Identifying Landscape Character in Multi-Ethnic Areas in Southwest China: The Case of the Miao Frontier Corridor

Abstract

The landscapes of China’s multi-ethnic areas are rich in natural and cultural value, but they are threatened by homogenization and urbanization. This study aims to establish a method for identifying and classifying the landscape characters in China’s multi-ethnic areas to support the protection and sustainable development of the landscape in these areas. Taking the Miao Frontier Corridor as an example, the study optimized a parameterization method of landscape character assessment (LCA), integrated relevant cultural and natural elements, and used the K-means clustering algorithm to determine the landscape character types and regions of the Miao Frontier Corridor. The results show that (1) the natural conditions, ethnic exchanges, and historical institutions of the Miao Frontier Corridor have had a significant impact on its overall landscape; and (2) using ethnic group culture as a cultural element in LCA helps to reveal the unique cultural value of areas with different landscape characters. This study expands the LCA framework and applies it to multi-ethnic areas in China, thereby establishing a database that can serve as the basis for cross-regional landscape protection, management, and development planning in these areas. The research methods can be widely used in other multi-ethnic areas in China.

1. Introduction

The landscape of China’s multi-ethnic areas is undergoing rapid change. China is a multi-ethnic country that includes Han Chinese and 55 ethnic minorities [1]. According to the seventh national census, China’s ethnic minority population is 125.47 million www.stats.gov.cn (accessed on 23 July 2025), with most of them living in remote mountainous areas [2]. Among them, Hunan, Guizhou, and Yunnan provinces are the most diverse provinces in China in terms of ethnic types, with Guizhou’s minority population accounting for 39% of the province’s total population. During the Song and Yuan dynasties, large-scale ethnic migration and cultural exchanges occurred in the southwest. Due to the invasion and oppression by the Mongol Yuan army, many Han, Baiyue, and other ethnic groups fled the Central Plains and migrated to the southwest region, where they exchanged, clashed, and merged with local Yi, Miao, Dai, and other ethnic minorities. This historical process gave rise to rich natural and cultural landscapes. However, with the rapid pace of China’s modernization and under the government-led market economy system, the environment in these minority areas has developed at an accelerated rate. As a result, many unique natural and cultural landscapes are disappearing at an accelerated rate [3].

Landscape character assessment (LCA) [4] is a tool to support landscape conservation and management. LCA represents the landscape character of an area by identifying and categorizing landscape types into distinct units. Dividing landscapes into different types of units is a traditional task in environmental and geographical research [5], as it allows for clearer explanations of landscapes and helps protect their uniqueness and diversity [6,7]. LCA involves two processes: the characterization process, which includes the delineation of the area, selection of elements, landscape classification, and characterization, followed by the judgment process, which informs decision-making [8,9]. In LCA, landscape character is defined as a unique, recognizable, and consistent pattern of elements, focusing on identifying differences between landscapes rather than determining which is superior or inferior [8]. The value of LCA lies in the creation of a landscape resource database for a region, providing comprehensive information and a spatial framework for landscape conservation and management [10]. Understanding regional landscape character is crucial for preserving the unique and diverse values of its landscapes [6].

Since the 21st century, based on the European Landscape Convention (ELC) [11] understanding of the landscape, LCA has become an important decision-making aid at the national/regional terrestrial scale in Western and Northern European countries. It has been successfully implemented in the UK [10], the Netherlands [12], Belgium [13], Austria [14], Portugal [15], New Zealand [16], Cyprus [17], and other countries/regions. Initially, Traditional assessments of landscapes in the UK and Europe have mainly characterized them through biophysical and cultural–physical dimensions [18]. At the beginning of the 21st century, research expanded to include dimensions of human disturbance intensity and perception [19]. Over the past decade, research has further incorporated dimensions characterizing intangible cultural and ecological functions, enriching the indicators measuring the perceptual and cultural–physical dimensions [20].

Developing a framework for landscape character assessment (LCA) in multi-ethnic areas remains a significant challenge. Due to the cultural diversity and spatial heterogeneity of these regions, where landscapes are often deeply influenced by national cultures, it is crucial to incorporate socio-cultural factors that reflect these differences when conducting LCA. However, there are few references available for LCA research in China in this regard. The LCA in Hong Kong was conducted in 2001, and Hong Kong was the first city in Asia to apply LCA. Unlike Western countries, which typically have clear distinctions between urban and rural areas, the evaluation in Hong Kong covered both urban and rural landscapes, providing a demonstration and model for urban and rural landscape planning and management in mainland China [21]. After 2012, the LCA method of evaluating the landscape character of China’s countryside has been applied more in the implementation of projects [22,23,24] and scenic area planning [25]. Subsequently, local-scale LCA-based studies began to emerge, focusing on a variety of landscapes, such as river corridors [26], mountainous scenery areas [27], towns at different scales [28], and urban and rural boundaries [29]. While numerous LCA studies have been conducted in China as part of landscape spatial development planning, and many LCA research results are used to guide landscape planning [30], research specifically on multi-ethnic areas remains scarce [27]. Furthermore, in these studies, landscape classification and evaluation primarily focus on biophysical and aesthetic dimensions, with only a few incorporating cultural elements [24].

Landscape classification generally follows two primary methods: the holistic method and the parametric method [31]. The holistic approach begins with a comprehensive observation of the landscape, often involving manual classification by experts through aerial imagery [6]. This method is quick and broad in scope but is highly susceptible to significant subjectivity. In recent years, with the increase in data sources and improvements in statistical methods, the parametric approach has become increasingly popular in LCA studies [32,33,34,35]. The parametric method involves combining various thematic maps into a composite map, which is then used to identify and classify landscape character types. However, parametric methods rely on basic data that covers the entire area [7], such as areal data, which means that point-based geospatial data, like heritage site data or points of interest (POIs), cannot be directly applied in LCA. Furthermore, there are certain limitations with the statistical variables in some parametric methods. Since most base data are in raster format and consist mainly of nominal variables, once a grid is created, the variables within the grid are either present (1) or absent (0) [7]. However, the grid’s resolution is typically lower than that of the original dataset, causing the attribute value of each grid cell to be represented by the most prevalent variable within that cell [36]. As a result, different ecosystems may be statistically grouped into a single category [7], failing to capture the finer texture of the landscape [37].

