Ecosystem Services Value Realization and Ecological Industry Design in Scenic Areas of Karst in South China

Abstract

Ecosystem services (ESs) value realization and ecological industry (eco-industry) are essential components of regional development. Due to the vulnerability and non-renewability of natural landscape resources in Karst areas, once unreasonable resource development takes place, it is easy to pose threats and causes damage to its ecosystem. This article selects the grain data correction equivalent factor coefficients in Guizhou Province, China, and establishes accounting indicators for Karst scenic areas. It is found that the total economic value of ESs is as follows: Shanmuhe Scenic Area (CNY 5096.3 thousand) > DaXiaoQiKong Scenic Area (CNY 2778.6 thousand) > Huangguoshu Scenic Area (CNY 2130.7 thousand). Among them, the value of regulating services plays a dominant role in the composition of ESs, and the value of forests accounts for the largest proportion. Through web crawlers, tourism data can be acquired, and the Product–Experience–Feedback–Improvement (PEFI) model can be applied to reveal that tourists have a predominantly positive perception of Karst scenic areas. This indicates that karst landscape resources are deeply loved by domestic and foreign tourists, especially mountain, water and forest landscapes. Based on the results of the ES value accounting of the scenic area and the external perception data of tourists towards the scenic area, the eco-industry spatial layout development plan is formulated. According to local conditions, the development, construction, and protection of the scenic area are carried out, jointly promoting the realization of the ecological product value (EPV) of the Karst scenic area, to determine the optimal development direction of the eco-industry, and to promote the coordinated development of ecological resources and assets.

1. Introduction

The 2030 Agenda for Sustainable Development, adopted at the 70th session of the United Nations General Assembly, marks the beginning of a new era for humanity to move toward a sustainable society [1]. Ecosystem services (ESs) is a general term for all goods and services provided directly or indirectly by natural and non-natural ecosystems to meet human survival and development needs [2,3,4,5,6]. Ecological products (eco-products) include products that are based on natural resources and possess properties related to ecological protection, environmental friendliness, and unique ecological value, such as ecological agricultural products, ecological tourism, etc. The main difference between eco-products and ESs lies in their conceptual attributes. Therefore, ecological product value (EPV) can be regarded as being the same as ecological services value (ESV) when calculating the value [7]. Thus eco-products are in line with ESs, but the difference is that Chinese characteristics are integrated into eco-products [8]. In October 2022, the 20th National Congress of the Communist Party of China proposed the establishment of a mechanism for realizing the value of eco-products. This proposal aimed to create a favorable ecological environment as a strong support for sustainable and healthy economic and social development, promoting the coordinated development of landscape resources and ecological assets.

The ecological industry (eco-industry) comprises the reintegration of resources—that is, the transformation of resource clusters into industrial chains [9]. However, the current scenic resources have not been effectively transformed into high-quality eco-products and public services, and the EPV has not been fully manifested and quantified. With the prominence of social and environmental problems, ecological value accounting has great practical significance in today’s society. Under the current scenario of severe environmental pollution, it is of great significance to find a method that can accurately and scientifically calculate environmental value [10]. The unified, measurable, and computable value standards for eco-products help promote the formation of green development and lifestyle [11], providing a quantitative reference for the formation of a spatial pattern and industrial structure that saves resources and protects the environment. The logical relationship between eco-product value accounting and the eco-product value realization mechanism is that if there is only the former without the latter, eco-product value accounting will remain in the paper capital stage [12]. The realization of EPV can promote the preservation, appreciation, improvement, and sharing of EPV [13].

Landscapes are a product of the combined actions of the ecological environment, and assessing their ecological quality is important for the sustainable development of the environment [14,15]. A landscape pattern is defined as the spatial heterogeneity found where environmental factors are unevenly distributed [16]. Understanding landscapes as a socio-ecological system where systematic interactions occur among diverse ecosystems and human society is necessary for sustainable landscape and resource management [17]. Landscape perception is the process of human cognition, understanding, and evaluation of the surrounding environment. The theories and methods of landsenses ecology can help to guide the public to understand the scientific value connotations and diverse forms of eco-products. [18]. In a policy context, the perceived distinctiveness of landscapes can contribute to decision making on how to further develop landscapes while maintaining their particularities [19]. Eco-industry spatial pattern planning refers to the formulation of a reasonable industrial layout and regional planning based on factors such as regional characteristics, resource distribution, and ecological demands [20].

Karst landscapes are special landforms formed by geological processes and feature unique natural beauty and abundant ecosystems [21]. These landscapes attract a large number of tourists and have become an important tourism resource. For example, the unique Cappadocia Karst landscape in Turkey is characterized by its ravines, peculiar formations of stone columns and valleys, semi-cave dwellings with their artificial rock cave remains [22], and hot air balloon “house tours”. Florida, with its unique underground rivers, caves, and limestone peaks, has gained widespread global recognition for the distinctiveness and diversity of its Karst landscapes [23]. As a typical region, Karst scenic areas have high ecological resource potential due to their unique geological formations and natural landscapes. As the best example of the same type of Karst landforms in the world, the Karst landscape in South China has unique and typical geographical landscape features. Its unique environment and ecosystem provide high-quality landscape resources and represent one of the most fragile ecosystems on Earth, urgently requiring human protection and inheritance, as well as effective governance and development [24]. As a typical region, the unique geological form and natural landscape of Karst scenic areas endow them with a high potential for eco-product resources. The achievement of eco-product value and the growth of the eco-industry can boost the economic advancement of Karst areas [25]. By scientifically planning the spatial pattern of eco-industries, these resources can be reasonably utilized and protected, effectively enhancing the eco-product output capacity and economic benefits of Karst scenic areas.

