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BY-NC-ND 3.0 license Open Access Published by De Gruyter Open Access April 28, 2016

Campgrounds Suitability Evaluation Using GIS-based Multiple Criteria Decision Analysis: A Case Study of Kuerdening, China

  • Wang Cuirong , Yang Zhaoping EMAIL logo , Liu Huaxian , Han Fang and Xia Wenjin
From the journal Open Geosciences

Abstract

The main objective of this study was to evaluate the suitability and select the most appropriate areas for building campgrounds in Kuerdening, China. To achieve this aim, AHP and GIS-based weighted overlay methods were adopted. AHP was used to determine the weights of the indexes, and ArcGIS 10 was used to calculate and map the campground suitability. In pursuit of minimum environmental effects and sustainable development, this paper identifies four factors to evaluate the suitability of areas for building campgrounds: natural environment condition, landscape condition, safety condition and infrastructure condition. The final outcome of this studywas the suitability map for building campgrounds. This research not only provides a theoretical guide for the construction of campgrounds in this area but also provides a scientific and efficientworkflow to evaluate the appropriateness of other areas. The result is reasonable and operable for camping facilities development and also useful for managers and planners working in local governments as well as investors.

1 Introduction

Camping, which is a form of outdoor recreation that is part activity and part accommodation [1], has become popular in many developed countries. According to the Outdoor Foundation, more than 40 million Americans went camping in 2013 for a total of 597.7 million days [2]. In England, 4.5 million camping trips were taken by British residents during the first half of 2015, which was an 8% increase in trips compared to the same period in 2014 [3]. Campgrounds, which are also known as trailer parks, travel parks and RV parks and resorts, consist typically of open ground spaces where a camper can pitch a tent or park a camper. In addition, campgrounds are fixed locations that are always situated in nature preserves. Campgrounds were first suggested in US National Parks in 1901, and the first public campgrounds in the United States were nothing but open places that allowed tourists to pitch tents [4]. The comfort levels of campgrounds have continued to rise in recent years [1] in accompaniment with significant change of camping styles and options, and the basic necessities such as fireplaces, public kitchens and laundry rooms have been augmented by game rooms, swimming pools, onsite sports, restaurants, bars, spas and other amenities. Campgrounds are not just wild places where tourists have short rests during their journeys but are also small communities where people live, entertain and communicate. Thus from this perspective, they not only provide affordable public access to nature as physical sites, but also possess sociological and psychological significance [5].

However, considerable evidence have illustrated the environmental effects resulting from activities around campgrounds, such as decrease of vegetation cover, degradation of soil, damage to live trees, and disturbance on wildlife communities [615]. Although negative impacts on the environment caused by camping cannot be completely eliminated, many of them can easily be avoided [16]. Monz and Twardock [17] examined the resource conditions of backcountry campgrounds in Prince William Sound, Alaska, USA, and concluded that campground substrates may play a substantial role in influencing the degree of impact of campgrounds on the environment. Marion and Cole [18] suggested that the most effective way to minimizing the total impact to the environment is to maximize the spatial concentration of campgrounds. Thus, considering potential impacts and choosing suitable locations for new campgrounds are crucial and are also reasonable ways to reduce the influence on the environment.

In most developing countries, camping is in a fledgling period and may strongly develop in the future. Recently in China, in accompaniment with the improvement in people’s incomes and living standards, tourists have been seeking more diversified ways to travel, including camping. In fact, the National Tourism Administration of China has indicated that camping tourism is an investment priority during China’s thirteenth five-year plan period (2016–2020), which indicates that the large-scale construction of campgrounds is ready to proceed. Several campgrounds for tourists are being planned in the Kuerdening scenic area in western China, which has been a major tourist destination since it was included in the World Heritage list in 2013 as a component of Xinjiang Tianshan. Thus, the selection of campgrounds needs to be approached cautiously because of its particular natural geographic location. In pursuit of minimum environmental effects and sustainable development, various factors, including the natural environment, geographic safety and infrastructures, need to be taken into account when selecting new campground locations.

