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Article

How to Seek a Site for Forest Health Care Development—A Case Study in Hainan Tropical Rainforest National Park, China

by
Ziqi Zheng
1,
Jieling Chu
1,
Guang Fu
1,*,
Hui Fu
1,*,
Tao Xu
2 and
Shuling Li
1
1
School of Tropical Agriculture and Forestry, Hainan University, Haikou 570228, China
2
School of Architecture, Tianjin University, Tianjin 300072, China
*
Authors to whom correspondence should be addressed.
Land 2025, 14(5), 1076; https://doi.org/10.3390/land14051076
Submission received: 1 April 2025 / Revised: 9 May 2025 / Accepted: 12 May 2025 / Published: 15 May 2025
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Abstract

:
Identifying the most suitable areas for developing forest health care in Hainan Tropical Rainforest National Park (HTRNP) is of great significance to its ecological protection and development. This study selected 107 health care points in HTRNP as research objects to monitor environmental factors, a forest health care evaluation system was constructed based on those environmental factors, and the health care resource points were rated. Kernel density analysis and buffer zone analysis were used to analyze other factors such as roads, villages, and water inside and outside of the national park. Multi-factor superposition analysis of the first-level health care points with other impact factors was performed to obtain a map of the distribution of health care potential in different sub-areas of HTRNP. A total of 67 first-level health care points were selected through the forest health care evaluation system. Through superposition analysis, it was found that, among the seven sub-areas of HTRNP, there are 42 first-level health care points within the 5 km buffer zone for roads and waterways, including 11 in Diaoluo Mountain, 10 in Limu Mountain, 6 in Yingge Ridge, 5 in Jianfeng Ridge, 4 in Bawang Ridge, 4 in Maorui, and 2 in Wuzhi Mountain. There are nine first-level health care points located in the area with a village kernel density greater than 3000, including three in Diaoluo Mountain, two in Limu Mountain, two in Yingge Ridge, and two in Maorui. At the same time, to meet the above two conditions of the first level of health care points, there are six, including three in Diaoluo Mountain, two in Maorui, and one in Yingge Ridge. Through the results analysis, Diaoluo Mountain is considered to be the area with the greatest potential for developing forest health care in HTRNP. In addition, the comprehensive performance of Limu Mountain is second only to Diaoluo Mountain, and Limu Mountain, Maorui, and Yingge Ridge are listed as areas with great potential for developing forest health care.