According to the actual situation, in which the value realization mechanism of eco-products is not perfect, a green eco-industry circulation system has not yet been formed in the Karst scenic areas in South China, and the organic integration of the eco-industrial environment and the development of characteristic industries is not high. Front-end scientific issues related to the regulation strategy and innovation regarding the eco-industry formation mechanism, as well as the planning and design of eco-industry regions in the Karst scenic area, are thus addressed in this study. Combining the international commitments to ecosystem restoration, eco-product value realization, and eco-industry design in scenic areas, this article adopts the technical route of eco-product value accounting and eco-industry design, as well as the equivalent factor method after validating accounting indicators, web text data mining, and qualitative analysis methods as research methods. By elucidating the value endowment of regional resources, revealing the value distribution pattern of “lucid waters and lush mountains”, we clarify the path to realizing the value of eco-products, promoting the formation mechanism of eco-industry, and constructing an eco-industry development model with the deep integration of multiple industries in Karst scenic areas, providing a scientific basis for the formation mechanism and design of the eco-industry in scenic areas.

The common factors that exist in Karst scenic areas in China are as follows: rich ecological landscape resources, especially prominent forest resources; the historical and cultural heritage is profound and has not been fully developed and utilized, making it difficult for tourists to fully appreciate the cultural heritage of this scenic area; and the eco-industry has rich linkage in various forms, but tourism development and construction projects are not coordinated with the overall environment. In response to the above issues, there is an urgent need to examine unique landscapes and resources, intensify the research on the special characteristics of Karst eco-industries, and innovate the development format of characteristic ecotourism. Therefore, this paper selects South China Karst scenic area as the research object; uses the theory of spatial heterogeneity [26] and landscape pattern [27]; combines remote sensing and geographic information system technology; constructs the spatial pattern of eco-industry landscape; and explores the stability of the ecosystem of Karst scenic areas, the development direction of eco-industry, and the overall development planning and other internal characteristics.

This study aims to (1) integrate the ecological characteristics of sensitivity, fragility, vulnerability, and natural regeneration ability in Karst areas and select suitable eco-product value-accounting indicators for the scenic areas in southern China’s Karst landscape. (2) By collecting network text data, we gain insights into tourists’ preferences and interests in scenic areas, and reveal the development trends and regional differences of scenic area industries. We also propose regulatory strategies for the realization mechanism of EPV based on the scenic area, namely the Product–Experience–Feedback–Improvement (PEFI) model, in order to provide a reference for the development of ecological tourism products and services. (3) The characteristics of the scenic area itself are not fully explored, and the differences cannot be highlighted. By implementing a staggered development strategy, the formation of the entire scenic area and the coordinated development of the eco-industry are promoted. Realizing these goals can enable governments and policy makers to design targeted policies and planning schemes, providing a reference for ecological restoration and ecological civilization construction.

2. Materials and Methods

2.1. Study Area

Guizhou is located in the eastern part of China’s Yunnan–Kweichow Plateau, which is the most developed Karst region in China. The unique mountains, beautiful water resources, exquisite rock formations, and strange caves, with their multitude of shapes and unique characteristics, are interwoven with the rich, interesting, and ancient ethnic customs, creating a perfect fusion of natural and human landscapes. The selected study area with its unique natural landscapes and ecosystems, has had multifaceted impacts on economic and social development (Figure 1), representing the basic characteristics of the Karst landscape in South China.

• Libo Zhangjiang National Scenic Area, Da Qi Kong Scenic Area—Xiao Qi Kong Scenic Area (DaXiaoQiKong Scenic Area)

The DaXiaoQiKong Scenic Area is located within Libo County, Qiannan Buyi and Miao Autonomous Prefecture, Southern Guizhou Province, China (N 25°07′–N 25°39′, E 107°37′–E 108°18′). It is predominantly known for its Karst forest landscapes. There are many types of ecological landscape resources in this area, but the characteristics of the eco-products are not obvious, and the phenomenon of widespread regionalization is severe.

2.

Wuyang River National Scenic Area, Yuntai Mountain Scenic Area, Shanmu River Scenic Area, and Water Source Ecological Reserve (Shanmu River Scenic Area)

The Shanmu River Scenic Area is located in Shibing County, Guizhou Province, in the southwest of China (N 26°57′–N 27°17′, E 107°41′–E 108°26′). It is rich in natural landscape resources with high ecological value, and its cultural resources are also abundant, but the social attributes and sharing functions of cultural resources have not been fully demonstrated. The unscientific development and utilization of this area have led to the idle use of traditional cultural resources and the waste of modern cultural resources, resulting in a situation where a large number of cultural resources cannot be transformed into cultural products.

3.

Huangguoshu National Waterfalls Scenic Area (Huangguoshu Scenic Area)

The Huangguoshu Scenic Area is located in the southwest of Anshun City, Guizhou Province, in the southwest of China (N 25°53′–N 26°02′, E 105°35′–E 105°42′) and belongs to the river type scenic area. It has an extremely high geological structure and retains rare natural Karst landscapes and beautiful natural environments, with extremely high aesthetic, ecological, and scientific value.