Site selection for campgrounds is a typical multiple-criteria decision analysis (MCDA) problem as various factors need to be considered simultaneously. Additionally, geographic information system (GIS), which is a useful tool for spatial planning and management, can be particularly valuable for visualization and site selection assessment based on spatially related criteria [1921]. The approach adopted in this study is MCDA integrated in GIS environments, which has been widely used to determine the suitability of fire stations [2224], seismic stations [25], ecotourism [26, 27], wind farm sites [19], and PV solar plant [28]. The methodology is to generate suitability map for building campgrounds.

The remaining sections of this paper are arranged as follows. Section 2 introduces the Kuerdening study area. Section 3 describes the methodology, including the sources of the relevant data, choice of evaluation criteria, design of a pair-wise comparison matrix, formulation of the weights of criteria using AHP and the normalization and overlay analysis of the spatial data. The results of the research are reported and discussed in Section 4, and the study is summarized in Section 5.

2 Study Area

The Kuerdening scenic area is located in the central part of Xinjiang Tianshan, west China, from 42°55’ to 43°15’N latitude and 82°29’ to 83°26’E longitude. The scenic area covers 1638 km2.

The area is characterized by a temperate continental semi-humid climate. It is cool and humid, with a late autumn and early spring. In the winter, the climate is relatively warm. The annual average temperature is 5–7°C, the annual evaporation is 1,100–1,200 mm, and the annual average relative humidity is 70%. The total number of frost-free days is 120. The precipitation is relatively abundant, with an annual precipitation of 600–800 mm, which is the largest amount of rainfall in the Tianshan Mountains. Because Kuerdening has the most abundant precipitation in the Tianshan Mountains, the environment offers good living conditions for wild animals and plants and is a refuge for many ancient relict species. It is the key centre of biological diversity in the Tianshan Mountains in Xinjiang. The original forests of Picea schrenkiana, which are endemic to the Tianshan Mountains and have undergone 40 million years of evolution, make their home here.

The natural landscapes of Kuerdening have some of the highest aesthetic values of the biological landscape of the Tianshan Mountains in Xinjiang. There are exquisite scenic views of alpine meadows, subalpine meadows, pure snow spruce forests, spruce and broadleaved mixed forests, wild fruit forests and mountain steppes. The abundant and diverse types of landscape combine to present an overall landscape that is majestic and graceful.

Since the scenic essence of Kuerdening was included in the World Heritage list in 2013, the number of tourists had a remarkable growth according to local tourism authority. Although most tourists are content to view the landscape from tourist routes, many hike into the grassland and forest. Free camping activities in campgrounds developed by tourists their own have caused environmental effects in this area. Local tourism authority and investors are planning to construct several campgrounds to avoid more serious impacts. Because Kuerdening contains several protected area, such as the World Natural Heritage (WNH) and State Natural Reserve (SNR) areas (Figure 1), and lies within the Global 200 Ecoregion 111, “Middle Asian montane woodlands and steppe”, it is sensitive to climatic change and ecological interference. A comprehensive consideration of ecological impacts must be taken into account during the site selection of campgrounds in this area.

Figure 1  Location of Kuerdening.
Figure 1

Location of Kuerdening.

3 Methodology and Data

3.1 Suitability Evaluation System

To evaluate the suitability for campgrounds, multiple factors must be considered. Unfavourable factors need to be weakened or eliminated and favourable factors need to be fully taken advantage of. Because of the absence of research that evaluates the suitability for campgrounds, our work mainly considered national and local regulations regarding the construction of campgrounds. After a comprehensive review of the relevant state laws, regulations and industry rules, especially the very first “National Standards for Recreational Campgrounds of People’s Republic of China”, which sets rules for the classification, choice of locations and layout requirements of campgrounds, consultations with experts in the fields of tourism, ecology, environment and geology and considerations of the actual situation in Kuerdening and the availability of related accurate data, this paper selected four suitability evaluation factors: natural environment condition, landscape conditions, safety condition, and infrastructure condition. Each of the four factors contains several criteria, the details of which are shown in Table 1.

Table 1

Indexes of Kuerdening campground suitability.

