Accessibility and Population Matching Analysis of Public Service

Facilities Based on the Gaussian Mobile Search Method

Huanyu Zhang

and Xiaopeng Cui

2,* b

Sports Institute, Harbin University of Commerce, University street, Harbin, China

School of Finance and Public Administration, Harbin University of Commerce, University Street, Harbin, China

Keywords:

Public Service Facilities Accessibility, Natural Breaks, Gaussian Two-Step Mobile Search Method.

Abstract:

Public service facilities are an essential index to measure urban infrastructure, people's livelihood and

well-being and a necessary standard to evaluate public service management. Taking Daoli District and

Nangang District of Harbin City as the study area, this paper calculates and analyzes the coverage and

population distribution of 15-minute accessibility of public service facilities in the study area based on the

Gaussian two-step mobile search method and ArcGIS Natural breaks. The results show that: 1) The overall

layout of the study area is reasonable, but the spatial layout of public facilities such as cultural, sports, and

medical facilities needs to be strengthened. 2) The data shows that the spatial layout of Daoli District is

more reasonable. 3) Most residents can reach five types of public service facilities within 15 minutes.

1 INTRODUCTION

The construction of public service facilities is the

basis of urban spatial layout and convenience for

residents, which is also an important performance to

measure the working ability of the government and

fulfill the purpose and obligation of the government.

The essence of public service facilities is to serve

citizens, so we should pay attention not only to the

increase in quantity but also to the quality of service.

There are abundant research results on the

accessibility of public service facilities. In terms of

research objects, some scholars pay attention to the

accessibility of park green space (Chen 2020), while

others pay attention to the accessibility of medical

facilities (Xiao, Yuan, Xu 2009). It is relatively

single, so this paper tries to construct a dual index

for analysis. There are also many research methods,

such as the nearest distance method (Fryer 2010),

and the spatial interaction-based method (Spencer

2014, Luo 2004). Through comparison and careful

consideration required in this paper, the Gaussian

two-step search method (Tao 2016) is used for

research and analysis. ArcGIS was used to transform

the data into a plan to show the distribution of public

https://orcid.org/0000-0001-6137-6915

https://orcid.org/0000-0002-4904-6208

service facilities and population, and the concept of

the 15-minute life circle was introduced to evaluate

the matching degree of the two.

2 OVERVIEW OF THE STUDY

AREA

Harbin, the capital city of Heilongjiang Province, is

the provincial capital city with the highest altitude in

the country and is located in the center of Northeast

Asia. By 2021, Harbin had jurisdiction over nine

districts and seven counties, with a total area of

53,186 square kilometers and a permanent

population of nearly 10 million. Nangang District

and Daoli District, which were developed earlier, are

taken as the research areas of this paper.

3 DATA SOURCES AND

RESEARCH METHODS

3.1 Data Sources

The subjects included population, health care,

education, commerce, sports, and public services

such as parks. According to the latest yearbook of

Zhang, H. and Cui, X.

Accessibility and Population Matching Analysis of Public Service Facilities Based on the Gaussian Mobile Search Method.

DOI: 10.5220/0012069600003624

In Proceedings of the 2nd International Conference on Public Management and Big Data Analysis (PMBDA 2022), pages 30-34

ISBN: 978-989-758-658-3

 2023 by SCITEPRESS – Science and Technology Publications, Lda. Under CC license (CC BY-NC-ND 4.0)

the local statistics department, as of October 2021,

there were 2,488,109 people in the experimental

area. Among, Daoli District 1097430 people, and

Nangang District 1390679. Other data were obtained

from local education, planning, civil affairs, and

other relevant departments or government public

information.

3.2 Research Methods

The mobile search method used in the early stage is

based on the calculation of the census unit as the

center, in a given radius of the search area supply

and demand ratio to the target accessibility and two.

Compared with the former, the Gauss two-step

mobile search engine adopted in this paper has two

advantages. First, it solves the problem that the

distance between supply and demand is too long to

be used. Second, it solves the problem of

cross-regional supply of demand by suppliers. The

Gaussian mobile search method is divided into two

steps. First, the coordinates of public facilities are

set as point J, and all residents within the threshold

range of point J are searched. The weighted sum of

the Gaussian function is used to obtain the resident

data within the threshold range of the point where

the facilities are located, and then the

demand-supply ratio of facility J is calculated. The

specific calculation formula is as follows:

𝑅







∑











,







∈

（









(1)

Where: Rj is the supply-demand ratio of facility

point j, S

is the scale (area) of facility point j, D

the distance between facility point j and settlement I

(road network distance), D0 is the search threshold,

is the scale (population) of settlement I within the

threshold, and G (D

, D0) is the Gaussian function.