2.2. Research Methods

2.2.1. Spatial Analysis Method

In order to understand the current status and distribution of land use and ecosystem types in the research area, and to more accurately use the equivalent factor method to calculate the EPV, there is a need to reveal the spatial and temporal changes in EPV based on land use, and to study the land use data of the research area through remote sensing interpretation. In order to obtain remote sensing interpretation data on land use types, areas, and land use patterns within the study area, we comprehensively collected satellite remote sensing images from the American Landsat-8 OLI, Landsat TM/ETM+, Tianditu satellite images, DEM data, and land use data from 2021 to 2024. We selected the Landsat remote sensing image maps of the DaXiaoQiKong Scenic Area, Shanmu River Scenic Area, and Huangguoshu Scenic Area in 2021. We used ENVI 5.2 and ArcGIS 10.2 software to crop the images, performed the radiometric calibration and atmospheric correction of the remote sensing images and conducted supervised classification to extract features such as tree forests, shrubs, water, grassland, cropland, wetland, etc. from the images. After classification and post-processing, accuracy verification was carried out, and combined with field investigation data and socio-economic data, the land use type and area data of the study area were obtained. Specific values were calculated and presented in a chart for analysis (

Table 1. Land use planning regulation table for the study area in 2021.

DaXiaoQiKong Scenic Area
Data Acquisition	Land Use Type	Current Area (km2)	Spatial Distribution of Land Use Types
Time: 11–16 December 2022; Venue: DaXiaoQiKong Scenic Area, Zhangjiang Scenic Area Management Office in Libo County, China, Cultural and Tourism Bureau in Libo County, etc.	Tree forest	21.42
	Shrubs	17.34
	Grassland	15.74
	Cropland	7.86
	Water	10.64
	Wetlands	8.86
Shanmu River Scenic Area
Data acquisition	Land use type	Current area (km2)	Spatial distribution of land use types
Time: 24–30 August 2022; 4–10 December 2022; Venue: Shanmu River Scenic Area; Shibing Karst World Heritage and Scenic Area Management Bureau: Guizhou Bashan Bingshui Tourism Development Co., Ltd.; Shibing County Cultural, Sports, Radio; Television and Tourism Bureau/Shibing County Chengguan Town Music Fountain Tourist Service Center; etc.	Tree forest	163.422
	Shrubs	18.987
	Grassland	3.403
	Cropland	15.436
	Water	4.151
	Wetlands	1.415
Huangguoshu Scenic Area
Data acquisition	Land use type	Current area (km2)	Spatial distribution of land use types
Time: 8–15 September 2023; Venue: Huangguoshu Scenic Area Management Committee, Huangguoshu Tourist Service Center, Huangguoshu Scenic Area, Dishuitan Waterfall, Huangguo Fruits Base, etc.	Tree forest	33.815
	Shrubs	29.062
	Grassland	8.784
	Cropland	31.998
	Water	3.105
	Wetlands	0.705

).

2.2.2. Equivalent Factor Method

The equivalent factor method is used to construct the value of various service functions of different types of ecosystems with quantifiable standards and evaluate them in combination with the distribution area of the ecosystem. This method uses less data, is relatively intuitive and easy to use, and is suitable for the evaluation of the value of ecosystem services at regional and global scales. Constanza et al. (1998) determined the unit prices of 17 ESs for 16 types of ecosystems worldwide [2]. Building upon the research of Constanza et al., Xie et al. (2003) developed a dynamic assessment method for the ESV in mainland China based on the unit area equivalent factor method [28].

The “Norms for Accounting of Total Ecological Product Value” clarify the indicators, specific algorithms, data sources, and statistical caliber for the accounting of total EPV, but cannot be directly applied to specific regions. It is necessary to choose appropriate accounting methods according to local conditions in order to calculate the EPV. The selection of eco-product value-accounting indicators in this study was mainly based on three aspects. The first was related standard specifications such as the Technical Guidelines for Gross Domestic Product Accounting of Terrestrial Ecosystems. The second was an overview of the actual situation of scenic areas in Guizhou Province, China. The third was the latest research results at home and abroad. When selecting indicators, comprehensive consideration was given to the standardization of accounting, practical fit, availability of data, and feasibility of accounting to avoid duplicate calculations and ensure comprehensive, systematic, and scientifically reasonable accounting [29].

2.2.3. Web Text Data Mining

Using the “Octopus” crawler software (v8.6.7.112311), we selected the top two travel websites—Trip.com Group (https://you.ctrip.com (accessed on 25 September 2023)) and Tongcheng Travel Holdings Limited (https://www.ly.com (accessed on 25 September 2023))—to collect samples. We accessed the webpage related to the research area, selected the fields needed for this paper, such as guest reviews and ratings, created loop pages, and enabled the software to automatically identify the desired subelements. When exporting data, the software automatically eliminated duplicates and the manual removal of irrelevant content was also performed to ultimately obtain the desired research data. We used Rost Content Mining (ROST CM6.0), a piece of software developed by Professor Shen from Wuhan University, China, as an tool for text analysis, including word segmentation, word frequency statistics, semantic network analysis, and sentiment analysis. Through the public service platform, we gathered the elements of scenic area development, integrated information resources, changed the structure and development of the regional tourism market, and established a co-construction and sharing model for ecological tourism development [30].

2.2.4. PEFI Model

Xu Youlong et al. (2023) took the Longji Terraced Scenic Area in Guilin, China, as an example [31] and proposed a tourism scenic area value co-creation PEFI model based on four aspects, namely product, experience, feedback, and improvement (Figure 2), which helped to expand research and applications in tourism scenic areas. Product refers to the objects of tourists’ consumption, specifically including the eco-products of the scenic area composed of material products, regulatory products, and cultural products generated by the scenic area. Experience, the process of tourist consumption, specifically refers to the comprehensive tour experience within tourist attractions (including viewing experience, participation experience, transportation experience, dining experience, accommodation experience, shopping experience, entertainment experience, etc.). Feedback refers to the feedback provided by tourists after visiting the attractions, usually through online platforms for commenting, scoring, or posting online travel notes. Improvement refers to the improvement displayed by scenic areas based on feedback from tourists and their own situation, including but not limited to enhancing tourism facilities, improving tourism services and management levels, and continuously enhancing the quality of tourist experiences.