The Miao Frontier Corridor, located in southwestern China, is one of the country’s six major ethnic corridors. It connects three provinces with the highest concentration of ethnic groups in China, making it a quintessential multi-ethnic region. This corridor also links China’s three major geographical terraces, and its distinctive natural and cultural landscapes are emblematic of the nation’s ethnic minority areas. For nearly 700 years, it has served as a vital communication route between the ancient Central Plains and the borderlands, fostering a wealth of both tangible and intangible heritage. It has made significant contributions to the preservation of local multiculturalism and to regional social development.

This study focuses on the Miao Frontier Corridor’s multi-ethnic landscape, using it as a case study to apply the LCA method. It integrates both natural and cultural elements, such as ethnic group culture, and employs quantitative data analysis to identify the region’s landscape characteristics. The findings can serve as a tool for landscape protection and management in the region, while also providing a foundation for landscape studies in other multi-ethnic areas. By incorporating cross-regional data, the study aims to promote the systematic integration of landscapes in multi-ethnic regions, both spatially and administratively, with the goal of advancing a comprehensive LCA across China.

2. Materials and Methods

2.1. Study Area

The Miao Frontier Corridor stretches for 1400 km and covers an area of more than 70,000 square kilometers. It encompasses the counties and cities connected by the ancient post road, which runs from Yuanling in Hunan Province to Kunming in Yunnan Province (Figure 1). This region links China’s three major geographical terraces and features typical landforms, including plateaus, karst landscapes, and plains. The elevation ranges from −10 m to 2867 m, gradually rising from east to west. The relief amplitude varies between 0 and 356 m at a 1 km resolution, with the Guizhou section having a slightly higher average relief amplitude compared to the Yunnan and Hunan sections.

The main ethnic minorities in the Miao Frontier Corridor include the Miao, Buyi, Dong, Gelao, She, Yi, Tujia, and Yao [38]. According to data from China’s Seventh National Census (2020), the total population of ethnic minorities in the corridor is approximately 10.21 million (www.stats.gov.cn). Many of these ethnic groups have developed unique cultural traditions, traditional settlements, and local architectural styles. As of December 2020, a total of 440 villages in the corridor were listed as national or provincial traditional settlements.

Originally, the Miao Frontier Corridor served as a government road established at the end of the Yuan Dynasty and the beginning of the Ming Dynasty to strengthen the state’s control over the southwestern region, contributing to the nationalization of the southwestern border [39]. During the Hongwu period of the Ming Dynasty, large numbers of Han Chinese military personnel and civilians migrated to the area, giving rise to the “military settlement culture,” which facilitated the integration of Han culture with that of the Miao, Bouyei, Yi, and other ethnic groups. Following the Qing Dynasty’s policy of “replacing local chieftains with imperial officials,” the region’s population surged from 10,000 at the beginning of the Qing Dynasty to 5 million by the end of the Qianlong era, forming a land-based economic corridor linking the Yangtze and Pearl River systems. Building on this foundation, Confucianism, Chinese characters, lantern dances, and Han ethnic festivals spread westward along the corridor. In turn, rice terrace farming techniques, Miao–Dong songs and dances, Bouyei wax printing, and Yi medicine spread into the interior. The influx of immigrants and trade activities further promoted cultural integration between the Central Plains and the southwest. Unlike the now-abandoned “Tea–Horse Ancient Road,” this corridor remains a densely populated and culturally vibrant economic belt to this day.

2.2. Selection of Variables and Data Preprocessing

We selected five types of landscape elements to participate in LCA and collected five types of detailed, high-quality basic data based on these elements, including raster data sets showing their natural geographical characteristics and vector data sets reflecting their cultural attributes. The four types of raster datasets are as follows: the European Space Agency (ESA) Global Land Cover (2009), a 30 m Digital Elevation Model (DEM) (2010), soil type data at a 50 m resolution, and vegetation type data at a 50 m resolution. The vector dataset consists of spatial location data for traditional settlements in the Miao Frontier Corridor, sourced from several authoritative publications: seven batches of Chinese Famous Historical and Cultural Villages published by the Ministry of Housing and Urban–Rural Development and the State Administration of Cultural Heritage; five batches of national traditional settlements released by the Ministry of Housing and Urban–Rural Development and related departments; three batches of national minority characteristic villages published by the State Ethnic Affairs Commission (SEAC); and two batches of provincial minority characteristic villages released by the SEAC of Guizhou and Yunnan Provinces.

In terms of natural elements, we selected topography and landform, land cover, vegetation, and soil as assessment elements. A total of 38 natural geo-environmental variables were considered, with elevation and relief derived from the DEM dataset. The elevation of the study area ranges from −10 m to 2867 m, increasing gradually from east to west, while relief varies from 0 m to 356 m. The area features 15 land cover types, the largest of which is broad-leaved evergreen tree cover, closed to open (>15%) (LC5), covering 14,409 km², or 20.8%, followed by mosaic cropland (>50%) and natural vegetation (tree, shrub, herbaceous cover) (LC3), covering 11,617 km², or 16.8%. There are 10 soil types, with iron bauxite (S6) being the most prevalent, covering 39,197 km², or 56.6% of the total area, followed by primary soil (S2), covering 20,504 km², or 29.6%. The study area is home to 11 vegetation types, with the largest proportion being subtropical and tropical evergreen broad-leaved and deciduous broad-leaved scrub (often containing rare tree species) (V6), covering 20,233.8 km², or 29.2% of the area. This is followed by subtropical coniferous forest (V1), covering 18,254 km², or 26.4% of the area.