Target LayerFactor LayerCriteria Layer
Kuerdening Campground SuitabilityNatural Environment Condition A1B1 SlopeB2 AspectB3 Canopy DensityB4 Reserve LevelB5 Drainage System Density
Landscape Condition A2B6 Distance from Scenic SpotB7 View-shed
Safety Condition A3B8 Geological DisasterB9 Threat of Dangerous AnimalsB10 Forest Fire
Infrastructure Condition A4B11 TelecommunicationB12 Transportation

3.2 Data Sources and Pre-processing

The data used in this research include Landsat 8 OLI images collected in 2013 and 2014 at 30-m resolution, ASTER GDEM V2 data, Xinjiang land-use data (2010), the geological map of Xinjiang, reports of Xinjiang Tianshan World Heritage sites, the locations of communication base stations and scenic attractions and the statistical Yearbook. Table 2 presents the sources of the data. The Landsat 8 OLI data were radiometric calibrated, geometrically corrected and speckle reduced. All of the datasets were co-registered using the ENVI 5.1 image processing package and ArcGIS 10.2, and all of the data were uniformly projected. The layer data were divided into 1,820,798 parcels of 30 m × 30 m raster data, and each land parcel was considered to be a basic spatial evaluation unit.

Table 2

Indexes of Kuerdening campground suitability.

DataSource
Landsat8 OLIGeospatial Data Cloud (http://www.gscloud.cn)
ASTER GDEM V2Geospatial Data Cloud (http://www.gscloud.cn)
Xinjiang Land-Use Data (2010)The Resources and Environment Remote Sensing Database (http://www.remotesensing.csdb.cn/)
Drainage MapXinjiang Bureau of Surveying Mapping and Geoinformation
Road MapXinjiang Bureau of Surveying Mapping and Geoinformation
Scenic AttractionsField survey with portable GPS
Communication Base StationsField survey with portable GPS
Xinjiang Geological MapXinjiang Bureau of Geology and Mineral Resources

3.3 Data Normalization

The spatial data for the twelve criteria used in this research (shown in Table 1) were normalized using reclassification, surface analysis and buffer analysis in ArcGIS 10.2. The raster data were assigned a designation of 1 (very low) to 5 (very high), and the higher values indicate higher suitabilities for campgrounds (Table 3). Details of these criteria are explained below.

Table 3

Criteria scores used to identify campground suitability.

FactorsCriteriaSuitability Rating
Very highHighModerateLowVery low
54321
B10°~5°5°~10°10°~15°15°~20°> 20°
B2[*]Flat &SSW &SEE &WNE &NWN
B3<35%35%~45%45%~56%56%~68%> 68%
A1B4Demilitarizedz ZoneSNR Experimental ZoneSNR Buffer ZoneSNR Core Zone & WNH Buffer ZoneCore Zone of WNH
B50.453~0.7100.328~0.4530.217~0.3280.089~0.2170~0.089
A2B6<1.5km1.5km~3km3km~4.5km4.5km~6km> 6km
B780%~100%60%~80%40%~60%20%~40%0%~20%
A3B8<5%5%~17%17%~31%31%~49%> 49%
B9> 3km2km~3km1km~2km0km~1km0km
B10<1%1%~16%16%~57%57%~83%> 83%
A4B110~4km4km~8km8km~12km12~16km> 16km
B12> 0.4930.332~0.4930.232~0.4930.146~0.2320.054~0.146

3.3.1 Natural Environment Condition (A1)

Natural Environment Condition contains five criteria: namely Slope (B1), Aspect (B2), Canopy Density (B3), Reserve Level (B4) and Drainage System Density (B5). The Slope and Aspect were calculated based on the DEM data. Slopes greater than 20° were considered to be extremely unsuited for construction because it may cause serious soil erosion [29]. According to Huang [29], slope ranges were assigned scores from 5 to 1. Low average temperatures (yearly average temperature of 7.4°) in this area make sunlight an important factor for more comfortable campgrounds, therefore aspect was used to measure the available sunlight. Areas facing south and flat areas were considered to have the most suitable aspect.