3. Results

3.1. Total Spatial EPV

3.1.1. Accounting Indicators for the EPV in Scenic Areas

The classification of land use data in scenic areas includes six primary types, namely cropland land, forests, grasslands, water, construction land, and unused land, as well as ten secondary classifications, namely scenic and recreational land, tourist facility land, residential and social land, transportation and engineering land, forest land, gardens, cultivated land, grasslands, water bodies, and retained land. This study integrates land use data into five types of ecosystems: Cropland land, forest land, wetlands, water, and grassland [32]. Based on the ES function research conducted by Xie Gaodi et al. (2015) on the current status of ESs in China [33], this study refined land use types using a secondary classification of ecosystems (

Table 2. EPV equivalent per unit area of Chinese ecosystems.

Ecosystems Classification		Provisioning Services			Regulating Services				Support Services			Cultural Services
Primary Classification	Secondary Classification	Food Production	Raw Material Production	Water Resource Supply	Gas Regulation	Climate Regulation	Hydrological Regulation	Environmental Purification	Soil Conservation	Maintaining Nutrient Cycling	Biodiversity	Aesthetic Landscape
Farmland	Dry land	0.85	0.40	0.02	0.67	0.36	0.27	0.10	1.03	0.12	0.13	0.06
	Paddy	1.36	0.09	−2.63	1.11	0.57	2.72	0.17	0.01	0.19	0.21	0.09
Forests	Coniferous	0.31	0.71	0.37	2.35	7.03	3.51	1.99	2.86	0.22	2.60	1.14
	Shrubs	0.19	0.43	0.22	1.41	4.23	3.35	1.28	1.72	0.13	1.57	0.69
	Coniferous	0.22	0.52	0.27	1.70	5.07	3.34	1.49	2.06	0.16	1.88	0.82
	Broad leaf	0.29	0.66	0.34	2.17	6.50	4.74	1.93	2.65	0.20	2.41	1.06
Grassland	Scrub	0.38	0.56	0.31	1.97	5.21	3.82	1.72	2.40	0.18	2.18	0.96
	Meadow	0.22	0.33	0.18	1.14	3.02	2.21	1.00	1.39	0.11	1.27	0.56
	Grassland	0.10	0.14	0.08	0.51	1.34	0.98	0.44	0.62	0.05	0.56	0.25
Water	Water	0.80	0.23	8.29	0.77	2.29	102.24	5.55	0.93	0.07	2.55	1.89
	Glacial snow	0.00	0.00	2.16	0.18	0.54	7.13	0.16	0.00	0.00	0.01	0.09
Wetlands	Wetlands	0.51	0.50	2.59	1.90	3.60	24.23	3.60	2.31	0.18	7.87	4.73
Deserts	Deserts	0.01	0.03	0.02	0.11	0.10	0.21	0.31	0.13	0.01	0.12	0.05
	Bare ground	0.00	0.00	0.00	0.02	0.00	0.03	0.10	0.02	0.00	0.02	0.01

). This method is based on the value equivalent factor table and has the advantage of simple operation and easy data acquisition. It is often suitable for large-scale evaluation research, including at the national, global, and regional scales [34]. The definition of scenic areas indicates that they are not the main body providing service development and that they have a relatively low value proportion.

3.1.2. Unit Area EPV

The EPV equivalent factor can be used to quantify the average annual value of ESs generated per unit area of ecosystems across the country, representing the potential ES contribution capacity of different ecosystems [15]. The value of the EPV equivalent factor for each standard unit area refers to the economic value of the annual grain yield of each hectare of farmland [35]; however, under natural conditions, the grain yield of farmland is affected by many factors, making it difficult to accurately calculate its economic value. Therefore, based on the statistical data in the China Statistical Yearbook (

Table 3. Statistical of grain data in Guizhou Province, China.

Year	Total Production (t)	Sown Area (hm2)	Yield per Unit Area (kg/hm2)
2020	376,400	82,837	4543.863
2019	375,500	81,221	4623.189
2018	381,700	88,977	4289.873
2017	436,600	109,250	3996.339
2016	437,100	111,767	3910.814
Average value	2,007,300	474,052	4234.456

), the yield per unit area of grain is multiplied by the sowing area of grain, and the ratio of planting grain cost to income is comprehensively determined. The calculation formula is as follows:

$$D=\left(\raisebox{1ex}{$1$}\!\left/ \!\raisebox{-1ex}{$7$}\right.\right)\ast P\ast Q$$

(1)

In this formula, D is the value of an equivalent factor, namely the EPV per unit area; 1/7 is the ratio of grain benefits to costs; P is the grain yield per unit area, obtained by dividing the grain yield by the grain cultivated land area; and Q is the national wheat protection price in 2021.

According to the China Statistical Yearbook of Guizhou Province from 2016 to 2021, the average grain yield per unit area in Guizhou Province was calculated to be 4234.5 kg/hm². Due to the influence of social demand on annual grain prices each year, in order to reduce calculation errors and improve the comparability of data, we adopt the 2021 national wheat protection price of CNY 2.26/kg as the grain price, and the value of the equivalent factor is calculated to be CNY 1367.14.

3.1.3. Identification of Landscape Values

According to the “EPV equivalent per unit area of Chinese ecosystem” (Table 2), combined with the calculation results of the standard equivalent factor value of Guizhou Province, China, the ES equivalent factor table is multiplied by the standard equivalent factor value of scenic areas. The estimated formula for the EPV of each individual in different land use types is as follows:

$${{\displaystyle EPV}}_K={{\displaystyle Y}}_K\ast D\ast {{\displaystyle A}}_K$$

(2)

In the formula, EPV_k represents the total value of eco-products in the region (CNF·hm⁻²·a⁻¹), Y_k represents the ESV equivalent factor corresponding to land use type k (Table 1), D represents the value of one standard unit of ESV equivalent factor, and A_k represents the ratio of the corresponding land use type area to the unit area (1 hm²), resulting in the EPV unit area value table (

Table 4. EPV value table (million yuan).