In terms of cultural elements, we chose ethnic group culture as an assessment element. A total of 14 cultural variables were considered. We employed the cost allocation tool in ArcGIS 10.8 to calculate spatial units representing the ethnic cultural influence ranges of each traditional settlement. This tool accounts for the unique topographical features of the Miao Frontier Corridor in calculating the cultural influence range. Elevation, relief amplitude, and land cover were selected as cost distance factors. Based on existing research and professional advice, the analytic hierarchy process (AHP) was used to assign weights to these three datasets. The ArcGIS 10.8 raster calculator tool was then used to combine these weights and construct a comprehensive cost surface. Traditional settlements were treated as cultural sources, and the cost allocation tool was applied to analyze the comprehensive cost surface, dividing it into ethnic cultural units. Finally, the ethnicity of residents in traditional settlements was regarded as the name of their ethnic culture. Based on the ethnic composition of residents within traditional settlements, a type value was assigned to each unit, which serves as a cultural variable (Figure 2). A key point of this study is the identification of certain units as Han–minorities integration types or minority integration types, as these units contain multi-ethnic mixed communities. Among the 115 ethnic cultural units identified (Figure 3), the largest in scale is the Han–minorities integration type, comprising 23 units with a total area of 16,366 km², accounting for 23.65% of the total area, and exhibiting a dispersed distribution pattern. The second largest is the Miao ethnic group, consisting of 20 units with a total area of 12,999 km², or 18.79% of the total area, also displaying a dispersed distribution pattern. The smallest is the She ethnic group, with only 1 unit covering 431 km², or 0.62% of the total area (

Table 1. Detailed information on the ethnocultural genealogical units of traditional settlements.

Ethnic Cultural	Number of Units	Area (km2)	Percentage
Buyi	13	6856	9.49%
Dong	1	5252	7.30%
Ge Jia	2	99	0.14%
Ge Lao	3	190	0.26%
Han	15	15,987	22.22%
Hui	2	692	0.96%
Miao	20	12,999	18.10%
She	1	431	0.60%
Shui	2	704	0.98%
Tujia	6	3750	5.21%
Yi	6	3272	4.55%
Yao	3	1663	2.31%
Han–minorities integration	23	16,366	22.75%
Multi-minorities integration	18	3692	5.13%

).

Table 2. Variables used for landscape character classification. Land cover data provided by the European Space Agency http://due.esrin.esa.int/page_globcover.php (accessed on 2 June 2025). Soil, vegetation, and DEM data were collected from the China Resource and Environment Data Cloud Platform http://www.resdc.cn/ (accessed on 2 June 2025).

Variables	Acronym	Variables	Acronym
Topography and landform		Lake	S9
Elevation (m)	E	River	S10
Relief amplitude (m)	RA	Vegetation
Land cover		Subtropical coniferous forest	V1
Cropland, rainfed	LC1	Subtropical deciduous broad-leaved forest	V2
Cropland, irrigated or post-flooding	LC2	Subtropical mixed evergreen and deciduous broad-leaved forests	V3
Mosaic cropland (>50%)/natural vegetation (tree, shrub, herbaceous cover) (<50%)	LC3	Subtropical broad-leaved evergreen forest	V4
Mosaic natural vegetation (tree, shrub, herbaceous cover) (>50%)/cropland (<50%)	LC4	Subtropical and tropical bamboo forests and thickets	V5
Tree cover, broad-leaved, evergreen, closed to open (>15%)	LC5	Subtropical, tropical broad-leaved evergreen, deciduous broad-leaved scrub (often containing rare trees)	V6
Tree cover, broad-leaved, deciduous, closed to open (>15%)	LC6	Subtropical, tropical grasses	V7
Tree cover, needle-leaved, evergreen, closed to open (>15%)	LC7	Temperate grasses, miscellaneous grass meadows	V8
Mosaic tree and shrub (>50%)/herbaceous cover (<50%)	LC8	Biannual water-and-drought food crops, plantations, and economic forests	V9
Mosaic herbaceous cover (>50%)/tree and shrub (<50%)	LC9	Biannual or ternary drought and water rotations (with double-season rice) and evergreen fruit tree orchards, subtropical economic forests	V10
		Water	V11
Shrubland	LC10	Ethnic Culture
Grassland	LC11	Buyi	EG1
Tree cover, flooded, saline water	LC12	Dong	EG2
Shrub or herbaceous cover, flooded, fresh/saline/brackish water	LC13	Ge Jia	EG3
Urban areas	LC14	Ge Lao	EG4
Water bodies	LC15	Han	EG5
Soil		Hui	EG6
Alluvial soil	S1	Miao	EG7
Primary soil	S2	She	EG8
Semi-hydromorphic soils	S3	Shui	EG9
Hydromorphic soils	S4	Tujia	EG10
Anthropogenic soil	S5	Yi	EG11
Iron bauxite	S6	Yao	EG12
Urban	S7	Han–minorities integration	EG13
Rock	S8	Multi-minorities integration	EG14

lists 52 variables with their corresponding codes from the five datasets.

ArcGIS 10.8 was employed to create a fishing net grid for analyzing the basic data, addressing the limitations of holistic methods, which often rely heavily on expert judgment to subjectively delineate landscape character areas. After removing invalid values, the entire study area was subdivided into 69,185 1 km × 1 km fishing net grids. To ensure the accuracy of the clustering results, the raster data was vectorized, and the identification tool in ArcGIS 10.8 was used to overlay the vectorized data onto the grid cells. This overlay process allowed for the calculation of the area of each variable within each grid cell. Each grid cell was treated as a landscape sample, and all variables listed in Table 1 were integrated. ArcGIS 10.8 was then used to count the variable values corresponding to each grid cell and to establish a landscape element dataset.

2.3. Identification of Landscape Character Types and Their Areas

Clustering methods are commonly used to identify landscape character types with similar attributes [40,41,42,43,44]. In this study, the K-means algorithm was applied for this purpose. Before performing the clustering, we first normalized the landscape elements dataset and constrained the selection of initial cluster centers to fall within the dataset’s range. This step was taken to minimize the uncertainty introduced by the random initialization of cluster centers. The K-means algorithm was implemented using MATLAB 2024b (MathWorks, Inc. Natick, MA, USA). To select the optimal number of clusters (K), we ran the K-means algorithm across a range of K-values from 10 to 50. Based on the comprehensive evaluation formula for clustering effectiveness (Equation (1)), we assessed the clustering results to determine the optimal K-value. The five K-values with the highest composite scores were chosen, and their corresponding clustering results were visualized to identify the best landscape classification. To visualize the clustering results, we first established a matrix linking type values with grid cells [69,185 × 52] and imported the clustering type values into the corresponding geo-coded grid cells. Finally, the clustering results were visualized using the GIS platform.

