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2444-8656
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Study on inefficient land use determination method for cities and towns from a city examination perspective

Published Online: 05 Sep 2022
Volume & Issue: AHEAD OF PRINT
Page range: -
Received: 03 Mar 2022
Accepted: 15 May 2022
Journal Details
License
Format
Journal
eISSN
2444-8656
First Published
01 Jan 2016
Publication timeframe
2 times per year
Languages
English
Introduction

With the advancement of urbanisation process in cities, the disarranged outward extension of city results in a great many lands being wasted, and the concept of stock planning comes with it. When existing old urban districts are renovated, the inefficiently used lands in the city have become an emphasis during renovation and transformation [1].

It is difficult to determine the inefficient urban land use in China also to identify them due the lack of policy support and strict quantitative criterion. However, existing studies on inefficient urban land use basically analyse from policy and institutional system, which seldom has been implemented in practice or provides specific strategies and methods for renovating inefficiently used lands [2].

Problems in existing determination of inefficient land use
Data come from various sources but with low actual availability

In the studies of inefficient land use, the data source generally comes from the traditional data of departments and industries as well as the open-sourcing big data, and the data is processed by spatial overlay research method. Numerous analysis methods are highly persuasive, but the data suitable for establishing legal high-level planning is still limited.

Different land premium capacity

As the way of land transfer changes and the land supply falls short of demand, the urban renovation and transformation process is accelerated to revitalise urban stock lands. In the process of such transformation, a lot of lands will face to use change and plot ratio increase, the land transformation cost will also be greatly reduced due to the change of transformation methods, thus the inefficient stock lands will show assets premium. The large-scale land premium makes it hard to study the land price estimation, influencing the determination of inefficient land use.

Different urbanisation stage

First, the cities may be at different urbanisation stages, so it is unable to assign a uniform standard for the determination of inefficient land use. Second, in view of China's urbanisation development situation, the regional urbanisation development displays an obvious unbalanced condition, and the studies of inefficient land use couldn’t provide a uniform judging data yet [3].

Determination of inefficient urban land use from city examination perspective

Under the background of ‘city disease’ caused by national land space planning and the generation of megacities, city examination rises at this right moment. City Examination refers to the quantitative analysis and evaluation on such problems as traffic circulation, employer-resident relationship, environmental health and public service in the city development process. The determination and excavation of inefficient urban land use is an essential content of city examination and also a breakthrough of city renovation and transformation. Therefore, taking city examination as a viewing angle to identify and judge inefficient urban land use is a question worthy of inquiry [4].

Establishment of evaluation framework of inefficient urban land use

According to the current situation of urban land use, the multi-factor superposition method is used to evaluate the inefficient degree of land and designate the inefficient degree partition of land use. In future, these lands will be reconstructed moderately to quicken urban renovation process and reduce renovating cost. The research idea and steps are shown in the diagram are shown in Figure 1 [5].

Fig. 1

Framework of evaluation index system for ineffective urban land use.

Establishment of evaluation system of inefficient urban land use
Principle for establishing the evaluation system of inefficient urban land use
Comprehension principle

The determination of inefficient urban land use is a complex comprehensive evaluation system affected by multiple factors. On one hand, it is necessary to take an overall consideration of the internal renovation factors of a city, including subjective judgement kind and objective quantitation kind; on the other hand, proper methods should be selected to integrate various factors, so as to obtain an objective and comprehensive assessment.

Hierarchy principle

Urban land is a complicated system; the judgement of it can be influenced by many factors, so the evaluation system should be hierarchical to a certain extent. Thus, according to the basic theory of the system theory, we have to differentiate the subsystems of different influencing factors and choose specific evaluation indicators according to different subsystem's target and requirement. By referring to relative studies, an ‘target layer-criterion layer-index layer’ evaluation index system framework was established, which took the influencing factors of city examination as the subsystem of criterion layer and chose specific evaluation indexes according to the factors affecting the inefficiency of urban land use.