	Provisioning Services			Regulating Services				Support Services			Cultural Services
Classification	Food Production	Raw Material Production	Water Resource Supply	Gas Regulation	Climate Regulation	Hydrological Regulation	Environmental Purification	Soil Conservation	Maintaining Nutrient Cycling	Biodiversity	Aesthetic Landscape	Total	Percentage
DaXiaoQiKongScenic Area EPV
Forests	1.36	3.10	1.61	10.22	30.61	30.61	8.86	12.45	0.95	11.34	4.97	91.34	32.87%
Grassland	0.30	0.44	0.24	1.55	4.09	3.00	1.35	1.88	0.14	1.71	0.75	11.72	4.22%
Farmland	0.91	0.43	0.02	0.72	0.39	0.29	0.11	1.11	0.13	0.14	0.06	2.93	1.05%
Water	0.94	0.27	9.79	0.91	2.70	120.77	6.56	1.10	0.08	3.01	2.23	144.17	51.89%
Wetlands	0.34	0.33	1.72	1.26	2.39	16.10	2.39	1.53	0.12	5.23	3.14	27.67	9.96%
Total	3.85	4.57	13.38	14.66	40.19	170.77	19.27	18.08	1.42	21.43	11.17	277.86	100.00%
Shanmu River Scenic Area EPV
Forests	7.42	16.98	8.84	56.16	168.04	87.12	47.78	68.36	5.25	62.16	27.26	419.6	82.33%
Grassland	0.18	0.26	0.14	0.92	2.42	1.78	0.80	1.12	0.08	1.01	0.45	6.95	1.36%
Farmland	1.79	0.84	0.04	1.41	0.76	0.57	0.21	2.17	0.25	0.27	0.13	5.75	1.13%
Water	0.45	0.13	4.70	0.44	1.30	58.02	3.15	0.53	0.04	1.45	1.07	69.26	13.59%
Wetlands	0.10	0.10	0.50	0.37	0.70	4.69	0.70	0.45	0.03	1.52	0.92	8.08	1.59%
Total	9.94	18.31	14.23	59.30	173.22	152.17	52.64	72.63	5.66	66.42	29.82	509.63	100.00%
Huangguoshu Scenic Area EPV
Forests	2.19	4.99	2.58	16.47	49.31	29.54	14.29	20.06	1.53	18.26	8.01	127.38	59.78%
Grassland	0.46	0.67	0.37	2.37	6.26	4.59	2.07	2.88	0.22	2.62	1.15	17.94	8.42%
Farmland	3.72	1.75	0.09	2.93	1.57	1.18	0.44	4.51	0.52	0.57	0.26	11.94	5.60%
Water	0.34	0.10	3.52	0.33	0.97	43.40	2.36	0.39	0.03	1.08	0.80	51.82	24.32%
Wetlands	0.05	0.05	0.25	0.18	0.35	2.34	0.35	0.22	0.02	0.76	0.46	4.03	1.89%
Total	6.75	7.56	6.81	22.27	58.46	81.04	19.49	28.06	2.32	23.29	10.69	213.07	100.00%

).

Ecological resources are the dominant production factors of the fourth industry and are the starting point of industrial formation [36]. This article evaluates the EPV of the DaXiaoQiKong Scenic Area, Shanmu River Scenic Area, and the Huangguoshu Scenic Area in 2021 and illustrates the differences between the three scenic areas through charts. The magnitude of value is influenced by the selection of indicators, parameters, and accounting methods, as well as the construction level and management of the scenic area [37]. From Table 2 and Figure 3, it can be seen that through value accounting, the proportions of EPV per unit area of land in the selected research area are ranked in the following order: DaXiaoQiKong Scenic Area > Shanmu River Scenic Area > the Huangguoshu Scenic Area. From the value of different land use types, it can be seen that among the different land use types in the DaXiaoQiKong Scenic Area, Shanmu River Scenic Area, and the Huangguoshu Scenic Area, the largest proportion is taken up by forests and water, with a total proportion of 72.30%, 95.77%, and 82.68%, respectively.

The EPV of different land use types in the DaXiaoQiKong Scenic Area in 2021 is ranked as follows: water > forests > wetlands > grassland > farmland. The value of water is CNY 1.4837 million, accounting for the highest proportion, at 46.54%, of the total value of the scenic area. The EPV of different land use types in Shanmu River Scenic Area is ranked in the following order: forests > water > wetlands > grassland > farmland. The value of forests is CNY 5.5539 million, accounting for a high proportion of the total (84.88%). In the Huangguoshu Scenic Area, the EPV of different land use types is ranked as follows: forests > water > grassland > farmland > wetlands. The value of forests is CNY 1.6722 million, accounting for up to 62.69% of the total. The value of forest eco-products in the DaXiaoQiKong Scenic Area and the Shanmu River Scenic Area is relatively high, with a unit area and forest eco-product value of approximately CNY 30,000/hm² and CNY 30,400/hm², respectively. Meanwhile, the corresponding value for the Huangguoshu Scenic Area is relatively low, at about CNY 26,600/hm². The proportion of the EPV in forest-based scenic areas also demonstrates the integrity and authenticity of the ecosystem and landscape resources in the scenic area. From the perspective of the categories of EPV, the regulatory service value plays a dominant role in the EPV composition of the DaXiaoQiKong Scenic Area, Shanmu River Scenic Area, and Huangguoshu Scenic Area (Figure 4), accounting for 75.34%, 66.83%, and 67.95% of the total, respectively. The reason behind this is that the coverage of forest and water in the scenic areas is relatively high, and the ecological environment is similar, resulting in similar eco-product structures.

