Identifying carbon emissions from land-use change at the county scale is important for promoting low-carbon development and sustainable use and management of land resources in counties. Thus, here, taking Jiangxi province as an example, we use the spatial autocorrelation model and Logarithmic Mean Divisia Index (LMDI) method to analyze the spatiotemporal pattern evolution and the influencing factors of land-use carbon emissions in the counties, based on land-use data and socio-economic data of Jiangxi Province from 2000-2020. The results show that: (1) the carbon emissions from land use in different districts showed an increasing trend, but the growth rate of carbon emissions and the average carbon emission intensity decreased in 2000-2020. However, some districts showed a change in the growth rate of carbon emissions that increased after 2015. Construction land is the primary source of carbon emission growth, while forest land has an important role as a carbon sink. (2) Spatially, the distribution of carbon emissions from land-use change shows obviously spatial differences, with a high north to low south distribution and a relatively stable clustering pattern, and the spatial distribution of light and heavy emission areas and above is more concentrated. With economically developed regions and counties being the "core" and undeveloped regions and counties being the "periphery" of carbon emissions growth. And this "core-periphery" pattern is continuously strengthening. (3) In general, the main factors inhibiting the growth of carbon emissions are carbon emission intensity and land-use efficiency; the driving factors are the level of economic development and the scale of construction land. However, the carbon emission intensity of some districts and counties show the effect of "early driving and later suppressing", and the suppressing effect is smaller than the driving effect, so the carbon emission of land use in these districts and counties is still growing significantly. Therefore, Jiangxi counties should actively adjust their industrial structure and continue to reduce their carbon emissions intensity and improve land use efficiency by optimizing the allocation of land resources. For example, people should use an appropriately intensive model to improve the efficiency of construction land use for avoiding blind expansion and waste. Moreover, the undeveloped and developed regions need to strengthen exchanges and cooperation in the areas of capital and technology. In addition, different regions and counties in Jiangxi province should also take into account their own local conditions, define their own development goals and follow a low-carbon, high-quality development path with their own county characteristics.