Operability principle

The evaluation index of inefficient urban land use contains subjective judgement indexes and objective quantitation indexes, i.e. qualitative indexes and quantitative indexes. In the process of index selection and quantitation, the basic situation of the city should be considered and linked up with prevailing code standard. Through field survey, the evaluation indexes of subjective judgement can be quantified as far as possible, intuitively reflecting the actual situation of city construction land and improving the index system operability. The objective quantitation indexes can be obtained from the data information of relevant government departments and statistical organs.

Establishment of evaluation index system of inefficient urban land use
Evaluation system framework

The basic framework of three hierarchies namely target layer, criterion layer and index layer has been established as shown in Table 1. Therein, the target layer shows the comprehensive indexes for evaluating inefficient urban land use; the criterion layer shows the analytical results of influencing factors, including such three aspects, that's ‘sharing’, ‘coordinating’ and ‘green’; the index layer shows the specific expression indexes of each criterion indexes, finally, a three-layer evaluation index system was built step-by-step from specific indexes.

List of evaluation index system of inefficient urban land use.

Target layer Criterion layer Index layer

Evaluation on inefficient urban land use Sharing Distance to public service facility, primary and secondary schools, commercial facility, and arterial traffic
Coordination Construction quality, plot ratio, renovating cost, population density
Green Green coverage ratio, central greenbelt coverage ratio
Selection of evaluation indexes

Based on summarising and analysing existing evaluation index system, integrated with existing judgement principle of inefficient urban land use and the latest evaluation indexes of city examination and by consulting professionals and scholars, ten evaluation indexes were screened out finally, and an evaluation index system of inefficient urban land use was built with target layer, criterion layer and index layer for such three influencing factors as sharing, coordination and green. Among them, the sharing criterion layer takes the convenience degree of the land reaching surrounding infrastructures into consideration, including the distance to public service facility, primary and secondary schools, large-scale commercial facility and arterial traffic [6, 7]; the coordination criterion layer contains facility immovability, construction quality, plot ratio, renovating cost and population density [8]; the green criterion layer contains river and lake water coverage ratio, green coverage ratio and central greenbelt coverage ratio [9,10]. These indexes not only cover quantitative indexes such as plot ratio and green coverage ratio, but also cover some qualitative indexes such as construction quality. So the index quantification methods and standards are also different (Table 1).

Calculation of index weight of inefficient urban land use

According to above-mentioned evaluation method of inefficient urban land use and based on AHP method, the multi-layer analytical structure model, judgement matrix, weight calculation and consistency check were established to confirm the weight of evaluation indexes of inefficient urban land use.

Construction of multi-layer analytical structure model

The evaluation index system of inefficient urban land use is hierarchical, and a hierarchical structure model was established based on three layers: target layer, criterion layer and index layer (Figure 2).

Fig. 2

Schematic diagram of AHP hierarchical structure model of inefficient urban land use evaluation.

Construction of judgement matrix

This paper built a two-layer judgement matrix: target layer-criterion layer, and criterion layer-index layer. In the judgement matrix, Xab aims at the relative importance of item a to item b of each criterion layer in the target layer, or the relative importance of item a to item b of each index layer in the criterion layer. To improve the accuracy of judgement matrix, the relative importance of the two sides of each index was determined through multiple experts.

As there is strong subjectivity when scoring by using analytic hierarchy process method, this study adopted the Delphi method to obtain the opinion of different experts about the importance degree between each evaluation indexes, and used the 1–9 scale method established by American Operations Researcher A.L. Saaty to give grade (Table 2), so as to eliminate the subjectivity caused by using analytic hierarchy process to determine index weight and make index weight to be more objective and accurate.

1–9 scale scoring table.

Index A/B Extremely important Very important Important Weakly important Same important Weakly unimportant Unimportant Very unimportant Extremely unimportant
Index A's evaluation value 9 7 5 3 1 1/3 1/5 1/7 1/9
Index B's evaluation value 1/9 1/7 1/5 1/3 1 3 5 7 9
Remark Take 8, 6, 4, 2, 1/2, 1/4, 1/6, 1/8 as the medians of above evaluation values
Weight calculation

After completing the scoring of criterion layer and factor layer, the YAAHP software was used to figure out the weights of each evaluation index of criterion layer and factor layer (Table 3).

