Rural ecological landscapes are shaped by coupled natural processes and human activities, yet practical evaluation and governance often remain constrained by fragmented datasets, indicator inconsistency, and limited decision-support efficiency. To address these gaps, this study constructs a multi-dimensional evaluation model for rural ecological landscapes and embeds it into a modular digital platform to enable integrated data management, standardized computation, and visual decision support. The model is organized into four dimensions ‒ ecological baseline conditions, landscape spatial structure, ecosystem service functions, and ecological risk response ‒ forming a state-organization-outputpressure logic chain. A platform-enabled workflow is established to orchestrate multi-source data harmonization, algorithmic execution, and interactive visualization. A pilot study in Huangshandian Village, Beijing, is utilized to validate both the ecological applicability of the model and the operational effectiveness of the platform. Results demonstrate that the multi-dimensional model accurately captures complex spatial differentiations, successfully identifying high-quality conservation cores in peripheral natural areas and elevated composite risks in the central development corridor. Simultaneously, the platform's automated geoprocessing engine proved effective in resolving data interoperability issues and executing these complex diagnostics without requiring fragmented GIS operations. Furthermore, the interactive frontend visualization empowers non-expert stakeholders to dynamically generate and query comprehensive ecological grading maps. Overall, this study contributes a scientifically robust ecological evaluation framework and operationalizes it through an accessible digital platform, transforming traditional fragmented analyses into an integrated planning support system for data-driven ruralgovernance.