Ecosystem services are closely related to human well-being and are vulnerable to high-intensity human land-use activities. Understanding the evolution of land use and land cover (LULC) changes and quantifying ecosystem service value (ESV) are significant for sustainable development. In this study, we used land use and land cover data and other data from 2000 to 2020 to analyze the evolution of land use and land cover and ESV in Tongliao, China. With the goal of exploring the characteristics of different cellular automata (CA)-based models, CA-Markov, Future Land Use Simulation (FLUS), and Patch-generating Land Use Simulation (PLUS) models were used to simulate future land use and land cover, and the results were verified and compared. Considering the impacts of policies for capital farmland (CF) and ecological protection red line (EPRL) in the context of territorial spatial planning, four scenarios (inertial development, S1; CF, S2; EPRL, S3; EPRL and CF, S4) were set. The results showed that from 2000 to 2020, farmland and built-up land increased the most (341.18 km2 and 220.56 km2), while grassland had the largest decrease (380.08 km2). The main mutual transitions were from grassland and farmland. The total ESV showed a decreasing trend (from 52,364.56 million yuan to 51,620.62 million yuan). The simulation results for 2035 under four scenarios were similar, where farmland would decrease the most (96.81 km2). The ESV in 2035 would decrease from 51,620.62 million yuan to 51,541.12 million. In addition, under scenarios for the impact of policy, the land showed a trend of scattered expansion. This study provides a scientific basis for making regional sustainable development policy decisions and implementing ecological environmental protection measures.

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A land-use simulation model oriented toward ecological constraints is effective for evaluating the ecological impact of urban spatial planning. However, few studies have incorporated dynamically nested ecological spatial constraints into the model or fully considered the urban development, agricultural production, and ecological function among the ecological spatial constraints. Therefore, this study developed an improved land-use simulation model with dynamically nested ecological spatial constraints (LSDNE). We fully considered the multilevel ecological spatial constraints from the perspectives of ecological (ecological protection red line, EPRL), production (capital farmland, CF), and living (urban development land-use suitability, UDLS). Five scenarios in terms of future land-use distribution in 2030 were set, namely, inertial development (S1), considering EPRL (S2), considering CF (S3), considering EPRL and CF (S4), and considering EPRL, CF, and UDLS (S5). This new approach was implemented in the rapidly developing provincial capital city of Changchun, China. The results show that, due to the occupation of arable land, Changchun had the largest increase in built-up land (2019.75 km2 to 3036.36 km2) from 2010 to 2020. Terrain elevation was the most significant factor in all kinds of land expansion. According to future land spatial distribution results in 2030, under S4, Changchun’s built-up land will be more compact compared with S1–S3 and S5, which showed more scattered built-up land. These predicted results show that Changchun’s spatial planning put forward high requirements for the efficient use of land and constraints in red-line areas. Due to a clear evaluation of the impact of ecological spatial constraints on future land expansion, the LSDNE model provides more accurate support for the efficient use of land resources and future territorial spatial planning.

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