Complexity

Complexity / 2020 / Article
Special Issue

New Models, New Technologies, New Data and Applications of Urban Complexity from Spatio-temporal Perspectives

View this Special Issue

Research Article | Open Access

Volume 2020 |Article ID 4137145 | https://doi.org/10.1155/2020/4137145

Huiqiang Ma, Jianchao Xi, Qing Wang, Jiale Liu, Zhigang Gong, "Spatial Complex Morphological Evolution and Influencing Factors for Mountain and Seaside Resort Tourism Destinations", Complexity, vol. 2020, Article ID 4137145, 11 pages, 2020. https://doi.org/10.1155/2020/4137145

Spatial Complex Morphological Evolution and Influencing Factors for Mountain and Seaside Resort Tourism Destinations

Guest Editor: Wen-Ze Yue
Received10 Mar 2020
Revised15 May 2020
Accepted15 May 2020
Published19 Aug 2020

Abstract

Spatial restructuring of tourism destinations is important not only for optimizing the spatial structure but also for promoting its sustainable development. This study adopted participatory rural assessment (PRA), GIS spatial analysis, and Google Earth remote sensing images as the main research methodology. The case studies of mountain resort destination, Huangshui Town, and seaside resort destination, Jinshitan, were analyzed. The study contributes to complex morphological evolution from the perspectives of external structure expansion and internal function reconstruction, revealing the spatial characteristics and explaining the influencing factors. The results showed that (1) in the process of tourism development, these two places have experienced large-scale growth of construction land and expansion of spatial scope. The external spatial structure of Huangshui Town is concentrated in the center and is scattered outward, changing from the form of a strip to a radiating pattern and finally to clusters. The spatial layout of Jinshitan has shifted from scattered to concentrated, changing from scattered to a strip along the coastline. (2) In particular, the internal functional structures of the two places have transitioned from a single residential function to a multicomposite function that integrates accommodation, dining, and entertainment. Among them, Huangshui Town is an “axial belt + group type” structure, and Jinshitan is a “wave type” structure. (3) The results also showed that natural factors such as traffic, terrain, rivers, lakes, and coastlines and anthropogenic factors such as government intervention and community participation are the main factors affecting the evolution of the spatial form of tourism destinations. The two tourist destinations in the study represent mountain resort type and coastal resort type, thereby showing that the spatial structure evolution model has certain typicality and representativeness.

1. Introduction

Studies on spatial restructuring have been a focus in academic circles. Spatial restructuring is related to urbanization, involving the reconstruction of production, evolution of settlement land use, and transformation of the inhabitants’ life styles. Tourism urbanization has become an important type of novel urbanization in China, having a profound impact on the process of spatial reconstruction, especially in urban areas. Currently, studies on spatial restructuring mainly focus on the following aspects: revealing the expansion model and the types of spatial structures [13], analyzing the spatial evolution and development process [46], understanding the influencing factors [7, 8] and the internal mechanism of spatial evolution [911], and exploring the quantitative measurement and the external effects of spatial evolution [1215]. The growth of a city is a two-way process of external structure expansion and internal function reorganization. At each stage, a new structure will be added, which will take the form of a symbiosis with the outside and substitution on the inside, thus creating a new spatial form.

In tourist cities, rural settlements, tourist attractions, and economic factors have a dominant influence on urban spatial structure evolution, and economic development drives urban spatial structure expansion [16, 17]. With the rapid development of tourism, urban spatial patterns, land use, and internal and external functions of tourist destinations have undergone profound changes [18, 19], especially in special areas such as mountainous regions [20]. Based on spatial analysis methods and spatial analysis models for tourist destinations [21], few exploratory studies have focused on the spatial structure of tourist destinations. They have mainly focused on the types of rural tourist destinations [22].

With the advancements in tourism, tourist destinations constantly undergo land space expansion and land function transformation [2325]. The factors that affect spatial structure formation and development in tourism destinations are complex and diverse. The evolution of an urban form is the product of the movement and the interaction of internal and external factors [26, 27]. The tourism industry in tourist destinations is the key supporter of economic productive activities. Thus, the evolution of the tourism industry is the core driving force that promotes changes in the urban spatial structure [28, 29]. In recent years, research on the spatial structure of tourist destinations has focused on the evolution mechanism and optimization and the influence and reconstruction of the tourism industry on the urban spatial structure [3034].

Studies on spatial evolution and influencing factors are popular research topics; hence, many research models have been developed and applied in this field. In land change research, some scholars used the simulated cellular automata model to explore the problems [3538]. Muluken Mekuyie used remote sensing, field observation, focus group discussions, and semistructured interviews to analyze trends in land-use and land-cover changes and their drivers in the period from 1985 to 2015 [39]; Pan et al. used stochastic greedy algorithm to study the urban structure and land-use model of Chicago [40]; Boavida-Portugal et al. developed a cellular automata (CA) model to provide a LUCC modeling approach to explore the impacts of tourism development on built-up areas [41]. Ahmadi et al. used a GIS software package and analytic hierarchy process to analyze the land suitability of Hormuz Island, and the findings clearly show land suitability for industrial, agricultural, and tourism land-use development [42].

