1. Introduction
Due to the special topography, the exploitation of resources and economic development in mountainous areas have been limited by the fragile ecological environment [
1]. The unreasonable exploitation of resources and the environment has led to an incompatibility between people and mountainous areas. As urban construction in China continues to expand, the state has increased efforts to protect cultivated land, resulting in difficulties in balancing development and protection [
2]. There is a need to assess the suitability of mountainous areas to be used as construction land and to identify the spatial distribution of land suitable for construction and land which is not to allow for the expansion of urban development spaces and identification of high-quality cultivated land [
3]. Through such means, a foundation can be laid for the spatial control of national land resources, the sustainable utilization of land resources and agricultural production. Evaluation indicators and research methods regarding the suitability of land for construction in mountainous areas are regarded as highly significant by relevant scholars. The assessment factors vary slightly depending on the research field and focus and can be divided into two main categories. The first category is assessment of the suitability of the land for construction based on key factors. For instance, Bagheri [
4] combined ArcGIS and the D-AHP model to identify the risk zone of Kuala Terengganu, an eastern coastal city of Peninsular Malaysia, and constructed a land-use suitability map for disaster management. The other is the exploration of the suitability of land for construction based on selected factors, such as natural factors, ecological factors, social traffic, economic development and population density [
5,
6]. As an example, Ustaoglu [
5] used ArcGIS and multicriteria assessment (MCA) to assess the suitability of land for urban construction in Pendik in eastern Istanbul, Turkey based on indicators such as geophysical features, accessibility, built-up areas and infrastructure, vegetation and other green and blue facilities. The focus of existing research has largely been on the evaluation of the suitability of land for construction in mountainous areas, with the aim of improving the evaluation method and enriching evaluation cases. However, the application value of suitability evaluation has not been fully explored. Therefore, continuous improvement of evaluation indicator systems and methods regarding the suitability of land for construction is worthy of additional attention, in addition to further expansion of the application field.
As one of the most common and threatening geological hazards, landslides primarily occur in mountainous areas due to the complex terrain, geological conditions and human engineering activities [
7]. Landslides easily cause significant losses to towns because of the high susceptibility, frequency and speed thereof [
7]. According to statistics, during the period from 2014 to 2018, landslides killed 4914 people, rendering 27,110 people homeless and resulting in asset losses totaling approximately USD 2.1 billion [
8]. As a typical area in the Three Gorges reservoir area, Hechuan District in Chongqing is characterized by a large number of mountains and hills, with frequent landslides as the main geological disaster [
9]. A series of explorations of landslide prediction methods have been conducted by scholars in the Three Gorges reservoir area [
10]. As reported by the Hechuan District Land Resources and Housing Administration, new landslide sites develop in the area every year, none of which is within the original key monitoring areas. Thus, the exploration of machine learning methods based on landslide susceptibility in fragile ecological and geological environments will facilitate accurate identification of disaster sites and highly disaster-prone areas and is of considerable significance for the safety of local residents, development of national land and ecological protection. Landslide susceptibility based on machine learning has been extensively adopted in research on disaster prevention and mitigation in urban areas and towns. Several examples include random forest (RF) [
11], logistic regression (LR) [
12] and artificial neural network (ANN) models [
13,
14]. Such methods possess significant advantages over conventional methods in terms of assessment, verification and prediction of landslide susceptibility [
9]. Among the methods, random forest is highly accurate and efficient and can process high-dimensional data while maintaining a high level of data accuracy, even if features are missing or unbalanced [
8]. Depending on the geographical location, climatic conditions and the amount of available data on the researched area, an appropriate model should be selected to obtain satisfactory evaluation results. The modelling of landslide susceptibility has been widely used due to the generalization ability thereof. Analytical hierarchy process (AHP) analysis, which is used to evaluate the suitability of land for construction, is also a common weight evaluation model and was found to be applicable to the present study [
15].
In summary, scholars have conducted a series of studies on landslide susceptibility and the suitability of land for construction. However, there has been a scarcity of research on the suitability of land for construction in mountainous areas with frequent disasters based on the foregoing two aspects. Thus, empirical research with in-depth and extensive discussion is needed, with a particular focus on determining how to evaluate the suitability of land for construction in mountainous areas from the perspective of disasters, as well as key problems, such as the improvement of evaluation indicator systems, evaluation criteria and technical methods concerning the suitability of land for construction from the perspective of disasters in mountainous areas.
As such, the Hechuan District of Chongqing was investigated, and random forest and AHP were adopted to explore the suitability of land for construction in mountainous areas from the perspective of landslide susceptibility. First, 754 historical landslide sites were sampled in the Hechuan District according to the theoretical method of landslide susceptibility assessment, and a landslide susceptibility model was established based on the RF model of Hechuan District; then, on the basis of the disaster safety model, an evaluation model of the suitability of land for construction in mountainous areas was established, considering social, ecological and economic factors.