1. Introduction

Forest health care is a general term for service activities such as rehabilitation, convalescence, and old-age care based on high-quality forests and their surrounding ecological environments for the purpose of promoting public health and organically integrating with medical treatment and health care [1,2]. The forest health care base is the main base for carrying out forest health care activities and developing the forest health care industry [3,4]. Some studies have shown that forest health care activities have positive effects on human health [5,6,7,8], and activities such as health care and ecotourism can effectively alleviate life stress [9]. The concept of forest health care first originated in Germany in the 1840s, with “forest bathing” as the main form of practice in the early days. “Forest bathing” was first proposed by Japan in 1982 [10], and then gradually spread to other developed countries in Europe and the United States. Forest bathing, or forest therapy, refers to immersing oneself in nature and experiencing the atmosphere of the forest in order to improve mental and physical health [11,12]. Forest health care has also been integrated into the treatment research of many diseases, such as cancer [13,14], and significant benefits of forest health care for disease treatment have been observed [15]. At present, Germany, Japan, South Korea, and the United States are leading the world in the development of forest health care [16]. The research results on forest health care mainly focus on the impact of forest health care benefits on the human body and mind [17,18], and there are relatively few comprehensive evaluations or studies on forest health care resources [19,20,21,22]. Although domestic research on forest health care started late, it has developed at a faster pace. Its overall development trend manifested in the gradual clearing of health care themes, the gradual improvement of health care facilities, and the continuous enhancement of service capabilities [23,24]; moreover, the total supply of forest health care services is gradually increasing [25], the quality is gradually being optimized, and the layout is becoming more balanced [26]. Here, we mainly focus on the following four aspects: construction and evaluation indexes of forest health care bases, development strategies of forest health care, the classification of forest health care products, and influencing factors of spatial distribution of forest health care resources [27].
Environmental factors, also known as ecological factors, according to the nature of the classification, can be divided into biotic and abiotic factors of two categories, which can also be divided into physical environmental factors and chemical environmental factors [28]. Environmental factors are in an indispensable position in the research of forest health care. At present, relevant studies mainly focus on exploring the interaction between environmental factors and the community distribution and ecological characteristics of plants and animals [29,30,31,32]. From the perspective of environmental factors affecting forest health care functions, the currently recognized beneficial environmental factors include the following: a more comfortable microclimate, cleaner air, a softer light environment, a quieter acoustic environment, and certain types of organic volatile of plant [33]. Domestic and foreign scholars generally choose environmental indicators such as atmospheric environmental quality, negative air ions, bacterial content, suspended particulate matter in the air, and plant essences to monitor, investigate, analyze, and evaluate forest environmental factors in due time [34,35,36].
With the advancement of urbanization and the rapid development of the forest health care industry, people’s demand for forest parks is increasing, and how to scientifically evaluate the health care function of forest parks is a prerequisite for scientifically arranging the time and place of forest health care activities [37]. The forest health value has become an integral part of forest ecological value and service value evaluation. However, there is still a big gap in the field of research on forest health value evaluation, and there is considerable room for development [38]. This paper takes HTRNP as the study area, and 107 health care points were selected in the study area, aiming to identify the most suitable areas for the construction of health care projects through scientific quantitative analysis, to provide scientific guidance for the construction of forest health care industry in HTRNP, and to promote full utilization of the island’s resources and research, as well as the further development of the sources of forest health care resources in Hainan. At the same time, it will expand new areas for Hainan Island’s tourism industries and provide new reference ideas and methods for site selection of health care points in other areas.
Hainan is located on the northern edge of the tropics, is China’s largest tropical forest area, provides tropical rainforest resources in the richest provinces, and is known as the “Tropical Plant View Garden”, “Biological Species Gene Pool”, “Butterfly Kingdom”, and so on [39]. Having a good climate, high-quality environment, the most beautiful forests, the most open policy, and rich ethnic culture and Li-Miao medicine resources are the five advantages of Hainan in developing forest health care [40]. There are few studies on Hainan’s forest health care. Before 2023, the focus was mainly on theoretical research on Hainan’s forest health care, such as the analysis of the problems and countermeasures faced by Hainan in developing the forest health care industry [41]. Only in the past two years have a few actual case studies on the evaluation of Hainan Forest’s health base appeared [42]. There are many gaps in the current research on forest health care evaluation in Hainan.
The evaluation of forest health care includes the following 11 methods: principal component analysis, hierarchical analysis, fuzzy comprehensive evaluation, indicator species evaluation, artificial neural network, health distance, gray correlation analysis, multiple linear regression, index evaluation, cluster analysis, and comprehensive index evaluation [43]. These research methods have their own advantages and disadvantages. The hierarchical analysis [44] and fuzzy comprehensive evaluation [45] are affected by subjective factors, the artificial neural network method requires sufficient data [46], and the multiple linear regression method requires a certain amount of experience. The method used in this study is based on the index evaluation method, combining the comprehensive index evaluation method with the comprehensive evaluation method formed by spatial analysis. The coefficient of variation method is used to calculate the indicator weights, eliminating subjective influences. It combines the advantages of the index evaluation method and the comprehensive index evaluation method, namely, fewer data requirements and rigorous logic. The method framework refers to the provisions on assessment methods in the “Quality Assessment of Forest Health Care Bases” (LY/T 2934-2018) issued by the State Forestry Administration of China, which combines quantitative indicators (such as forest coverage rate and negative oxygen ion concentration) with qualitative evaluation. In this study, we aimed to target the following existing research gaps: insufficient research on the quantitative evaluation and spatial location selection of forest health resources in specific areas of Hainan and the insufficient application of multi-factor superposition site selection methods. This study aims to fill this gap by constructing a targeted evaluation system and multi-factor spatial analysis method.

2. Materials and Methods

2.1. Study Area

Hainan Tropical Rainforest National Park is located in the central part of Hainan Island. From Nanqiao Town, Wanning City, Hainan Province is in the east, to Banqiao Town; Dongfang City is in the west, to Maozhen Township; Baoting Li and Miao Autonomous County are in the south, to Qingsong Township; and Baisha Li Autonomous County is in the north, with geographic coordinates of latitude 18°33′16″–19°14′16″ N and longitude 108°44′32″–110°04′43″ E (Figure 1). HTRNP zoning covers a total area of 4269 km2, divided into the following seven divisions: Jianfeng Ridge (JF), Bawang Ridge (BW), Diaoluo Mountain (DL), Limu Mountain (LM), Yingge Ridge (YG), Wuzhi Mountain (WZ), and Maorui (MR) (Figure 2). This includes the following nine cities and counties: Wuzhishan, Qiongzhong, Baisha, Dongfang, Lingshui, Changjiang, Ledong, Baoting, and Wanning in the central part of Hainan Province, and accounts for about 12.1% of the land area of Hainan Island and 25.4% of the land area of the nine cities and counties where it is located.