A multiagent system (MAS), which features a “bottom-up” logical order of simulation modeling, includes complex system theory, artificial life, distributed artificial intelligence, and other technologies to simulate environmental policies [43]. Veldkamp and Fresco proposed using this dynamic model to simulate land-use change, and later the application of the model was used more extensively [44]. The model has outstanding advantages in spatial evolution and land-use change simulation and prediction. In the research field, the MAS model was used to simulate and forecast land-use status at different spatial and temporal scales, focusing on the macro level and the micro level [4548]. Agarwal et al. reviewed land-use change models and BDI decision-making [49, 50] and, based on the simulation theory of regional land-use change, aimed to optimize and improve the process, proposed a new cognitive structure, and applied it to the spatial evolution of tourism destinations; GIS method has also been widely used in the research of regional spatial evolution of tourism destinations [51, 52]; DEMATEL-GIS/MCDA hybrid and participatory method and other methods have also facilitated research and contributed to the field of rural planning under the influence of tourism [53].

However, relatively few studies have combined participatory rural assessment (PRA), GIS spatial analysis, and Google Earth remote sensing images as methodologies to analyze the spatial evolution and influencing factors of tourist destinations. In particular, comparative studies on the evolution of spatial structures of different types of tourist destinations are lacking. Thus, this study chose Huangshui Town, a mountain resort, and Jinshitan, a coastal resort, as the research cases for studying the evolution process and formulation of rules for the urban spatial morphology of two types of tourist destinations. We also analyzed the influencing factors. The results of the study will be significant in promoting the sustainable development of tourist destinations and creating livable tourist areas.

2. Data and Methods

2.1. Study Area

Huangshui Town is located in Shizhu Tujia Autonomous County of Chongqing City, which is an important minority area in China (Figure 1). It is 240 km away from the downtown area of Chongqing and lies to the east of the city. It is one of the seven major exporting centers of Chongqing City, and it has relatively convenient transportation. Huangshui Town began developing its tourism industry in 2004. Tourist arrivals and tourism income in Huangshui Town have maintained a high growth in recent years. In 2016, 2,662,000 tourists arrived in the town, with a daily tourist arrival rate of 100,000. The daily tourist arrival rate was 170,000 in 2017.

Jinshitan is located to the south of Jinzhou District, 50 km away from the center of Dalian City, and has excellent transportation. Jinshitan, with a coastline of 30 km, is surrounded by the sea on three sides (Figure 1). It comprises an eastern peninsula, western peninsula, and an open hinterland and bathing beach located between the two peninsulas. It has a state-leveled scenic spot, state-leveled tourism resort, national 5A grade scenic spot, and national geological park. In 2015, Jinshitan received a total of 6 million domestic and foreign tourists.

Huangshui Town and Jinshitan are taken as case study areas based mainly on the following two aspects:(1)They are two different types of typical tourist destinations. Huangshui Town is a typical mountain resort, while Jinshitan Beach is a seaside resort.(2)Their tourism industry has been well developed with a clear and complete development plan, and, for more than 10 years, the two tourist destinations have been explored and consolidated.

2.2. Data Sources and Methods
2.2.1. Data Sources

The study data were obtained from remote sensing imagery, land-use mapping (1 : 2000) (Huangshui Town 2004–2017; Jinshitan 1992–2015) by PRA and high-resolution imagery from Google Earth. PRA is a comprehensive questionnaire survey comprising a combination of demographic, social, and economic statistics. The PRA method was utilized as follows: First, urban land-use data were collected and labeled. The data were collected according to the Google Earth 0.6 m high-resolution remote sensing images, maps of major settlements and roads, and so forth. Second, door-to-door surveys were conducted from March 2004 to April 2018. Under the leadership of the chief government tourism officer for the towns of Jinshitan and Huangshui, the government conducted a series of door-to-door surveys of local businesses, mainly investigating the sources of the businesses, composition of their employees and the quality of the population, operating income and expenditure, the amount of various types of land use, and so forth. Third, the core interview subjects were selected. The selected interviewees mainly comprised those engaged in tourism development, including hotel owners, government officials, and community residents, all well-informed people who understood the overall situation of the town. The visit included the distribution, ownership, and related land-use policies of various types of land use in cities and towns; discussions on land-use types and their distribution on remote sensing imagery; and field surveys. Fourth, the information was revised after the interview. A core group of interviewees were convened to discuss land-use status, political and socioeconomic changes over time, and the processes and causes of land-use change; key node dates were selected, and survey information was compiled on land-use maps. Finally, an a posteriori evaluation was performed. The information obtained from the survey sites was analyzed considering the relevant materials, and preliminary knowledge was obtained. This information was then returned to core group of interviewees who were invited to comment on and finalize the data used in the study. At the same time, to improve the accuracy, the land-use hand-drawn map formed by PRA was scanned and then defined through a map projection system, image registration, and layered vectorization by ArcGIS 10.3 software to produce thematic maps.

2.2.2. Land-Use Classification System

There is no unified standard for classifying the types of land use in tourist destinations. Based on the standards of Classification of Land Use Status in China (GB/T 2100-2007) and Classification of Retail Forms (GB/T 18106-2004), considering that tourism has dual characteristics of both commercial services and tourism services, a classification system for land use in tourist destinations was established by combining the actual investigation and research (Table 1).


