seattle-area startups with Japanese investors.
Apr 2015 – Mar 2018
Forest Agency, Japan — Tokyo
Chief, National Forest Management Division
Led budgetary and legal coordination for national forest management. Established Japan-wide drone usage regulations for national forests and standardized operational procedures across regional offices.
Apr 2009 – Mar 2015
Forest Agency / Ministry of Internal Affairs — Japan
Forestry Officer & Local Finance Chief
Oversaw 2,000 ha of national forest in Shikoku region. Developed forest policy documents and coordinated local government finance for wildlife and marine debris legislation.

Portfolio

Highlights from my MSc research in GIS, remote sensing, and machine learning.
View Full Visualization Portfolio

Golden Jackal movement paths map

Golden Jackal Movement Paths

Land classification by machine learning

Land Classification by Machine Learning

Deep learning multi-label classification predictions

Multi-label Classification via Deep Learning

MobileNet fine-tuning training history

MobileNet3 Fine-Tuning Training History

Confusion matrix

Confusion Matrix — MobileNet3 Fine-Tuning

Wageningen University campus

And more — visit the full portfolio

Publications

Peer-reviewed Preprint · 2025

Ishikawa, T., Bonannella, C., Lerink, B. J. W., & Rußwurm, M. (2025). Assessing the Effectiveness of Deep Embeddings for Tree Species Classification in the Dutch Forest Inventory. arXiv preprint. Under review.
DOI: 10.48550/arXiv.2508.18829

UNFCCC Technical Review · 2025

Expert reviewer for the technical assessment of proposed REDD+ forest reference emission levels from Costa Rica (2025) under the UNFCCC Enhanced Transparency Framework.

About Me

Wageningen University campus

I am Takayuki Ishikawa, a Remote Sensing Specialist at the Food and Agriculture Organization of the United Nations (FAO) based in Rome, Italy, working on the global Forest Resource Assessment Remote Sensing Survey.

Before joining FAO, I completed an MSc in Geo-information Science at Wageningen University & Research (2023–2025), where I focused on deep learning for tree species classification and satellite-based land-use change detection.

Prior to academia, I spent over 15 years as a Japanese government officer at the Forest Agency, serving as the national REDD+ focal point at UNFCCC conferences (COP26, COP27) and designing afforestation frameworks under the Joint Crediting Mechanism. I am a certified UNFCCC technical reviewer for Biennial Transparency Reports and REDD+ reference levels.

My work sits at the intersection of Earth observation, AI/ML, and international climate policy — translating satellite data into actionable insights for forest conservation and carbon accounting.

Contact

Have a question or a collaboration idea? Feel free to reach out.