Evaluation Values = (CH + SL) − (DB + WCSS)

(1)

Equation (1). Clustering effectiveness evaluation formula based on CH value, SL value, DB value, and WCSS value

Among them, the CH index, proposed by Caliński and Harabasz in 1974 [45], is defined as the ratio of the inter-cluster distance to the intra-cluster distance across all clusters. A higher CH index score indicates better performance of the algorithm on the dataset [46]. SL is the silhouette coefficient, a metric introduced by Peter J. to evaluate clustering effectiveness. It reflects the clarity of the boundary of each cluster, with a larger silhouette coefficient indicating better clustering quality [47]. The DB value refers to the Davies–Bouldin (DB) index, calculated by dividing the sum of the average intra-cluster distances of any two clusters by the distance between their centers, and finding the maximum value [48]. A smaller DB value indicates that the intra-cluster distance is smaller and the inter-cluster distance is larger, signifying better clustering performance. WCSS measures the compactness of clusters by calculating the sum of squared distances between data points and the cluster centers they belong to [49]. A lower WCSS value indicates tighter, more compact clusters. The above four indicators are quantitative measures used to assess the effectiveness of clustering from different perspectives [50]. Similarly, we normalized the values of all four assessment indicators and used the normalized values to compute the composite score.

Building on the selected landscape classification results, the multi-scale segmentation tool in eCognition 10.3 software and the GIS platform were utilized to integrate and refine the visualization map. This process involved delineating landscape character areas using satellite imagery and basic data as references. The variable information within each landscape character area was then recalculated to create the result database. Finally, drawing from the database and field surveys, the landscape characteristics of each type were described.

3. Results

3.1. Results of Identification of Landscape Character Types

We selected the five K-values with the highest composite evaluation scores from the round-robin calculation, in the following order: 48, 50, 46, 44, and 41. The corresponding composite scores were 0.954, 0.929, 0.862, 0.854, and 0.814 (

Table 3. Ranking table of the five K-values with the highest scores in the comprehensive assessment of clustering effect metrics.

Number	CH	CH-Normalized	SL	SL-Normalized	DB	DB-Normalized	WCSS	WCSS-Normalized	Evaluation Values	K
1	2946.043	0.027	0.289	0.974	1.721	0.022	79,559.924	0.026	0.954	48
2	2901.758	0.014	0.291	1.000	1.761	0.085	78,157.091	0.000	0.929	50
3	2981.328	0.038	0.287	0.941	1.745	0.060	81,245.939	0.057	0.862	46
4	3065.122	0.064	0.286	0.926	1.746	0.061	82,201.532	0.074	0.854	44
5	3203.252	0.105	0.282	0.880	1.751	0.070	83,733.228	0.102	0.814	41

). After visualizing and analyzing the clustering results, K = 44 was identified as the optimal clustering parameter, resulting in 44 distinct landscape character types for the region (Figure 4). Among these, the Guizhou section exhibited the highest number of types, while the landscape characteristics of the Hunan, Guizhou, and Yunnan sections were clearly differentiated in both type and visual form (Figure 5).

3.2. Results of the Regional Division of Landscape Character Types

After consolidation and refinement, a total of 37 landscape character areas were delineated, comprising 174 landscape character units (Figure 6). The main landscape character types in the Hunan section of the eastern part of the corridor include types 1, 4, 6, 7, 9, 25, 27, 29, 31, 32, and 34. In the Guizhou section of the central part, the types are 2, 10, 12, 13, 15, 18, 20, 21, 22, 26, 30, 33, 35, and 36. In the Yunnan section of the western part, the types are 3, 5, 14, 16, 19, 23, 24, 28, and 37. The remaining three types, 8, 11, and 17, are found in both the Hunan and Guizhou sections.

The data in

Table 4. Set of key variables for landscape character types in the Miao Frontier Corridor (taken from the result database).