Class IClass IIClass IIIMeaning
NumberNameNumberNameNumberName

01CroplandLand for growing crops, including paddy fields, irrigated land, and dry land
02WoodlandWoodland, shrub woodland, and other woodlands
03GrasslandLand dominated by growing herbaceous plants
04Commercial service land041Land for tourism commercial services0411Tourism lodgingHotels, agritainment, etc.
0412Tourism cateringRestaurants, food stalls, snack bar, etc.
0413Tourist shoppingLocal specialty shops, crafts shops, tourist shops, etc.
0414Tourism recreationScenic spots, opera houses, amusement parks, bars, billiards rooms, Mahjong rooms, etc.
042Land for nontourism commercial services0421Wholesale-retailShopping malls, supermarkets, convenience stores, grocery stores, market, clothing stores, shoe and hat stores, home center, etc.
0422Business financePostal, telecommunications, e-commerce, express service, welfare lottery, banks, credit cooperatives, insurance companies, and other lands
0423Resident serviceHairdressing, physiotherapy clinics, automotive appliances maintenance, decoration companies, etc.
05Industrial warehouse landIndustrial production and material storage
06Residential land061Common residential landResidential housing and its subsidiary facilities for local residents
062Residential land for immigrantsImmigrant residence
063Second residential landGarden apartments and villas with both tourist accommodation and residential functions
07Public management-services landLand used for government organizations, press and publishing, science, education, culture and health, public facilities, etc.
08Transport landTransport lines, stations, etc.
08Transport landTransport lines, stations, etc.
09Land for water and water conservancy facilitiesWaters, ditches, hydraulic structures, etc.
10Other landsUndeveloped open land, bare land, etc.

2.2.3. Expansion Intensity Index and Main Indicators

(1)As shown in equation (1), the expansion intensity index (M) expresses the speed of urban construction land expansion. The area of urban construction land expansion is expressed by U, A is the total study area, and is the time interval:(2)The proportion of land use describes the proportion of various types of land in the total study area (Table 1).

3. Results and Analysis

3.1. Evolution of Spatial Structure
3.1.1. External Structure Expansion

Table 2 and Figure 2 show that the two areas have experienced large-scale growth of construction land and outward expansion of spatial scope in the process of tourism development.(1)The construction land of Huangshui Town increased from 60,504.35 m2 in 2004 to 459,817.41 m2 in 2017, with the maximum expansion speed and the maximum expansion intensity (3.86) in 2008–2012. According to the expansion intensity and the field investigations, the evolution of the external spatial form of Huangshui Town can be divided into three stages:(i)Slow embryonic period (2004–2008): with an expansion intensity of 0.90, the expansion of construction land was relatively slow in the infancy of tourism development. In contrast, the spatial form of Huangshui Town evolved from the belt spatial structure in 2004 to the star-like spatial structure in 2008, with construction and improvement of roads.(ii)Rapid growth period (2008–2012): with the rapid development of tourism, the construction land of Huangshui Town also spread rapidly and its expansion intensity tripled in the last period (3.86). At this time, the town showed a radial spatial structure.(iii)Stable growth period (2012–2017): in the late stage of tourism development, because land development tended to be saturated, the speed of construction land expansion decreased with the intensity of expansion, which decreased to 1.15; the spatial structure of construction land showed a group pattern and gradually dispersed.(2)The construction land of Jinshitan increased from 4,283,360.78 m2 in 1992 to 47,612,227.03 km2 in 2015. Unlike Huangshui Town, the expansion intensity of Jinshitan increased, with the maximum expansion speed and the maximum expansion intensity (9.21) between 2010 and 2015. Therefore, the evolution of the external spatial form of Jinshitan can be divided into three stages:(i)Slow embryonic period (1992–2000): during the slow land development, with the expansion intensity of only 0.57, most of the construction land scattered into the interior of Jinshitan was residential areas in the early stage of tourism development, and a small amount of coastline was developed such that it showed a preliminary trend of a belt structure.(ii)Rapid growth period (2000–2010): with the development of the tourism industry, especially the coastline tourism by the government, the expansion of construction land also accelerated with the expansion intensity, which increased to 0.94, and it also showed an obvious belt structure of coastline distribution; the trend of agglomeration and expansion from coastline to inland in space was also observed.(iii)Explosive growth period (2010–2015): owing to the establishment of the national tourism resorts, real estate emerged rapidly and in large quantities, and the expansion intensity (9.21) of the construction land showed explosive growth. From the spatial viewpoint, the strip structure of the coastline expanded from coastal to inland areas.


YearArea (m2)Expansion area (m2)Extended contribution rateExtension intensity

Huangshui Town200460,504.35
2008118,743.0158,238.6614.580.90
2012367,438.39248,695.3862.283.86
2017459,817.4192,379.0223.131.15

Jinshitan19924,283,360.78
20007,595,676.883,312,316.107.640.57
201014,388,953.386,793,276.4915.680.94
201547,612,227.0333,223,273.6576.689.21

Spurred by tourism, the external spatial structure of Huangshui Town spread into the city with the central area concentrated and then scattered outward, finally forming clusters. By contrast, the spatial distribution of Jinshitan evolved from scattered to concentrated and from a punctate structure to a belt along the coastline.