Finally, the suitability for construction of different areas was rated, and the spatial distribution of land suitable for construction was revealed, providing a scientific basis for the evaluation of the suitability of land for construction in Hechuan District and constructing an accurate, operatable and generalizable evaluation model. By constructing an accurate, operatable and generalizable evaluation indicator system and research method, the present study provides a scientific basis for evaluation of the suitability of land for construction in Hechuan District, offering a reference for planning and construction of other mountainous areas with frequent disasters.
4. Results
4.1. Safety Level
The q-value of the mean Gini coefficient in the random forest explains the contribution of the factor, that is, the degree of influence of the degree factor on the landslide. The results show that the three factors of average multiyear rainfall, elevation and lithology had the greatest influence on landslides (Figure 8).
Landslides are a typical dichotomous problem, and the confusion matrix can be used to analyze the accuracy of the model.
Table 6 shows the confusion matrix of the entire data set of the random forest model. According to the confusion matrix, the constructed random forest model exhibited a high degree of accuracy and high predictive value (
Table 6).
In addition, the landslide susceptibility results constructed by the RF model were assessed by means of ROC analysis. In this research, ROC curve analysis was performed in R Studio software using the R language. The AUC values for the training, test and all samples were 0.999, 0.756 and 0.989, respectively (
Figure 4). The test AUC values were greater than 0.7, indicating that the model prediction accuracy was high and stable.
To evaluate the likelihood of landslides in the study area, a random forest model was applied to each grid in the area. The results of the random forest model were imported into ArcGIS 10.6, classified using the natural breakpoint method and adjusted according to the procedures described in prior research [
8,
22]. Landslide susceptibility was classified into the following five levels: extremely low, low, medium, high and extremely high susceptibility areas (
Figure 5 and
Table 7).
The majority of the regions in Hechuan District were found to have an extremely low or low landslide risk level. High-susceptibility zones are primarily situated in the northeast and near water systems. Landslides are rare in hilly basins with gentle terrain, and historical landslide areas correlate with the landslide susceptibility zones. With an enhancement in landslide susceptibility, the proportion of areas at each level, except the extremely high level, decreased. The number of landslides increased gradually, with the density strengthened, and there were a total of 753 landslide spots. The combined region of low and very low susceptibility accounts for 76.58% of Hechuan District’s land area. The total landslides occurred in 15.25% of the total area. Landslides were possible in 74.14% of the land area, but regions of high and extremely high susceptibility accounted for only 9.01% of the land area.
As a crucial measure, extremely high-susceptibility areas should be largely concentrated along river valleys and mountains, which, to a considerable extent, affect urban development. The area of high or extremely high susceptibility spans 208.47 km2, accounting for 9.01% of the total area, mainly distributed along the Qujiang and Jialing Rivers, including Xianglong Town, Shuanghuai Town, Xiaomian Town, Shitan Town, Guandu Town, Yunmen Subdistrict, Shuangfeng Town, Tongxi Town, Yanjing Street and Laitan Town. Such areas are strongly affected by surface water and rainfall. The rise and fall of river levels can result in landslide disasters during heavy rain. Landslide disasters in such areas induce changes in the courses of rivers; endanger infrastructure, residential areas and arable land; and have significant social impacts. The area of medium susceptibility spanned 333.62 km2, accounting for 14.41% of the total area. Here, landslide disasters endanger infrastructure, residential areas and arable land, in addition to producing significant social impacts. The low-susceptibility area occupies 709.95 km2, accounting for 30.67% of the total area, whereas the extremely low-susceptibility area spans 1062.88 km2, accounting for 45.91% of the total area. Landslide disasters in such areas mainly threaten general facilities, residential areas and cultivated land, with a low level of risk. Differing from high- and extremely high =0susceptibility areas, low- and extremely low-susceptibility zones are extensively spread at lower altitudes in riverbank basins and around central metropolitan areas.
4.2. Suitability Evaluation of Construction Lands
4.2.1. Analysis of Evaluation Results
Given the complexity of mountainous areas, there are difficulties associated with determining the weights of evaluation factors using a quantitative assignment method. Although the judgement of expert experience has a certain degree of flexibility, the subjective assignment method can effectively adjust the weights for the land conditions of different regions, making the regional evaluation results more relevant and reliable. The safety factor in this research had a considerable impact in mountainous areas and was delineated as 33.377%. The natural factor, as the resource endowment of mountainous towns, involved more factors and had the highest weight. The social factor gradually emerged as a significant factor for evaluation. A veto system was adopted for the influence range indicator of the ecological factor, and the area to which it belongs was directly classified as a non-construction zone. Therefore, only the weight was calculated with the indicators using the hierarchical analysis method. The weighting values for the indicators of suitability of land for construction in mountainous areas were obtained with reference to previous studies
There are two types of indices for a judgement matrix: an index of consistency (CI) and a random consistency index (RI). The value ratios of the suitability, nature and society factors of construction land with respect to the consistency of the matrix were calculated to be 0.052, 0.097 and 0.000, respectively. All of the values were less than 0.1, thereby passing the consistency test and demonstrating that the results of the evaluation index weighting were reasonable (
Table 8,
Table 9,
Table 10 and
Table 11).