The abundant vegetation resources in scenic areas not only provide tourists with a beautiful environment and enhance the appreciation value of the regional landscape, but they also promote the vigorous development of the eco-industry [38]. Karst scenic areas can make full use of the local characteristic plant resources as raw materials, produce green eco-products, and enhance the overall image and brand value of the scenic area. In the process of developing the eco-industry, the protection and restoration of vegetation are emphasized to ensure the balance of ecosystems, providing a continuous source of power for the development of the eco-industry in scenic areas [39].

At the ecological level, forest resources and cultural resources are interdependent. Forests, as an important component of the Earth’s ecosystem, not only provide habitats for organisms but also carry rich historical and cultural heritage. Protecting forest resources means protecting the ecological environment of cultural resources. The value of cultural services is much lower than the value of regulating services when calculated using this method. Part of the reason for this is that cultural resources have not been well developed and utilized, and cultural resources have not been fully explored and displayed. Moreover, the value of cultural services provided by scenic areas is usually intangible, such as psychological relaxation, spiritual comfort, and other values that are difficult to measure using traditional economic methods. Scenic resources often have a deep connection with the local history and culture [40]. They are not only natural wonders but also carry the traditions and stories of the local people. Smardon R demonstrated the interconnected nature of benefits and services as well as the ubiquity of intangible values by reviewing the methodological challenges and new methods used for assessing cultural ecosystem services [41].

The development of the scenic tourism industry is usually accompanied by an increase in environmental awareness. Based on this, this article further explores the path to realizing the value of eco-products from the perspective of tourists’ perceptions of the landscape. Through investment and attention regarding the scenic tourism industry, the protection of the landscape can be strengthened, thereby maintaining its long-term attractiveness and sustainable development.

3.2. Anatomy of a PEFI Model Based on Landscape Perception

3.2.1. Landscape Sensing Data Processing

In the digital age, the massive amount of online user-generated content such as online comments has become a new type of data for measuring landscape perception [42]. Online review data reflect peoples’ objective and realistic perceptions of the landscape and have the characteristics of being documentary, open, free, shared, and constantly updated [43,44]. Through the Octopus data collector, a total of 9311 comments were collected regarding the selected research area, including 5689 comments from the Trip.com Group and 3622 comments from Tongcheng Travel Holdings Limited (

Table 5. Tourism comments of scenic areas obtained by various tourism websites.

	DaXiaoQiKong Scenic Area			Shanmu River Scenic Area			Huangguoshu Scenic Area
Website	Number of Comments/Piece	Number of Positive Reviews/Piece	Positive Review Rate	Number of Comments/Piece	Number of Positive Reviews/Piece	Positive Review Rate	Number of Comments/Piece	Number of Positive Reviews/Piece	Positive Review Rate
Trip.com Group	2765	2293	82.929%	78	64	82.051%	2846	2384	83.767%
Tongcheng Travel Holdings Limited	947	793	83.738%	116	100	86.207%	2559	2116	81.447%

).

After manually removing duplicate, irrelevant, and invalid comments such as “hour”, “no use”, “minute”, “as”, “a bit”, etc., synonyms were merged to obtain the top 100 highest-frequency words. The 100 highest-frequency words mainly included adjectives and verbs. Verbs mainly reflected the activities of tourists in the scenic area, such as “take pictures”, “row a boat”, “walk”, etc. Adjectives mainly included high-frequency words used by tourists to provide feedback on various experiences in scenic areas, such as “convenient”, “spectacular”, “shocking”, etc., indicating that tourists have a high overall satisfaction with the scenic area, a deep impression of the scenery, and are willing to visit again.

3.2.2. Analysis of the PEFI Model’s Application

• Eco-Products (Product)

Scenic resources include natural scenery and cultural relics such as mountains, rivers, lakes, seas, landforms, forests, flora and fauna, fossils, special geology, astronomy, meteorology, revolutionary monuments, historical sites, gardens, buildings, engineering facilities, and other cultural relics with ornamental, cultural, and scientific value, as well as their environments and local customs. The eco-products of scenic areas mainly focus on regulating services provided by scenic resources, supplemented by a small amount of material products and cultural products. This study mainly elaborates on the eco-products related to scenic resources.

The eco-products of the DaXiaoQiKong Scenic Area can be divided into two categories. The first category is represented by natural scenery sources such as the funnel forest of XiaoQiKong, stream pools and waterfalls, and the Karst cave hall of the DaQiKong Scenic Area. The rich forest vegetation, unique landforms and diverse flora and fauna resources together constitute the scenic area’s unique ecological charm. The second category is the cultural landscape, characterized by the ethnic customs of the Yao, Buyi, and (Va) Shui ethnic groups, which is rich, simple, and colorful. The scenery of the Shanmu River Scenic Area is serene and elegant, romantic and passionate, shrouded in clouds and mist, with towering peaks. The focus of eco-products is on regulating service products, thereby improving the overall ecological environment through the comprehensive regulation of gas, climate, and hydrology in the ecosystem. The Huangguoshu Scenic Area is first represented by a magnificent waterfall, the largest in China, and a diverse Karst waterfall group, combined with Karst geological and hydrological landscapes, long-standing historical and cultural relics, and other cultural resources, forming a unique landscape-resource characteristic system (Figure 5).

2.

