In recent decades, the role of heritage railways has gradually shifted from transportation, economy, and trade to tourism, culture, and ecology. The heritage railway landscape is experiencing multiple changes along with a value ambiguity problem. There is a need to comprehensively recognize this landscape in order to promote the transformations and monitor the changes. Inspired by Landscape Character Assessment (LCA), this paper adopts a two-scaled identification framework of landscape character types and areas of the Yunnan–Vietnam Railway (Yunnan section) by integrating holistic and parametric methods. At the regional scale, the landscape character was divided by five natural variables: landform, vegetation, hydrology, soil, and geology. At the corridor scale, the landscape character was classified by five natural and cultural variables: altitude, slope, aspect, land use, and heritage density. At these two scales, k-prototype cluster analysis and multiresolution segmentation (MRS) tool were used to identify landscape character types and areas. The results showed that there were 11 different landscape character types and 80 landscape character areas at the regional scale, and 12 different landscape character types and 58 landscape character areas at the corridor scale. Furthermore, the composition, area, and distribution of these landscape character types and areas were described. The results of this study can form a database for planning, management, and evaluation of the railway.

Green spaces are an essential aspect of building an eco-livable city and play an important role in building for eco-livability in the central Yunnan urban agglomeration. However, there are relatively few studies evaluating the eco-livability of green spaces. The establishment of a green-space eco-livability assessment system may help researchers to analyze the eco-livability of urban green spaces more effectively. To address this research gap, we constructed an ecological livability-evaluation index system for green spaces that incorporates three determinants—economic development, social life, and the ecological environment—using the green spaces of the urban agglomeration in central Yunnan as a case study. We used the entropy method to calculate the suitability for ecological livability of the green spaces in each district and county in the central Yunnan urban agglomeration for 2010, 2015 and 2020. We used the spatial autocorrelation analysis function of ArcGIS 10.8 software to explore the spatial clustering characteristics of the suitability for ecological livability of green spaces in the central Yunnan urban agglomeration. The results showed that, from 2010 to 2020, the suitability for ecological livability of green spaces of the 49 districts and counties in the central Yunnan urban agglomeration increased in some districts and decreased in others. The spatial characteristics were high in the central districts and counties and low in the peripheral districts and counties. The spatial characteristics of the suitability of the target layers for economic development and ecological-environment target were consistent with the overall suitability. Through a spatial autocorrelation analysis, we observed that the suitability of green spaces for ecological livability had a positive spatial correlation and demonstrated significant spatial clustering. In this study, we propose recommendations to improve the suitability for ecological livability of green spaces from two dimensions of government policy and urban development, using a combination of the three target layers. The results of the study provide a reference for decision-making in the construction of eco-livable cities in the central Yunnan urban agglomeration.