3.1.2. Internal Function Reorganization

Indeed, the internal functional structure of the two places has evolved from a single residential function to a multifunctional combination of eating, living, traveling, shopping, and entertainment in the process of tourism development (Table 3, Figure 3).(1)The land function of Huangshui Town has mainly transformed from cropland, woodland, grassland, and unused land to second residence, common residence, tourist, accommodation, and other lands. At the early stage of tourism development in 2004, the construction land was mainly residential land, which was distributed in a band along an old street called Yinxiang Road, while there was only a small amount of tourist accommodation land (1.41%) and catering land (0.04%) in the space and both were scattered along the road. When the tourism industry entered a stable and mature stage of development in 2017, the second residence land represented by vacation villas and vacation apartments experienced an explosive growth, occupying an absolute dominant position, and was scattered around the town in the form of groups. The tourism industry also matured and developed to a high-end industry, with the proportion of land used for tourism accommodation, catering, and shopping substantially increasing, especially for tourist accommodation (9.71%). Notably, the proportion of wholesale and retail land was also relatively high in this period mainly because Huangshui Town is not only a tourist reception town but also a central town serving the surrounding countryside with clothing stores, decoration stores, furniture stores, and other convenient businesses. In spatial distribution, nontourist sites such as wholesale, retail, business, and finance were mainly distributed in a band along the old streets, while the tourist sites were mainly extended along the North-South Huanglian Avenue and the East-West Yingbin South Road-Chuan-E Road. In addition, the proportion of common residential land distributed in a block-like structure in the rear of the road was as high as 23.24%.(2)The function of land in Jinshitan has mainly transformed from cropland, woodland, and aquaculture land to entertainment land, second residences, and tourist accommodation. In the early stage of tourism development in 1992, the main function of construction land was residential, and the proportion of common residential land which dispersed into inland areas was 6.92%. In contrast, a few development projects of coastal scenic spots appeared and the land for tourism and entertainment only accounted for 0.69%; however, the trend of strip distribution along the coastline was initially formed. By 2015, Jinshitan had experienced two large-scale expansions with tourism land increasing substantially, especially the land for tourist entertainment (23.96%). Second, residences such as coastal vacation spots, villas, and resorts had also clustered in distribution, with the proportion as high as 18.45%, and the belt spatial structure along the coastline had been formed. Similar to Huangshui Town, the tourism industries such as accommodation, catering, and shopping were also expanding on a large scale and scattered in the inland areas. Notably, the proportion of ordinary residential buildings declined, mainly because local residents demolished bungalows to live in high rises because of the expansion of urbanization and tourism. The ordinary residential land was far away from the coastline in space and was concentrated in the inland periphery zone.


Land typePercentage of land use in Huangshui Town (%)Percentage of land use in Jinshitan (%)
2004201719922015

Tourist accommodation1.419.7109.07
Tourist catering0.045.8500.25
Tourist shopping00.6300.71
Tourist entertainment01.030.6923.96
Wholesale and retail0.667.400
Commercial and financial0.050.820.100.20
Residential service0.051.300
Industrial and mining storage2.050.2300.36
Common residence2.6023.246.921.71
Immigrant residence07.050
Secondary residence039.75018.45
Public management and public service0.172.990.026.43
Aquaculture land008.832.43
Other lands13.0201.655.45
Cropland53.97032.303.76
Woodland9.73042.0627.40
Grassland16.2507.531.54

The internal spatial structures of both tourist destinations have undergone an evolution of diversification and compounding of functions. However, the spatial structure of Huangshui Town is a “belt + cluster,” with several belts from cutting apart tourist sites, nontourist sites, and common residential sites on traffic lines, and the second residential land is surrounded by a group structure. The spatial structure of Jinshitan is mainly a “wave” structure, which has evolved from the tourism and entertainment land to the second residential land + tourist business land to the common residential land, showing a belt distribution along the coastline from the coast to the inland areas.

3.2. Influencing Factors

Based on the land-use changes, the influencing factors of the complex morphological evolution of the two tourism destination cases were analyzed and classified. The conclusions are as follows.

3.2.1. Land-Use Pattern Change of Tourism Destinations

The existing land-use type of the Jinshitan tourism destination is mainly forest land. Urban land is relatively concentrated in the central region. From the perspective of spatial distribution, the area northwest of Jinshitan is dominated by forest land; the northeast area is relatively rich in land-use types, such as garden land, cultivated land, and water area; the area in the southwest direction is dominated by forest land, construction town, and rural residential area; the area of forest land to the southeast is less than that in the northeast direction, and the area of other land-use types is increased. As a whole, the land-use change pattern is influenced by the coastline and traffic line, as it approaches the coastline, and tourism land use has a trend of expanding to the surrounding areas.

In terms of time scale, the land-use types of Jinshitan are different from those in previous years. The area of forest land has an obvious trend of shrinking and increasing compared with the tourism land. Parts of the forest land, cultivated land, grassland, and so forth are transformed into tourism land, and parts of the garden land, forest land, and so forth are transformed into other types of land.

The existing land-use types in Huangshui Town are mainly ordinary residence and second residence, mainly distributed in regions to the south and north. The overall land-use change pattern mainly changes from cultivated land, forest land, grassland, and unused land to the second residence, ordinary residence, tourism, and accommodation. Owing to traffic road improvements and the promotion of tourism, the spatial pattern of Huangshui Town has changed from a “strip pattern” in 2004 to a “star pattern” in 2008. In 2017, with the development and maturity of tourism, the proportion of land for tourism accommodation, catering, and shopping has increased substantially; among this group, nontourist places such as wholesale and retail, business, and finance are mainly distributed along the old street strip, while tourist places are mainly distributed along the old street filling distribution and the main traffic road strip.

3.2.2. Driving Mechanism of Spatial Complex Morphological Evolution

The evolution of the spatial structure of tourist destinations is mainly influenced by natural factors such as transportation, topography, rivers, lakes, and coastlines and human factors such as government intervention and community participation. The spatial evolution of two different types of tourism destinations shows different and complex driving mechanisms.