Weights of each evaluation index of criterion layer and factor layer.

Target layer Criterion layer Index layer Index weight

Inefficient urban land use Sharing 0.2617 Distance to public service facility 0.0413
Distance to primary and secondary schools 0.0275
Distance to arterial traffic 0.1377
Distance to commercial facility 0.0551

Coordination 0.5179 Population density 0.1007
Construction quality 0.1726
Renovating cost 0.1151
Plot ratio 0.1295

Central greenbelt coverage ratio 0.0315
Green 0.2204 Green coverage ratio 0.1889

It can be discovered from the weights of each evaluation index that the effect of three kinds of influencing factors of inefficient urban land use can be sorted from largest to smallest which is: coordination > sharing > green, and the land properties such as construction quality and plot ratio indexes have the greatest effect on the inefficiency of urban construction land; the secondary greatest effect on the use efficiency of urban construction land is the accessibility of public facility. Specifically, the green coverage ratio, construction quality and plot ratio indexes have great impact on the use efficiency of urban construction land, which could also reflect the important approaches of internal renovation of a city.

Determination of evaluation standard of inefficient urban land use
Single-factor evaluation standard

It is known from the evaluation index system of inefficient urban land use that the evaluation indexes include quantitative and qualitative indexes. Through investigating the defined basic requirement of the multi-factor superposition evaluation method, the quantification method of each evaluation index was discussed, and finally the fuzzy comprehensive evaluation method was used to determine the value of each evaluation index, which can effectively handle with the unification and standardisation problem of quantitative and qualitative indexes. The basic idea of quantifying evaluation indexes by fuzzy comprehensive evaluation method is: first, build an evaluation semantic set {extremely inefficient, slightly inefficient, inefficient, slightly efficient, extremely efficient}, and assign their corresponding values as {1, 3, 5,7, 9}, in which, the larger the value is, the higher the land use efficiency is, and the more improper such land is to be redeveloped; second, according to the actual value of evaluation indexes as well as the index classification standards of relevant studies and norms, the efficiency class of evaluation index was established, and each land block was assigned a land use efficiency value uniformly. The specific index standard is shown as below.

Sharing

Sharing criterion measures the accessibility of current land block to various facilities, mainly referring to four indexes determined by the service radius of various facilities in the facility classification and norm specified in the Code of Practice for City Examination & Evaluation in Spatial Planning. The land with far distance with various facilities has low availability efficiency and poor habitability. The specific index quantification and value are shown in Table 4 [11].

Classification table for land use efficiency value of indexes in sharing criterion layer.

Sharing index layer Land use efficiency value

1 3 5 7 9

Distance to public service facility (m) 1000–2000 500–1000 200–500 <200 >2000
Distance to primary and secondary schools (m) >2000 1000–2000 500–1000 200–500 <200
Distance to arterial traffic (m) >400 200–400 100–200 50–100 <50
Distance to commercial facility (km) >5 3–5 2–3 1–2 <1
Coordination

Coordination criterion layer measures the economic value of current land block, and the economic value is always reflected in renovation cost. The low the renovation cost is, the easier the land block is to renovate, otherwise, the higher the renovation is, the more improper such land block is to renovate. While the renovation cost is influenced by land price, construction quality and population composition, and the renovation cost class of each land block is primarily determined by referring to local comprehensive land price standard and the real estate transaction price of each community in second-hand housing transaction website. Besides, the larger the population density of a land block is, the higher the renovation and removal cost will be, and the more disadvantageous it will be to the redevelopment and reconstruction. The specific index quantification value is shown in Table 5 [12].

Classification table for land use efficiency value of indexes in coordination criterion layer.

Coordination index layer Land use efficiency value

1 3 5 7 9

Population density Very low Lower Average Higher Very high
Construction quality Very poor Poor Average Good Very good
Renovation cost Level 1 Level 2 Level 3 Level 4 Level 5
Plot ratio >2.0 1.5–2.0 1.0–1.5 0.5–1.0 <0.5
Green

Green criterion layer measures the green situation of current land block. The smaller the green coverage ratio of a land block is, the more proper it is to be redeveloped and reconstructed. And the poorer the accessibility of a land block to central greenbelt is, the more prior it should be redeveloped and renovated. The specific index quantification value is shown in Table 6.

