Study on the Spatial Pattern Characteristics and Influencing Factors of Inefficient Urban Land Use in the Yellow River Basin

Abstract

In order to realize the optimization of urban spatial patterns in the Yellow River Basin, a study on the inefficient use of urban land in the Yellow River Basin was carried out. In this study, Dali County and Hancheng County in Weinan City are selected as the research areas. Firstly, the analytic hierarchy process is used to build a comprehensive evaluation system for the identification of inefficient land in stock; secondly, the standard deviation ellipse method and spatial kernel density estimation method are used to quantitatively analyze the spatial distribution characteristics of inefficient land. Thirdly, the contribution model is used to analyze the influencing factors of inefficient land use. Finally, corresponding redevelopment suggestions are given for each type of inefficient land. The results show that Dali had the smallest area of inefficient land; second is Xincheng Street in Hancheng City; and Longmen Town, Hancheng City has the largest area. The distribution of inefficient land in Dali and Longmen Town in Hancheng City is relatively balanced, while the distribution of all kinds of inefficient land in Xincheng Street in Hancheng City is not concentrated. The density of the road network is the most important contributing factor to inefficient land use in the study area. This paper comprehensively uses the methods of economics and geography to study inefficient land use, quantifies the spatial-temporal characteristics and influencing factors of land use units, explores the spatial patterns of land use and enriches the research into relevant theories.

1. Introduction

Cities and towns are important space carriers of human social, economic and cultural activities [1]. Since the reform and opening up of China, the rapid process of urbanization, industrialization and informatization in China has driven the rapid development of the social economy and the great improvement in people’s living standards and thus promoted the rapid expansion of urban scale. However, the development mode of ignoring connotation and tapping potential adopted in the expansion of urban scale inevitably produces a large area of inefficient urban land [2]. Under the background of ecological civilization construction and new urbanization, China has implemented the strictest cultivated land protection system and ecological red line control. Therefore, the extensive land use mode of the outward expansion of the urban development boundary has been difficult to sustain and the contradiction between the supply and demand of urban construction land has become increasingly prominent. Low land use efficiency has become an obstacle to the sustainable development of urban society and economy [3]. Land use planning is an important part of sustainable urban planning [4]. China’s land use planning practice has developed through exploration and has played an important role in protecting arable land, optimizing land resource allocation and promoting sustainable economic and social development [5]. Promoting the economical and intensive use of land, implementing urban renewal and shifting from incremental expansion to the stock of inefficient land, tapping this potential will become the best choice for the development of urban land space [6].

Inefficient urban land refers to the urban stock construction land that has been determined as construction land by the second national land survey, with clear ownership, no disputes and legal disputes, but a scattered layout, extensive utilization, unreasonable use and dilapidated buildings [7]. Inefficient land use is reflected in the sustainable development of the industry, ecological security, land use status, income status, use allocation and other aspects, mainly manifested in unreasonable use (such as not being in line with the plan), backward production capacity (such as not being in line with the national industrial policy), non-compliance with environmental protection requirements (such as high energy consumption, high emissions and high pollution), extensive land use (such as a low plot ratio and building coefficient) or poor income (such as low average tax per m² and low average industrial output value of the land).

In this new situation, in order to ensure the national strategic goal of serving the high-quality development of the Yellow River Basin [8], carrying out research on inefficient land use in cities and towns in the Yellow River basin can provide theoretical and technical support for the redevelopment strategy for inefficient land in regional cities and towns and the preparation and implementation of relevant planning, help address inefficient land use in cities and towns in the Yellow River Basin, increase the effective supply of urban construction land, realize the economical and intensive use of land, improve the sustainable guarantee ability of land for economic and social development, promote the optimization of land use structure and enhance the driving force of urban and rural economic development.

Based on the results of the third national land survey, according to the data on inefficient residential land, inefficient industrial land and inefficient commercial land in Dali County and Hancheng County, Weinan City, this study uses the GIS spatial analysis method to quantitatively analyze the spatial distribution characteristics of inefficient urban land at the street and town scales and analyzes the influencing factors of the three types of inefficient land in order to improve the allocation efficiency of land resource elements in the study area. It aims to establish the current situation of inefficient land use in cities and towns in typical regions, deeply explore its main influencing factors, formulate technical methods and solutions for the investigation and evaluation of inefficient land use in cities and towns in the Yellow River Basin (Shaanxi section), improve the optimization of urban spatial patterns in the Yellow River Basin (Shaanxi section), save and intensively use land, achieve high quality local economic and social development, provide a reference for the practical application of inefficient land use in similar regions across the country and perform a theoretical exploration of the high-quality development of cities against the background of stock planning. The research area of this study is shown in Figure 1 below.

2. Literature Review

The research on inefficient land use in cities and towns is based on the continuous development of the social economy with the transformation of current times. Some dilapidated intercity villages, old factories and mines and old towns have come to represent inefficient land use in cities and towns for various reasons and secondary planning and development are needed to help them meet the new requirements for the development of urbanization.