The Canopy Density was calculated by Forest Canopy Density (FCD) Model, which is an efficient approach brought by Rikimaru in 1996. This approach to map forest canopy density using four indices (advance vegetation index, bare soil index, shadow index and thermal index). Advance Vegetation Index (AVI) reacts sensitively for the vegetation quantity so that grassland can be distinguished from forest. Shadow Index (SI) increases as the forest density increases. Thermal Index (TI) increase as the vegetation quantity decreases and Bare Soil Index (BSI) increases. In this study, Landsat 8 OLI data was used to calculated these four indices by following equations:

(1)AVI=(Band5+1)(65536Band4)Band5Band43VI=0ifBand5<Band4
(2)BSI=(Band6+Band4)(Band5+Band2)(Band6+Band4)+(Band5+Band2)100+100
(3)SI=(65536Band2)(65536Band3)(65536Band4)3

Thermal index (TI) used data from thermal infrared band of Landsat 8 OLI. Because of the high negative correlation betweenAVI andBS, they were synthesized into Vegetation Density (VD) value by Principal Component Analysis.VI andSI synthesized into Scaled Shadow Index (SSI) by linear transformation ofSI. Details in Rikimaru [30], Rikimaruet al. [31] and FCD-mapper [32]. At last, Forest Canopy Density (FCD) value was calculated as:

(4)FCD=VDSSI+11

The Reserve Level scores were assigned according to actual conditions. Although construction of any type is forbidden in the core zone of the WNH and SNR, small-scale and environmental friendly construction projects can be undertaken in the buffer and experimental zones, and thus different scores were assigned according to the regulations. The Drainage System Density was calculated based on water system diagrams. Areas with a high density of rivers are more cost-effective when building water utilization systems in campgrounds, and scores were assigned along natural breaks. The detailed assignment scores for each of the criteria are shown in Table 3.

3.3.2 Landscape Condition (A2)

The Landscape Condition contains two criteria: Distance from Scenic Spot (B6) and View-shed (B7). The locations of scenic spots were recorded in the field survey using a portable GPS, and a polycyclic buffer analysis was then applied in ArcGIS 10.2 around the locations. The score increases as the distance to attractions decreases. The View-shed was calculated based on the location of attractions and the DEM data and by applying the view-shed calculation processing in ArcGIS 10.2. Locations with better views of attractions received higher scores, and the scores were assigned along natural breaks. The detailed assignment scores for each criterion are shown in Table 3.

3.3.3 Safety condition (A3)

Safety condition contains three criteria: Geological Disaster (B9), Threat of Dangerous Animals (B10), and Forest Fire (B11). The primary geological hazards in the study area are landslides, and the likelihood of geological disasters was calculated based on the DEM, slope and lithology [3335]. GIS technology is also been used increasingly in all aspects of wild land fire management recently [36]. In this research, the likelihood of forest fire was calculated based on vegetation type, elevation, and slope [3739]. Different vegetation types were assigned different scores, for example, coniferous forest was assigned 5 and water-body was assigned 0. Elevation is related to the precipitation in mountain areas, the higher the elevation is, the lower the possibility of the forest fire is due to the moist air. Slope is related to wind behavior, fire travels faster in areas with steeper slopes. Areas with a high likelihood of geological disaster and forest fire were assigned lower scores and considered to be less suitable for campgrounds, and the scores were assigned along nature breaks. Wild boars are the main threat animals in the study area [40], they habitat the forest during the day and roam the edges of the forests, therefore a polycyclic buffer analysis was used to assign higher scores in areas further from forest areas. The assignment scores for each criterion are shown in Table 3.

3.3.4 Infrastructure Condition (A4)

Infrastructure Condition contains two criteria: Telecommunication (B11) and Transportation (B12). The location of telecommunication bases were recorded in the field survey with portable GPS, and the polycyclic buffer analysis in ArcGIS was applied around the bases. Areas closer distances to the bases have better telecommunication conditions and were assigned higher scores. Transportation was calculated using linear density analysis based on the road map of the study area, and the scores were assigned along nature breaks. The assignment scores for each criterion are shown in Table 3.

3.4 Index Weight

An Analytic Hierarchy Process (AHP) was used to determine the weights of the indexes for the Kuerdening campground suitability evaluation. This process was first developed by Saaty in the late 1970s [41] and has been widely used in government, management, engineering, education and other activities [42]. The AHP is a simple and flexible decision-making tool to conduct multi-criteria evaluation [43] and thus can be used with integrated GIS spatial analysis for the site selection of campgrounds. Five steps must be sequentially performed to output a structured decision using expert judgment through AHP: (1) model the problem as a hierarchy, which was already accomplished in the former part (see Table 1); (2) establish a pairwise comparison matrix to evaluate the priorities among the elements of the hierarchy; (3) synthesize those judgments to yield a set of overall priorities for the hierarchy; (4) check the consistency of the judgments; and (5) reach a final decision based on the results of the process [44].