Classification table for land use efficiency value of indexes in green criterion layer.

Green index layer Land use efficiency value

1 3 5 7 9

Central greenbelt coverage ratio (m) >2000 1500–2000 1000–1500 500–1000 <500
Green coverage ratio (%) <5 5–15 15–25 25–35 >35
Comprehensive evaluation standard

Taking the land block classification of land usage in urban master planning as the fundamental zoning method is easier to quantify the land block property, which is feasible to the zoning of comprehensive index of urban construction land use inefficiency. So, the CAD file of land usage is input in ArcGIS software, and the category is set as 4 by using classification function, then the urban land use efficiency is classified into four grades according to [1, 3], (3, 5], (5, 7] and (7, 9] [13].

Field case analysis
Establishment of inefficient urban land use database

The Suiling County is selected to explore and verify this method. The spatial data used in this article is the overall planning of central downtown status map of Suiling County in 2010. First, the land blocks were divided in ArcGIS according to topographic map and central downtown status map, and a total of 560 land blocks in construction land unit of Suiling County were vectorised edited (in case of a larger range, the land blocks can be numbered in detail according to administrative district). Then, the ID of each planning unit was edited and input as the spatial basis for further evaluation of inefficient urban land use (Figure 3).

Fig. 3

Vectorised schematic diagram of internal construction land for central downtown in Suiling County.

Assigned value of lands

In the design process of construction land efficiency database or central downtown in Suiling County, each evaluation unit was coded orderly as the ID code's associate attribute data and spatial data; according to evaluation indexes of inefficient urban land use, the field was designed as LAND (current land usage), BUILDING (construction quality), FAR (plot ratio), COST (renovation cost), POP (population density), GREEN (green coverage ratio), etc. With the above process, the internal stock land database of central downtown in Suiling County was established, with all data visualised by field selection and editing, and Spatial Analyst tool can be used to perform spatial analysis on inefficient land use.

Calculation and analysis of inefficient urban land use index
Calculation of sharing criterion layer

The status urban construction land of central downtown in Suiling County is primarily a residential land and industrial land. Residential land mainly available on the east part of central downtown, while industrial land on the west part of central downtown, spreading along both sides of railway. Through extracting and sorting the online map's POI data, the current distribution of primary and secondary schools, medical and health care facilities, and city-level commercial facilities within central downtown in Suiling County was obtained (Figure 4). After performing an spatial analysis on the accessibility of primary and secondary schools, from the spatial distribution, the accessibility of central commercial facilities is better which basically covers the residential area, and only a few industrial districts have a poor accessibility (Figure 5); the coverage of public service facilities is weaker than central commercial facilities, a part of central residential area is also far from public service facilities (Figure 6); the coverage of primary and secondary schools is even smaller, and a part of residential area also has a poorer accessibility (Figure 7).

Fig. 4

Public facility distribution in Suiling County.

Fig. 5

Distribution of distance factor evaluation of central commercial facilities.

Fig. 6

Distribution of distance factor evaluation of public service facilities.

Fig. 7

Distribution of distance factor evaluation of primary and secondary schools.

In Suiling central downtown status map, there is one urban railway and three arterial roads (Figure 8). Through the spatial analysis of arterial roads and by calculating the buffer zone of different distances, it can be said that the south and north sides of the city are far from urban arterial roads, with poor accessibility (Figure 9).

Fig. 8

Distribution of urban arterial roads.

Fig. 9

Distribution of distance factor evaluation of arterial roads.

Calculation of coordination criterion layer

In 2010, the permanent resident population was 96,000 in central downtown of Suiling County. The basic population density was determined according to land use and permanent resident population proportion. Taking this as a standard, the population density level can be determined combing with land usage, community occupancy rate and current resident population (Figure 10); the plot ratio of land blocks in Suiling is higher in residential area, in which the high-rises have the highest ratio, reaching up to above 2.0 (Figure 11).

