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Article

Quantitative Assessment of Spatial Pattern of Geodiversity in the Tibetan Plateau

by
Tianyu Rong
1,2,
Shuting Xu
2,
Yayan Lu
1,2,
Yanjun Tong
1,2 and
Zhaoping Yang
1,2,3,*
1
State Key Laboratory of Desert and Oasis Ecology, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi 830000, China
2
University of Chinese Academy of Sciences, Beijing 100049, China
3
Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100049, China
*
Author to whom correspondence should be addressed.
Sustainability 2023, 15(1), 299; https://doi.org/10.3390/su15010299
Submission received: 10 November 2022 / Revised: 13 December 2022 / Accepted: 21 December 2022 / Published: 24 December 2022
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Abstract

:
Geodiversity is considered a new tool to exploit the resources of regional and local geotourism. Hitherto, few assessments of geodiversity have been conceived for huge geographic units. The spatial pattern of geodiversity in the Tibetan Plateau (TP) is the purpose of this study. A total of 96 abiotic units in six geo-groups of hydrology, pedology, landform, elevation, geology, and geosites were quantified and normalized to assess the geodiversity index. Geosites that represent interdisciplinary and specific abiotic elements are included as an independent component in the parameters of geodiversity assessment. The TP was divided into 1145 areas by fishnet, for counting of abiotic units, geodiversity calculation, and visualization of findings. The results indicated that the Pamir Plateau, Mt. Kunlun, the Delingha area, Mt. Qilian, the Xining area, Langmusi Town, Mt. Siguniang, Mt. Hengduan, the Nyainqentanglha Range, and the Lhasa area are the zones with very high geodiversity. The low geodiversity areas are mainly concentrated in the Qaidam Basin, the Qingnan Plateau, and the South Tibet region. In the TP, international tourist destinations such as UNESCO World Natural Heritage Sites and Global Geoparks, are developed in areas of high geodiversity. The spatial pattern of geodiversity could be indicative of geotourism potential, and be used to guide the development planning of geotourism in the TP. The quantitative assessment of geodiversity also provides a new parameter for geoconservation in China.

1. Introduction

The term “geodiversity” was first coined by Sharples [1] in 1993 after the Convention on Biological Diversity was launched at the Earth Summit in 1992 [2]. Geodiversity, as the complementary set to biodiversity in natural diversity [3], is the multiformity of abiotic elements [4], which include geomorphological, hydrological, pedological, and geological features [5]. With the in-depth understanding of geoscience and the exploration of earth resources, the abiotic units of geodiversity should be constantly changed and supplemented [6]. They are the stock of natural resources that together constitute the geosystem services for providing lasting benefits to human society [7]. Since 2010, geodiversity has attracted the interest of a growing number of scholars.
Geodiversity presents the potential to emerge as a research tool in biology, ecology, and landscape science [8,9]. Santos et al. [10] illustrated that geodiversity could effectively explain plant distribution patterns through assessment mapping. On the seafloor, the richness of geodiversity affects the degree of benthic diversity [11]. In addition, the analysis of regional geodiversity may strengthen the conservation and management of wetland reserves [12]. More than biodiversity and ecology, regional geodiversity may be treated as the foundation of resource utilization and sustainability [5,13,14].
Several practical contributions to the capabilities of geodiversity can be summarized as (1) improving the overall local attractiveness; (2) defining the level of geoscientific values and the construction potential of Geoparks; (3) enhancing the level of nature education and the awareness of geological conservation; and (4) serving as a source of inspiration for the arts. [15,16,17,18,19,20,21]. These ideas are partly supported by Migon et al. [22] and Ansori et al. [23], in their studies about UNESCO Global Geoparks, where geodiversity can provide multifarious geoeducational values and landscape features to visitors. By determining the quantity of abiotic elements, geodiversity often reveals the abundance of natural resources. Scholars subsequently discovered that the characteristics of geodiversity could be utilized to ascertain touristic attractions and their boundaries [24], and the value of geodiversity has been enhanced by regional and local comparative studies of landforms among countries [25,26]. In the study of the geoheritage inventory of Chirripó National Park, Quesada-Román elaborated that geodiversity assessment improves the management of nature conservation and geotourism [27]. Thus, the development of geodiversity is possible to support the land-use planning of regional and local tourism [28,29]. In addition, geodiversity can serve sports [30], and is highly relevant to local logo design and the residential experience of the inhabitants [31]. It can be argued that a region is inevitably influenced by local geodiversity. For this reason, the assessment and visualization of geodiversity has received increasing attention from scholars.
The assessment of geodiversity is still in the initial period [32]. For the quantitative assessment of geodiversity, scholars possess different views on methods and standards [33]. Albani et al. [34] adopted field counting to assess the geodiversity; however, this method is only applicable to the assessment in small areas. The analytic Hierarchical Process (AHP) was utilized by Elkaichi et al. [35] and Ferrando et al. [36] to measure geodiversity. Najwer et al. [37] evaluated geodiversity by combining geomorphic data and expert assessment. The above methods, all of which involve the participation of experts, are semi-quantitative decision-making techniques. The differences in the opinions and weighting of experts cause the assessment results to be unified and compared. Grid and centroid analysis could be the commonly adopted method among all kinds of quantitative assessments of geodiversity. The advantage of gridding regions or fishnet analysis used for geodiversity assessment is that the unit grid can be modified as the size of the study area varies, so that it can be applied at various scales without relying on experts to weight and score it. Several attempts quantified the distribution characteristics of geodiversity by grid analysis, however, the abiotic elements they chose were various combinations [38,39,40,41]. Geological factors are crucial components of geodiversity assessment, but less than half of the previous studies included geological elements [42]. In addition, the abiotic elements of the interdisciplinary section have not received sufficient attention, such as important mineral resources, geothermal resources, paleontological sites, and geohazards. In this study, the geosites were added to the parameters of geodiversity by grouping these valuable interdisciplinary elements.
For the size of the study area, scholars have mainly focused on small and medium-scale research, whereas few published articles have discussed the assessment of geodiversity in huge geographical units. Expert counting and weighting methods would have low feasibility in huge geographic units with extreme environments, treacherous terrain, and rudimentary infrastructure. The Tibetan Plateau (TP), which experienced complex geological events, is eligible for all these characteristics. However, tourism as a pillar industry in the TP requires an assessment of geodiversity to support its regional tourism planning and to explore more potential geotourism sites.
The study of geodiversity in the TP is lacking. The spatial distribution characteristics of geodiversity could provide new directions for the development planning and management of geotourism in the TP. This work strived to quantitatively assess the spatial distribution of geodiversity in the TP, a region with an area of 2,583,199 km2. In this area, abiotic elements with the same attributes or common geological features are grouped into a set, named geo-group in this research. This study adopted six geo-groups with a total of 96 abiotic units as the basis for quantitative assessment, and developed a method that can be applied for geodiversity assessment in a huge geographic area. Finally, we quantified the geodiversity characteristics of the TP by using grid and the inverse distance weight (IDW) for visualization.

