All Earth

Earth Observations and GeoAI for Carbon Dynamics: Linking Spatial Insights to SDGs

Traditional carbon emission research has largely relied on inventory-based accounting methods, which provide an essential foundation for climate reporting and carbon management. However, these approaches often face constraints in revealing spatial heterogeneity, temporal dynamics, and socioeconomic drivers of carbon emissions and carbon sinks, limiting their applications for fine-scale urban planning and near-real-time climate governance. Addressing the ambitions of SDG 11 (Sustainable Cities and Communities), SDG 12 (Responsible Consumption and Production), and SDG 13 (Climate Action) requires high-resolution carbon information that is rapidly updated. Similarly, robust assessments of blue and green carbon dynamics are needed to track progress toward SDG 14 (Life Below Water) and SDG 15 (Life on Land).

Recent developments in Earth Observations (EO) and GeoAI provide new opportunities for both improving carbon-related datasets and extracting spatial insights from existing emission inventories and carbon datasets. Spaceborne carbon missions provide direct retrievals of atmospheric CO₂ and CH₄ columns. Meanwhile, complementary datasets, including nighttime light imagery, high-resolution land use maps, and thermal or radar observations, serve as effective proxies for socioeconomic activity, energy intensity, and ecosystem structure. When these diverse datasets are integrated with existing or newly developed carbon datasets and analyzed using spatial statistics and GeoAI, they enable researchers to map carbon dynamics, identify spatial inequalities and emission clusters, investigate socioeconomic and environmental drivers, evaluate policy outcomes, and simulate future carbon trajectories across multiple spatial scales.

This Article Collection welcomes original research and review articles addressing:

• Carbon data development and enhancement: Construction, downscaling, validation, or updating of carbon emission inventories and blue/green carbon datasets using EO, geospatial data, and data-driven approaches.
• Geospatial analytical methods: Spatial clustering, hotspot analysis, geographically weighted regression, and machine learning approaches for identifying and attributing drivers of carbon dynamics.
• Integration with socioeconomic data: Studies combining EO-derived indicators with census or statistical data to assess regional disparities in carbon intensity, environmental justice, or energy poverty.
• Scenario simulation and policy evaluation: Spatial modeling of carbon trajectories under different land use, energy, or urban planning scenarios, with direct relevance to SDG 11, 12, 13, 14, and 15.

By linking fine-scale EO insights to policy-relevant indicators, this collection aims to operationalize SDG monitoring and reporting. The published work will directly support evidence-based decision-making for SDG 11, SDG 12, and SDG 13 by informing urban zoning and climate action plans. Furthermore, by clarifying the spatial links between emissions and ecosystem health, the collection contributes to the integrated implementation of SDG 14 and SDG 15. Ultimately, this collection seeks to establish EO-driven geospatial intelligence as an essential tool for tracking progress toward multiple Sustainable Development Goals and for guiding equitable, low-carbon transitions worldwide.

This Article Collection will be included in Taylor & Francis’ SDG Article Collection Series.

Keywords:

1. Carbon Emissions
2. Earth Observations
3. GeoAI
4. Sustainable Development Goals
5. Spatial Analytics

­­All manuscripts submitted to this Article Collection will undergo a full peer-review; the Guest Advisor for this Collection will not be handling the manuscripts (unless they are an Editorial Board member).

Please review the journal scope and author submission instructions prior to submitting a manuscript.

The deadline for submitting manuscripts is April 30, 2027.

Please contact Kara Roberts at [email protected] with any queries on discount codes regarding this Article Collection.

Please select Earth Observations from the list of available sections during submission. Failure to select the appropriate Article Collection or Section name can result in delays.

Dr. Yifu Ou is a EU-funded Marie Curie Fellow at Heriot-Watt University, and serves as an Associate Editor for the Earth Observations section of All Earth. Dr. Ou’s research focuses on urban sustainability and environmental change, with particular interests in integrating earth observations, geospatial analytics, and applied econometrics to support carbon assessment and sustainable development. He has published over 40 papers in leading journals, including GIScience & Remote Sensing, Sustainable Cities and Society, Environmental Impact Assessment Review, and Journal of Cleaner Production.

Dr. Xu Nan is an Associate Professor at the School of Architecture and Urban Planning, Shenzhen University. His research focuses on Environmental remote sensing applications, including coastal zones, water resources, wetlands, and disasters. He has published over 60 SCI papers as the first/corresponding author in journals such as Nature Communications, PNAS, Science Bulletin, Remote Sensing of Environment, IEEE Transactions on Geoscience and Remote Sensing, International Journal of Applied Earth Observation and Geoinformation.

Dr. Xiao Huijuan is an Assistant Professor at the Department of Geography, Hong Kong Baptist University. Her research focuses on carbon emission mitigation, climate change economics, and Sustainable Development Goals analysis.She has published high-quality SCI-indexed papers as first author in leading journals, including Nature Communications, where her paper was recognized as a Highly Cited Paper, and The Innovation.

Guest Advisors do not declare any potential conflicts of interests in line with our Editorial Policies.