Research on inefficient land use in cities and towns started late in China. The redevelopment of inefficient urban land at the government level began with the “three old” transformation first carried out in Guangdong Province in 2007 and went through the stages of ten provincial-level pilot explorations in Shanghai, Jiangsu, Fujian, etc., and then comprehensive national promotion [9]. With the bottleneck of urban land expansion, inefficient urban land use has gradually attracted the attention of scholars, leading to comprehensive research from the perspectives of geography, land management, urban and rural planning, human settlements, urban ecology and so on. Zhang Saisai took Ningbo as the research area and analyzed the spatial patterns of inefficient land in cities and towns at the township scale [10]. Gu Yuewen and others are committed to research on the renewal mechanism of inefficient land use in stock, based on the perspective of property rights [11]. Peng and Yunfei [12] studied the continuous process of the transformation from construction land to ecological land and finally argued that the model of Shenzhen can improve the ecological environment and promote the sustainable use of land. Ye, Yuyao [13] developed a method to simulate the high-resolution economic efficiency of construction land and this study revealed the temporal and spatial dynamics of the process, providing a scientific reference for informed land use planning and policymaking. Bai and Yang [14] combed the adjustment policies of inefficient urban land use in China, compared and verified the analysis process and provided a reference for the adjustment and improvement of relevant policy systems in China. Wang and Xiangdong [15] argued that the measurement and analysis of urban industrial land use efficiency in China were not accurate and in-depth. There is still a lack of research on efficiency loss and intensification potential and their relationship. A quantitative model was constructed to measure and evaluate the intensive potential of China’s urban industrial land use and the efficiency loss of China’s three major urban agglomerations was calculated using stochastic frontier analysis. Wang and Jingyi [16]’s reasonable evaluation of urban land’s intensive use has become a hot spot in urban research. By constructing a unified evaluation framework of urban land intensive use, the application of this analysis framework was empirically tested by using the panel data of Chongqing, China. The final research results show that the urban land intensive use evaluation framework based on the stochastic frontier analysis model of decomposition technical efficiency can better integrate the intensive land use evaluation and factor analysis process. Pang and Yayuan [17] used the super SBM model to estimate construction and cultivated land use efficiency in Shandong Province and analyzed its temporal and spatial changes. The results show that the efficiency of construction land generally fluctuates and rises and there is still room for efficiency improvement in the future. Lu [18] studied the impact of transportation infrastructure on land use efficiency. Niu [19] studied the relationship between urbanization and land use. Wang and Aiping [20] studied the relationship between smart city construction and green land use efficiency. Lu and Xiao [21] studied the green utilization efficiency of cultivated land in the Yellow River Basin. Tang [22] studied the efficiency of urban land use under the guidance of green development. Qiu [23] studied the evaluation of land use conflict and its temporal and spatial characteristics. Yansui and Liu [24] studied the allocation efficiency of construction land. Li [25] studied the relationship between land use and economic spatial spillovers in urban agglomerations. Lu [26] studied the impact of high-speed rail on urban land use efficiency. Zhou [27] studied the mode and mechanism behind the process of land use change. Dai [28] studied the spatial distribution of different types of industrial land transfer. Chen Yi [29] argued that rapid economic growth and the rapid development of urbanization have profoundly changed the space–time mode of land use in China, especially in that construction land is the carrier of all economic activities. The efficiency of construction land not only affects regional economic development, but also affects regional sustainable development. Zhang and Yiwen [30] argued that urban and rural construction land is an important material basis and spatial carrier for urban and rural development, carrying multiple composite functions such as population, economy, society and ecology, and is an important focus for the implementation of the strictest, most economical and intensive land use system. Zhou and Yue [31] stated that the utilization efficiency of construction land is of great significance for optimizing the allocation of regional resources and guiding the sustainable development of the regional social economy. Xu and Huixiao [32] argued that construction land is the spatial carrier of urban economic and social activities and its utilization efficiency is an important basis for regulating the expansion and allocation of construction land. Zhang and Lixin [33] argued that the efficient and rational use of urban land is crucial to the sustainable development of the urban economy. The spatial imbalance of land use efficiency in different cities is of great significance to the use of urban land resources. Liguoyu [34] argued that, under the premise of energy conservation and emission reduction, continuously improving the efficiency and quality of urban construction land use is a key scientific problem to be solved urgently. The research shows that some regions with high-speed economic development are often accompanied by the excessive utilization of resources and a high level of greenhouse gas and pollutant emissions and the development mode of high input, high growth and high emissions needs to be further optimized. Therefore, we should strictly control the supply of construction land in large cities, limit the speed and scale of expansion of medium and small towns and encourage the redevelopment of inefficient urban land. Liang Jianfei [35] argued that the utilization efficiency of urban construction land represents the coupling strength between the urban system and construction land system and is an important indicator to measure the rationality of regional resource allocation and the efficiency of urbanization development quality. Zhou Qingfeng [36] stated that the overall utilization level of urban construction land in China is still at a low level. Meanwhile, Wangqiaoling [37] demonstrated that the overall utilization efficiency of construction land in Jiangxi Province is at a medium level. Wei Jianfei [38] analyzed the spatial pattern evolution and coupling characteristics of construction land use efficiency and the economic development level at the municipal scale in China. The results show that, from the perspective of the spatial differentiation pattern, Beijing and Shanghai are the two cores of construction land use efficiency and economic development level, forming high-value prominent areas; the median area is distributed in Zhengzhou, Wuhan and other high urbanization areas in the central part of China and low-value areas are continuously distributed in the western region.

In addition, this paper also explores the international experience in dealing with spatial patterns of land use. Foreign studies focus on the synchronization of land use and land planning implementation [39], the use of indicators to assess the impact of spatial planning policies [40], the role of spatial data of land use in integrated planning [41], the search for sustainable land use planning solutions in the field of water management in spatial planning [42] and the integration of spatial planning and land management [43].

To sum up, in terms of specific research methods, due to the heavy workload of on-site investigations of inefficient land and difficulties in data acquisition, previous studies mainly focused on comprehensive qualitative research, while quantitative analysis based on survey data and redevelopment suggestions for inefficient land are relatively rare and the analysis and research on spatial distribution characteristics and influencing factors are even weaker.

For a long time, the phenomenon of inefficient use of urban construction land in China has been relatively common. Against the background of new urban construction, by establishing a comprehensive evaluation system for the identification of inefficient land in stock, exploring the spatial distribution law of inefficient land, analyzing the influencing factors of inefficient land and comprehensively promoting the redevelopment of inefficient land in cities and towns, a new path is found to deal with the unreasonable use of urban construction land and improve the level of economical and intensive land use. This represents an important measure in achieving high-quality leapfrog development led by the construction of ecological civilization.

3. Research Method

Taking into account the distinctive topographic and geomorphic characteristics of the Yellow River Basin and the Loess Plateau, the large stock of and demand for construction land, the high level of local economic and social development and the developed county economy, Dali city center, Xincheng Street in Hancheng City and Longmen Town were selected as the study areas.

3.1. Data Source and Processing

The research data included urban master planning, land use master planning, cadastral database and socio-economic statistics. The data on social and economic development came from the statistical yearbook of Shaanxi Province and the statistical data of official websites. As other types of inefficient land use are directly affected by policies and superior planning, this study focused on inefficient residential land, inefficient industrial land and inefficient commercial land. Using Google Scholar, Elsevier and Web of Science, we reviewed about 200 papers and cited 48 of them.