A pair-wise comparison matrix was made to evaluate the importance level of the indexes. Table 4 shows an example of a pair-wise comparison matrix for the safety condition that was used in this research. A scale from 1 to 9 is used to indicate the importance level of the two indexes. An explanation of the meaning of the scale is given in Table 5. If one expert considers Geological Disaster to be strongly important relative to the Threat of Dangerous Animals, in order to represent the Safety Conditions, Sij should equal 5.

Table 4

Sample pair-wise comparison matrix.

Compare the importance levels of two criteria to the Safety Condition
Geological DisasterThreat of Dangerous AnimalsForest Fire
Geological Disaster1Sij
Threat of Dangerous Animals1
Forest Fire1
Table 5

Scale of preferences between two parameters in AHP [41].

Preference factorDegree of preferenceExplanation
1EquallyTwo factors contribute equally to the objective
3ModeratelyExperience and judgment slightly to moderately favours one factor over another
5StronglyExperience and judgment strongly or essentially favours one factor over another
7Very stronglyA factor is strongly favoured over another, and its dominance is shown in practice
9ExtremelyThe evidence of favouring one factor over another is of the highest degree possible of an aflrmation
2, 4, 6, 8IntermediateUsed to represent compromises between the preferences in weights 1, 3, 5, 7 and 9

In this research, eight specialists working in the academic sector, geology, tourism development, heritage protection and biological conservation were invited to be decision makers. A general consistency of all of the judgments is required, and the index weight will not reliable as a basis for decision making if the judgments are too inconsistent. To check the consistency of the matrix, the following indexes are calculated:

(5)CI=λmaxnn1
(6)CR=CIRI

whereCI is the consistency index, λmax is the maximum characteristic root of the judgment matrix, andRI is the average random consistency index (Table 6).CR is the random consistency proportion. WhenCR equals 0, the judgment matrix has perfect consistency, and theCR value increases as the judgment matrix becomes more inconsistent. The judgment matrix has an acceptable consistency whenCR < 0.1 [45].

Table 6

Random consistency index (RI) [45].

N123456789101112131415
RI000.580.901.121.241.321.411.451.491.521.541.561.581.59

For a judgment matrixA, the calculation should satisfy:

(7)AW*=λmaxW

where W* is the normalized eigenvector corresponding to λmax, and W’s component Wi is the weight of the corresponding element single arrangement. The judgment matrix and weight calculation results are shown in Table 7. The calculation results are considered to be consistent (CR < 0.1). In terms of the factor layer, the results show that Safety Condition is the most important factor for building a campground, followed by the Natural Environment Condition. This result is consistent with the national standards for recreational campgrounds, which specify that suitable campgrounds should be environmentally safe, flat, have plenty of sunshine and exert little influence on rare animals and plants. The least important factor is Infrastructure Condition.

Table 7

Judgment matrix and weights of the campground suitability evaluation indexes.

IndexA1A2A3A4B1B2B3B4B5B6B7B8B9B10B11B12Weight
A111.76820.36732.50830.2337
A210.27132.43450.165
A313.10350.4987
A40.27130.27130.271310.1026
B111.62812.1521.33490.73890.244
B212.07530.63420.61260.1657
B310.57950.4430.1077
B411.10370.2249
B510.2577
B613.25460.765
B710.235
B811.28261.13780.3687
B910.48630.2353
B1010.396
B1111.1440.5336
B1210.4664
λmax4.13585.06542.00003.0449 2.0000
CI0.04530.016300.02240
RI0.901.1200.580
CR0.05030.01460.00000.03870.0000

3.5 Weighted Overlay Analysis

The weighted overlay analysis in ArcGIS was applied to calculate the comprehensive campground suitability in Kuerdening. The linear equation for the spatial superposition computation is

(8)S=iWAijWBjSj

where S is the final score of a unit, WAi is the weight of factor i, WBj is the weight of criterion j, and Sj is the score of criterionj of this unit. Using this method, every unit in the study area was assigned a score, and the scores were mapped using ArcGIS 10.2.