According to the calculated weight results, as well as the classification and assignment of each index, ArcGIS was applied to superimpose a raster layer of each factor and to remove ecological red line space, thereby allowing for five levels of suitability for construction land in Hechuan District to be obtained: the most suitable area (1), more suitable area (2), basically suitable area (3), unsuitable area (4) and prohibited construction area (5) (
Figure 6).
4.2.2. Suitability Zoning of Construction Lands
Using the ArcGIS10.6 platform, the aforementioned landslide susceptibility results and natural, social and ecological factors were superimposed and calculated according to Equation (3), with the results divided into the following zones according to the natural breakpoint method: prohibited construction, unsuitable, basically suitable, more suitable and the most suitable [
2,
30]. The ecological red line space was superimposed and divided into prohibited construction zones, and the final results of the suitability assessment of construction land in Hechuan District were obtained.
The suitability for construction was found to be good in Hechuan District. The suitable area spanned 2002.07 km2, accounting for 84.28% of the total area, and the most suitable land was distributed in urban areas, where the three rivers meet or around small towns. The most suitable area spanned 637.18 km2, accounting for 26.82% of the total area, and was mainly distributed in valley areas along the Jialing and Fujiang Rivers. Located at the confluence of many rivers, Yunmen Subdistrict has a low elevation and flat terrain, with sufficient water sources and convenient transportation. The more suitable area spanned 812.25 km2, representing 34.19% of the total area. Such areas were divided into tracts in Zhongyunmen Subdistrict, Qiantang Town, Dashi Subdistrict, Heyangcheng Subdistrict and wide, hilly areas in Nanjin Town and Caojie Subdistrict. Most of the areas that cover such land are 220 m–350 m above sea level. The urban construction lands with basic suitability occupied 552.64 km2, accounting for 23.26% of the total area, and were primarily found in the hilly regions outside the Huaying and Longduo Mountains. The less suitable areas spanned 241.90 km2, accounting for 10.18% of the total area, scattered in the mountains with high elevations and were evenly distributed between Sanmiao Town, Yanwo Town, Sanlang Town, Longfeng Town, Taihe Town, Shayu Town, Guandu Town, Xianglong Town and Shuanghuai Town. The prohibited construction land covered an area of 131.65 km2, accounting for 5.54% of the total area, and mainly distributed in the southeast area, the Huaying mountainous area and in regions in the ecological red line area, where there is the highest forest coverage.
6. Conclusions
In this research, the suitability of land for construction in mountainous areas was evaluated based on landslide susceptibility, and an indicator system was constructed that considers the four dimensions of safety, nature, society and ecology. In response to the drawbacks of existing methods, an attempt was made to identity the factors of landslide susceptibility using machine algorithms based on the number and spatial location of each indicator. Through such means, the rating of suitability of land for construction in mountainous areas was explored. The case study of the foregoing evaluation framework and method was conducted in the Hechuan District of Chongqing. The research results were as follows:
- (1)
The average accuracy of the tenfold cross-validation training set landslide data reached 0.978; the accuracy of the test set reached 0.913; the accuracy of the confusion matrix reached 97.2%; and the AUC values of the training test and all samples were 0.999, 0.756 and 0.989 respectively. The historical landslide sites in Hechuan District were mostly concentrated in highly susceptible areas, where the spatial areas of land with high landslide susceptibility and very high landslide susceptibility were 1.98 km2 and 2.22 km2, respectively, accounting for 2.47‰ and 6.53‰ of the study area. The areas with high landslide susceptibility were mainly concentrated in the south and southeast valleys and near the water system, whereas landslides were less frequent in the gentle hilly basin.
- (2)
The suitability of land for construction in mountainous areas was found to be most influenced by landslide susceptibility, the distance from roads and the distance from built-up areas. Furthermore, the annual average rainfall, elevation and lithological factors were significant factors influencing landslides in such areas. The suitability of land for construction in mountainous areas near the main city was promoted by locational advantages and restricted by disasters.
- (3)
Under the constraints of landslide susceptibility, the Hechuan District has considerable potential land reserves for construction in terms of more suitable areas and the most suitable areas (accounting for 61.01% of the study area) for construction. In terms of space, the more suitable and most suitable areas for construction were mainly distributed in the urban area, where the three rivers converge and the surrounding areas of small towns, showing a spatial distribution pattern characterized by a high central part and two low sides. The basically suitable areas for construction were mainly distributed at the buffer space on the periphery of the more suitable areas for construction.
Compared with existing research, the proposed evaluation indicator system and method with respect to the suitability of land for construction represent clear academic concepts, reflecting the essence and practical value of the suitability of land for construction in mountainous areas. The indicator system is simple and clearly structured with complete coverage, providing a basis for research and practice concerning the suitability of land for construction in other mountainous areas. The evaluation method is precise, easy, flexible and practical. In exploring a more accurate and convenient evaluation framework and method and extending the application scope of suitability evaluation in mountainous areas, the present study overcomes the issues encountered in previous research related to the suitability of land for construction in mountainous areas based on the perspective of disasters. However, the presented indicator system and evaluation method are only applicable to towns in mountainous areas with frequent disasters, and the validity thereof in other types of land and areas should be further verified.