Landscape Character Type	Topography and Geomorphology (m)	Land Cover	Soil	Vegetation	Ethnic Culture	Area (km2) and Proportion
1	E:404/RA:19	LC3, LC1, LC5	S2, S6, S5	V1, V6, V10, V9	EG2, EG13	1049/1.52%
2	E:996/RA:28	LC3, LC4, LC7, LC5, LC1	S2, S6, S5	V7, V9, V6, V1	EG13, EG2, EG7, EG14	2143/3.10%
3	E:2020/RA:26	LC7, LC4	S6, S1, S2	V9, V7, V1	EG11, EG5	1567/2.26%
4	E:225/RA:16	LC3, LC1, LC2, LC14	S6, S5, S2	V10, V6, V1	EG5	1267/1.83%
5	E:1807/RA:28	LC4, LC7, LC11	S6, S1, S2	V7, V9	EG5, EG11	736/1.06%
6	E:277/RA:20	LC5, LC3, LC4, LC1, LC2	S2, S5, S6	V1, V6, V10	EG5, EG7, EG10	1648/2.38%
7	E:390/RA:26	LC5, LC4, LC3, LC1	S6, S2	V6, V10, V1	EG5	805/1.16%
8	E:724/RA:28	LC1, LC3, LC4, LC5, LC7	S6, S5	V6, V9, V1	EG13	1238/1.79%
9	E:794/RA:31	LC5, LC7, LC4, LC3	S6, S1, S5	V7, V1, V6, V10	EG5, EG12, EG10, EG13	1280/1.85%
10	E:1208/RA:27	LC3, LC4, LC1, LC5	S2, S6	V7, V6, V9, V1	EG14, EG13	1650/2.38%
11	E:744/RA:25	LC3, LC5, LC1, LC7, LC4	S2, S6, S5	V6, V1, V9, V7	EG7	2813/4.07%
12	E:1198/RA:26	LC1, LC5, LC3, LC4, LC7, LC6	S6, S2, S5	V6, V9, V7, V1	EG1, EG13	3963/5.73%
13	E:1239/RA:28	LC4, LC1, LC3, LC7	S6, S2, S5	V9, V6, V7	EG13, EG9, EG1	2149/3.11%
14	E:2076/RA:25	LC7, LC4, LC11	S1, S6, S2	V9, V7, V6, V1	EG13, EG7, EG9, EG3	2010/2.91%
15	E:1311/RA:22	LC3, LC1, LC4	S2, S6, S5	V9, V6, V7	EG13, EG5, EG7	1338/1.93%
16	E:2098/RA:22	LC7, LC4, LC1, LC11, LC8	S6	V1, V9, V7, V6	EG7	2558/3.70%
17	E:666/RA:28	LC5, LC3, LC4, LC1, LC7	S6, S2	V1, V6, V9	EG13, EG12, EG5, EG7, EG3	2451/3.54%
18	E:989/RA:27	LC5, LC1, LC3, LC6	S2, S6, S5	V1, V6, V9	EG13, EG7, EG14	1197/1.73%
19	E:1981/RA:25	LC7, LC4, LC1	S6, S2, S1	V1, V9, V7, V8	EG11, EG5, EG6	2315/3.35%
20	E:1264/RA:24	LC3, LC1, LC4, LC7, LC2	S6, S2, S5	V6, V9	EG13, EG5, EG1, EG4	1314/1.90%
21	E:1290/RA:21	LC3, LC1, LC5, LC4, LC6	S2, S6, S5	V6, V1, V9	EG13, EG1, EG14	1849/2.67%
22	E:976/RA:27	LC5, LC3, LC6, LC1	S2, S6, S5	V6, V1, V9	EG13, EG1	1899/2.75%
23	E:1734/RA:28	LC4, LC7, LC11	S6, S2, S1	V7, V9, V1	EG5, EG13	1246/1.80%
24	E:1931/RA:16	LC14, LC1, LC2, LC4	S5, S6	V9, V7	EG7, EG5, EG11	1661/2.40%
25	E:307/RA:25	LC5, LC3, LC1, LC4	S2, S6	V6, V1, V10	EG10, EG5	2713/3.92%
26	E:1192/RA:30	LC5, LC1, LC6, LC3	S6, S2, S1, S5	V6, V9, V7, V4	EG7, EG1	1788/2.58%
27	E:404/RA:26	LC3, LC5, LC7	S6	V1, V6, V7, V10	EG5, EG12	1607/2.32%
28	E:2054/RA:21	LC7, LC4, LC11, LC1	S6, S1	V1, V9, V7, V6	EG5, EG13, EG6	3448/4.98%
29	E:403/RA:28	LC5, LC4, LC3, LC1	S6	V1, V6, V10	EG5	3790/5.48%
30	E:860/RA:27	LC5, LC3, LC1, LC6, LC7	S6, S2, S5	V6, V9, V1	EG2, EG8, EG7, EG13	1661/2.40%
31	E:585/RA:29	LC5, LC3	S6	V1, V6	EG2, EG14	2003/2.89%
32	E:542/RA:27	LC3, LC5, LC7, LC1	S6	V1, V7, V10	EG2	1330/1.92%
33	E:947/RA:30	LC5, LC3, LC7, LC6	S6, S2, S5	V6, V9, V1, V4, V7	EG7, EG13, EG10, EG4	1950/2.82%
34	E:393/RA:29	LC5, LC4, LC1	S6, S2	V1, V6, V10	EG10, EG5	1451/2.10%
35	E:1291/RA:21	LC1, LC3, LC4, LC10	S2, S5, S6	V6, V9	EG13, EG1	1185/1.71%
36	E:1169/RA:21	LC1, LC3, LC14, LC5, LC4	S2, S6, S5	V6, V9, V1	EG1, EG7	2500/3.61%
37	E:1556/RA:27	LC4, LC7, LC3, LC1	S6, S2, S1	V7, V9, V1	EG13, EG7	1614/2.33%

show that most landscape character types occupy an area of 1–5%. Among them, type 12 has the largest area, covering 3973 km², which accounts for 5.73% of the total area. It has an average elevation of 1198 m and a relief amplitude of 26 m, located in Guanling, Zhenning, and other areas in Guizhou Province. Type 5 has the smallest area, covering 736 km², or 1.06% of the total area. It has an average elevation of 1807 m and a relief amplitude of 28 m, primarily located in the Panxian Special Zone of Guizhou Province. Type 12 encompasses the most diverse land cover types (LC1, LC5, LC3, LC4, LC7, LC6), while type 17 is characterized by the richest traditional village cultural genealogy types (TSCG7, TSCG14, TSCG5, TSCG8, TSCG3), found in the eastern regions of Hunan and Guizhou Provinces. Most landscape character types are dominated by soil types S2 and S6 and vegetation types V1, V6, V7, and V9.

Regarding the distribution of ethnic landscape character types, the landscape characters of the ethnic groups in the Miao Frontier Corridor are diverse. Among the major ethnic groups, the Bouyei have six types of landscape character (types 12, 13, 20, 21, 26, and 36), with an altitude of 1169–1290 m. The main landscape character is farmland located in river valleys, hillsides, hills, or gentle areas of karst mountains, surrounded by a large amount of mixed vegetation.

The Dong and Tujia ethnic groups have four (types 2, 30, 31, and 32) and five (types 6, 9, 25, 33, and 34) landscape character types, respectively. The Dong people live in an area with an altitude of 542 m to 996 m, and the main landscape character is villages distributed along rivers and terraced fields on the slopes on both sides of the rivers.

The Han, Miao, Han–minorities integration have 16 types (types 3, 4, 5, 6, 7, 9, 15, 17, 19, 20, 23, 24, 25, 27, 28, 29), 13 types (types 2, 6, 11, 14, 15, 16, 18, 24, 26, 30, 33, 36, 37), and 19 types (types 1, 2, 8, 9, 10, 12, 13, 14, 15, 17, 18, 20, 21, 22, 23, 28, 33, 35, 37) of landscape character types. These three ethnic groups are distributed throughout the region, and the distribution of landscape characters is not uniform. The altitude range of the landscape character area where the Han people live is 225–2054 m, and the relatively prominent landscape character is the plain or hilly agricultural landscape.

The altitude range of the landscape character area where the Miao people live is 227–2098 m, and the relatively prominent landscape character is the hilly and karst mountainous landscape accompanied by terraced fields or plain farmland.