Three stages of analysis in ArcGIS were processed: (1) All of the twelve criteria were calculated separately to develop criterion division campground suitability index maps; (2) Based on those maps that gained in stage (1) and their weights for each criterion, four factors were then calculated to generate factor division campground suitability index maps. Within maps that obtained in both stage (1) and (2), study areas were classified into high, less high, moderate, less low, and low suitable zones using natural break classifier, they were assigned with 5 to 1 respectively; (3) At last, the comprehensive campground suitability index map was drawn based on those four maps obtained in stage (2) and their weights for each factor. The five levels from V to I for the campsite suitability were divided along natural break.

4 Results and Discussions

4.1 Natural Environment Suitability

Slopes in the study area range from 0° to 70.88°. The northern part of the study area is gently stretching, while in the south the terrain is rugged with large topographic reliefs. 2.90% of the regional unit was valued as highly suitable areas for campgrounds. However, 64.77% of the area, primarily in the south, is not suitable for campgrounds because of the steep slope (Figure 2A). Ridges and valleys in the study area are alternatingly arranged, thus the aspects are quite diverse from area to area. 4.94% of the regional unit was valued as highly suitable for campgrounds (Figure 2B). Most of the study area is covered with grasslands rather than forests, and thus suitable area in terms of canopy density is quite large. 84.06% of the area was valued as highly suitable areas (Figure 2C). In terms of reserve level, 38.47% of the study area is not part of any protected category and is therefore considered to be highly suitable for campgrounds (Figure 2D). Most of the rivers are concentrated in the middle and northeast of the study area, which accounts for 9.20% of the overall study area; from the perspective of water availability, this area is considered to be highly suitable for campgrounds (Figure 2E). By combining the five criteria in ArcGIS 10.2, a natural environment condition suitability index map was produced (Figure 3A). 0.23% of study area is highly suitable for campgrounds.

Figure 2  Kuerdening maps based on criteria scores for: A) slope, B) aspect, C) canopy density D) reserve level, E) drainage system density, F) distance from scenic spot, G) View-shed, H) geological disaster, I) threat of dangerous animals, J) forest fire, K) telecommunication and L) transportation.
Figure 2

Kuerdening maps based on criteria scores for: A) slope, B) aspect, C) canopy density D) reserve level, E) drainage system density, F) distance from scenic spot, G) View-shed, H) geological disaster, I) threat of dangerous animals, J) forest fire, K) telecommunication and L) transportation.

Figure 3  Kuerdening maps based on factor scores for: A) natural environment condition, B) landscape condition, C) safety condition and D) infrastructure condition.
Figure 3

Kuerdening maps based on factor scores for: A) natural environment condition, B) landscape condition, C) safety condition and D) infrastructure condition.

4.2 Landscape Suitability

Twenty-three view spots are concentrated in the northwest of the study area. 6.93% of the study area possesses the easiest accessibility to the view spots (Figure 2F). Regarding the View-shed, the southwestern part of the study area has better View-sheds because of its high elevation (Figure 2G). After combining the two criteria, 0.15% of the study area is highly suitable for campgrounds (Figure 3B).

4.3 Safety Suitability

Areas with altitudes between 1000 m and 1800 m with sandstones, conglomerates and mudstones have a high probability of geological hazards. Most of the study area (79.72%) is relatively safe. Those areas are distributed in the south of the study area, which has a hard lithology (Figure 2H). Areas with small numbers of dangerous animals account for 15.42% of the study area. 21.56% of the study area is considered to be safe because they are far from the habitats of dangerous animal (Figure 2I). Only 0.14% of the study area is considered to be safe from forest fires (Figure 2J). Additional attention must be given to forest fire prevention in this area. After combining the three criteria, 10.93% of the study area is highly suitable for campgrounds (Figure 3C).

4.4 Infrastructure Suitability

There are three communication base stations in the northwestern part of the study area, and the most suitable parcels account for 2.66% of the units (Figure 2K). Over 66.59% of the area has a score of 1, thus the presence of the communications infrastructure is relatively inconvenient. In addition, accessibility to roads in this area is poor. 3.16% of the area has a score of 5 while 56.03% has a score of 1 (Figure 2L). After combining the two criteria, 2.30% of the study area is highly suitable for campgrounds (Figure 3D).

The detailed parcel percentages under each criterion and factor are presented in Table 8.

Table 8

Distribution of the different levels of campground suitable zones.