3.2. Index Weight Calculation Method

The analytic hierarchy process, also known as AHP, is a systematic decision-making method combining quantitative and qualitative analysis. The richness of the connotation of inefficient land in stock determines the universality of the evaluation dimension of the prioritization of inefficient land in stock. Different index layers contain different influence factors, so the determination of the index weight of evaluation priority classification is more suitable for the analytic hierarchy process [44]. In this paper, the priority of low-efficiency land in stock was taken as the target layer and the criteria layer and index layer were established in turn to comprehensively build a comprehensive evaluation system for determining the priority of low-efficiency land in stock.

3.2.1. Establish the Hierarchical Structure

According to the established priority evaluation index system for the identification of inefficient land in stock, it was determined that the identification priority was classified as the overall goal and the index layer constructed the index system according to different types of inefficient land.

3.2.2. Construct a Pairwise Discriminant Matrix

A discriminant matrix directly determines the objectivity and accuracy of weight determination results, which is the key point of the AHP method. In this paper, the 1–9 scale method was used to compare the indicators, as shown in

Table 1. Saaty scale of the analytic hierarchy process.

Scale	Meaning Description
1	Index I and index J are equally important to the goal
3	Compared with index J, index I is slightly more important than index J
5	Compared with index J, index I is significantly more important than index J
7	Compared with index J, index I is more important than index J
9	Compared with index J, index I is extremely important
2, 4, 6, 8	Intermediate value of the above two adjacent judgments
1/3	Compared with index J, index I is slightly less important than index J
1/5	Compared with index J, index I is less important than index J
1/7	Compared with index J, index I is stronger than index J, which is not important
1/9	Compared with index J, index I is extremely unimportant
1/2, 1/4, 1/6, 1/8	Intermediate value of the above two adjacent judgments

. On the premise of taking the identified priority as the overall goal, the subordinate relationship between each goal and index was evaluated. The specific method involved soliciting opinions from a number of experts on the relative importance of the opinions of each index at the same level and averaging the results of the pairwise comparison of each target and each index at the same level. The discrimination matrix of the target layer and index layer is as follows:

$$A_{ij}=\left(\begin{array}{ccc}{a}_{11}& \cdots & a_{1n}\\ ⋮& \ddots & ⋮\\ a_{m1}& \cdots & a_{mm}\end{array}\right)$$

(1)

where A_ij represents the scale of I factor compared with J factor, A_ij > 0, i, j = 1, 2, 3, …, n.

3.2.3. Computing the Weight Vector and Consistency Test

We used the geometric average method to calculate the eigenvector of each judgment matrix, w = {w_i}, where:

$$W_I={(\underset{}{\overset{}{{\displaystyle {\displaystyle {\prod }_{j=1}^n{a}_{ij}}}}})}^{\frac{1}{n}}$$

(2)

The feature vector was normalized to obtain the weight vector of each corresponding evaluation level. We checked the consistency of the judgment matrix and calculated the consistency ratio. When the ratio was less than 0.1, the judgment matrix was considered to have passed the consistency test; otherwise, the judgment matrix was readjusted [45].

By establishing the evaluation index and adopting the evaluation model, the quantitative evaluation score of inefficient land use was calculated. Combined with the natural discontinuity method, the assessment object was judged as to whether it belonged to inefficient land. The land use type was defined based on the number axis method. The natural discontinuity was used to divide the score section of the comprehensive score of inefficient land evaluation and 20% of the land with the lowest score ranking is judged as inefficient land.

The design of evaluation indicators for inefficient land use in cities and towns should start from the connotation of inefficient land use, comprehensively analyze and summarize the contents involved and scientifically and accurately extract the required indicators. According to the selection principle of evaluation indicators of inefficient land use in cities and towns, guided by the evaluation of inefficient land use and based on the availability of data in the study area, and according to the characteristics of different land use function types, based on the degree of intensive land use, the legal and compliance status of land use and the current situation of land use, from the perspective of building attributes and economic vitality, three sets of evaluation index systems were established according to three aspects of environmental quality, as shown in

Table 2. Identification standards of inefficient residential land.

Type	Sub Dimension Layer	Evaluating Indicator
Inefficient residential land	Inefficient use configuration	Residential land that does not conform to the overall plan of land use and does not belong to the scope of conditional construction areas and allowable construction areas
		Residential land that does not conform to the overall urban planning and the current use is inconsistent with the planned use
	Government focus on remodeling	Residential land included in the shanty town reconstruction and “three old” reconstruction by the government
		Approved but not built residential land

,

Table 3. Identification standards of inefficient industrial land.

Type	Inefficient Type	Evaluating Indicator
Inefficient industrial land	Inefficient use configuration	Industrial land that does not conform to the overall plan for land use and does not belong to the scope of conditional construction areas and allowable construction areas
		Industrial land that does not conform to the overall urban planning and the current use is inconsistent with the planned use
		Industrial land that does not conform to the industrial planning and the current industrial type does not conform to the planned industrial type
	Government focus on remodeling	Industrial land included in shanty town reconstruction and “three old” reconstruction by the government Unsafe industrial land with dilapidated buildings Industrial land that does not meet the requirements of safety production and environmental protection
		Industrial land listed in the category of national prohibition and elimination

and

Table 4. Identification standard of low-efficiency commercial land.

Type	Inefficient Type	Evaluating Indicator
Inefficient commercial land		Commercial land that does not conform to the overall plan for land use and does not belong to the scope of conditional construction areas and allowable construction areas
	Inefficient use configuration	Commercial land that does not conform to the overall urban planning and the current use is inconsistent with the planned use
	Government focus on remodeling	Commercial land included in shanty town reconstruction and “three old” reconstruction by the government Approved but not built commercial land
		Dilapidated and unsafe commercial land

.