2.2. Data Sources

The data sources of this study are shown in Table 1. The environmental factor data of the health care points was obtained through on-site monitoring by the research team, based on the project “Comprehensive Survey and Monitoring of the Resource Background of HTRNP” carried out by the Forestry Bureau of Hainan Province in cooperation with the School of Tropical Agriculture and Forestry of Hainan University, combined with the environmental characteristics of HTRNP and the field investigation, and with reference to the opinions of the experts, 107 health care points were initially screened for evaluation based on the following five basic conditions: ① The health care site is located within the scope and restrictions of permitted development and does not violate the ecological protection red line. ② The health care site has a certain area of flat terrain for development and construction. ③ The health care site has basic transportation conditions and can be reached directly by car. ④ It has a certain facility base such as trestles and viewing platforms. ⑤ The safety of the site meets the standard and satisfies the conditions of no poisonous plants, no ferocious animals, no dangerous terrain such as cliffs, etc., (Figure 2).

2.3. Research Methods and Data Analysis

Using a combination of field research and data analysis, researchers went to HTRNP from September to October 2023 to monitor environmental factors such as temperature, humidity, sound pressure, wind speed, and air negative oxygen ion concentration at 107 health care points for a week. In the environmental factor data monitoring process, two people in a group carried an ELSEN-800 air anion detector and a multi-function noise meter to measure the air temperature, humidity, air anion concentration, and other environmental factors for 24 h of continuous monitoring. The air data were monitored intermittently for the following three time periods: 7:00–8:00, 11:00–12:00, and 15:00–16:00).

2.3.1. Indicator Selection and Scoring

With reference to the currently recognized beneficial environmental factors (i.e., more comfortable microclimate, cleaner air, quieter environment, etc.) and the environmental factors commonly selected by domestic and foreign scholars (i.e., atmospheric environment quality, negative air ions, etc.) [34,35,36], combined with the environmental characteristics of Hainan Tropical Rainforest National Park and the availability of data, four indicator variables, namely air quality, microclimate comfort, sound pressure, and surface water quality, were selected as evaluation indicators of the health care evaluation system from the two aspects of ecological quality and human comfort. The environment of the health care point was scored based on the monitored data, the sound pressure scoring was based on the Acoustic Environment Quality Standard GB 3096-2008 [47], the microclimate comfort was based on the comprehensive comfort index proposed by Dinghuang Lu et al. [48], the surface water quality scoring was based on the surface water environment quality standard (GB 3838-2002 [49]), the air quality was evaluated quantitatively with the air negative oxygen ion concentration as the basic observation index, and the unipolar coefficient and air ion evaluation coefficient were based on the evaluation index of air quality [50] (Table 2). The obtained score data are shown in Table 3.
The unipolar coefficient (q) refers to the ratio of positive ions to negative ions in the air. Many scholars have shown that the q value is usually about 1.2 on land, and most scholars believe that the q value should be equal to or less than 1 in order to give people a sense of comfort.
The air ion evaluation coefficient (CI) refers to the degree to which the concentration of ions in the air approaches the natural level of air ionization, i.e.,
Cl = n-/1000 q
where CI is the air quality evaluation index, n- is the negative air ion concentration (pcs/cm3), q is the unipolar coefficient, and 1000 is the negative air ion concentration (pcs/cm3) that meets the minimum requirements for human biological effects.

2.3.2. Data Normalization and Weight Assignment

The health care point scores were standardized by the max–min method:
x* = (x − min)/(max − min)
where x* is the value after standardization; and max − min is the difference between the maximum and minimum values of all data.
The coefficient of variation method was used to process the standardized data to obtain the weights of the indicators. Among the four indicators, the sound pressure score had the highest weighting, accounting for 37%; the air quality score had the lowest weighting of only 11%, which is mainly due to the fact that all of the health care points can achieve the “cleanest” air anion concentration, with no obvious variability; and the water quality score and the human comfort scores accounted for 28% and 24%, respectively (Table 4).