Fig. 10

Distribution of population distribution factor evaluation.

Fig. 11

Distribution of plot ratio factor evaluation.

In Suiling County, the construction quality is the best in central residential area, general in surrounding industrial area and the poorest in shanty area around the city (Figure 12); by referring to the influence of construction quality and land price and integrating with the comprehensive land price standard in Suiling, the renovation cost is classified into five grades (Figure 13).

Fig. 12

Distribution of construction quality factor evaluation.

Fig. 13

Distribution of renovation cost factor evaluation.

Calculation of green criterion layer

Based on the green distribution map in national geographic information system, the green coverage evaluation factor distribution was obtained, in which the green coverage rate of newly built communities, park and greenbelts is higher (Figure 14); though extracting and sorting the online map's POI data, the position and range of central greenbelts were extracted, the Select Layer By Location of ArcGIS was used to select the service range of central greenbelts, and the residential area around central greenbelts shows good accessibility, while the industrial area shows a poor accessibility to central greenbelts (Figure 15).

Fig. 14

Distribution of green coverage factor evaluation.

Fig. 15

Distribution of central greenbelt coverage factor evaluation.

Calculation and analysis of comprehensive indexes of inefficient urban land use

The ultimate purpose of inefficiency evaluation of central downtown construction land in Suiling County is to obtain the inefficiency composite index of each planning unit. Referring to relevant studies, the multi-factor superposition method was used to calculate and the weight was given appropriately according to the impact degree of different evaluation indexes on evaluation target, then the evaluation indexes applied with weighted superposition analysis to obtain the comprehensive index of redevelopment potential (Table 7). The land use quantity of each level in Suiling County is shown in Table 8.

Summary of comprehensive index of inefficient land use in Suiling County.

Region ID Inefficient land use index

Suiling County SL-01 7.8441
SL-02 7.7891
SL-03 5.6765
. . . . . .
SL-559 2.4577
SL-560 2.3153

Classification of central downtown's construction land use efficiency grade in Suiling County.

Wight grade [1, 3] (3, 5] (5, 7] (7, 9]
Land block No./piece 68 242 160 91

According to the evaluation results of inefficient urban land use, the higher the comprehensive index of target layer is, the more efficient the urban construction land use in Suiling County will be, otherwise, the lower the comprehensive index is, the more inefficient the urban construction land use will be. The comprehensive index of all land blocks in Suiling County is marked as 5.04, indicating a high efficiency in over land use but still with room for improvement. Viewing from spatial distribution, the efficient districts focus on the residential area in southeast part of the city, and the inefficient districts focus on the industrial area and wild land around the city. By comparing the status land usage, it can be discovered that the lands with higher land use efficiency composite index are mainly class-II residential land; while the lands with lower land use efficiency composite index are mainly industrial lands, class-III residential lands and shanty area (Figure 16).

Fig. 16

Comprehensive index distribution of construction land use efficiency of central downtown in Suiling County.

Conclusion

This set of index system has been verified by inefficient urban land use evaluation system under the background of city examination, which highly coincides with the direction and framework of status of inefficient urban land use. This indicates the indexes selected are effective and accurate and of certain significance to the preliminary determination of inefficient urban land use direction and range.

Fig. 1

Framework of evaluation index system for ineffective urban land use.
Framework of evaluation index system for ineffective urban land use.

Fig. 2

Schematic diagram of AHP hierarchical structure model of inefficient urban land use evaluation.
Schematic diagram of AHP hierarchical structure model of inefficient urban land use evaluation.

Fig. 3

Vectorised schematic diagram of internal construction land for central downtown in Suiling County.
Vectorised schematic diagram of internal construction land for central downtown in Suiling County.

Fig. 4

Public facility distribution in Suiling County.
Public facility distribution in Suiling County.

Fig. 5

Distribution of distance factor evaluation of central commercial facilities.
Distribution of distance factor evaluation of central commercial facilities.

Fig. 6

Distribution of distance factor evaluation of public service facilities.
Distribution of distance factor evaluation of public service facilities.