Looking at the simulation of Jinshitan’s land-use type transformation, combined with social and economic statistical data, it is found that there are many characteristic factors that affect the transformation of land-use type, and tourism urbanization in coastal areas has a more prominent impact on Jinshitan. Jinshitan’s leisure tourism is another feature. As the largest outdoor entertainment place in Northeast China, Jinshitan’s Discovery Kingdom receives nearly 6 million tourists every year, which drives the economic development of surrounding areas. Under the huge change in the economic trend, Jinshitan has developed from single function to multiple functions. In the process of economic development, owing to the lack of appropriate planning or differences in the development time of resources, the distribution of other land uses is inequitable and the degree of utilization is different, resulting in the waste of land resources. The pattern change is not only related to the natural environment and social economic factors but also closely related to national macroeconomic policies, regional government decisions, laws and regulations, and so forth. However, these artificial characteristics are difficult to quantify accurately; hence, there are still deficiencies in the research.

In addition, the coastline is the most critical factor affecting the evolution of the spatial structure of a coastal tourism destination and it even determines the direction of spatial expansion. The construction land of Jinshitan has always been belt-like along the coastline, especially the land for tourism and entertainment, and multiple seascape houses such as vacation houses, villas, and resorts have been built on the coastline, which has become an important summer resort.

By analyzing the influencing factors of the land-use type transformation in Huangshui Town, we find that the change of the spatial form of Huangshui Town from 2004 to 2008 is due more to traffic road construction and improvement, and the traffic factor becomes the main influencing factor in this stage. Transportation is the primary factor affecting the evolution of the spatial structure of tourist destinations, which is constantly remolding the spatial structure of tourist destinations. The construction land in Huangshui Town showed belt distribution along traffic lines in the early stages of tourism development. With the construction of crossed and grid roads, the construction land evolved into a radial structure along traffic lines, especially tourism, accommodation, catering, and other lands for tourism, and its distribution was clearly along traffic lines. This factor can also be seen from the conclusion of the study: influenced by the traffic road, the tourism land in Huangshui Town is mainly distributed in a belt along the old street; the common residential land is “cut” by the traffic road, showing a massive distribution; the spatial form of Huangshui Town from 2008 to 2012 shows a radial pattern, and the main influencing factors in this stage include improvement of the traffic network and the driving force of human factors, which are closely related to the support of government policies and the continuous improvement of community participation.

Topography, an important factor affecting the spatial structure evolution of tourist destinations, has a certain restrictive effect on the evolution of the spatial form of tourist destinations. Restricted by the mountain terrain in Huangshui Town, the newly built second residences can only be exploited in the plateau area of the surrounding mountainous areas in the late stage of tourism development, thus forming a vacation group and showing a cluster development pattern. Furthermore, sources of water are the primary factors affecting and supporting the evolution of tourism spatial morphology. As rivers and lakes have a certain ornamental landscape value, the vacation villas of Huangshui Town built in the later stage are distributed near rivers and lakes for waterscape utilization.

4. Discussion

4.1. Value and Innovation

The novelty of this study is that it provides a comparative analysis of different types of tourism case areas and summarizes the general laws of their spatial evolution. The study analyzed the spatial characteristics of the driving force and explained the influencing factors. This is a relatively systematic study that explains the spatial complex morphological evolution and influencing factors for two different types of tourism destinations (mountain tourism destination and coastal tourism destination).

Huangshui Town and Jinshitan are representative mountain tourist and coastal tourist destinations, respectively. Mountain resorts show a combined conglomeration spatial structure because of the restrictions of mountain terrain, and coastal resorts often show a strip-like structure as affected by the coastline. Significantly, multiple factors such as natural environment, resource endowment, historical development, and humanistic characteristics influence the evolution of the spatial morphological model; thus, any case study should be based on the actual situation.

From the perspective of different spatial reconstruction processes of cities and towns driven by tourism, the spatial reconstruction of tourism formats is combined with the process of new-type urbanization. Hence, it is crucial to establish a suitable model of land improvement and functional improvement. With the development of tourism, the reconstruction of production and living space in tourism-dependent areas will lead to the transformation of other lands to tourism land, which will bring about the transfer of land rights and interests. The transfer of the power subjects and the requirements of related systems are constructed. Therefore, it is necessary to follow the characteristics and main driving factors of the spatial development of different types of tourism destinations, provide appropriate policy guidelines for different types of tourism destinations based on the circulation system of tourism land, and establish a comprehensive system of pluralistic investment and financing, social security, ownership adjustment, supervision, and management to meet the needs of the spatial transformation and development of tourism destinations.

4.2. Limitations

This study had several limitations. First, because of data limitations, we could only investigate a small number of important factors. More potentially important factors, for example, financial support and policy implementation, should be investigated if data are available. Second, only a brief analysis of the influencing factors was provided, and a deeper seated mechanism should be investigated; this is an important issue that should be addressed in future research. Third, more resort types and tourism destinations need to be investigated. For example, rural tourist destinations, heritage tourist destinations, and ancient city tourist destinations need to be considered to depict more spatial complex morphological evolution and influencing factors.

5. Conclusions

In this study, we found that the spatial evolution characteristics of different types of tourist destinations driven by tourism revealed complex morphological evolution from the perspectives of external structure expansion and internal functions, revealed the spatial characteristics driving the changes, and explained the influencing factors.

The study results support the fact that, during the process of tourism development, both tourist destinations selected for case study have experienced large-scale growth of construction land and outward spatial expansion. The external spatial structure of Huangshui Town evolved from a centralized to dispersed structure, from belt to radial, and finally to a cluster. By contrast, the spatial distribution of Jinshitan evolved from dispersed to centralized and from scattered to belt-like along the coastline.

