Rural reconstruction plays a pivotal role in the revitalization of rural areas and the development of regions. Understanding the pattern and direction of rural settlement reconstruction is crucial for effectively coordinating urban and rural development, as well as promoting regional rural revitalization. The present study proposes a novel approach to elucidate the evolution and spatial reconstruction of rural settlements by integrating features of agglomeration effect and ecological effect. By employing GIS spatial analysis technology and ecosystem service value modeling, the research analyzes the combined spatial agglomeration and ecological value characteristics of rural settlements in an arid oasis area, specifically focusing on the Hexi Corridor. Based on the analysis, the study identifies specific rural settlement reconstruction zoning and directions for optimization, considering rural settlement accessibility. The study reveals three key findings: (1) There are significant differences in the scale density and spatial distribution of rural settlements across the Hexi Corridor. (2) The overall ecological environment quality is good, and there is significant spatial differentiation in the ecosystem service value, influenced by topographic factors. (3) The optimal layout mode for rural settlements in the Hexi Corridor is the combination type of ‘higher-ecological higher-density’. Based on the combined agglomeration effect and ecological effect features, the research determines the reconstruction scope of alienated rural settlements. Additionally, four predominant reconstruction modes are identified: urban agglomeration type, central village construction type, internal coordination type, and ecological protection type. The study proposes viable reconstruction paths for rural settlements based on these modes.

Rapid urbanization and agricultural expansion in arid regions have profoundly altered carbon cycles and landscape stability. Focusing on the Hexi Corridor, China, this study integrates multi-source geospatial data (1990–2020) to analyze the spatiotemporal evolution and driving factors of land-use carbon emissions (LUCE) and landscape ecological risks (LER). By integrating carbon accounting, LER assessment, bivariate spatial autocorrelation, and the Optimal Parameter Geographic Detector (OPGD), we quantify the intricate relationship between carbon dynamics and landscape integrity. Results indicate a transformative pattern of anthropogenic expansion and natural contraction, with a 2315.49 km² net loss of unused land. Net carbon emissions surged 4.6-fold, while forest and grassland sinks exhibited a significant “lock-in effect” due to fragile ecological foundations. Simultaneously, LER followed an “inverted U-shaped” trajectory; the refined 5 × 5 km grid scale revealed a significant drop in high-risk areas from 44.65% to 10.96% following ecological restoration. Spatial analysis reveals a significant “spatial mismatch” between LUCE and LER, with oases manifesting “high carbon–low risk” clustering. Driver detection confirms a driving asymmetry. LUCE is dominated by anthropogenic factors (nighttime light, q > 0.90), whereas LER is profoundly constrained by natural backgrounds. Future governance must shift toward a collaborative system centered on source-based emission control and precise regional management to synergize low-carbon transition with landscape security.