2. Study Area

The TP is known as the “Roof of the World” [43]. The formation of the TP originated from the subduction of the Indian plate into the Eurasian plate [44], a process that has lasted 3.4 million years [45] and has created the largest geomorphic unit in Eurasia [46]. The study area is the entire TP within China, covering mainly Tibet and Qinghai provinces, with some areas in Xinjiang, Gansu, Sichuan, and Yunnan provinces (Figure 1). The study area is bounded by the Pamir Plateau to the northwest, the Karakoram to the west, the Himalayas to the south, Mt. Hengduan to the southeast, Mt. Min to the east, Mt. Qilian, Mt. Altun, and Mt. Kunlun to the north. The average elevation exceeds 4000 m.
The TP is the birthplace of many great rivers in Asia, including the Yangtze River and the Yellow River, the two longest rivers in China. In addition, the Mekong River, the Brahmaputra River, and the Salween River, which are transnational rivers feeding Southeast Asia, also originate on the TP. The Three Parallel Rivers region in Mt. Hengduan serves as a drainage channel for these rivers to leave. Snowmelt and precipitation are the primary sources of water that recharge these rivers in the TP [47]. The largest lake in China, the Qinghai Lake, is to the northwest of Xining city. There are over 1200 lakes larger than 1 km2 in the TP [48], most of which are developed from the Qiangtang Plateau and the Hoh Xil Nature Reserve. Lakes and glaciated landscapes are closely linked, especially in the TP [49]. The Pamir Plateau, Karakorum, Mt. Kunlun, and Mt. Qilian are a concentrated zone of glaciers in the northern part of the TP, and glaciers in the south are mainly developed in the Qiangtang Plateau, the Nyainqentanglha Range, the Gangdise Range, the Himalayas, and Mt. Hengduan [50]. The hydrological system on the TP has also shaped the unique combination of landforms.
High mountains surround the TP and have huge altitude drops from neighboring areas, but the interior is relatively gentle in most areas [51]. As a result of tectonic movements and fluvial erosion, the southeast of the TP is characterized by high mountains and deep valleys with large undulations. Mountainous terrains and basin plains dominate the northern part of the TP. The Qaidam Basin is the largest basin plain in the TP, and its central area is the fifth largest desert in China. In the central part of the TP, the Qiangtang Plateau and the Hoh Xil Nature Reserve are composed of terraces, plains, hills, and mountains with relatively low elevation relief [52]. Like the southeast, the northwestern part of the TP has formed a mountainous landscape because of strong orogeny. The second-highest peak in the world, Mount Chogori (K2), rises in the joint of the Pamir Plateau and the Karakoram Range. The Gangdis range, the Himalayas, and the Nyainqentanglha range construct a coherent mountainous landform in the south of the TP.
From northeast to southwest, the chronostratigraphic units of the TP are roughly from Paleogene to Triassic. The igneous rocks mainly outcrop in the Gangdies, the Qiangtang plateau, and the Hoh Xil belts [53]. Many orogenic belts in the TP have generated abundant mineral resources, including chromium, gold, copper, lead, zinc, lithium, and rare metals [54]. The TP reserves the largest amount of copper resources in China, with the Gangdise copper belt and the Yarlung Zangbo River copper belt being the most representative [55]. Gold ores are often associated with copper ores and are widespread in the TP, with large deposits mainly in the Gangdise, the Yarlung Zangbo River suture zone, and the Mt. Min region [56]. Large lead-zinc deposits are found in Mt. Hengduan and the Nyainqentanglha orogenic belt [57]. Geothermal resources abound in the TP due to vibrant crustal activities. The most potent hydrothermal activity is exposed in the Himalayas, the Nyainqentanglha Range, and Mt. Hengduan, with a decreasing trend from south to north [58]. The complex structure of geology on the TP has resulted in numerous geohazard events and relics. Debris flow is the most hazardous and widely distributed geohazard in the southwest of the TP, and the majority of them are the types of valley and slope [59]. The geohazards in Mt. Hengduan are very serious, and it is probably the hardest-hit area of geohazards in the TP [60]. In addition, Mt. Siguniang, Mt. Min, and the Huangshui valley are also concentrated regions of geohazards.