3.3. Research Methods of Spatial Pattern Characteristics

We analyzed the spatial pattern of inefficient land use in cities and towns, examined the macro pattern at the overall level according to the categories of all of the inefficient land use patches in the cities and towns included in the survey results, obtained an insight into the meso layout at the county level and explored the micro distribution at the town scale. Our study mainly revealed the sub characteristics of the spatial patterns, including the following steps:

Firstly, the standard deviation ellipse (SDE) method of geographical center distribution measurement was used to reveal the point spatial location and direction characteristics of inefficient land use and pay attention to its density and orientation, so as to form a macro cognition of the spatial pattern of inefficient land use. The calculation formula is as follows, where (SDE_x, SDE_y) is the center of the ellipse and θ is the bearing angle:

$$SD{E}_X=\sqrt{\frac{{{\displaystyle \sum }}_{i=1}^n{(x_i-\stackrel{}{\overline{X}})}^2}{n}}$$

(3)

$$SD{E}_y=\sqrt{\frac{{{\displaystyle \sum }}_{i=1}^{\mathrm{n}}{(y_i-\stackrel{}{\overline{Y}})}^2}{n}}$$

(4)

$$\tan a=\frac{A+B}{C}$$

(5)

$$\mathrm{A}=\left({\displaystyle \sum _{i=1}^n{\tilde{x}}_i^2}-{\displaystyle \sum _{i=1}^n{\tilde{y}}_i^2}\right)$$

(6)

$$\mathrm{B}=\sqrt{{\left({\displaystyle \sum _{i=1}^n{\tilde{x}}_i^2}-{\displaystyle \sum _{i=1}^n{\tilde{y}}_i^2}\right)}^2}+{\left(4{\displaystyle \sum _{i=1}^n{\tilde{x}}_i^2}{\tilde{y}}_i^2\right)}^2$$

(7)

$$\mathrm{C}=2{\displaystyle \sum _{i=1}^n{\tilde{x}}_i^{}}{\tilde{y}}_i^{}$$

(8)

The standard deviation ellipse method is a common spatial pattern analysis method in geography. It can accurately reveal the center, dispersion and direction of the spatial distribution of geographical elements [46]. The central trend and direction trend of different types of urban inefficient land are different. The standard deviation ellipse can distinguish the overall outline and direction characteristics of the spatial distribution of various types of urban inefficient land. The standard deviation ellipse should be composed of the center and rotation angle θ and the standard deviation along the main axis (x axis) and the auxiliary axis (y axis), respectively. The rotation angle represents the main direction of the spatial distribution of each inefficient point; the main axis and the secondary axis represent the degree of deviation of the low efficiency point from the center in the primary and secondary directions, reflecting the centripetality and discreteness, respectively. The difference between the main axis and the auxiliary axis is positively correlated with the strength of directivity. The greater the difference, the stronger the directivity. When the two axes are completely equal in length—that is, they are circular—it means that there is no directional feature; the area and center of the standard deviation ellipse represent the breadth and center position of the inefficient point distribution, respectively. We used arc gis10.2 software to extract the geometric center of various types of urban inefficient land use map spots and used ellipse analysis tools to generate standard deviation ellipses of various types of urban inefficient land use.

Secondly, the spatial kernel density (KD) estimation method was used to explore the morphological characteristics of inefficient land agglomeration. Kernel density analysis is the most widely used nonparametric estimation method in spatial analysis, which is used to calculate the unit density of point elements and line elements in the specified field and can directly reflect the distribution of discrete measured values in the continuous region [47]. The calculation formula is as follows:

$$D=\frac{3{\left(1-scal{e}^2\right)}^2}{\mathrm{\Pi }{r}^2}$$

(9)

where 𝑠 represents the search radius and 𝑡𝑐𝑎𝑚𝑒 represents the ratio of the distance from the point and line object to the grid center point and the search radius.

The results of kernel density analysis were composed of smooth surfaces with large intermediate values and small peripheral values; the grid value represents the unit density of feature distribution and its unit is the reciprocal of the square of the original dataset unit. At the boundary of the field, the density drops to 0 and, at the superposition of the neighborhood, the density values are added. The density value of each output grid is the sum of all core surface values superimposed on the grid.

The inefficient land in stock is mainly composed of dot shaped, banded and massive plots with different scales and small areas. Nuclear density analysis can reveal the distribution and morphological characteristics of discrete inefficient land in the regional scope. In this paper, ArcGIS 10.2 software was used to estimate the nuclear density of the stock of inefficient land. Firstly, the geometric center of the urban inefficient land map was extracted and then the kernel density tool was used to analyze the total inefficient land and the corresponding land distribution density characteristic map was generated.

3.4. Research Methods for Influencing Factors

Based on the various types of inefficient land use in the three study areas studied in this paper, the contribution model was used to calculate the maximum index of the contribution of each plot of inefficient construction land in the three areas and analyze the characteristics of this index. It included statistical analysis of the largest contribution indicators of inefficient residential land, inefficient industrial land and inefficient commercial land in the three towns and the largest contribution sub-dimensions of inefficient construction land in each plot of the three towns. The indicators and weights used in the analysis are shown in

Table 5. Sub-dimension evaluation indicators and their weights.

Sub-Dimension Layer	Evaluating Indicator	Weight Value
Inefficient residential land	Building density	0.35
	Commercial service facilities	0.15
	Scientific and educational style	0.15
	Park and green space	0.10
	Communal facilities	0.05
	Road network density	0.20
	Building density	0.35
Inefficient industrial land	Road network density	0.20
	Idle rate of land	0.45
Inefficient commercial land	Building density	0.65
	Road network density	0.35

.

Based on the measurement of the evaluation value of inefficient land use, the contribution model was used to diagnose the inefficient construction land and its sub dimensions and the main contributing factors were mined. The method is as follows:

$$C_j=\frac{F_j\times I_j}{{\displaystyle \sum _{j=1}^n{F}_j\times I_j}}\times 100\%$$

(10)

$$D_r=\frac{W_r\times K_r}{{\displaystyle \sum _{r=1}^3{W}_r\times K_r}}\times 100\%$$

(11)

In the formula, ij is the factor membership, that is, the ratio of the single factor index value to the target layer value, F_J is the weight of the jth factor to the target layer and C_J is the contribution of the jth factor to the target layer. K_R is the membership degree of the sub dimension, i.e., the ratio of the sub dimension value to the target layer value, W_R is the weight of the rth sub dimension to the target layer and D_r is the contribution of the rth sub dimension to the target layer [48].

4. Analysis of Spatial Pattern Characteristics of Urban Inefficient Land Use in the Study Area

4.1. Analysis of the Current Situation of Urban Construction Land in the Study Area

According to the statistics of the third national land survey, the total land area of Dali’s central urban area is 7329.92 hectares, the total land area of Xincheng Street in Hancheng City is 8511.73 hectares and the total land area of Longmen Town in Hancheng City is 9721.57 hectares. According to the classification of the third national land survey, it is divided into agricultural land, construction land and unused land. According to its regional characteristics, construction land is divided into residential land, commercial land, industrial land and other types of construction land. The details of land use in each region are shown in Figure 2.

