The local land use carbon budget (LUCB) balance is an important factor in achieving regional carbon neutrality. As the basic unit of China’s economic development and social governance, the county level is an important part of the realization of the “double carbon” goal. This paper focuses on 1069 county units within the Yangtze River Economic Belt (YREB). It utilizes data on land use, nighttime light, energy consumption, and social and economic factors to construct carbon emission models. The spatiotemporal characteristics of LUCB in these county units are analyzed using standard deviational ellipse (SDE) and spatial autocorrelation methods. Additionally, a zoning study is conducted by examining the economic contribution coefficient (ECC) of carbon emissions, the ecological support coefficient (ESC), and their coupling relationship. The results show that (1) the total land use carbon emissions (LUCE) increased significantly during the research period, and the total carbon sink was relatively stable. (2) The LUCB is spatially high in the east and low in the west, with the center of gravity moving to the southwest as a whole. (3) The LUCB shows positive spatial autocorrelation and has significant spatial agglomeration characteristics, which are mainly high–high and low–low regional agglomeration types. (4) The ECC is high in the east and low in the west, the ESC is high in the west and low in the east, and the coordination and coupling degrees of the two are low. (5) According to the ECC and ESC, the county unit is divided into a low-carbon conservation area, an economic development area, a carbon sink development area, and a comprehensive optimization area. This study is helpful in promoting the sustainable development of carbon neutrality and low carbon in the YREB.

Land use changes significantly impact both carbon emissions and ecosystem service value (ESV). However, few studies have been conducted on the spatial relationship between land use carbon emissions (LUCE) and ESV. Thus, focused on the Yellow River Basin (YRB), this study independently calculates carbon emissions from land use change (LUCE) and ecosystem service values (ESV) in the region. Utilizing spatial autocorrelation methods, we analyze the spatiotemporal pattern of LUCE and ESV and subsequently apply the bivariate spatial autocorrelation method to explore their spatial relationship. The results prove that: (1) The YRB’s LUCE has continuously increased, with construction land acting as the dominant carbon source and woodland acting as the main carbon sink. The LUCE in the YRB had a positive spatial autocorrelation. (2) The YRB’s ESV increased. Spatially, the ESV in the YRB showed a positive autocorrelation. (3) Both LUCE and ESV exhibited negative spatial autocorrelation, with predominant patterns of bivariate localized spatial autocorrelation identified as High-Low agglomeration (H-L) and Low-High agglomeration (L-H). Cities with the L-H pattern were primarily located in Qinghai Province and Inner Mongolia. In contrast, cities with the H-L pattern were mainly observed in the western section of Shandong and the northeastern region of Henan. The study revealed the negative impact of increased carbon emissions from land use on the value of ecosystem services, providing assistance in the development of relevant environmental policies and promoting sustainable development in the YRB.