3. Materials and Methods

In the workflow, there are four steps to quantitatively assess the geodiversity of the TP: (1) selection of geo-groups and abiotic units in each group, (2) compilation of geodiversity database, (3) vectorization of maps if necessary, and (4) fishnet-based geodiversity assessment. The assessment was based on six geo-groups: hydrology, pedology, landform, elevation, geology, and geosites. The data sources consist of remote sensing data, atlases, and online databases. The information on data and pre-processing is specified in the following text.

3.1. Hydrology

Hydrological diversity consists of the surface water system and the groundwater system in this research (Figure 2a). Elements of surface water include glaciers, lakes, and rivers. The data for both glaciers and lakes were derived from the Tibetan Plateau Data Center (TPDC) [61,62]. The coverage distribution of net glaciers was modified from Landsat 8 Operational Land Imager (OLI) multi-spectral remote sensing data, with a resolution of 30 m [63]. The lake data was made up of water bodies larger than 1 km2, and modified from 2020 Landsat remote sensing data [64]. The drainage data was referenced from the website of the National Earth System Science Data Center (NESSDC), and contained all official records of rivers from levels one to five. The distribution of groundwater was revised according to both the 1:5,000,000 scale Groundwater Resources Map of China [65], mapped by the Institute of Hydrogeology and Environmental Geology (IHEG), and the 1:12,000,000 Hydrogeological Map of China [66], in the Geological Atlas of China. This information includes the types of groundwater, the types of bedrock, and a classification of the water storage degree (Table 1).

3.2. Pedology

This study adopted the pedogenesis classification to categorize soils into anthrosol, luvisol, pedocal, semi-luvisol, entisol, hydromorphic soil, ferralsol, xerosol, semi-hydromorphic soil, desert soil, saline-alkali soil, alpine soil, and pellicular salt. The pedology data in the TP (Figure 2b) were edited from the 1:4,000,000 scale Soil Map of China, which was a summary of 1:1,000,000 soil maps of all provinces [67].

3.3. Landform

The digital landform map (Figure 2c) provided by the TPDC was scanned and coordinate-calibrated according to the 1:4,000,000 scale Geomorphological Map of China [68]. The geomorphological map contains information about landform diversity. The landform is composed of hills, mountains, terraces, and plains. It was specifically divided into 13 basic landform units, according to the sedimentary and dynamic environment.

3.4. Elevation

The degree of elevation relief characterizes the geodiversity on the vertical axis. The altitude of the TP varies greatly, not only compared with neighboring areas but also in a single grid under the study area. The elevation data was obtained by the Digital Elevation Model (DEM) of Shuttle Radar Topography Mission (SRTM), with a 90-m resolution.