Evaluation IndexSuitability ScoreTotal
54321
Natural Environment Condition0.23%13.26%66.18%19.90%0.43%100.00%
Slope2.90%7.69%11.19%13.45%64.77%100.00%
Aspect4.94%17.42%32.65%32.22%12.77%100.00%
Canopy Density84.67%0.01%4.19%9.10%2.02%100.00%
Reserve Level38.47%2.12%1.80%20.98%36.63%100.00%
Drainage System Density9.20%15.51%23.64%30.04%21.60%100.00%
Landscape Condition0.15%7.46%15.45%17.83%59.11%100.00%
Distance from Scenic Spot6.93%13.66%11.61%7.75%60.05%100.00%
View-shed0.34%0.86%1.94%9.98%86.88%100.00%
Safety Condition10.93%42.71%38.75%7.34%0.27%100.00%
Geological Disaster79.72%9.07%6.36%3.40%1.46%100.00%
Threat of Dangerous Animals21.56%8.94%12.82%41.27%15.42%100.00%
Forest Fire0.14%15.38%41.69%42.21%0.58%100.00%
Transportation2.30%3.38%18.28%27.11%48.94%100.00%
Telecommunication2.66%9.04%11.08%10.63%66.59%100.00%
Transportation3.16%6.61%22.18%12.03%56.03%100.00%

4.5 Comprehensive Campground Suitability

Using the GIS overlay technique, a campground suitability index map was produced and is shown in Figure 4. 2.2% of the units, which have an area of 36 km2, are highly suitable for building campgrounds. These areas are distant from protected areas and have little impact on rare animals and plants, are little threatened by animals and forest fires and possess good views of natural beauty. Thus, these areas can be listed as the highest priority areas to build campgrounds. The majority of the study area (64.09%) was classified as Level IV, and areas with this level can be considered as potential development zones to conduct camping activities. Caution needs to be exercised when developing those areas because some of them are sited in protected areas. Further investigations are needed to avoid potential impacts on the environment and ecology. Areas below Level III are considered as not suitable for building campgrounds. This paper suggests that eco-tourism activities such as hiking can be conducted in those areas, but construction should be prohibited.

Figure 4 Kuerdening campground suitability index map.
Figure 4

Kuerdening campground suitability index map.

5 Conclusions

The aim of this research was to evaluate the suitability of areas in Kuerdening for building campgrounds. To achieve this aim, AHP and GIS-based weighted overlay methods were adopted. Twelve criteria belonging to four evaluation factors were selected based on a comprehensive review of relevant research, regulations and expert consultations. The weights were determined using an AHP analysis. Division and overall suitability maps were generated using ArcGIS 10.2. The primary conclusions are now presented.

  1. The safety condition is the most important factor for building campgrounds, followed by natural environmental conditions. Therefore, in addition to location suitability evaluations prior to campground construction, the monitoring and prediction of geological hazards, forest fires and dangerous animals also need be conducted to manage campgrounds in the future.

  2. The suitability of Kuerdening for building campgrounds was divided into five levels, where Level V areas are the most suitable for construction. In contract, Level I areas are extremely unsuited for campgrounds. 2.2% of the units, which have an area of 36 km2, are highly suitable for building campgrounds, and majority of the study area (64.09%) can be considered as potential development zones to conduct camping activities, but further investigations must be undertaken to avoid potential impacts on the environment and ecology.

Given the evaluation of the suitability of Kuerdening for campgrounds, the most suitable areas were mapped. After conducting field investigations, the calculated results of this research were proven to be reasonable and operable. This research therefore not only provides a theoretical guide for the construction of campgrounds in this area but also provides a scientific and efficient workflow to evaluate the appropriateness of other areas. Finally, the main limitation of this research is that wind chill and air anion concentrations, as well as local economic conditions were not considered as factors because of the low differentiation in this area. In future research, especially in large-scale studies, these factors must be considered.


Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences; Tel.: +86-991-7885352

Acknowledgement

The study was supported by the National Natural Science Foundation(No. 41301163), the Western PhD project of Chinese Academy of Sciences (XBBS201210).

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Received: 2015-12-16
Accepted: 2016-3-2
Published Online: 2016-4-28
Published in Print: 2016-4-1

© 2016 Wang Cuirong et al., published by De Gruyter Open

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

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