2.3.3. Construction of Health Care Evaluation System

A linear weighted summation formula is established based on the score weights of each indicator:
N = F1W1 + F2W2 + F3W3 + F4W4
where N represents the final evaluation score of the health care point; and F1–F4 and W1–W4 represent the sound pressure score, surface water quality score, air quality score, human comfort score, and the corresponding weight of each index of the health care point, respectively.
We constructed a forest health care rating scale based on the scores of each environmental factor combined with the analysis of the coefficient of variation (Table 5). Among them, the higher the N value (comprehensive evaluation score), the better the forest health care function. The 107 health care points were rated through the health care evaluation system to obtain 67 first-level health care points (Table 6).

2.3.4. Multi-Factor Superposition Analysis

A high-quality ecological environment is the foundation for the establishment of forest health care; good traffic is the necessary condition for material transportation and infrastructure construction; and water is an important factor affecting the growth and distribution of vegetation, and, at the same time, it can form a unique landscape and provide landscape resources for the development of forest health care and tourism industry [51]. The core functions of forest health care services cover social needs such as healing and rehabilitation, leisure and recreation, and health care for the elderly. On the basis of environmental factor evaluation, it is necessary to add complex indicators such as transportation accessibility, water resource security, and settlement spatial distribution. These natural geographical factors and humanistic and social factors together constitute the decisive parameters that affect the effectiveness of health care services. There is an old Chinese saying, which goes as follows: birds choose good trees to roost in, the choice of village locations brings together the wisdom and inheritance of several generations of local residents, and the village density reflects the comfort and livability of the area. At the same time, the village labor force can save the manpower scheduling costs of forest health care construction, and the development of forest health care can provide local residents with jobs and opportunities, both of which complement each other.
From the above analysis, it can be seen that the accessibility of roads, water, and settlements has important reference significance for the value of health care points. Areas close to roads, water, and villages are more suitable for developing forest health care. Therefore, the forest health potential of different areas was further evaluated by establishing roads (national highways, provincial highways, and county roads) and water system buffers in ArcGIS and conducting village kernel density analysis. Four scales of 1 km, 3 km, 5 km, and 10 km were selected to construct buffer zones. Based on the results of buffer zones at different scales, the 5 km scale buffer zone was retained as the final option, taking into account the effective coverage number of health care points and the significance of screening. The village kernel density analysis uses 3000 as the critical value, and areas with kernel density values greater than 3000 are considered to be high-value areas. Finally, the buffer zone, village kernel density map, and the above-mentioned 67 first-level health care points were overlaid for analysis. By observing the distribution of each health care point under different conditions, we can find the sub-areas with the greatest health care potential.

3. Results

3.1. Evaluation Results of Health Care Points

Through the constructed health care evaluation system, 107 first-level health care points were evaluated and analyzed, and the results showed that the health care level in HTRNP is very high, with 67 first-level health care points, accounting for 63% of the total number of health care points.

3.2. Results of Overlay Analysis

The superimposed buffers (the area where the 5 km buffer zone for roads and the 5 km buffer zone for water intersect, Figure 3a) has the advantages of convenient transportation, easy access to materials, and abundant natural resources. The results (Figure 3c) of superimposing this area with the village kernel density map (Figure 3b) and the first-level health care points are shown in Table 7. There are 42 first-level health care points within the superimposed 5 km buffer zone. According to the ranking of quantity distribution, there are 11 in DL, 10 in LM, 6 in YG, 5 in JF, 4 in BW, 4 in MR, and 2 in WZ. The number of first-level health care points located in DL and LM accounts for half of the total. There are nine first-level health care points located in the area with a village kernel density greater than 3000, including three in DL, two in LM, two in YG, and two in MR. At the same time, to meet the above two conditions of the first level of health care points, there are six, including three in DL, two in MR, and one in YG. DL, LM, MR, and YG showed significant advantages in the analysis results, especially DL and LM. There are three health care points that meet the two conditions of village nuclear density and buffer zone in DL, but none in LM, so the comprehensive level of DL is higher. MR and YG have two first-level health care points in the area of a village kernel density greater than 3000, but there are fewer health care points in the buffer zone, and fewer health care points meet the above two conditions compared to DL. In order to compare the results more intuitively, the data in Table 7 are visualized (Figure 4). It is not difficult to find that, among the seven sub-areas of the national park, the four sub-areas of DL, LM, MR, and YG have greater potential for health care development. DL has the largest number of first-level health care points screened out under the conditions of buffer zone and village kernel density, making it the health care area with the greatest development potential among the seven sub-areas of HTRNP. Next are LM, YG, and MR. JF, BW, and WZ did not perform well in the analysis results.