3.5. Geology

Figure 2d records the chronostratigraphic units and the distribution of igneous rocks in the TP. Since there was no available geological data with attributes that can be directly imported into GIS software, this data was obtained by vectorization of the 1:16,000,000 scale Geological Map of China [69]. The map contains chronostratigraphic information from Archean to Quaternary, with the system as the minimum unit.

3.6. Geosites

The aforementioned geo-groups were commonly assessed by scholars in the evaluation of geodiversity, but some interdisciplinary abiotic units had not been summarized into the parameters. For example, hot springs are a common manifestation of geothermal and hydrological resources, and geohazards are controlled by a combination of landform and geological factors. Undoubtedly, these factors belong to the components of geodiversity. In our study, the geosites group was integrated into the assessment system of geodiversity, as a representative of such valuable abiotic elements.
The geosites in this study consisted of mineral resources, fossil remains, volcanic craters, hot springs, landslides, collapses, and debris flow (Figure 3). The data of mineral resources in this paper were modified from the Distribution Map of Important Mineral Resources in China, which is a map containing the mega and most typical mineral resources in China. The original data sources of these seven components are shown in Table 2, and the data sources were separately obtained from the Institute of Mineral Resources (IMR) Chinese Academy of Geological Sciences, the GeoCloud online database of China Geological Survey, the New Geological Structure map of China in Geological Atlas of China [70], the Institute of Hydrogeology and Environmental Geology (IHEG) Chinese Academy of Geological Sciences [71], and China Institute of Geo-Environment Monitoring (CIGEM) [72], respectively.

3.7. Principles and Algorithms

The grid is a common analysis tool for the quantitative assessment of geodiversity. The method in this study is modified from the method proposed by Pereira et al., in 2013 [41]. This assessment method of geodiversity is widely accepted and used by scholars. The study area in Pereira’s research is one of the largest areas in the current geodiversity evaluation studies. In our study, we try to use this method on a huge-scale geographic unit.
The TP was divided into 1149 regions made up of 50 km × 50 km grids. The abiotic elements within each grid determined the geodiversity value of the area. Through the compilation and processing of six geo-groups, the normalized geo-data, which could be used for statistics and assessment, were recorded in the software of the geo-information system. To ensure the standardization of vectorization and the consistency of grids area, the Albers equal area projection was applied to illuminate the geodiversity of the TP. ArcGIS 10.5 was used for rasterization, quantitative assessment, and visualization of the results.
This method of assessment was based on the following principles: (1) Each abiotic element appearing in the grid was scored 1 point (Figure 4). (2) If an element of the same attribute appears multiple times, it is still awarded only one point. (3) The length of line-attribute elements and the area of polygon-attribute elements did not disturb the diversity score. (4) The elevation diversity score is calculated as the difference between the maximum and minimum elevation values within the grid. (5) Each of the six geo-groups independently counted their diversity scores. Principles 2 and 3 are designed to ensure the evaluation of diversity regardless of the richness of the elements. Principle 5 is established for the normalization of each geo-group.
With the principles described above, six scores are obtained for each grid. Since each geo-group has a different scale and contains various abiotic units, normalization can illuminate the diversity distribution characteristics of each group in proportion [73]. The normalization of the diversity score is shown in Equation (1),
G sub   =   Q grid   −   Q min Q max   −   Q min   ×   100 %
where Gsub is the normalized value of diversity for each geo-group, Qgrid is the score in each grid, Qmin is the minimum score of all grids in each geo-group, Qmax is the maximum score of all grids in each geo-group. The Geodiversity Index (GI) for each grid was summed from the Gsub of the six geo-groups, and Ghyd, Gped, Glan, Gele, Ggeo, and Ggeos are the normalized values of the diversity of hydrology, pedology, landform, elevation, geology, and geosites.