Tourist Experience (Experience)

Ignoring the tourist experience and the lack of a sustainable development concept are the root causes of failure in operating tourist attractions in China [45]. The representative definition of tourism experience is “the direct observation or participation of consumers in the tourism process, as well as the feelings formed on this basis” [46]. The diversity of scenic resources is a necessary condition for unique tourist experiences, and without the diversity of the ecological environment, it cannot provide better experiences to tourists. The geological landscape is the biggest geographical characteristic of Karst areas, in which mountains, water, and people rely on each other, and there are many breathtaking unique experiences in the scenic areas.

The DaXiaoQiKong Scenic Area combines primitive mountains, water, forests, caves, lakes, and waterfalls. Visitors can experience the exquisite scenery composed of primitive forests, clusters of stalagmite caves, Karst lakes, and cascading waterfalls. The Shanmu River Scenic Area and Yuntai Mountain Scenic Area contain more than 20 mountains, and most of them can be traversed, which can be quite thrilling and exciting experience, providing visitors with different feelings. The magnificent and earthshaking force of the Huangguoshu Waterfall is heart-stopping. Tourists can also experience large-scale immersive mountain and water sights in this scenic area, immerse themselves in the grandeur and richness of waterfalls under the moonlight, feel the dream-like night, and experience the rich ethnic customs of the Buyi.

3.

Information Feedback (Feedback)

The emotional perception and experience of tourists regarding the landscape greatly affect their tourism behavior, such as their experience quality, destination image perception, and satisfaction [47]. Traditional tourism surveys often employ methods such as questionnaires and interviews, which have limited information richness and quantity. The answering process lacks privacy, and their credibility has certain limitations [48]. However, the short text comments that tourists post about scenic areas after the trip have the characteristics of being numerous and concise. Most of them also provide ratings alongside the textual comments. By utilizing Emotion Calculator software (v1.9.0.2)for sentiment analysis, the distribution results of tourists’ landscape perception characteristics were obtained (

Table 6. Landscape perception characteristics distribution of tourists in scenic areas.

Perceived Tendency	Frequency/Times	Proportion (%)	Intensity	Frequency/Times	Proportion (%)	Field
Positive perception	8018	74.41	Normal	2741	25.44	Recommended, spectacular, picturesque, mountainous, and green
			Moderate	2350	21.81	Convenient and time-saving
			High	2927	27.16	Poorly managed, to be redeveloped, and over-commercialized
Neutral perception	73	0.68				Convenient and time-saving
Negative perception	2685	24.92	Normal	588	5.46	Poorly managed, to be redeveloped, and over-commercialized
			Moderate	165	1.53
			High	123	1.14

).

Research has found that there are three main perceptual characteristics of landscapes: positive, neutral, and negative. Positive perceptions are dominant, with both neutral and negative perceptions being relatively small in proportion. A positive perception occurred 8018 times in our dataset, accounting for 70.41% of the total instances, mainly expressed through words of praise for scenic areas. A neutral perception occurred 73 times, accounting for 0.68% of instances, mainly consisting of vocabulary without emotional connotations. A negative perception occurred 2685 times, accounting for 24.92% of instances, mainly focused on issues such as poor management and a lack of order. From this, it can be concluded that visitors tend to have a positive opinion of scenic areas as a whole, with a high satisfaction rate of 83.23%, mainly praising scenic resources such as mountains, water and forests in scenic areas. As one tourist commented, “The XiaoQiKong Scenic Area truly deserves the green belt on Earth, with lush greenery and clear water accompanying it! It is well deserved and worth visiting”.

4.

Improvement of Absorption (Improvement)

The potential improvements to the ecotourism products and enhancements to the tourism experience in these scenic areas are as follows. Firstly, the tourism resources of the scenic area should be integrated, improving the traffic flow within the scenic area through facilities and activity organization. The time that visitors spend in touring the scenic area should be rationally arranged, rather than spending time on traffic. Secondly, the product positioning of the scenic area should be combined, developing richer tourism products, abandoning stereotypical tourism products, and instead exploring diverse eco-products of different Karst landscapes to meet the needs of different groups. Tourism products such as mountain climbing, cultural tourism, and folk experience tours for ordinary visitors should be actively developed.

Positive reviews are a recognition of the attractions by tourists and provide important support for expanding the influence of scenic areas. Negative factors can affect the tourism destination’s reputation and brand image, which is not conducive to the healthy development of the scenic area. These negative evaluations have important guiding significance for optimizing the mechanism of realizing the value of eco-products. Therefore, when examining online comments, the issues and suggestions raised by tourists should be given sufficient attention. Improvements should not be just superficial and should go more in depth in order to explore the deeper influencing factors. By analyzing the results of the text mining software and the sentiment analysis of comments, combined with the current economic and social development status, decision makers can further enhance the tourism image of scenic areas, attract more tourists, create more ecological value, and promote the realization of the EPV.

Based on the combined results of the valuation of the eco-products of the scenic area and the perception data of tourists, it can be concluded that the value of the Karst landscape resources and eco-products in the studied scenic areas has not been maximally developed and utilized. It is necessary to develop and design the eco-industry spatial pattern based on the differences in landscape resources, in order to further enrich the developmental connotations of the eco-industry and achieve goals such as enhancing the landscape’s functionality, sustainability, and aesthetics.

4. Discussion

The current development model of the Karst scenic area eco-industry is relatively small scale, and the main income channels are still dominated by tourist attraction tickets and sightseeing buses [49]. After comparative analysis, it was found that there are similar product and industrial activity modes in the study area, with serious homogenization, and the landscape’s heterogeneity cannot be fully reflected. It is necessary to clarify the differences between the eco-industry of the scenic area and other industries and implement a “staggered development” strategy.