4. Discussion

4.1. Results Analysis

DL is famous for water. There are streams and lakes of all sizes, and there are “Hainan’s first waterfall”, Huangguoshan Waterfalls, internet celebrity waterfalls, Dali Waterfalls, Shiqing Waterfalls, and hundreds of unnamed waterfalls, enjoying the reputation of “Dream Rainforest, Hundred Waterfalls Dioaluo” and “After returning from Diaoluo, will never look at other waters again”. In addition, there are Hainan’s leisure resorts—Diaoluo Mountain Resort, Hainan’s most beautiful town—Dioaluo Town, Lake of Heaven, Diaoluo Sacred Tree, the old site of the Miao King Walled City, the river valley rocky beaches, Little Sister Lake, and other landscape attractions, as well as many natural ecological education bases, including lowland tropical rainforest, mountain tropical rainforest, valley rainforest, etc. Water plays an important role in regulating the ecological environment. The distribution of water areas will also affect the distribution of village points. The abundant water resources of DL may be an important reason for its excellent performance in health care evaluation. As an area with the most potential for health care development in HTRNP, existing natural conditions and humanistic industries have laid a solid ecological and material foundation for its development. While developing forest health care, it is necessary to make full use of the abundant water resources. It is a good idea to build a health care complex that combines health care, tourism, and nature education based on the existing tourism industry.
The development potential of the three areas of LM, MR, and YG is second only to DL. Among them, although there is no first-level health care point in LM that meets the village kernel density of ≥3000, it has 10 first-level health care points located in the buffer zone, which is close to DL in number and far exceeds that of the other areas. Therefore, there is a large potential for health care development in LM to be explored, and LM is listed as the second area with development potential, second only to DL. Taking the local brand “Limu Coffee” of LM and Hainan’s characteristic Li medicine as examples, a composite health care platform and characteristic brand of “Li medicine health care + forest coffee” can be created on this basis to promote the common development of forest health care and regional economy in HTRNP.
MR and YG have fewer health care points in the buffer zone, which is related to the number and distribution of roads and water in the zone. The distribution of water is a natural factor that cannot be changed at will. Improving the forest health care level of these two areas can be achieved by strengthening road planning and construction in the area and improving the degree of fit between high health care value points and traffic accessibility. BW, JF, and WZ do not have first-level health care points located in areas with high village kernel density, but this does not mean that these three areas do not have points suitable for the development of forest health care. The vegetation and terrain conditions in the tropical rainforest are complex, and its forest health care resources need to be further explored.

4.2. Significance and Suggestions

Excellent ecological and environmental benefits are the prerequisite for realizing the function of forest health care. In the development, construction, and later maintenance of forest recreation space, it is necessary to pay attention to the dynamic monitoring of various environmental factors, so as to realize the combination of long-term positioning observation and short-term mobile observation. We must fully consider the change characteristics of forest recreation factors on the multi-directional scales of time and space and analyze their change trends and influencing factors, so as to provide theoretical support for the improvement of the recreation environment. The selection of indicators before the establishment of the recreation evaluation system needs to be closely related to the actual situation of the area. The four indicators of air quality, microclimate comfort, sound pressure level, and surface water quality in this study are universal indicators selected after certain literature research, which can be flexibly changed according to the actual situation in order to build a more targeted evaluation system. It is very important to ensure uniformity and randomness in the selection of recreational resources in order to improve the reliability of the research results. The comprehensive consideration of natural and social factors, such as transportation, water, altitude, etc., in the selection of the research object in the early stage can effectively reduce the difficulty of data monitoring and ensure the feasibility of the development and construction in the later stage. The permanent residents around the national park are mainly villagers engaged in agricultural production who do not know much about the national park and forest recreation but have a high awareness of ecological protection. Vigorously publicizing the ecological benefits of forest recreation is conducive to the establishment of a good public base, and, at the same time, brings new employment and entrepreneurial opportunities for the surrounding residents. It is suggested that all urban areas should coordinate their development, avoid homogenized competition, strengthen communication and information resource sharing among themselves, and make reasonable use of the local forest resources to carry out staggered development, so as to form a more complete “multi-district integrated” forest recreation industry system.
The practical significance of this study is that Hainan Island is a nationally renowned ecological environment of high quality and is an ideal retirement area for many people. Tourism is the pillar industry of Hainan Island. This study on the HTRNP forest health care base can expand new areas for Hainan Island’s tourism industry and health care industry and further explore the ecological resources of HTRNP. Its theoretical significance is that it provides a new idea for forest health care site selection, which can be used as a reference for regional forest health care site selection.