4. Results

4.1. Normalized Diversity of Geo-Groups

Each geo-group possesses different characteristics of diversity after normalization (Figure 5). The grids with Ghyd larger than 0.8 are more dispersed than the other geo-groups in the TP (Figure 5a). In the northern part of the study area, grids with Ghyd in the range of 0.8–1 surround the periphery of the Qaidam Basin, because the margin of the Qaidam Basin is the boundary zone between salt and fresh water. The high values of hydrological diversity (Ghyd > 0.8) in the south of the TP are concentrated in the western shore of the Yamzho Yumco Lake, the Egon region, and Ranwu Town, which are dense areas of rivers, lakes, and glaciers. Most areas with Ghyd lower than 0.2 are found in the Huangshui Valley and the Qingnan Plateau, where the groundwater is only fissure water. Figure 5b illustrates that the high values of soil diversity (Gped > 0.8) are concentrated in the northwest of the TP. The region of Duran County is the area with the highest pedological diversity. Most grids with low values of pedological diversity (Gped < 0.2) occur in the Karakorum and the Hoh Xil Nature Reserve, which are all desert soil and alpine soil.
Figure 5c shows the normalized diversity of landform. The grids with Glan greater than 0.8 are distributed in the Qiangtang Plateau and the western part of Mt. Qilian. Various plains, lacustrine terraces, and hills are distributed in the Qiangtang Plateau. Each landform is relatively small in size, so that the whole area forms a complex combination of landforms. The regions with Glan less than 0.2 are mainly in the Nyainqentanglha Range and Mt. Hengduan, which spread over homogeneous mountains. However, the normalized values of elevation diversity in these areas are relatively high (Figure 5d). The Yarlung Zangbo Gorge, located in the south of the Nyainqentanglha Range, has an elevation drop of 6060 m in one grid. In contrast, although the Qiangtang Plateau has high landform diversity, the terrain is relatively flat, with Gele widely less than 0.2. The Pamir Plateau and the Everest section of the Himalayas have both high Glan and Gele. The south of the Qaidam Basin possesses both lower Glan and Gele.
Figure 5e shows the normalized result of geological diversity. The high values of geological diversity (Ggeo > 0.6) mainly occur in orogenic and fault zones, including the middle part of the Yarlung Zangbo suture zone, the Xining region, the intersection of Mt. Qilian with the Qaidam Basin, the junction of the Nyainqentanglha Range and the Himalayas. The geosites are non-homogeneous sites, which are the most valuable factors in geodiversity [74]. Due to the rarity of the geosites, Ggeos values are widely less than 0.2 (Figure 5f). Most of the grids with Ggeos larger than 0.6 are distributed around Lhasa, Xining, and Mt. Hengduan. In the east of the Lhasa area, Ggeos is mainly dominated by the rich mineral resources, where copper, molybdenum, zinc, silver, and gold ores are deposited. Minerals and various geohazards enlarge the values of Ggeos in the south of the Xining area. In Mt. Hengduan, all kinds of geosites except volcanic craters are distributed with relatively high density.

4.2. Spatial Pattern of Geodiversity

Figure 6 is the spatial pattern of geodiversity summed by normalized diversity values of six geo-groups. The maximum and minimum values of GI are the upper and lower limits. The degree of geodiversity is equally divided into five grades: very low (0.56–1.17), low (1.18–1.79), medium (1.80–2.40), high (2.41–3.02), and very high (3.03–3.64). Among 1145 grids, there are 28 grids with very high levels, accounting for 2.4% of the total. The numbers of the high, medium, low, and very low are 278, 593, 208, and 38, accounting for about 24.3%, 51.8%, 18.1%, and 3.3%, respectively.
The geodiveristy of the TP is characterized by higher marginal areas and lower central areas. The regions with a very high GI are distributed in Mt. Qilian, the Delingha area, the Xining area, Langmusi Town, Mt. Siguniang, Mt. Hengduan, the Nyainqentanglha Range, the Lhasa area, the Pamir Plateau, and Mt. Kunlun. In the northeast of the TP, the Xining area, which consists of the Qinghai Lake Basin, the Huangshui Valley, and the Gonghe Basin, is the region with the highest concentration of very high grids. All six geo-groups emerged with high normalized values in this area, contributing to the largest and the highest GI area in the TP. The very high grids in the middle and western parts of Mt. Qilian are mainly influenced by the rich geological and pedological diversity. On the eastern edge of the TP, a high GI corridor connects two grids where the GI is very high. These two places are Langmusi Town and Mt. Siguniang. The grids with very high GI in the southeast are distributed in Mt. Hengduan and the Nyainqentanglha Range. In these regions, the diversity of elevation and geosites are the most critical supporting factors for the value of GI. In the south of the TP, the area around Lhasa encompasses three very high grids, including the southern shore of the Namucuo Lake and the western shore of the Yamzho Yumco Lake, which are dominated by the diversity values of hydrology, geology, and geosites. In the Pamir Plateau, a geodiversity passway based on high diversity values of hydrology, pedology, landform, and elevation is linked by Mt. Muztagata, Mt. Kongur, and the Taxkorgan Valley.
The Qiangtang Plateau and the Hoh Xil Nature Reserve lie in the hinterland of the Tibetan Plateau and together form the most widespread area of moderate geodiversity. The very low GI grids are scattered in the Qaidam Basin, the Qingnan Plateau, and the South Tibet region, which are also the zones with large areas of low GI. The lowest GI in the Qaidam Basin is found at the Cold Lake (Figure 7c), an ancient lake basin with flat terrain and an arid climate. The Gped, Gele, Ggeo, and Ggeos are all in the range of 0–0.2, resulting in very low GI in this area. In the Qingnan Plateau, the two grids of very low GI are located in Dari County, which is a plateau grassland with only alpine soil. The low topographic relief and hydrological diversity also contribute to the extremely low geodiversity in this area.