4.1. ”Staggered Development” Strategy

The DaXiaoQiKong Scenic Area promotes the empowerment of cultural industry in scenic areas through strengthening its brand, industry integration, and scene operation. By carrying out cultural tourism, it empowers the development of scenic areas and creates an “ethnic cultural tourism-driven” development model, promoting the transformation of cultural value into economic value. From the perspective of the “rural society ecosystem”, the Shanmu River Scenic Area reconstructs the production–living–ecological spaces of the scenic area and countryside; optimizes the living space pattern; strengthens the deep integration of primary, secondary, and tertiary industries; improves the output efficiency of production space; and ultimately achieves the organic integration of mountains, water, forests, fields, and villages [50], thus promoting the harmonious development of production–living–ecological spaces. The Huangguoshu Scenic Area integrates the development of the forestry and fruit industry with scenic tourism, fully leveraging its resource and industrial advantages, promoting tourism through forestry and fruit, and promoting forestry and fruit through tourism. Furthermore, it is continuously improving the quality and quantity of forest resources to achieve the green and sustainable development of scenic areas, and ultimately achieve the coexistence of industry and ecology as a whole (Figure 6). It transforms ecological value into economic value, enables ecological benefits to positively impact people’s well-being, and realizes the organic unity of ecological protection and economic development.

4.2. Territorial Development and Industrial Clustering

For industrial development, the all-for-one tourism strategy poses a comprehensive challenge to the infrastructure and public services of tourist destinations [51], and the development model centered on scenic areas, which is known as “from points to areas”, is being transformed into a “from areas to points” model. By exploring the eco-industry landscape planning path of scenic areas, various forms of eco-industry channels, such as “ecology + spatial layout”, “ecology + modern agriculture”, “ecology + forest recuperation”, “ecology + industrial park”, and “ecology + characteristic culture”, can be opened up within scenic areas. This assists scenic areas to create a new mode of production and a development model for the tourism industry; achieves the transformation from a ticket economy to a comprehensive economy, from sightseeing scenic areas to leisure vacation and cultural experiences, and from isolated scenic areas to integrated regional development [52]; promotes the flow of tourism elements throughout the region; helps to realize the value of eco-products; and promotes the high-quality development of the eco-industry (Figure 7).

5. Conclusions

We conducted field visits and processed remote sensing data to calculate and compare the EPV of the DaXiaoQiKong Scenic Area, the Shanmu River Scenic Area, and the Huangguoshu Scenic Area. We have found that the value of eco-products is displaying a good developmental trend, and the value of regulation services dominates in the value composition. Next, the proportion of EPV per unit area of land in the scenic areas decreased as follows: DaXiaoQiKong Scenic Area > Shanmu River Scenic Area > Huangguoshu Scenic Area. The total EPV of the study area is as follows: Shanmu River Scenic Area (CNY 6.5436 million) > DaXiaoQiKong Scenic Area (CNY 3.1879 million) > Huangguoshu Scenic Area (2.6674 million yuan). In each level of ESV, the Shanmu River Scenic Area has a higher proportion compared to the other two study areas. This is because the Shanmu River Scenic Area has a higher level of protection, and its tourism and industrial development are both considered protective development, maintaining the integrity and authenticity of the scenic area’s natural ecology.

Using online text as data, we conducted high-frequency word and semantic network analysis on landscape perception data. This expanded research and application in tourism scenic areas from four perspectives: eco-products, tourist experience, information feedback, and the improvement of absorption. We propose strategies for regulating the realization of differentiated value in scenic areas to promote the realization of EPV. We recommend the provision of targeted guidance and support for the participation of local communities in the development of eco-industries and forestry, maximizing the development and utilization of landscape resource value, creating interactive landscapes, and meeting the diverse needs of tourists and villagers [53]. Sharing the achievements of tourism development with tourists and villagers (Figure 8), promoting employment and poverty alleviation through tourism, and promoting shared prosperity between the scenic areas and local communities would also be helpful measures.

This article aims to fully leverage the advantages of scenic landscape resources and explore differentiated development paths based on local conditions. It seeks to expand the channels for the development of eco-friendly industries in scenic areas, promote the formation and upgrading of the overall eco-friendly industry development pattern, and achieve resource sharing, customer interaction, and mutual benefit. The realization of the value of eco-friendly products and the formation and development of eco-friendly industries play a certain role in promoting the future development of scenic areas. Scenic areas must keep up and make targeted adjustments to the spatial allocation of scenic resources to achieve a deeper understanding of the scenic area [54], promote ecological livability and industrial prosperity, and create a more beautiful ecological picture (Figure 9).

The Karst scenic areas have a fragile ecological environment in the Karst region in South China and are economically underdeveloped. While regional economic development needs to be promoted, it is also constrained by the protective regulations of these scenic areas. It is worth further exploring how to meet the demands of scenic area development while ensuring the protection of the ecological environment of these scenic areas [55]. This article utilizes the equivalence factor method to calculate the overall ecological value, which results in relatively stable numerical values, and therefore has greater standardization and horizontal comparability. Web crawler data can provide accurate and real-time tourism information and quantitative analysis for scenic area spatial design; however, the analysis of the depth and core of landscape resources, based on the word frequency analysis of online texts, is mainly based on tourists’ evaluations, which to some extent have subjectivity. Therefore, the evaluation subjects should be expanded to comprehensively analyze the mechanism of eco-product value realization. However, simply relying on accounting results as a mechanism to promote value realization may be too simplistic. In future research, it is still necessary to conduct further in-depth research and exploration based on the ecological environment of the scenic area and the current status of industrial development and select more comprehensive and specific indicators to evaluate and quantify the eco-industry for comparative analysis.