The results also supported that although the internal spatial structure of the two tourist destinations has undergone the process of diversification and compounding of functions, it shows a “belt + cluster” structure in Huangshui Town; “belt” is mainly from traffic lines which divide the land for tourist, nontourist, and ordinary residential, and the second residential land shows “cluster” structure around the township. In Jinshitan, the spatial structure is mainly a “wave” structure, which has evolved from tourism and entertainment land to second residential land + tourist business land to common residential land, showing a belt-structure along the coastline from the coast to the inland.

The results showed that driving forces can be categorized into two major types: First, natural factors such as transportation, topography, rivers, and coastlines significantly affect land evolution. Second, government intervention, community participation, and other humanistic elements are the primary factors that affect the spatial structure of tourist destinations.

Data Availability

The data and analyses can be used for research and can be published.

Conflicts of Interest

The authors declare that there are no conflicts of interest regarding the publication of this paper.

Acknowledgments

This research study was supported by the National Natural Science Foundation of China (Grants nos. 41671151, 41771178, and 41630749) and Liaoning Province Innovative Talents Support Program (Grant no. LR2017017). The authors would like to thank all experts for their contributions to the urban thermal environment and urban planning.

References

  1. F. Liu, Z. Zhang, L. Shi et al., “Urban expansion in China and its spatial-temporal differences over the past four decades,” Journal of Geographical Sciences, vol. 26, no. 10, pp. 1477–1496, 2016. View at: Publisher Site | Google Scholar
  2. M. Symes, “The compact city: a sustainable urban form?” Land Use Policy, vol. 14, no. 3, pp. 232-233, 1997. View at: Publisher Site | Google Scholar
  3. J. Yang, A. Guo, Y. Li, and X. Li, “Simulation of landscape spatial layout evolution in rural-urban fringe areas: a case study of Ganjingzi district,” GIScience & Remote Sensing, vol. 56, no. 3, pp. 388–405, 2019. View at: Publisher Site | Google Scholar
  4. P. I. Korah, P. B. Cobbinah, A. M. Nunbogu, and S. Gyogluu, “Spatial plans and urban development trajectory in Kumasi, Ghana,” GeoJournal, vol. 82, no. 6, pp. 1113–1134, 2017. View at: Publisher Site | Google Scholar
  5. L. Wang, C. X. Qiu, and D. S. Xue, “The evolution and remolding mode of globalization space in world city: a case study of Potsdamer Platz in Berlin,” Human Geography, vol. 34, no. 3, pp. 75–82, 2019, in Chinese. View at: Google Scholar
  6. F. S. K. Agyemang, E. Silva, M. Poku-Boansi et al., “Understanding the urban spatial structure of Sub-Saharan African cities using the case of urban development patterns of a Ghanaian city-region,” Habitat International, vol. 85, pp. 21–33, 2019. View at: Publisher Site | Google Scholar
  7. X. Lin, Y. Wang, S. Wang, and D. Wang, “Spatial differences and driving forces of land urbanization in China,” Journal of Geographical Sciences, vol. 25, no. 5, pp. 545–558, 2015. View at: Publisher Site | Google Scholar
  8. K. Wang, X. Gao, and T. Chen, “Influencing factors for formation of urban and rural spatial structure in metropolis fringe area-taking Shuangliu county of Chengdu in China as a case,” Chinese Geographical Science, vol. 18, no. 3, pp. 224–234, 2008. View at: Publisher Site | Google Scholar
  9. F. Wang, Y.-Y. Xu, Y. Zhao, and X.-H. Zhu, “Belt or network? The spatial structure and shaping mechanism of the Great Wall cultural belt in Beijing,” Journal of Mountain Science, vol. 15, no. 9, pp. 2027–2042, 2018. View at: Publisher Site | Google Scholar
  10. X. Du, X. Jin, X. Yang, X. Yang, and Y. Zhou, “Spatial pattern of land use change and its driving force in Jiangsu Province,” International Journal of Environmental Research and Public Health, vol. 11, no. 3, pp. 3215–3232, 2014. View at: Publisher Site | Google Scholar
  11. J. Yang, J. Sun, H. Zhao, J. Xi, and X. Li, “Spatio-temporal differentiation of residential land for coastal town: a case study of Dalian Jinshitan,” Chinese Geographical Science, vol. 26, no. 4, pp. 566–576, 2016. View at: Publisher Site | Google Scholar
  12. H. Tao, J.-M. Liu, Y. Deng, and A. Du, “Tourism sectorization opportunity spectrum model and space partition of tourism urbanization area: a case of the Mayangxi ecotourism area, Fujian province, China,” Journal of Mountain Science, vol. 14, no. 3, pp. 595–608, 2017. View at: Publisher Site | Google Scholar
  13. P. Gaubatz, “China’s urban transformation: patterns and processes of morphological change in Beijing, Shanghai and Guangzhou,” Urban Studies, vol. 36, no. 9, pp. 1495–1521, 1999. View at: Publisher Site | Google Scholar
  14. L. W. Chen and K. Z. Yang, “Agglomeration and dispersion: integration of intra-urban commuting cost and external technological externalities,” China Economic Quarterly, vol. 1, pp. 53–70, 2008, in Chinese. View at: Google Scholar