4.2. Identification Standard of Inefficient Urban Land in the Study Area

4.2.1. Identification Standard of Inefficient Residential Land

This study adopts a combination of qualitative and quantitative methods. According to the qualitative evaluation method of inefficient land and the identification standard of urban inefficient land, two types of inefficient land, namely, inefficient land use allocation and government focused transformation, are determined first. For residential land, the summary results of qualitative evaluation are shown in Table 5.

Firstly, according to the qualitative evaluation criteria of housing, some plots with inefficient use allocation and key government reconstruction are directly included in the scope of inefficiency and then the remaining individual items are scored separately. In order to ensure the scientific accuracy and authority of the evaluation results as much as possible, the Delphi grade expert scoring method is used to determine the importance of various factors in the construction of the identification index system of inefficient land use. Experts in relevant fields are invited to compare and score the indicators in each level of the evaluation system in combination with theoretical knowledge and practical experience, which is an important basis for determining the weight of evaluation indicators in the analytic hierarchy process.

According to the comprehensive calculation of the analytic hierarchy process, the weight of the evaluation index of inefficient residential land is shown in Table 5.

According to the analysis results, the residential plot score is calculated according to the weight of each factor and the index grading score. Through analysis, 20% of the objects with the lowest scores are selected as inefficient residential land.

4.2.2. Identification Standard of Inefficient Industrial Land

First, according to the qualitative evaluation method, two types of inefficient land use, namely, inefficient use allocation and government focused transformation, are determined. The summary results of qualitative evaluation are shown in Table 5.

Firstly, according to the qualitative evaluation criteria, some plots with inefficient use allocation and key government reconstruction are directly included in the scope of inefficiency and then the remaining individual items are scored separately. The analytic hierarchy process and the Delphi method are still used to determine the index weight of the quantitative evaluation of inefficient industrial land. According to the analysis results, the score of the industrial plot is calculated according to the weight of each factor and the grading score of the index. Through analysis, 20% of the objects with the lowest scores are selected as inefficient industrial land.

According to the analytic hierarchy process and the Delphi method, the weight of the evaluation index of inefficient industrial land is calculated as shown in Table 5.

4.2.3. Identification Standard of Inefficient Commercial Land

First, according to the qualitative evaluation method, two types of inefficient land use, namely inefficient use allocation and government focused transformation, are determined. The summary results of qualitative evaluation are shown in Table 5.

Firstly, according to the qualitative evaluation criteria, some plots with inefficient use allocation and key government reconstruction are directly included in the scope of inefficiency and then the remaining individual items are scored separately. The analytic hierarchy process and the Delphi method are still used to determine the index weight of the quantitative evaluation of industrial inefficient land. According to the analysis results, the score is obtained according to the weight of each factor and index classification.

We calculated the scores of commercial plots. Through analysis, 20% of the objects with the lowest scores are selected as low-efficiency commercial places.

According to the comprehensive calculation of the analytic hierarchy process and the Delphi method, the weight of the evaluation index of inefficient commercial land is shown in Table 5.

4.3. Study of the Spatial Characteristics of Inefficient Urban Land Use in the Region

4.3.1. Spatial Distribution Characteristics

ArcGIS is used to output the ellipse analysis results of the standard deviation of inefficient land use in the central urban area of Dali County, as shown in Figure 3 and

Table 6. Standard deviation ellipse parameters of inefficient urban land use location distribution.

Type	Area (M2)	XStdDist (m)	YStdDist (m)	Rotation Angle (°)
Inefficient land use	25,753,311.3	2271.0	3609.8	86.4
Inefficient residential land	19,755,421.4	3228.3	1947.9	93.1
Inefficient industrial land	34,403,760.9	2428.6	4509.4	69.9
Inefficient commercial land	32,505,611.5	2594.5	3988.2	86.1

.

The distribution centers of the four standard deviation ellipses are located next to the geographic geometric center of the central urban area of Dali. Taking the central position of the overall situation as a reference, the inefficient residential land, inefficient commercial land and the overall situation remain at the same level and the central position of the inefficient industrial land is located in the southwest, indicating that the distribution of the central positions is relatively concentrated, the positions are adjacent to each other and not far from the geometric center, which shows that the distribution of these three types of urban inefficient land in the study area is relatively balanced.

As shown in Table 6 and Figure 3, all kinds of standard deviation ellipses are located around the center of the central urban area of Dali and the rotation angle is ranked as follows: inefficient residential land > inefficient land > inefficient commercial land > inefficient industrial land. Among these values, the rotation angles of inefficient land, inefficient residential land and inefficient commercial land are all between 85° and 95°, while the rotation angle of inefficient industrial land is 69.9°, but there is little difference from other types of rotation angles. The main direction of the low-efficiency points of low-efficiency land, low-efficiency residential land and low-efficiency commercial land is roughly east–west, the directions of the three types of inefficient land have little difference and the distribution direction is relatively consistent, while the direction of low-efficiency industrial land is roughly northeast–southwest.

The difference between the x-axis and y-axis of inefficient industrial land is the largest and the difference between those of inefficient residential land is the smallest, indicating that the distribution of inefficient industrial land is more directional and the primary and secondary directions extend a long way, with a certain degree of dispersion, while that of inefficient residential land is the opposite. From the perspective of elliptical area, that of inefficient industrial land is the largest, indicating that the distribution area of inefficient industrial land is wide and scattered, while the elliptical area of inefficient residential land is the smallest, indicating that the distribution area is small and concentrated.

ArcGIS is used to output the ellipse analysis results of the standard deviation of inefficient land use in Xincheng Street, Hancheng City, as shown in Figure 4 and

Table 7. Standard deviation ellipse parameters of the distribution of inefficient land use sites in Xincheng Street.

Type	Area (M2)	XStdDist (m)	YStdDist (m)	Rotation Angle (°)
Inefficient land use	26,364,753.3	3766.7	2228.1	160
Inefficient residential land	23,967,561.4	1793.9	4253.1	2.4
Inefficient industrial land	25,536,364.4	3698.3	2198	143.1
Inefficient commercial land	20,232,862.9	3393.1	1898.1	151.3

.