5. Discussion

5.1. Human Factors in Geodiversity Assessment

The South Tibet region lies on the southern flank of the Himalayas and is the third largest low-value (GI ≤ 1.79) zone of geodiversity in the TP. The GI in the South Tibet area is mainly supported by the diversity values of elevation and landform. On the other hand, Moto County in South Tibet is the last county in China to be accessible by modern road, which was officially opened on 31 October 2013. Thus, it is possible that the lack of cognition around South Tibet is the reason why the GI is low in this area. This idea also validates the previous result that geosite diversity is denser around cities where natural resource surveys are more frequent. Both Xining and Lhasa are surrounded by areas of very high geodiversity, which are largely supported by the diversity of geosites. Almost all national roads from the TP to developed areas of China have to pass through Mt. Hengduan. This area has more human activity than other non-urban areas in the TP, so it could lead to a higher variety and density of geosites in the area. Therefore, the status of abiotic element surveys in the region directly affects the assessment of geodiversity. Moreover, the discovery and utilization of natural resources are subjective. The elements of geodiversity will increase as human cognition of the Earth deepens, and the abundance of geodiversity elements will increase with the expansion of resource exploration. Geodiversity could be treated as a regional geo-information database, and the assessment of geodiversity should be updated with the update of geological surveys and cognition.

5.2. Correlation of Geodiversity and Landscape

Zakharovskyi and Nemeth [75] presented the results of geodiversity assessment through photographic images of the landscape. Panoramic images taken by Unmanned Aerial Vehicle (UAV) were used to determine whether geodiversity can reflect the richness of the landscape. Figure 7a is the contour map processed by the inverse distance weighted (IDW) method for the spatial pattern of geodiversity. Six locations were sampled on the map, with two spots of low GI (Figure 7c,d), two spots of medium GI (Figure 7b,e), and two spots of high GI (Figure 7f,g). Figure 7c was shot in the Cold Lake area, the lowest value of geodiversity in the Qaidam Basin, where the landscape and soils are homogeneous, and the horizon is flat. In contrast, Figure 7d was recorded at the Qinghai Lake. Because the lake surface does not entirely enclose the grid, some of the abiotic elements around the lake enhance the GI of this area. Figure 7b was photographed in the plain between Mt. Kunlun and the Karakorum, and Figure 7e was captured in the Ruoergai wetland. The landscapes of both areas are very different, but the GI of both are similar. This illustrates the inability of geodiversity to define the type of landscape on the surface. Figure 7f,g are visually richer in the content of the combination of rivers, lakes, and steeper mountains. Figure 7f,g were captured in the north of Ranwu Town and on the western shore of the Yamzho Yumco Lake, respectively. Ranwu Town is in the grid with a high GI, while the Yamzho Yumco Lake is in the grid with a very high GI. The richness of the landscape is similar in both areas, although there exist differences in geodiversity. However, compared to the areas with low geodiversity (Figure 7c,d), there is a higher color and geometric richness. The value of GI can respond to the complexity of the surface landscape, but it is no longer obvious in the interval of higher geodiversity.

5.3. Parameter of Geotourism

The TP supports three UNESCO World Natural Heritage Sites (Jiuzhaigou, Huanglong, and Three Parallel Rivers), a UNESCO Global Geopark (Mount Kunlun Geopark), and a UNESCO Global Geopark candidate (Cambra Geopark). All five international destinations of geotourism are embedded in the grids with a very high or high GI, including Mt. Min, Mt. Hengduan, Mt. Kunlun, and the Xining area. The geodiversity of the Xining area is the most remarkable within the TP, and two National Geoparks are located in the region. The north of Lhasa area owns the Yangbajin National Geopark, which is distinguished by its unique geothermal landscape. Furthermore, the Yamzho Yumco Lake and the Namucuo Lake are famous geotourist attractions in the Lhasa area. The Pamir Plateau also features a very high GI but lacks well-known geotourism projects. However, Xu et al. [76] described the Outstanding Universal Value (OUV) of the Pamir Plateau through a series of global comparisons and concluded that the aesthetic, geological, and biodiversity values of this area meet the criteria of UNESCO World Natural Heritage Sites. The slow development of tourism in the Pamir plateau may be caused by poor accessibility, while the geotourism potential is exceptional. Thus, geodiversity should be considered as a parameter for the evaluation of regional geotourism potential as elaborated by Chrobak et al. [77].

