Search Results (4)

Disaster-prone mountainous regions face complex human–environment conflicts resulting from the combined influences of natural disaster threats, ecosystem conservation, and resource development. This study takes Mentougou District as the research area, leveraging landscape character identification methods to develop a multidimensional evaluation framework integrating safety, ecology, and landscape aspects, providing a foundation for zoning and management decisions. Four characteristic elements—elevation, geomorphology, vegetation type, and land cover type—were extracted during the landscape character identification phase. Two-step clustering and eCognition multi-scale segmentation were used to identify 12 landscape character types (LCTs) and delineate Landscape Character Areas (LCAs). The MaxEnt model was applied during the evaluation phase to assess debris flow susceptibility. At the same time, AHP and ArcGIS spatial overlay methods were used to evaluate ecological resilience and landscape resource quality. The three-dimensional evaluation results for the 12 LCAs were clustered and manually interpreted, resulting in four levels of protection and development areas. Management strategies were proposed from three perspectives: debris flow disaster prevention, ecosystem conservation, and landscape resource development. This method provides a pathway to balance human–environment conflicts in disaster-prone mountainous regions, promoting scientific zoning management and sustainable development in vast mountainous areas. Full article

The Landscape Character Assessment (LCA) method from the UK has proven effective in identifying landscape values and characteristics through a comprehensive mapping process. However, it is predominantly expert-led and lacks an evaluation of scenery, hindering the inclusion of the broader community’s preferences and visual attachment to their landscape. In Australia, the application of the Scenic Amenity Methodology (SAM) using Geographical Information System (GIS) mapping has engaged communities but has often overlooked the importance of landscape character. To overcome these limitations, this study presents an innovative scenic assessment methodology, referred to as modified Scenic Amenity Methodology (modified SAM). The methodology establishes landscape character types (LCTs) to map scenic preference ratings derived from community photo surveys. Simultaneously, it incorporates the visual exposure of the landscape from publicly accessible viewpoints, modelled using a Digital Elevation Model (DEM). The combination of scenic preferences and visual exposure enables mapping of the scenic amenity values held by the community. This methodology was first trialled in Bundaberg, then Cairns, the Whitsunday Islands, and, most recently, Toowoomba in Queensland, Australia. This paper presents the results of the Toowoomba study and reports on the challenges and limitations of informing landscape character type (LCT) values through a public photo survey, developing a scenic preference map from ratings of photos across a region, a map of the visual exposure of landscape elements from key public viewing locations, and, ultimately, a map of scenic amenity values across the Toowoomba Region. It indicates that integrating previous LCA approaches with public participation through community preferences is indeed feasible for regional landscape planning. Full article

The urban landscape is being affected by rapid urbanization, leading to a complexity of land features and a fragmentation of patches. However, many studies have focused on the prediction of land-use change with a lack of research on the landscape character types which have more integrated descriptions of land features. Hence, this study predicts and identifies landscape character types (LCTs) in different periods based on the PLUS model and the K-Medoids algorithm, taking the central city of Chongqing as an example, to reveal the differences in the influence of driving factors on LCTs. The results show that (1) the urban landscape characteristic types present a gradient change from the built-up area to the outward expansion. (2) The SHDI and LPI of landscape character types decreased significantly with the expansion of construction land. (3) Nighttime light, distance from water bodies, and distance from the motorways are the main factors affecting the change of landscape character types. This study predicts and identifies urban landscape character types and quantifies the impact of urban expansion on landscape character. It can be used to guide urban planning and help governments to make more informed decisions on sustainable urban development and ecological conservation. Full article

Landscape character assessment (LCA) is a widely used tool that integrates natural, cultural, and perceptual attributes to identify and portray landscape. In this study, we used the LCA method to identify the landscape characteristics of China at the national scale. Furthermore, we applied cultural and landscape structural factors along with spatial transmission to improve the identification system. First, we incorporated all the parameters in the assessment. We selected 15 landscape character factors from four factor types including nature, culture, spatial geographic co-ordinates, and landscape structure. These parameters were analysed using multilevel overlay and spatial connection tools in ArcGis 10.2, which resulted in 2307 landscape description units (LDUs). Second, the spatial structure properties of the LDUs were determined using a semivariogram and the moving window method in ArcGis 10.2 and Fragstats 4.2 software, respectively. Third, for visualisation, we applied the principal component analysis (PCA) using the SPSS software and elbow and k-means clustering methods using MATLAB to determine 110 landscape character types (LCTs) of China’s entire terrestrial landscape. Finally, we determined 1483 landscape character areas through semiautomatic segmentation and manual visual correction using eCognition. Based on the unique characteristics of the entire terrestrial landscape of China, a set of ideas and methods for the overall identification of LCTs was proposed. Our findings can be used to optimise territorial spatial planning and landscape protection and management, and promote multiscale land-use studies in China. Full article