## 1 Introduction
Investigating the factors influencing carbon emissions in territorial space is an essential way to formulate emission reduction policies accurately. Regional social, economic, and historical development variations lead to differing determinants of land-use carbon emissions. Scholars frequently employ spatial econometric and factor decomposition models to examine the driving mechanisms behind these emissions. For example, [PERSON] applied the geographically and temporally weighted regression (GTWR) method, identifying positive correlations between carbon emissions and factors such as population size, economic development, land-use intensity, and landscape configurations [18]. [PERSON] used Geodetector and K-means clustering to analyze the drivers and clustering patterns of county-level carbon emissions in Shaanxi Province [19]. [PERSON] employed the logarithmic mean Divisia index (LMDI) model to assess factors influencing land-use carbon emissions across nine provinces in the Yellow River Basin over 30 years [20]. Their findings indicated that population density, economic scale, and land-use structure contributed to emissions, with dominant factors varying by stage. In conclusion, a comprehensive understanding of the factors affecting land-use carbon emissions necessitates consideration of the distinct natural and economic characteristics of each region. This approach provides targeted scientific guidance for the low-carbon management of territorial space in lake-intensive regions. The study of land-use carbon emissions has expanded significantly in recent years. (1) In spatial scales, studies have gradually shifted focus from national and provincial scales to urban and county scales [21; 22; 23; 24]. However, the grid scale, the smallest geospatial research unit, has rarely been explored in land-use carbon budget studies. Additionally, research hotspots have focused on core cities or urban clusters undergoing rapid urbanization, such as Shanghai and Chongqing, with limited attention to the mechanisms driving carbon budget evolution in lake-adjacent regions with contiguous development. This highlights an urgent need to integrate grid and urban scales for carbon budget studies in lake-intensive regions. (2) In differentiation patterns, prior research on regional carbon emissions and sequestration has often neglected the spatiotemporal connections and clustering dynamics of carbon budgets within lake regions and between internal grid units. (3) In driving mechanisms, lake-dense regions pose unique analytical challenges due to their distinct land-use configurations. Unlike traditional urban risks stemming from cumulative pressures of expansion, these regions demand more nuanced analyses of the factors driving their carbon dynamics. The Dongting Lake region serves as both an active carbon source and a supplementary carbon sink amid the rapid urbanization of the Yangtze River Economic Belt. Since the early 21 st century, under the coordinated development strategy of the Yangtze River Economic Belt, energy industries have expanded rapidly along rivers and lakes, leveraging locational advantages [25]. However, this rapid economic growth has intensified conflicts with the ecological carrying capacity of the Dongting Lake region, undermining the ability of lake-intensive regions to achieve carbon reduction and sequestration goals. To address these challenges, this study builds on prior research by introducing innovations in research subjects, content, and methods. Regarding research subjects, this study focuses on lake-specific cross-regional areas, accounting for spatial heterogeneity in resources, industrial structures, and economic development across cities, and locates territorial carbon budget results at the smallest grid unit. Regarding research content and methods, a \"micromeso-macro\" framework is proposed to analyze the spatiotemporal dynamics and driving mechanisms of territorial carbon budgets.