  15. H. Dadashpoor and Z. Yousefi, “Centralization or decentralization? A review on the effects of information and communication technology on urban spatial structure,” Cities, vol. 78, pp. 194–205, 2018. View at: Publisher Site | Google Scholar
  16. J. B. Gao, H. T. Ma, and C. D. Ye, “On the urban industrial structure evolution and spatial structure transi-tion under the new economy development conditions,” World Regional Studies, vol. 17, pp. 35–40, 2008, in Chinese. View at: Google Scholar
  17. J. Yang, J. Su, F. Chen, P. Xie, and Q. Ge, “A local land use competition cellular automata model and its application,” ISPRS International Journal of Geo-Information, vol. 5, no. 7, p. 106, 2016. View at: Publisher Site | Google Scholar
  18. X.-Y. Mao, J.-J. Meng, and Q. Wang, “Tourism and land transformation: a case study of the Li River Basin, Guilin, China,” Journal of Mountain Science, vol. 11, no. 6, pp. 1606–1619, 2014. View at: Publisher Site | Google Scholar
  19. S. Sundriyal, V. Shridhar, S. Madhwal, K. Pandey, and V. Sharma, “Impacts of tourism development on the physical environment of Mussoorie, a hill station in the lower Himalayan range of India,” Journal of Mountain Science, vol. 15, no. 10, pp. 2276–2291, 2016. View at: Publisher Site | Google Scholar
  20. J.-C. Xi, Q.-Q. Kong, and X.-G. Wang, “Spatial polarization of villages in tourist destinations: a case study from Yesanpo, China,” Journal of Mountain Science, vol. 12, no. 4, pp. 1038–1050, 2015. View at: Publisher Site | Google Scholar
  21. S. Garcia‐Ayllon, “Geographic information system (GIS) analysis of impacts in the tourism area life cycle (TALC) of a mediterranean resort,” International Journal of Tourism Research, vol. 18, no. 2, pp. 186–196, 2016. View at: Publisher Site | Google Scholar
  22. J. Xi, X. Wang, Q. Kong, and N. Zhang, “Spatial morphology evolution of rural settlements induced by tourism,” Journal of Geographical Sciences, vol. 25, no. 4, pp. 497–511, 2015. View at: Publisher Site | Google Scholar
  23. J. Yang, Y. Ge, Q. Ge, J. Xi, and X. Li, “Determinants of island tourism development: the example of Dachangshan Island,” Tourism Management, vol. 55, pp. 261–271, 2016. View at: Publisher Site | Google Scholar
  24. A. E. Gaughan, M. W. Binford, and J. Southworth, “Tourism, forest conversion, and land transformations in the Angkor basin, Cambodia,” Applied Geography, vol. 29, no. 2, pp. 212–223, 2009. View at: Publisher Site | Google Scholar
  25. J. K. Strickland-Munro, H. E. Allison, and S. A. Moore, “Using resilience concepts to investigate the impacts of protected area tourism on communities,” Annals of Tourism Research, vol. 37, no. 2, pp. 499–519, 2010. View at: Publisher Site | Google Scholar
  26. A. M. Williams and G. Shaw, “Future play: tourism, recreation and land use,” Land Use Policy, vol. 26, pp. 326–335, 2009. View at: Publisher Site | Google Scholar
  27. S. Gossling, “Tourism, environmental degradation and economic transition: interacting processes in a Tanzanian coastal community,” Tourism Geographies, vol. 3, no. 4, pp. 230–254, 2001. View at: Publisher Site | Google Scholar
  28. J. Ding, H. Jiao, and J. Li, “Study on the mechanisms of evolution of urban industry on the evolvement of tourism urban spatial morphology: taking Huangshan city as an example,” Geographical Research, vol. 33, no. 10, pp. 1966–1976, 2014, in Chinese. View at: Google Scholar
  29. A. Guo, J. Yang, X. Xiao, J. Xia, C. Jin, and X. Li, “Influences of Urban spatial form on urban heat island effects at the community level in China,” Sustainable Cities and Society, vol. 53, p. 101972, 2020. View at: Publisher Site | Google Scholar
  30. L. Xue and J. Weng, “Study on microcosmic mechanism and dynamic simulation of China’s regional tourism spatial structure evolution,” Tourism Tribune, vol. 25, pp. 26–33, 2015, in Chinese. View at: Google Scholar
  31. X. L. Lu, L. B. Ma, Z. W. Sun, and A. L. Xie, “Optimization of tourism spatial structure of Beijing-Tianjin-Hebei metropolitan based on the promotion of the urban tourism energy level,” Areal Research and Development, vol. 37, pp. 98–103, 2018, in Chinese. View at: Google Scholar
  32. J. Davenport and J. L. Davenport, “The impact of tourism and personal leisure transport on coastal environments: a review,” Estuarine, Coastal and Shelf Science, vol. 67, no. 1-2, pp. 280–292, 2006. View at: Publisher Site | Google Scholar
  33. Z. F. Li and Z. Z. Cao, “Tourism-oriented new urbanization: a multi—dimensional comparative study,” Tourism Tribune, vol. 30, pp. 16–25, 2015, in Chinese. View at: Google Scholar
  34. D. G. Wang, “The spatial structure of urban tourism: its evolution and optimization—a case study of Suzhou city,” Urban Studies, vol. 14, pp. 21–26, 2007, in Chinese. View at: Google Scholar
  35. O. Charif, H. Omrani, F. Abdallah, and B. Pijanowski, “A multi-label cellular automata model for land change simulation,” Transactions in GIS, vol. 21, no. 6, pp. 1298–1320, 2017. View at: Publisher Site | Google Scholar
  36. N. Pinto, A. P. Antunes, and J. Roca, “Applicability and calibration of an irregular cellular automata model for land use change,” Computers, Environment and Urban Systems, vol. 65, pp. 93–102, 2017. View at: Publisher Site | Google Scholar