Fig. 7

Distribution of distance factor evaluation of primary and secondary schools.
Distribution of distance factor evaluation of primary and secondary schools.

Fig. 8

Distribution of urban arterial roads.
Distribution of urban arterial roads.

Fig. 9

Distribution of distance factor evaluation of arterial roads.
Distribution of distance factor evaluation of arterial roads.

Fig. 10

Distribution of population distribution factor evaluation.
Distribution of population distribution factor evaluation.

Fig. 11

Distribution of plot ratio factor evaluation.
Distribution of plot ratio factor evaluation.

Fig. 12

Distribution of construction quality factor evaluation.
Distribution of construction quality factor evaluation.

Fig. 13

Distribution of renovation cost factor evaluation.
Distribution of renovation cost factor evaluation.

Fig. 14

Distribution of green coverage factor evaluation.
Distribution of green coverage factor evaluation.

Fig. 15

Distribution of central greenbelt coverage factor evaluation.
Distribution of central greenbelt coverage factor evaluation.

Fig. 16

Comprehensive index distribution of construction land use efficiency of central downtown in Suiling County.
Comprehensive index distribution of construction land use efficiency of central downtown in Suiling County.

Weights of each evaluation index of criterion layer and factor layer.

Target layer Criterion layer Index layer Index weight

Inefficient urban land use Sharing 0.2617 Distance to public service facility 0.0413
Distance to primary and secondary schools 0.0275
Distance to arterial traffic 0.1377
Distance to commercial facility 0.0551

Coordination 0.5179 Population density 0.1007
Construction quality 0.1726
Renovating cost 0.1151
Plot ratio 0.1295

Central greenbelt coverage ratio 0.0315
Green 0.2204 Green coverage ratio 0.1889

List of evaluation index system of inefficient urban land use.

Target layer Criterion layer Index layer

Evaluation on inefficient urban land use Sharing Distance to public service facility, primary and secondary schools, commercial facility, and arterial traffic
Coordination Construction quality, plot ratio, renovating cost, population density
Green Green coverage ratio, central greenbelt coverage ratio

1–9 scale scoring table.

Index A/B Extremely important Very important Important Weakly important Same important Weakly unimportant Unimportant Very unimportant Extremely unimportant
Index A's evaluation value 9 7 5 3 1 1/3 1/5 1/7 1/9
Index B's evaluation value 1/9 1/7 1/5 1/3 1 3 5 7 9
Remark Take 8, 6, 4, 2, 1/2, 1/4, 1/6, 1/8 as the medians of above evaluation values

Classification table for land use efficiency value of indexes in green criterion layer.

Green index layer Land use efficiency value

1 3 5 7 9

Central greenbelt coverage ratio (m) >2000 1500–2000 1000–1500 500–1000 <500
Green coverage ratio (%) <5 5–15 15–25 25–35 >35

Classification table for land use efficiency value of indexes in coordination criterion layer.

Coordination index layer Land use efficiency value

1 3 5 7 9

Population density Very low Lower Average Higher Very high
Construction quality Very poor Poor Average Good Very good
Renovation cost Level 1 Level 2 Level 3 Level 4 Level 5
Plot ratio >2.0 1.5–2.0 1.0–1.5 0.5–1.0 <0.5

Classification of central downtown's construction land use efficiency grade in Suiling County.

Wight grade [1, 3] (3, 5] (5, 7] (7, 9]
Land block No./piece 68 242 160 91

Classification table for land use efficiency value of indexes in sharing criterion layer.

Sharing index layer Land use efficiency value

1 3 5 7 9

Distance to public service facility (m) 1000–2000 500–1000 200–500 <200 >2000
Distance to primary and secondary schools (m) >2000 1000–2000 500–1000 200–500 <200
Distance to arterial traffic (m) >400 200–400 100–200 50–100 <50
Distance to commercial facility (km) >5 3–5 2–3 1–2 <1

Summary of comprehensive index of inefficient land use in Suiling County.

Region ID Inefficient land use index

Suiling County SL-01 7.8441
SL-02 7.7891
SL-03 5.6765
. . . . . .
SL-559 2.4577
SL-560 2.3153

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