wildflowers315

Develop Nature-based Solutions
with GIS and AI

At the Forest Agency of Japan, I was responsible for the comprehensive management of national forests, particularly in the Shikoku region. My role included budget management, law compliance check, active forest management and planning, and data collection for National Forest Inventory. I led efforts to standardize drone usage regulations across regional forest management bureaus and unified operational protocols for national forest access. I also contributed to international environmental policy work related to the United Nations Framework Convention on Climate Change (UNFCCC) and Food and Agriculture Organization (FAO). In the climate policy domain, I was engaged in advancing REDD+ under the Paris Agreement and played a key role in Joint Crediting Mechanism (JCM) initiatives, including the design of afforestation guidelines for JCM, which leverage carbon credits, and participation in negotiations related to Article 6 of the Paris Agreement. I am a certified reviewer for Biennial Transparency Reports (BTR) under the UNFCCC and serving as a technical reviewer for REDD+ Forest Reference Emission Level (FREL) submissions in 2025. On the operational side, I managed and trained forest maintenance field staff, supported local teams and interns in Seattle, and supervised new employees at the agency. To further integrate AI, data science and geospatial expertise into forest monitoring, I have completed the Geo-Information Science MSc program at Wageningen University. My study focuses on evaluating tree species classification and canopy height model algorithms using satellite image time series and deep learning as well as exploring agroforestry crop classification and historical land-use change detection. I am working as a remote sensing specialist in FAO and focusing on Forest Resource Assessment Remote Sensing Survey, which is collecting samples by photointerpretation with help from AI model predictions.