Spatially explicit modeling and scenario-based projections of LULC-driven carbon stock changes in Japan
Abstract
Understanding the spatial and temporal dynamics of terrestrial ecosystem carbon stock is essential for effective climate mitigation and land management. This study presents a spatially explicit modeling approach to estimate historical and project future carbon stock changes across Japan from 2001 to 2050. Future projections were generated under three alternative land-use scenarios, including Business-as-Usual (BAU), Conservation, and High-Development pathways. Annual land use/land cover (LULC) maps were combined with class-specific carbon density parameters to calculate grid-level carbon stocks. Intertemporal differences in carbon stocks were computed at the pixel scale, enabling the identification of spatially heterogeneous carbon gains and losses. Future land transitions and carbon trajectories were projected using a CA-Markov model calibrated on observed LULC changes. Across all scenarios, total national carbon stock remains relatively stable, with changes of less than 3%; however, pronounced spatial disparities persist. Southwestern regions, particularly Kyushu and Shikoku, exhibit consistent carbon gains, whereas northeastern prefectures and northern Hokkaido show persistent declines. Forest loss accounts for approximately 8–9% of the total forest area and is overwhelmingly dominated by transitions to grass–savanna systems (>92%), while direct conversion to urban land remains negligible (≤0.15%). This indicates that the predominant contributors to forest carbon change are low-intensity land-cover transitions, and that carbon losses associated with direct urban expansion are highly limited in Japan. • Spatially explicit modeling quantified and projected Japan's carbon stocks under three scenario-based pathways. • Pixel-level carbon change maps revealed spatiotemporal dynamics across landscapes. • National carbon stocks exhibited minimal net change (92%), while conversion to urban land remained negligible (≤0.15%). • High-risk carbon loss occurred in Tohoku and Hokkaido; Kyushu and Shikoku showed gains.
Fields of Study & Subjects
Remote Sensing in Agriculture
Land Use and Ecosystem Services
Remote Sensing and LiDAR Applications
Publication details
- Journal / source
- Ecological Indicators
- Publisher
- Elsevier BV
- Volume
- 183
- Pages
- 114646–114646
- Publication date
- 24 January 2026
- Language
- EN