4.3. Limitations and Prospects

This study has certain limitations. First, the monitoring of environmental factors was only carried out for one week, which failed to capture the impact of seasonal changes. In the future, it can be considered to monitor environmental factors throughout the year with a seasonal cycle and collect more comprehensive data on the basis of this study to carry out in-depth research. Secondly, the influence of socioeconomic factors was not fully considered in the selection of indicators. In subsequent studies, the aspects and number of indicators covered in the construction of the health care evaluation system can be improved. In the research on forest health care evaluation, the main research methods used are principal component analysis, the hierarchical analysis method, and the comprehensive index evaluation method. This study innovatively added other factors to the comprehensive index evaluation for superposition analysis, which expanded the research ideas and methods of forest health care evaluation. However, there are still certain defects in the selection and calculation of indicators, which need to be further improved in the future.

5. Conclusions

Among the 107 health care points in this study, 67 reached the level of first-level health care points under the evaluation of the health care evaluation system, accounting for 63% of the total number of health care points, indicating that HTRNP has a high potential for forest health care development.
The results of multi-factor superposition analysis showed that 42 of the 67 first-level health care points in the national park met the buffer zone conditions, 9 met the village core density conditions, and 6 met both conditions. Taking into account the distribution of these health care points in different sub-areas, a health care potential level map of each sub-area was obtained (Figure 5). The first-level health care points in DL have significant advantages in quantity and quality, and it is listed as the area with the greatest potential for health care development in HTRNP. LM is the area with the second-highest development potential after DL; in addition, LM, MR and YG are listed as areas with general potential for health care development. In the future, the above four areas of HTRNP can be given priority when developing and constructing Hainan’s characteristic forest health care industry. The forest health resources of JF, BW, and WZ need to be further explored.

Author Contributions

Conceptualization, H.F. and Z.Z.; methodology, G.F.; software, J.C.; validation, J.C., T.X. and S.L.; formal analysis, J.C.; investigation, Z.Z. and J.C.; resources, H.F. and G.F.; data curation, H.F.; writing—original draft preparation, Z.Z.; writing—review and editing, H.F.; visualization, Z.Z.; supervision, H.F.; project administration, G.F.; funding acquisition, H.F. All authors have read and agreed to the published version of the manuscript.

Funding

The research was funded by Hainan Institute of National Park, Hainan Provincial Philosophy and Social Science Planning Project (HNSK(ZX)24-252); National Research and Training Project of Humanities and Social Sciences of Hainan University(25GJJPY-7); Hainan Provincial Higher Education Teaching Reform Research Fund (Hnjg2024-10); Hainan University Teaching Reform Research Project (hdjy2420); Hainan University Humanities and Social Sciences Young Scholar Support Project (24QNFC-14); and Natural Science Foundation of Hainan Province (722QN288).

Data Availability Statement

Due to privacy restrictions, the data generated during this study and the field monitoring data are not publicly available but are available from the corresponding author upon reasonable request. The rest of the data is available on open platforms: https://openmaptiles.org/ (roads, water), https://www.gscloud.cn/ (DEM), https://www.stats.gov.cn/ (village locations).

Conflicts of Interest

The authors declare no conflict of interest.