Overall, the distribution centers of the four standard deviation ellipses are not concentrated. The ellipse centers of inefficient land, inefficient commercial land and inefficient industrial land are all located near the geographic geometric center of Xincheng Street. Taking the central position of the overall inefficient land use as a reference, the central position of the inefficient residential land is to the south of the overall inefficient land use’s central position. The above shows that the central location distribution of all kinds of inefficient land is not centralized. Although it is not far from the geometric center, it is not on the same horizontal line, which shows that the three types of inefficient land in Xincheng Street are unevenly distributed within the study area.

As shown in Table 7 and Figure 4, all kinds of standard deviation ellipses are located around the center of Xincheng Street and the rotation angle is ranked as follows: inefficient land > inefficient commercial land > inefficient industrial land > inefficient residential land. The rotation angle of inefficient industrial land, inefficient commercial land and inefficient residential land is 140°–165°, while the rotation angle of inefficient residential land is 2.4°, which is quite different from the other types of inefficient land. The main direction of the low-efficiency points of low-efficiency land, low-efficiency industrial land and low-efficiency commercial land is roughly northwest–southeast. The directions of the three types of inefficient land have little difference and the distribution direction is relatively consistent, while the direction of low-efficiency residential land is south–north.

As shown in Table 7, the difference between the x-axis and y-axis of inefficient residential land is the largest and the difference between those of inefficient commercial land is the smallest, indicating that the distribution of inefficient residential land is more directional and the primary and secondary directions extend a long way, with a certain degree of dispersion, while that of inefficient commercial land is the opposite. From the perspective of elliptical area, the elliptical area of inefficient land is the largest, with an area of 26,364,753.3 square meters, indicating that the distribution of inefficient land is wide and scattered, while the elliptical area of inefficient commercial land is the smallest, with an area of 20,232,862.9 square meters, indicating that the distribution of inefficient commercial land is relatively concentrated.

ArcGIS is used to output the ellipse analysis results of the standard deviation of inefficient land use in Longmen Town, Hancheng City, as shown in Figure 5 and

Table 8. Standard deviation ellipse parameters of urban inefficient land use location distribution.

Type	Area (M2)	XStdDist (m)	YStdDist (m)	Rotation Angle (°)
Inefficient land use	33,019,007.6	2298.9	4572.1	42.5
Inefficient residential land	40,573,986.3	3044.2	4242.7	38.3
Inefficient industrial land	31,735,626.4	2128.3	4746.7	42.2
Inefficient commercial land	18,835,228.7	1434.2	4180.9	46

.

In general, the elliptical distribution centers of inefficient land, inefficient industrial land, inefficient residential land and inefficient commercial land are all located around the geographical geometric center of Longmen Town. Taking the central location of the overall inefficient land as a reference, the inefficient industrial land and inefficient commercial land are at the same level as the overall situation. The central location of the inefficient residential land is located in the southwest, but its central location is relatively concentrated and the locations are close to each other, which shows that the distribution of these three types of inefficient land in Longmen Town is relatively balanced.

As shown in Table 8 and Figure 5, the rotation angle of various standard deviation ellipses is ranked as follows: inefficient commercial land > inefficient land > inefficient industrial land > inefficient residential land and the angle difference between various types is very small. The main direction of the low-efficiency points of low-efficiency land, low-efficiency industrial land, low-efficiency residential land and low-efficiency commercial land is roughly in a northeast–southwest trend. The directions of these three types of land are not different and the distribution direction is relatively consistent.

From Table 8, it can be seen that the difference between the x-axis and y-axis of inefficient commercial land is the largest and the difference between those of inefficient residential land is the smallest, indicating that the distribution of inefficient commercial land is more directional and the primary and secondary directions extend a long way, with a certain degree of dispersion, while that of inefficient residential land is the opposite. In terms of elliptical area, the oval area of inefficient residential land is the largest, with an area of 40,573,986.3 square meters, indicating that the distribution area of inefficient residential land is wide and scattered, while the elliptical area of inefficient commercial land is the smallest, with an area of 18,835,228.7 square meters, indicating that the distribution area is small and concentrated.

4.3.2. Spatial Agglomeration Characteristics

There are spatial agglomeration phenomena in the inefficient land use of Dali city center, Xincheng Street and Longmen Town. The distribution and morphological characteristics of inefficient land are revealed by using nuclear density analysis. Using the kernel density tool of Arc GIS software, this paper analyzes the morphological characteristics of urban inefficient land accumulation and generates the corresponding characteristic map of inefficient land distribution density. The results are shown in Figure 6, Figure 7 and Figure 8.

As shown in Figure 6, in general, inefficient land forms two cores (A1, A2), inefficient residential land forms three cores (B1, B2, B3), inefficient industrial land forms two cores (C1, C2) and inefficient commercial land forms three cores (D1, D2, D3). From the perspective of nuclear center density, the density of each nuclear center varies greatly. The nuclear center density of inefficient residential land is higher than that of inefficient commercial land and inefficient industrial land. The density value of inefficient residential land is between 0 and 17.5539 per square meter and the density value of inefficient industrial land is the lowest, at between 0 and 2.9094 per square meter. From the perspective of spatial distribution, the overall situation of inefficient land use has formed a spatial pattern of “double core and large dispersion” and the outward radiation areas (A2) centered on x312 county road to the west of Business Street (A1) and the south of Dongxin Street have formed dense areas, respectively. The distribution of inefficient residential land is similar to the overall situation, with slight differences in the distribution range, but the concentration is relatively high, which plays a leading role in the formation of the overall situation pattern. The areas with high density values are mainly in the west of Business Street (B1), the south of the intersection of Fengyi Road and South Ring Road (B2) and the east of Dongxin Street (B3). Inefficient industrial land forms a “dual core” pattern, C1 and C2, which forms a cluster area, but the distribution is relatively divergent. The area with a high density value is mainly in Nanqi Village (C1) and the outward radiation area (C2) is centered on x312 County Road, south of Dongxin Street. Low-efficiency commercial land presents a spatial pattern of “large agglomeration and multi-core dispersion” in terms of morphological distribution. The areas with high density values are mainly in the northern (D1), western (D2) and eastern (D3) peripheral areas of the city.