5.4. Scales and Comparisons of Geodiversity

The definition of scales in geodiversity assessment still has no consensus among scholars. Studies of different scales should be targeted for different purposes. Large-scale geodiversity assessment should be considered as the basis of regional geoconservation, in order to discover nature reserves and geotourism areas. Mid and small-scale geodiversity evaluation may be used for local land management planning and geopark construction. It is difficult to compare the results of studies with each other at different scales. The unit area of the grid in a large-scale study may be larger than the entire study area in a small-scale study. For example, Hjort and Luoto used 500 m × 500 m grids to evaluate geodiversity and included the diversity of slope aspect [78]. However, in our study, all kinds of slope aspects exist in almost every 50 km × 50 km grid. Therefore, slope aspect may not be suitable in huge or regional scale studies. Based on the same evaluation parameters and grid size, it is possible to compare the geodiversity of TP with that of other plateaus in the world. Nevertheless, other plateaus in the world, such as the Ethiopian Plateau and the Mexican Plateau, do not cover such a large area as the TP. In the geodiversity assessment of these plateaus, higher accuracy data and smaller grid size would be used in the assessment of geodiversity, causing the results that are no longer comparable to the results of the TP. Therefore, the basis for comparing geodiversity among different regions is to reach a consensus on grid size and evaluation parameters for different scales. It is crucial and meaningful to propose a global standardized geodiversity evaluation system in future research.

6. Conclusions

The TP is actively developing its geotourism, but the research on its geodiversity is lacking. This study assessed the spatial distribution characteristics of geodiversity in the TP and developed a quantitative assessment method for huge geographic units. All abiotic elements utilized to measure geodiversity are common and easily accessible, which contributes to the unification of geodiversity assessment methods. The geosites, which contain mineral, geothermal, geohazard, and paleontological sites, were evaluated as a geo-group in this study to represent the diversity of interdisciplinary elements that are often neglected in geodiversity assessment.
The geodiversity of the TP exhibits characteristics of higher GI at the edges and lower GI in the interior. The areas with very high GI mainly occur in the Pamir Plateau, Mt. Qilian, the Xining area, Mt. Hengduan, and the Lhasa area. Among them, the Xining area has the largest distribution of very high GI in the TP. The Qiangtang Plateau and the Hoh Xil nature reserve characterize a moderate geodiversity. The Qaidam Basin, the Qingnan Plateau, and the South Tibet region are areas with a low concentration of GI.
This study concluded the following opinions: (1) geodiversity could represent the amount of regional geo-information, but only includes those elements that have been discovered and cognized by humans. (2) Quantitative assessment of geodiversity on large scales is a limited indicator of the richness of landscapes. (3) Geodiversity should be considered as a parameter in the evaluation of geotourism potential areas. As summarized, the quantitative assessment of geodiversity has identified potential areas of great value for geotourism, such as the Pamir Plateau. In future studies, a small-scale geodiversity assessment for areas with high geodiversity but are not yet developed for geotourism would be an effective approach to explore new geotourism sites.
Grid is still an effective tool for the quantitative assessment of geodiversity. Its advantage is that it can be adjusted according to the size of the study area and the scale of the data. However, the study area is often irregular. Grids at the edge of the study area are reduced in size by cropping, which will lead to the loss of geodiversity within the remnant grids. This is the reason why some grids with very low GI occur at the edge of the TP. This problem can be avoided if the fishnet is covered first for geodiversity assessment, and then the nets are clipped by the study area boundaries. However, the TP has a long national boundary, and there are still limitations in the standard and acquisition of data.

Author Contributions

Conceptualization, T.R.; methodology, T.R.; formal analysis, T.R. and S.X.; investigation, T.R. and Z.Y.; writing—original draft preparation, T.R.; writing—review and editing, T.R., Y.L. and S.X.; visualization, T.R. and Y.T.; supervision, Z.Y.; All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by the Second Tibetan Plateau Scientific Expedition and Research Program, grant number 2019QZKK1004.

Conflicts of Interest

The authors declare that no conflict of interest.

