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Assessing Terrestrial Ecosystem Carbon Storage Under Land Use and Cover Change: Methods, Models, and Spatiotemporal Dynamics

Jiashuo Hou
Vol.8, No.7, pp.32-48, 2026 DOI: 10.62051/ijnres.v8n7.03 August 4, 2026
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Abstract: Quantifying terrestrial ecosystem carbon storage is critical for understanding the global carbon cycle, mitigating climate change, and achieving carbon neutrality targets. Land use and land cover change (LUCC) represents one of the most significant anthropogenic drivers of terrestrial carbon dynamics. Within the peer-reviewed English-language literature, the integration of remote sensing, geographic information systems (GIS), and spatially explicit models has become a prominent approach for carbon storage assessment. This review synthesizes a purposive sample of 23 peer-reviewed studies (2006–2025) across four analytical dimensions: (1) carbon storage estimation models, including the InVEST framework, Gaussian process regression (GPR), DNDC, and CBM-CFS3; (2) land use simulation models such as FLUS, PLUS, and CLUE-S; (3) multi-scenario prediction frameworks; and (4) driving factor analyses. A structured comparison of model architectures, validation approaches, and reported accuracies reveals systematic strengths and limitations within each model class as represented in this corpus. The synthesis identifies five cross-cutting concerns in the reviewed literature: (i) a pronounced geographic concentration on Chinese study sites (65% of the corpus), which limits the global generalizability of the synthesized findings; (ii) the near-absence of out-of-sample validation for coupled LUCC–carbon frameworks within the reviewed studies; (iii) potential confirmation bias toward positive model performance reporting; (iv) a conceptual gap between static carbon density look-up approaches and dynamic biogeochemical process representations; and (v) a temporal scale mismatch between land use simulation time steps and carbon flux timescales. Future research priorities identified from this corpus include independent multi-model validation against field measurements, formal uncertainty propagation through coupled model chains, and the operationalization of carbon storage modeling within the Sustainable Development Goal (SDG) monitoring framework—each contingent on geographic diversification beyond the currently dominant Chinese study sites.
Keywords: Carbon Storage; Land Use/Cover Change; Invest Model; FLUS Model; Remote Sensing Estimation; Scenario Simulation; Uncertainty Quantification.
APA Citation: Jiashuo Hou (2026). Assessing Terrestrial Ecosystem Carbon Storage Under Land Use and Cover Change: Methods, Models, and Spatiotemporal Dynamics. International Journal of Natural Resources and Environmental Studies, 8(7), 32-48. https://doi.org/10.62051/ijnres.v8n7.03

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