The landscape character area where the Han–minorities integration ranges from 404 m to 2054 m above altitude, with relatively prominent landscape character of mountainous terraced fields and villages surrounded by mixed vegetation.

The She ethnic group has only one type of landscape (type 30), with an average altitude of 860 m. The main landscape character is large areas of tree-shaped mountains, with scattered farmland and villages at the foot of the mountains.

The Tujia live in an area with an altitude range of 277–794 m, and the main landscape character is villages located in gentle areas in the mountains and terraced fields on gentle slopes.

The Yi have four types (types 3, 5, 19, and 24), with altitudes between 1807 m to 2020 m. The main landscape character of the Yi ethnic group’s location is plateau agricultural landscapes and high-altitude mountain terraced landscapes, covering farmland and coniferous forests.

There are three types of landscape characters (types 9, 17, and 27) among the Yao people. The altitude ranges from 404 m to 794 m. The main landscape characters are traditional settlements on both sides of mountain rivers, with terraced fields on the lower slopes surrounding the settlements.

There are five types of multi-minorities integration communities (types 2, 10, 25, 33, and 34) with landscape characters, at altitudes ranging from 307 m to 1208 m above sea level. The main landscape characteristics of these areas are karst mountains or low-altitude hills, with settlements surrounded by gentle farmland or terraced fields located at the foot of the mountains.

Based on field surveys and satellite images, we recorded the key landscape characteristics of each landscape character zone (Figure 7). After analysis, these characteristics can be grouped into six major categories: karst landscapes, subalpine terraced landscapes, hilly-river valley agricultural landscapes, urban–suburban transition zone landscapes, alpine forest–grassland landscapes, and a number of unique landscapes that cannot be classified. Among these, the main features of karst landscapes include karst peaks, canyons, caves, waterfalls, and land desertification. The key features of subalpine terraced landscapes are continuous terraced fields on mountain slopes, ridge roads, and villages arranged in a comb-like or tree-like pattern. Hilly river valley agricultural landscapes are characterized by interwoven alluvial plains and low hills, with large areas dedicated to crop rotation, including rapeseed, rice, and vegetables. Settlements are typically aligned along rivers and roads, resembling a string of beads. The main landscape features of urban–suburban transition zones consist of alluvial plains or dissolution basins, with urban core areas at the center, surrounded by hills and forest belts. Finally, the alpine forest–grassland landscape is defined by large mountains, with slopes covered in a mix of coniferous and broadleaf forests, low shrubs, and settlements generally located on gentle slopes or in valleys.

The following are descriptions of the key landscape characteristics for each landscape character sub-area:

Type 1: A low-altitude hilly area featuring large, irregular, and continuous terraces surrounding villages on the eastern slopes, with plain agricultural landscapes on the low-altitude terraces along both sides of the river. To the west, gently sloping areas between the hills are used for rapeseed cultivation.

Type 2: A large settlement zone along the river, characterized by small undulating hills, rolling mountain ranges, and continuous hilly lines, with a small amount of irrigated farmland. This area is predominantly home to traditional settlements of the Miao, Dong, and Han–minorities integration.

Type 3: A mixed area of high-elevation hills and small undulating mesas, with massive ridges covered in dense forests and abundant natural vegetation. Farmland in the valley is neatly arranged along the roadsides in a comb-like pattern, while terraced fields and tea plantations cover the nearby hills. There are three traditional settlements of the Yi.

Type 4: Cities and villages are built on the alluvial plains near the Yuan River basin, surrounded by small patches of farmland. The riverbanks feature gentle slopes, and low-elevation hills with broad-leaved vegetation and small undulating mountains.

Type 5: A karst landscape combining high-elevation hills and small undulating mesas. The comb-like slopes have been reclaimed into numerous elongated terraces, while the upper and middle sections are covered with abundant natural vegetation. The lower slopes feature gently sloping farmland, interspersed with dense scrub and mixed vegetation. There are two traditional Han settlements.

Type 6: A mixed area of low-elevation plains and hills, where large rapeseed fields cover the plains, with rivers running through and villages scattered among the farmlands. To the north are meandering, densely vegetated, small rolling hills, home to three traditional Han settlements.

Type 7: A moderately undulating mid-hill area surrounding the city, with slopes covered in dense mixed forests and a few farmlands at the foot. Settlements are located on the hillside, surrounded by dense broad-leaved vegetation and bamboo forests.

Type 8: A karst landscape featuring wide gorges and high peaks. The slopes along both sides of the river form agricultural landscapes, with narrow roads cutting through the farmland. Some slopes exhibit desertification, and farmland is set around the mountains. This area is home to two traditional settlements of Han–minorities integration and a Red Chinese cultural site.

Type 9: A small, undulating low-mountain area with irrigated farmland along the mountain ridges, where a continuous north–south belt of farmland stretches through the region. Traditional Han settlements dominate the area.

Type 10: A valley area traversed by the Beipan River, with high bridges crossing the river. The region is dominated by karst landscapes, with gorges and waterfalls, and some mountains show rocky desertification. Slopes are covered with grass and broad-leaved vegetation, and large areas of photovoltaic panels cover the hills in the central region. The ruins of the old Tea–Horse Road are also found here. Integrated traditional settlements are prevalent.

Type 11: The area is home to numerous traditional Miao settlements, with small undulating low hills surrounded by patches of rain-fed farmland and a few terraces on the gentle hillsides.

Type 12: A traditional settlement area of the Buyi, featuring large grasslands on the gentle slopes of high-elevation hills in the west, with rivers running through the valleys and small patches of irrigated farmland on both sides. To the south, there is a plain amid the mountains, with slight undulations, small towns, and terraced rice paddies.

Type 13: A strip of mid-altitude hills interspersed with comb-like mountain ranges, the slopes of which are covered with dense evergreen coniferous forests and temperate meadows, with village clusters at the foot of the slopes. The hilly belt is interspersed with a small amount of rain-fed farmland. Traditional settlements are primarily of the Buyi, with a small presence of integrated groups.