  37. H. Aliani, M. Malmir, M. Sourodi, and S. B. Kafaky, “Change detection and prediction of urban land use changes by CA–Markov model (case study: talesh County),” Environmental Earth Sciences, vol. 78, no. 17, 2019. View at: Publisher Site | Google Scholar
  38. M. G. Munthali, S. Mustak, A. Adeola, J. Botai, S. K. Singh, and N. Davis, “Modelling land use and land cover dynamics of Dedza district of Malawi using hybrid cellular automata and Markov model,” Remote Sensing Applications: Society and Environment, vol. 17, p. 100276, 2020. View at: Publisher Site | Google Scholar
  39. M. Mekuyie, A. Jordaan, and Y. Melka, “Land-use and land-cover changes and their drivers in rangeland-dependent pastoral communities in the Southern Afar region of Ethiopia,” African Journal of Range & Forage Science, vol. 35, no. 1, pp. 33–43, 2018. View at: Publisher Site | Google Scholar
  40. H. Pan, B. Deal, Y. Chen, and G. Hewings, “A reassessment of urban structure and land-use patterns: distance to CBD or network-based?—Evidence from Chicago,” Regional Science and Urban Economics, vol. 70, pp. 215–228, 2018. View at: Publisher Site | Google Scholar
  41. I. Boavida-Portugal, J. Rocha, and C. C. Ferreira, “Exploring the impacts of future tourism development on land use/cover changes,” Applied Geography, vol. 77, pp. 82–91, 2016. View at: Publisher Site | Google Scholar
  42. A. Ahmadi, H. M. Mosammam, and N. Mirzaei, “Land suitability evaluation to determine the appropriate areas of development: a case study of Hormuz island,” Open Journal of Ecology, vol. 7, no. 9, pp. 518–534, 2017. View at: Publisher Site | Google Scholar
  43. M. Antona, P. Bommel, F. Bousquet, and C. L. Page, “Interactions and organization in ecosystem management: the use of multi-agent systems to simulate incentive 51 environmental policies,” in Proceedings of the 3rd Workshop on Agent-Based Simulation, C. Urban, Ed., pp. 85–92, SCS-European Publishing House, Ghent, Belgium, 2002. View at: Google Scholar
  44. A. Veldkamp and L. O. Fresco, “CLUE: a conceptual model to study the conversion of land use and its effects,” Ecological Modelling, vol. 85, no. 2-3, pp. 253–270, 1996. View at: Publisher Site | Google Scholar
  45. A. Ligtenberg, M. Wachowicz, A. K. Bregt, A. Beulens, and D. L. Kettenis, “A design and application of a multi-agent system for simulation of multi-actor spatial planning,” Journal of Environmental Management, vol. 72, no. 1-2, pp. 43–55, 2004. View at: Publisher Site | Google Scholar
  46. D. Valbuena, P. H. Verburg, and A. K. Bregt, “A method to define a typology for agent-based analysis in regional land-use research,” Agriculture, Ecosystems & Environment, vol. 128, no. 1-2, pp. 27–36, 2008. View at: Publisher Site | Google Scholar
  47. T. P. Evans, A. Manire, F. de Castro, E. Brondizio, and S. McCracken, “A dynamic model of household decision-making and parcel level landcover change in the Eastern Amazon,” Ecological Modelling, vol. 143, no. 1-2, pp. 95–113, 2001. View at: Publisher Site | Google Scholar
  48. N. E. Bockstael, “Modeling economics and ecology: the importance of a spatial perspective,” American Journal of Agricultural Economics, vol. 78, no. 5, pp. 1168–1180, 1996. View at: Publisher Site | Google Scholar
  49. C. Agarwal, G. M. Green, and J. M. GroveT. Evans and C. Schweik, “A review and assessment of land-use change models: dynamics of space, time, and human choice,” in Proceedings of the Fourth International Conference on Integrating GIS and Environmental Modeling (GIS/EM4), Banff, Canada, September 2000. View at: Google Scholar
  50. M. J. H. Huibers, G. van Breukelen, J. Roelofs et al., “Predicting response to cognitive therapy and interpersonal therapy, with or without antidepressant medication, for major depression: a pragmatic trial in routine practice,” Journal of Affective Disorders, vol. 152–154, pp. 146–154, 2014. View at: Publisher Site | Google Scholar
  51. S. García-Ayllón, “GIS assessment of mass tourism anthropization in Sensitive coastal environments: application to a case study in the mar menor area,” Sustainability, vol. 10, no. 5, p. 1344, 2018. View at: Publisher Site | Google Scholar
  52. L. Benguigui and D. Czamanski, “Simulation analysis of the fractality of cities,” Geographical Analysis, vol. 36, no. 1, pp. 69–84, 2004. View at: Publisher Site | Google Scholar
  53. J. S. Jeong, L. García-Moruno, J. Hernández-Blanco, and A. Sánchez-Ríos, “Planning of rural housings in reservoir areas under (mass) tourism based on a fuzzy DEMATEL-GIS/MCDA hybrid and participatory method for Alange, Spain,” Habitat International, vol. 57, pp. 143–153, 2016. View at: Publisher Site | Google Scholar

Copyright © 2020 Huiqiang Ma et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


More related articles

 PDF Download Citation Citation
 Download other formatsMore
 Order printed copiesOrder
Views253
Downloads197
Citations

Related articles

Article of the Year Award: Outstanding research contributions of 2020, as selected by our Chief Editors. Read the winning articles.