Identifying Terrestrial Landscape Character Types in China

Abstract

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.

Detecting Spatiotemporal Dynamics and Driving Patterns in Forest Fragmentation with a Forest Fragmentation Comprehensive Index (FFCI): Taking an Area with Active Forest Cover Change as a Case Study

“…A higher value denotes more obvious spatial autocorrelation. When the value reaches a relatively stable level, the scale can be considered a suitable window size for the landscape metrics of the study area [42]. In this study, we used ArcGIS 10.3 software to generate 10,000 random points in the study area and extracted the three calculated landscape metrics at 10 moving window sizes into these random points.…”

Integrating Heritage and Environment: Characterization of Cultural Landscape in Beijing Great Wall Heritage Area

“…The LCA method is currently diversified and practiced in European countries and commonly used in territorial spatial planning [43][44][45], land-use management [46,47], and other applications based on land initiatives [48,49]. Other regions, such as China, have just begun to study landscape characters in national, urban, protected areas, national parks, and other regions [50][51][52]. However, there is a lack of LCA practices for large-scale cultural heritage areas and even fewer studies using LCA for LCH areas [53].…”

Identifying Rural Landscape Heritage Character Types and Areas: A Case Study of the Li River Basin in Guilin, China

“…However, cultural element types and content complexity have not yet formed a systematic element system incorporated into the overlay analysis of character recognition. Certainly, some studies incorporate cultural characteristics such as ethnic populations, settlement culture, and architectural form into the recognition results at the cultural level [20][21][22]. However, overall, the selection of cultural data types tends to be relatively narrow, limiting the systematicity and reliability of LCA in the identification process.…”