Type 14: An agricultural landscape with slopes covered with continuous terraces and small settlement belts at the bottom of the slopes, with a traditional Shui settlement in its southern part.

Type 15: Urban fringe plains with distinct contours where they meet the mountains, covered by a mix of farmland and natural vegetation.

Type 16: Comb-shaped mesas and hills, partly covered with farmland, mixed natural vegetation, and low shrubs or meadows, with wind turbines on the slope tops. Scattered karstic rock formations and rock forests are present.

Type 17: Ridge valleys and dense forests in the middle and lower elevations. Four traditional Yao settlements are spread along the riverbanks, with rice terraces on the slopes. A few ruins of ancient border walls, watchtowers, and other military defense structures remain.

Type 18: Mountains covered with shrubs and broad-leaved evergreen forests, extending into hilly terrain with terraced fields at the foot. Karstic conical peak clusters and pagoda-shaped maple forests are present.

Type 19: Alpine terraced landscapes in the north, with many mountains having been reclaimed as terraces from the peaks to the bases. In the south, a vast plain agricultural landscape is found, with one traditional settlement of Hui and one of Yi. A large reservoir is located in the valley.

Type 20: A field scape with traditional settlements in the basin, characterized by scaly hills covered with abundant mixed natural vegetation.

Type 21: A karst landscape area with many mountains shaped by erosion, resulting in caves and waterfalls that have been developed as scenic spots. A mixture of artificial and natural landscapes is present, with the Hongfeng Lake reservoir in the valley. Many traditional Buyi settlements are found in the northeast.

Type 22: Mountains bordered by hills covered with dense broad-leaved evergreen forests, with three traditional Buyi settlements located in the gentle areas surrounding the mountains.

Type 23: A karst landscape area affected by human interference, where some mountain ranges show karstic rock desertification with bare rocks. Villages and farmlands are situated in the northern hilly areas.

Type 24: A high-altitude urban landscape surrounded by plains, which cover vast areas of agricultural land.

Type 25: Ridge valleys and dense forests in low-elevation areas, with meandering rivers running through them. The average elevation is 307 m above sea level, with traditional Tujia settlements scattered near roads in the northeast. The plains along the river in the southwest also feature numerous villages and farmlands.

Type 26: Comb-like ridges neatly aligned and intersected with hills in the north, where traditional settlements of Miao and Buyi are built on the hillsides, surrounded by terraced fields.

Type 27: Continuous hills covered with dense broad-leaved forests in lower-altitude areas, with villages scattered near roads and meandering rivers. Terraced fields follow the ridges and valleys, with traditional Yao settlements clustered in this area.

Type 28: A karst landscape area with exposed rocks on mountain slopes, scattered karstic rock formations, and stone forests. In the west, large areas of farmland are located on the plains, interspersed with mountains and hills. Reservoirs have been built for irrigation, and traditional settlements with both Han and Han–minorities integration are present.

Type 29: A mixture of comb-like and treelike mountain ranges with dense forests on the slopes, where villages are built on gentle valley areas and on alluvial plains along the rivers. It is home to a large number of traditional Han settlements.

Type 30: The eastern part is characterized by treelike mountains covered with dense forests, with roads built on mountain ridges and villages following the veins of the mountains. The west features karst landscapes with caves and gorges. Scaly hills meet alluvial plains on both sides of the river, forming distinct boundaries and a ribbon of farmland.

Type 31: Meandering valleys covered with dense broadleaf forests, where the slopes are terraced, rivers run through the valleys, and villages are located along the rivers. Sixteen traditional Dong settlements are clustered in the south.

Type 32: A vast mountainous area with dense vegetation on the slopes, through which the Yuan River and its tributaries flow, with cities and villages on both sides of the river.

Type 33: A mountainous area in the south, where many traditional Miao settlements are clustered, and farmland is irregularly distributed in the valleys. The northern part is hilly, with villages scattered along roads and rivers in a tree-like pattern.

Type 34: Crisscrossing mountains covered with dense broadleaf forests, with villages along rivers and roads, and three traditional Tujia settlements.

Type 35: Mountainous plains surrounding small towns, covered with farmland, and interspersed with a few medium-altitude hills. Villages are scattered across the plains, with many traditional Buyi settlements and fewer Han–minorities integrated settlements.

Type 36: A Karst basin and mid-altitude hills urban landscape, with a small amount of farmland and a hilly zone around the city. The slightly steeper basin edge features peaks and forests, while the flat base is covered with residual laterite soil.

Type 37: A Karst landscape area, with exposed rocks and rocky forests on the hills, and a large basin of farmland. There are two integrated traditional settlements and one Miao settlement.

For detailed proportions of each variable for each type, please refer to Appendix A.

4. Discussion

4.1. Differences in Landscape Character Caused by Natural Conditions

The Miao Frontier Corridor connects China’s three major geographical terraces and spans a wide range of altitudes, characterized by complex terrain and landforms. The results indicate that the main land cover in areas with high-altitude (1500–3500 m) landscape character types (types 3, 5, 14, 16, 19, 23, 24, 28, and 37) is mainly evergreen coniferous forest and mixed vegetation (LC7 and LC4), while the main land cover in areas with low-altitude (less than 500 m) landscape character types (types 1, 4, 6, 7, 25, 27, 29, and 34) is mosaic farmland and evergreen broadleaf forest (LC3 and LC5). Human intervention is more pronounced in low-altitude regions than in high-altitude areas [51], leading to a larger area of artificially planted vegetation [52,53,54], consequently, more farmland in these regions [55,56]. Additionally, broadleaf forests generally thrive in low-altitude regions, while coniferous forests are more common at higher altitudes [57,58,59].

From the perspective of relief amplitude, the average relief amplitude in the Guizhou section is 26.74 m, higher than that of the Yunnan section (23.17 m) and the Hunan section (24.55 m). Meanwhile, the average area of landscape character areas in the Guizhou section is 1632.74 km², smaller than that of the Yunnan section (1824.62 km²) and the Hunan section (1771.28 km²). This suggests that an increase in relief amplitude contributes to greater landscape fragmentation, as steeper mountainous areas reduce the availability of arable land and limit human activity [60,61]. As a result, the landscape becomes fragmented into smaller units, enhancing landscape diversity [62]. In contrast, gentler river valleys or plains tend to have more homogeneous landscapes [61,63]. These findings highlight the significant influence of natural conditions, such as altitude and relief amplitude, on the overall landscape character of the Miao Frontier Corridor.