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Figure 1. Location of the study area.
Figure 1. Location of the study area.
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Figure 2. Spatial distribution of health care resource points.
Figure 2. Spatial distribution of health care resource points.
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Figure 3. Multi-factor (buffer zone, kernel density, and health point) overlay result map.
Figure 3. Multi-factor (buffer zone, kernel density, and health point) overlay result map.
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Figure 4. Map of the number distribution of first-level health care points in different sub-areas under the superposition of multiple factors.
Figure 4. Map of the number distribution of first-level health care points in different sub-areas under the superposition of multiple factors.
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Figure 5. Health care potential map of different sub-areas.
Figure 5. Health care potential map of different sub-areas.
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Table 1. Data Information.
Table 1. Data Information.
NameSource
Road, water system dataOSM, https://openmaptiles.org/
(accessed on 13 October 2023)
The DEM dataGeospatial Data Cloud Platform https://www.gscloud.cn/ (accessed on 20 March 2024)
Village sites dataChina National Bureau of Statistics, https://www.stats.gov.cn/ (accessed on 15 October 2023)
Environmental factors dataData from on-site monitoring
Table 2. Air cleanliness level standards.
Table 2. Air cleanliness level standards.
GradeABCDE1E2E3
Air cleanlinessCleanestCleanModerately CleanAllowedSlightly PollutedModerately PollutedSeverely Polluted
CI>1.001.00~0.700.69~0.500.49~0.300.29~0.200.19~0.10<0.10
Table 3. Indicator scores for each health care point.
Table 3. Indicator scores for each health care point.
Serial NumberHealth Care Point NameMicroclimate ComfortAir QualitySound PressureWater Quality
1BW015553
2BW17034555
3BW03014454
4BW03024554
5DL014545
6DL035515
7DL044545
8DL064535
…………………
107MR0575535
Table 4. Evaluation index weight assignment.
Table 4. Evaluation index weight assignment.
IndicatorsAverage ValueStandard DeviationCV CoefficientWeight (%)
Noise score0.7150.3090.43237
Surface water quality score0.7850.2550.32428
Air quality score0.9860.1190.1211
Human comfort score0.8590.2420.28124
Table 5. Health care level evaluation.
Table 5. Health care level evaluation.
Evaluation ContentEvaluation ScoreLevelEvaluation Standards
Evaluation of forest health care functionsN ≥ 0.80IThe forest environment is very comfortable and very suitable for forest health care activities
0.65 ≤ N < 0.80IIThe forest environment is very comfortable and suitable for forest health care activities
0.50 ≤ N < 0.65IIIThe forest environment is relatively comfortable and relatively suitable for forest health care activities
0.35 ≤ N < 0.50IVThe forest environment is uncomfortable and not suitable for forest health care activities
N < 0.35VThe forest environment is very uncomfortable and extremely unsuitable for forest health care activities
Table 6. List of first-level health care points.
Table 6. List of first-level health care points.
Serial NumberHealth Care Point NameF1F2F3F4NHealth Care Point Level
1BW011110.60.888Level 1
2BW17030.751110.94Level 1
3BW03010.750.7510.80.8565Level 1
4BW03020.75110.80.884Level 1
5DL010.7510.810.866Level 1
6DL040.7510.810.866Level 1
7DL08110.810.926Level 1
8DL09110.810.926Level 1
……………....……
67MR057110.610.852Level 1
Table 7. The number distribution of first-level health care points in different sub-areas under the superposition of multiple factors.
Table 7. The number distribution of first-level health care points in different sub-areas under the superposition of multiple factors.
Number of Health Care Points
Branch NameBuffer Zone Within 5 kmVillage Kernel Density Index ≥ 3000In the Buffer Zone and the Kernel Density is ≥3000
JF500
BW400
YG621
MR422
WZ200
LM1020
DL1133
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MDPI and ACS Style

Zheng, Z.; Chu, J.; Fu, G.; Fu, H.; Xu, T.; Li, S. How to Seek a Site for Forest Health Care Development—A Case Study in Hainan Tropical Rainforest National Park, China. Land 2025, 14, 1076. https://doi.org/10.3390/land14051076

AMA Style

Zheng Z, Chu J, Fu G, Fu H, Xu T, Li S. How to Seek a Site for Forest Health Care Development—A Case Study in Hainan Tropical Rainforest National Park, China. Land. 2025; 14(5):1076. https://doi.org/10.3390/land14051076

Chicago/Turabian Style

Zheng, Ziqi, Jieling Chu, Guang Fu, Hui Fu, Tao Xu, and Shuling Li. 2025. "How to Seek a Site for Forest Health Care Development—A Case Study in Hainan Tropical Rainforest National Park, China" Land 14, no. 5: 1076. https://doi.org/10.3390/land14051076

APA Style

Zheng, Z., Chu, J., Fu, G., Fu, H., Xu, T., & Li, S. (2025). How to Seek a Site for Forest Health Care Development—A Case Study in Hainan Tropical Rainforest National Park, China. Land, 14(5), 1076. https://doi.org/10.3390/land14051076

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