As shown in Figure 7, on the whole, four cores (A1, A2, A3, A4) are formed in the low-efficiency land of Xincheng Street, two cores (B1, B2) are formed in the low-efficiency residential land, three cores (C1, C2, C3) are formed in the low-efficiency industrial land and three cores (D1, D2, D3) are formed in the low-efficiency commercial land. From the perspective of nuclear center density, the density of each nuclear center varies greatly. The nuclear center density of inefficient industrial land is higher than that of inefficient commercial land and inefficient residential land. The density value of inefficient industrial land is between 0 and 11.4797 per square meter and the density value of inefficient residential land is the lowest, at between 0 and 5.3005 per square meter. From the perspective of spatial distribution, the overall situation of inefficient land use has formed a spatial pattern of “small agglomeration and multi-core dispersion”. Dense areas have been formed near the North Zhaojiagou bridge (A1), near the north section of the Yellow River Street (A2), northeast of Nanzhouyuan Village (A3) and south of the eastward extension line of the east section of Taishi Street (A4). In particular, A1 and A2 show a “dual core” structure and there are obvious concentrated contiguous areas, Overall, small agglomeration in space is observed.

Inefficient residential land forms a spatial pattern of “double core and large agglomeration”. The areas with high density values are mainly in the north of Wangzhu Village (B1) and the south of the intersection of G108 national highway and the south section of Zhenzhou Avenue (B2). Inefficient industrial land forms a spatial pattern of “multi-core dispersion” and the areas with high density values are mainly near the North Zhaojiagou bridge (C1), the north section of Yellow River Street (C2) and the northeast of Nanzhouyuan Village (C3). The distribution of low-efficiency commercial land is similar to the overall situation, with slight differences in the distribution range, but the concentration is relatively high, which plays a leading role in the formation of the overall situation pattern. The areas with high density values are mainly near the north section of Yellow River Street (D2) and south of the eastward extension line of the east section of Taishi Street (D3).

As shown in Figure 8, in general, the inefficient land in Longmen Town forms two cores (A1, A2), the inefficient residential land forms one core (B1), the inefficient industrial land forms one core (C1) and the inefficient commercial land forms two cores (D1, D2). In terms of the density of nuclear centers, there is little difference between the density of nuclear centers. The density of nuclear centers of inefficient industrial land is higher than that of inefficient residential land and inefficient commercial land. The density value of inefficient industrial land is between 0 and 9.3762 per square meter and the density value of inefficient commercial land is the lowest, at between 0 and 5.374 per square meter. From the perspective of spatial distribution, the overall situation of inefficient land use has formed a spatial pattern of “multi-core and large dispersion”. The areas with high density values are mainly near Xinlingao Village (A1) and near the exit of G5 Expressway (A2). Inefficient residential land forms a spatial pattern of “multi-core and large dispersion” and the area with high density value is mainly near the exit of G5 highway (B1). Inefficient industrial land is still a spatial pattern of “single core and large dispersion”, which is similar to the overall situation in distribution, but there are differences in distribution range, which reflects the fact that the concentration of inefficient industrial land is relatively high and plays a leading role in the formation of the overall situation pattern. The area with a high density value is mainly near Xinlingao Village (C1). The low-efficiency commercial land presents a spatial pattern of “small agglomeration and dual core dispersion” and the areas with high density values are mainly near the intersection of G108 and g327 (D1) and northeast of the intersection of Longgang Avenue and G108 (D2).

5. Analysis of Influencing Factors on Inefficient Land Use in Cities and Towns in the Study Area

Based on the calculation and analysis of the contribution model, the contribution of various indicators of regional inefficient residential land, inefficient industrial land and inefficient commercial land is obtained and the distribution proportion of each contributing factor for the three types of inefficient land in each town is calculated. The results are shown in

Table 9. Contribution statistics of inefficient residential land.

	Region
Contributing Factor	Dali Central City	Xincheng Street	Longmen Town
Building density	16.5%	10.4%	24.9%
Commercial service facilities	18.3%	8.2%	6.9%
Scientific and educational style	14.8%	12.7%	6%
Park and green space	2.6%	8.6%	1.5%
Communal facilities	4.4%	7%	9.1%
Road network density	43.4%	53.1%	51.6%

,

Table 10. Statistics for low-efficiency industrial land contribution.

	Region
Contributing Factor	Dali Central City	Xincheng Street	Longmen Town
Building density	4.8%	10.9%	5.7%
Road network density	87.8%	72.6%	79.3%
Idle rate of land	7.4%	16.5%	15%

and

Table 11. Contribution statistics for inefficient commercial land.

	Region
Contributing Factor	Dali Central City	Xincheng Street	Longmen Town
Building density	12.2%	22.8%	16.5%
Road network density	87.8%	77.2%	83.5%

.

5.1. Analysis of Influencing Factors of Inefficient Residential Land

It can be seen from Table 9 that for inefficient residential land, the largest contribution index of the three research areas is the road network density factor, which accounts for nearly half of the total. In the central urban area of Dali, the contribution of commercial service facilities takes second place, accounting for 18.3%, followed by the distribution of building density and science, education and sports, with values of 16.5% and 14.8%, respectively. Therefore, for residential land, the central urban area of Dali can improve the efficiency of such land use by increasing the density of housing construction and improving the living environment.

5.2. Analysis of Influencing Factors of Inefficient Industrial Land

It can be seen from Table 10 that, for inefficient industrial land, the largest contribution index of the three research areas is the road network density factor, which accounts for more than 70% of the three towns. In the central urban area of Dali, the contribution of the building density factor is 4.8% and the contribution of the land idle rate factor is 7.4%. The contribution of the building density factor in Xincheng Street is 10.9% and the contribution of land idle rate factor is 16.5%. In Longmen Town, the contribution of the building density factor is 5.7% and the contribution of the land idle rate factor is 15%. Therefore, as far as industrial land is concerned, land use efficiency can be improved through the reasonable planning and utilization of land and increasing land utilization rate.

5.3. Analysis of Influencing Factors on Inefficient Industrial Land

It can be seen from Table 11 that, for inefficient commercial land, the contribution rate of the building density factor in the central urban area of Dali is 12.2%, while the contribution rate of the road network density factor is 87.8%. In Xincheng Street, the contribution rate of the building density factor is 22.8%, while the contribution rate of the road network density factor is 77.2%. In Longmen Town, the contribution rate of building density factor is 16.5%, while the contribution rate of road network density factor is 83.5%. In the three regions, the proportion for the road network density factor is far greater than that of the building density factor. Therefore, land use efficiency can be improved by properly developing and utilizing land and reducing idle land.