4.2. Differences in Landscape Character Caused by Historical Institutions

The formation of landscapes is deeply intertwined with human culture. Landscapes are undoubtedly the result of the dynamic interaction between natural and cultural factors, and this concept has gained multidisciplinary and comprehensive significance [14]. Historical institutions play a crucial role in shaping the landscape character of corridors. Beginning in the Ming Dynasty, large-scale migration of Han Chinese from the Central Plains to the southwest took place through the Miao Frontier Corridor. Research indicates that landscape character areas with a significant presence of Han Chinese cultural units are primarily located along river valleys and plains, such as types 4, 6, and 15. In contrast, areas dominated by ethnic minority cultural units tend to be situated in mountainous and high-altitude regions, such as types 12, 24, and 26. These areas have developed distinct landscape characters over time due to the long-standing practices of different ethnic groups. This is because the existence of the government and military during the Ming and Qing dynasties introduced various institutions, such as the “expulsion of the minorities for land development” institution in the Ming Dynasty, and the “replacing local chieftains with imperial officials” institution during the Qing Dynasty [64,65]. The implementation of these institutions led to the Han Chinese encroaching on areas with more favorable farming conditions, while ethnic minorities were pushed to marginal lands. This displacement forced many ethnic minorities into mountainous areas, where they adapted their lifestyles and production methods to the local environment based on the natural conditions. These adaptations, in turn, influenced the local natural landscape. The findings suggest that historical systems have indeed played a significant role in shaping the landscape character of the Miao Frontier Corridor.

Additionally, the establishment of the Miao Frontier Corridor provided a vital communication channel between ethnic groups, facilitating trade, cultural exchanges, and other interactions within the corridor and its surrounding regions. In the Hunan section of the corridor adjacent to the Central Plains, Han Chinese cultural units were prevalent in landscape character types 4, 6, 7, 9, and 17, accounting for 81.8% of the total landscape character types in this region. In the Guizhou and Yunnan sections, the presence of Han Chinese cultural units has decreased, appearing only in types 15 and 20. However, cultural units blending Han–minorities integration are abundant in types 2, 13, 14, 15, 18, 20, 21, 22, 23, 28, 33, and 35. The deployment of the military changed the ethnic composition of many traditional settlements, transforming them into mixed settlements. At the same time, in landscape character areas where Han–minorities integration cultures mix, agricultural landscapes account for a significant proportion, such as types 1, 4, and 20. This suggests that, over the 700 years since the establishment of the Miao Frontier Corridor, Han culture spread along this ancient postal route to the Yunnan–Guizhou Plateau, facilitating cultural and technological exchanges between Han commoners and indigenous peoples. This exchange led to the formation of a small portion of traditional settlements characterized by Han–minorities integration, while also transforming local agricultural landscapes and environments. However, a more profound impact stemmed from the Ming Dynasty’s military garrison institution, which led to the establishment of numerous “military settlements” within the Miao Frontier Corridor [66]. At the same time, the forced introduction of Han Chinese farming techniques significantly altered the lifestyles and land use practices of the indigenous peoples, thereby having a profound impact on the overall land use and landscape of the Miao border corridor.

4.3. Revelation for the Application of LCA in Multi-Ethnic Areas

This study identified the landscape character of the multi-ethnic regions of the Miao ethnic border corridor by integrating both natural and cultural elements. The results demonstrate that utilizing ethnic culture as a cultural element helps to reveal the diverse landscape characteristics of different ethnic groups, as well as the variations in landscape features between them. Secondly, the cost allocation method employed to delineate the extent of ethnic group cultural influence in geographical space is both objective and reliable. The study uses cost-allocation tools to analyze the influence range of ethnic group culture during its dissemination and diffusion. This approach is akin to the Tyson polygon principle. In regions where consistent historical, cultural, and socio-economic data are lacking, the quantitative method proposed in this study offers a means to gather relevant data, thus overcoming the limitation of point data, which often cannot be used as clustering variables in parameterization methods. Finally, area-based statistical variables prove more effective than the traditional 0/1 classification in retaining landscape details. The advantage of this method is that it can convert nominal variables into continuous numerical variables, while allowing each landscape sample to contain multiple variables in a single landscape element. As a result, it reduces the impact of grid resolution lower than the base datasets.

4.4. Limitations and Outlook

The study does have certain limitations. First, as additional settlements are discovered, the list of traditional settlements will change, which in turn will alter the data on cultural elements, making the results non-unique. As appropriate regional data continue to develop, the accuracy of classification results in future studies can be further improved. Second, the K-means algorithm used in this study has its limitations, including sensitivity to initial cluster centers and the potential for local convergence, which may lead to imperfect clustering outcomes. To enhance accuracy, alternative models in MATLAB 2024b and Python 3.13 could be employed, with the most suitable one selected through comparison. Finally, due to the challenge of obtaining consistent basic data across the entire region, the landscape character elements used in this study are not exhaustive. However, as data sources become more consistent and relevant stakeholders are involved, a more comprehensive landscape classification will be possible in the future. While this study does have limitations in methodology and data processing, these should not detract from its scientific value. Rather, they highlight opportunities for methodological advancements in future research.

5. Conclusions

Based on the incorporation of ethnic cultural variables, this paper identifies the landscape characteristics of the multi-ethnic areas of the Miao Frontier Corridor and generates a database on a regional scale. We have improved the variable statistical method in the parameterization process and proposed a method for quantifying cultural elements. In addition, the generated results database provides an important foundation for the overall protection, planning, and management of the Miao Frontier Corridor landscape. It can also serve as a basis for more detailed research on landscape characteristics at the local scale and research on the living environment and socio-economic development models of ethnic minorities. With the improvement of the accuracy of basic data in the future, the accuracy and amount of information in the landscape results database will also be improved. Due to the flexibility of this research method in data input and algorithms, our method can be widely applied to multi-ethnic areas in China and can also provide a reference for LCA in other similar areas.