Rural Ecotourism Dataset for the Upper Reaches of the Yangtze River Economic Belt

Rural ecotourism competitiveness refers to the ability of rural areas, relying on a sound ecological environment and taking rural natural landscapes and cultural landscapes as core resources, to effectively identify the development level and potential advantages of rural ecotourism, and to reveal differences among townships across various dimensions. Its construction can provide data support for the spatialization of regional rural ecotourism, balanced comprehensive development, and the implementation of rural revitalization strategies. Based on 16 evaluation factors across four dimensions—natural environment, ecological resources, infrastructure, and humanistic economy—we constructed a township‑scale rural ecotourism competitiveness dataset. The competitiveness was measured using a random forest model and the SHAP interpretable machine learning method, yielding spatial distribution results. The temporal scope is 2020, the spatial scope covers the upper reaches of the Yangtze River Economic Belt, the temporal resolution is annual, the spatial resolution is 30 m × 30 m, and the data format is GeoTiff. The advantages of this dataset are: it integrates multi‑source remote sensing, internet, and government statistical data, with relatively comprehensive indicator coverage; it employs machine learning methods for data‑driven measurement, which can reduce the subjectivity introduced by manual weighting to a certain extent; and it possesses both model interpretability and spatial representation capabilities, providing a fundamental basis for the identification of rural ecotourism resources, zone‑specific policy formulation, and cross‑regional collaborative planning in the Chengdu‑Chongqing economic circle.