6. Summary and Policy Recommendations

In this study, Dali and Hancheng County in Weinan City are selected as the research areas. First, the analytic hierarchy process is used to build a comprehensive evaluation system for the identification of inefficient land in stock; secondly, the standard deviation ellipse method and spatial kernel density estimation method are used to quantitatively analyze the spatial distribution characteristics of urban inefficient land. Finally, using the contribution model, the influencing factors of inefficient land use are analyzed. The results show that:

• The area of inefficient land in the central urban area of Dali is about 251.7 hectares. The inefficient land is mainly distributed in the marginal areas and the part of the central urban area gradually incorporated with the development of the city. The main inefficient land is residential land. The inefficient land area in Xincheng Street in Hancheng City is about 335.81 hectares. There is no obvious area difference between various inefficient land uses, which are mainly distributed on both sides of the Beijing Kunming Expressway and the suburban areas where the city expands northward. The inefficient land area of Longmen Town in Hancheng City is about 714.43 hectares. Longmen Town is a strong industrial town and the industrial warehousing enterprises cover a large area. In terms of the area distribution of all kinds of inefficient land, the area of inefficient industrial land is much larger than that of inefficient residential land and inefficient commercial land.
• The distribution of three types of inefficient land in the central urban area of Dali is relatively balanced, the distribution of inefficient industrial land is more directional and the primary and secondary directions extend a long way, with a certain degree of dispersion. The distribution of various inefficient land centers in Xincheng Street in Hancheng City is not centralized, the distribution of inefficient residential land is directional and the primary and secondary directions extend a long way, with a certain degree of dispersion. The distribution of inefficient land in Longmen Town of Hancheng City is relatively balanced and the distribution of inefficient commercial land is more directional. The extension of the primary and secondary directions is great, with a certain degree of dispersion.
• Through the contributing factor analysis of the three types of inefficient land in the study area, it is found that the road network density is the main contributing factor for the three types of inefficient land, while the building density, land idle rate and other factors do not contribute significantly to the determination of inefficient land.

Through the above analysis, we know that the scale, distribution and causes of the three types of inefficient land in the selected study area are different. Based on the qualitative and quantitative analysis of the influencing factors of the formation of various types of inefficient land, we provide corresponding redevelopment suggestions for each type of inefficient land.

• Inefficient residential land

According to the situation of inefficient land-use buildings in residential areas, their redevelopment methods can be analyzed correspondingly and they can be divided into three redevelopment methods: partial reconstruction, overall demolition and new construction and tapping the potential of idle land. Part of the reconstruction is mainly used in the reconstruction of old communities, old towns and old villages. This redevelopment method can avoid large-scale demolition and reconstruction, but achieve the purpose of tapping the potential through micro reconstruction. Overall demolition and reconstruction is mainly used in residential areas where the overall buildings are dilapidated and the environmental conditions are poor and it is impossible to improve the residential function through partial rectification. Only by taking overall demolition and reconstruction into account can we realize the effective utilization of residential land. Tapping the potential of idle land is mainly aimed at residential areas where there is idle land in the current land use situation. Because there are generally no aboveground buildings to be treated on idle ground, its development difficulty is the lowest. However, it should be noted that its development and construction should be carried out under the requirements of urban land use planning to avoid the wasting of land caused by the blind development of idle land.

2.

Inefficient industrial land

As the property rights structure and building structure of the industrial zone are simple and the plot ratio is low, the demolition volume is much smaller than that of the residential area. In addition, the capacity of the power supply, gas supply and water supply and drainage facilities in industrial areas is better than that of ordinary residential buildings, so the transformation of inefficient industrial land often eliminates large-scale municipal investment. However, the transformation of these industrial clusters is not a simple plant demolition and industrial replacement, but rather involves deeper industrial design and plant reuse, especially involving the transformation of local pillar industrial enterprises and as the industrial zone is related to the development of the whole city, we must be cautious. Based on the nature of such land, this study divides the redevelopment direction of industrial inefficient land into reconstruction and expansion, enterprise relocation and tapping the potential of idle land.

3.

Low-efficiency commercial land

For this kind of land, this study divides the redevelopment direction of inefficient land for commercial services into two types: remodeling and idle land tapping. The transformation type refers to the type that can improve the land utilization rate or function through the corresponding means or measures of the government or enterprises. Inefficient commercial land is mainly distributed in urban centers and urban fringe areas. Considering the actual situation of Dali County and Hancheng City at present, the proportion of residential and industrial land is high, while the proportion of road traffic, green space and other land is generally low. Focusing the metropolitan area where the central urban area is located, we can gradually guide the warehousing and logistics industries in the central urban area to move to the regions through fiscal and tax subsidies, enclave parks, innovation and industrial upgrading and other policies belonging to the idle potential tapping type. In order to avoid the problem of idle land, we should control the development of commercial land at the source. First, decision-makers should establish and improve the land supply for real estate development and provide it reasonably according to the market demand. Secondly, they should strengthen the effective control of the planning on the development of commercial services and strengthen the regulation of the planning on the real estate development area and development area.

7. Conclusions

At present, the academic research on low-efficiency land use in cities and towns is mainly qualitative. The main types and sections of analysis are relatively common and the perspective of national policies and the transformation of various roles is usually taken as the entry point. However, quantitative research on low-efficiency land use is relatively rare. This paper comprehensively uses the methods of economics and geography to study low-efficiency land use, quantifies the spatial and temporal characteristics and influencing factors of land use units, explores the spatial pattern of land use, enriches the research on relevant theories and shows a certain amount of innovation in its contribution.

The redevelopment of low-efficiency land in cities and towns has just started and many places are still exploring and implementing this process. Many existing excellent case studies are only based on current social and economic conditions. In addition, as social development and urban development are different in different regions, the redevelopment of inefficient land in different regions should also be implemented through more specific and detailed measures according to local conditions. On the basis of summing up the implementation of this work in China, this paper summarizes and analyzes the experience of several typical cities in the Yellow River Basin and seeks to put forward theoretical policy suggestions for the redevelopment of inefficient urban land in the Yellow River Basin. As for how to mobilize and activate the enthusiasm of multi-level, multi-agent and multiple resources and how to study a more suitable and specific low-efficiency land redevelopment model, we need to actively explore in the future specific work and research processes, which is also the future research direction of this paper.