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Figure 1. Location of the study area. (a) Location on the earth. (b) Location in China (source: GS(2020)4619). (c) Map of the study area: 1. Pamir Plateau; 2. Karakoram; 3. Himalaya; 4. Mt. Hengduan; 5. Mt. Min; 6. Mt. Qilian; 7. Mt. Altun; 8. Mt. Kunlun; 9. Qiangtang Plateau; 10. Gangdise; 11. Nyainqentanglha Range; 12. Qingnan Plateau; 13. Qaidam Basin; 14. Hoh Xil; and 15. South Tibet region.
Figure 1. Location of the study area. (a) Location on the earth. (b) Location in China (source: GS(2020)4619). (c) Map of the study area: 1. Pamir Plateau; 2. Karakoram; 3. Himalaya; 4. Mt. Hengduan; 5. Mt. Min; 6. Mt. Qilian; 7. Mt. Altun; 8. Mt. Kunlun; 9. Qiangtang Plateau; 10. Gangdise; 11. Nyainqentanglha Range; 12. Qingnan Plateau; 13. Qaidam Basin; 14. Hoh Xil; and 15. South Tibet region.
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Figure 2. Modified maps for quantitative assessment of the TP. (a) Hydrology map of the TP, based on [66] (b) Pedology map of the TP, based on [67] (c) Landform map of the TP, based on [68], and (d) Geology map of the TP, based on [69].
Figure 2. Modified maps for quantitative assessment of the TP. (a) Hydrology map of the TP, based on [66] (b) Pedology map of the TP, based on [67] (c) Landform map of the TP, based on [68], and (d) Geology map of the TP, based on [69].
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Figure 3. Modified map of geosites in the TP.
Figure 3. Modified map of geosites in the TP.
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Figure 4. Examples of diversity scores; the large-size numbers are the diversity score for each grid, the small-size numbers show the process of element counting (a) Hydrology. (b) Geosites.
Figure 4. Examples of diversity scores; the large-size numbers are the diversity score for each grid, the small-size numbers show the process of element counting (a) Hydrology. (b) Geosites.
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Figure 5. Maps of normalized diversity value for each geogroup. (a) hydrology. (b) pedology. (c) landform. (d) elevation. (e) geology. (f) geosites.
Figure 5. Maps of normalized diversity value for each geogroup. (a) hydrology. (b) pedology. (c) landform. (d) elevation. (e) geology. (f) geosites.
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Figure 6. Spatial pattern of geodiversity in the TP.
Figure 6. Spatial pattern of geodiversity in the TP.
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Figure 7. (a) Visualization of GI based on IDW. (b) Plain between Karakorum and Mt. Kunlun. (c) Cold Lake. (d) Qinghai Lake. (e) Wetland in Ruoergai county. (f) Landscape in Ranwu. (g) West shore of the Yamzho Yumco Lake.
Figure 7. (a) Visualization of GI based on IDW. (b) Plain between Karakorum and Mt. Kunlun. (c) Cold Lake. (d) Qinghai Lake. (e) Wetland in Ruoergai county. (f) Landscape in Ranwu. (g) West shore of the Yamzho Yumco Lake.
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Table
Table 1. The information of hydrological data.
Table 1. The information of hydrological data.
ElementScale/
Resolution		SourceAccess Date
Glacier30 mTPDC (http://www.tpdc.ac.cn) 15 June 2022
Lake>1 km2 (area)TPDC (http://www.tpdc.ac.cn) 15 June 2022
Drainage1:1,000,000NESSDC (http://lake.geodata.cn) 16 June 2022
Groundwater 1:5,000,000IHEG (http://www.iheg.cgs.gov.cn/) 21 June 2022
1:12,000,000Geological Atlas of China
Table
Table 2. The data information of geosites.
Table 2. The data information of geosites.
ElementScaleSourceAccess Date
Mineral resources1:5,000,000IMR (http://www.imr.cgs.gov.cn/) 25 June 2022
Fossil remains1:4,000,000GeoCloud (https://geocloud.cgs.gov.cn) 25 June 2022
Volcanic crater1:12,000,000Geological Atlas of China
Hot spring1:5,000,000IHEG (http://www.iheg.cgs.gov.cn/) 27 June 2022
Geohazards1:5,000,000CIGEM (http://www.cigem.cgs.gov.cn/) 28 June 2022
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Rong, T.; Xu, S.; Lu, Y.; Tong, Y.; Yang, Z. Quantitative Assessment of Spatial Pattern of Geodiversity in the Tibetan Plateau. Sustainability 2023, 15, 299. https://doi.org/10.3390/su15010299

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Rong T, Xu S, Lu Y, Tong Y, Yang Z. Quantitative Assessment of Spatial Pattern of Geodiversity in the Tibetan Plateau. Sustainability. 2023; 15(1):299. https://doi.org/10.3390/su15010299

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Rong, Tianyu, Shuting Xu, Yayan Lu, Yanjun Tong, and Zhaoping Yang. 2023. "Quantitative Assessment of Spatial Pattern of Geodiversity in the Tibetan Plateau" Sustainability 15, no. 1: 299. https://doi.org/10.3390/su15010299

APA Style

Rong, T., Xu, S., Lu, Y., Tong, Y., & Yang, Z. (2023). Quantitative Assessment of Spatial Pattern of Geodiversity in the Tibetan Plateau. Sustainability, 15(1), 299. https://doi.org/10.3390/su15010299

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