The specific calculation method is as follows:

𝐺









,



⎩

⎨

⎧





















1



0,𝑑



>𝑑

,𝑑



𝑑

(2)

Step 2: Centering on residential area i, search all

facility points within the threshold range, and

calculate the supply and demand ratio of all facility

points by weighting the Gaussian function. The

specific calculation formula is as follows

∑

G(d

j∈(d

d

)

(3)

Where: A

is the accessibility of settlement I, R

is the supply-demand ratio of facility point j, and G

j,d0) is a Gaussian function. In this paper, the

supply point and demand point are divided into a

50*50 meters grid, and the geographic center of the

grid is used for a two-step mobile search. The

practical significance of the representation of

accessibility calculated based on the Gaussian

two-step mobile search method is the number of

public service facilities accessible to each person in

the research unit. In this paper, the practical meaning

of the representation is the number of public service

facilities available to each person in the grid.

4 DISTRIBUTION

CHARACTERISTICS OF

ACCESSIBILITY OF PUBLIC

SERVICE FACILITIES IN THE

STUDY AREA

4.1 Accessibility of Public Services

4.1.1 Accessibility of Educational Facilities

The maximum value of accessibility to educational

facilities is 4196.04, and the minimum value is 0.

Using the natural break point method in ArcGIS10.2,

the accessibility of educational facilities in the grid

of the study area was divided and calculated

according to five levels. The results showed that

there were 22,557 grids, and the accessibility of

medical facilities for 2,455266 people was below

13.10. Units with per capita accessibility below

13.10 accounted for 98.68% of all grids and 96.24%

of the total population. Again, the natural break

point method was used to divide the grid with

accessibility below 13.10. It can be seen that the

accessibility of medical facilities is spatially "high in

the northwest and low in the southeast".

4.1.2 Accessibility of Medical Facilities

The maximum value of accessibility to medical

facilities was 95.75, and the minimum value was 0.

Using the natural break point method in ArcGIS10.2,

the accessibility of educational facilities in the grid

of the study area was divided and calculated

according to five levels. The results showed that

there were a total of 20193 grids, and the

accessibility of medical facilities for 218,724 people

was below 0.83. Units with per capita accessibility

below 0.83 accounted for 86.24% of all grids and

84.65% of the total population. Again, the natural

break point method was used to divide the grid with

accessibility below 0.83. It can be seen that the

accessibility of medical facilities is spatially "high in

the northwest and low in the southeast".

Accessibility and Population Matching Analysis of Public Service Facilities Based on the Gaussian Mobile Search Method

4.1.3 Accessibility of Commercial Facilities

Put the relevant data into the formula and calculate

the maximum value of commercial facilities

accessibility is 6769.29, and the minimum value is 0.

By using the natural break point method in

ArcGIS10.2, the accessibility of commercial

facilities in the grid of the study area was divided

and calculated according to five levels. The results

showed that there were 22,728 grids, and the

accessibility of commercial facilities for 2,733,165

people was below 41.41. The units with per capita

accessibility below 41.41 accounted for 97.07% of

all grids and 98.61% of the total population. Again,

the natural break point method is used to divide the

grid of accessibility under 41.41. It can be seen that

the accessibility space of commercial facilities

presents "high in the west and low in the east".

4.1.4 Accessibility of Cultural and Sports

Facilities

By putting relevant data into the formula and

calculating, the maximum value of accessibility to

cultural and sports facilities is 1577.73, and the

minimum value is 0. By using the natural break

point method in ArcGIS10.2, the accessibility of

educational facilities in the grid of the study area

was divided and calculated according to five levels.

The results showed that there were 23140 grids, and

the accessibility of cultural and sports facilities for

2,649,426 people was below 10.27. Cells with per

capita accessibility below 10.27 accounted for 98.83%

of all grids and 99.13% of the total population.

Again, the natural break point method is used to

divide the accessibility grid at 10.27. It can be seen

that the accessibility space of cultural and sports

facilities presents "high in the middle and low

around".

4.1.5 Accessibility of Park Facilities

The maximum value of accessibility to park

facilities is 1806.51, and the minimum value is 0.

Using the natural break point method in ArcGIS10.2,

the accessibility of educational facilities in the grid

of the study area was divided and calculated

according to five levels. The results showed that

there were 22,396 grids, and the accessibility of

cultural and sports facilities for 2,785,771 people

was below 14.72. Units with per capita accessibility

below 14.72 accounted for 95.65% of all grids and

96.99% of the total population. Again, the natural

break point method is used to divide the

accessibility grid at 10.27. It can be seen that the

accessibility space of park facilities presents "high

in the northwest and low in the southeast".

4.2 Public Service Facilities and

Population Analysis

Table 1: Accessibility of educational facilities and

population coverage.

index Nangang

District

Daoli

District

15-minute

accessibility

2.34 1.18

Population

coverage

95.82 97.73

As can be seen in Table 1, the accessibility of

educational facilities in Daoli District is 1.18, and

that in Nangang District is 2.34. The accessibility of

Nangang District is nearly twice that of Daoli

District. In terms of the population coverage of

education facilities within 15 minutes, the

population coverage rate of Daoli District is 97.73%,

and that of Nangang District is 95.28%. The

population coverage rate of Daoli District is about

two percentage points higher than that of Nangang

District.

Table 2: Accessibility of medical facilities and population

coverage.

index Nangang

District

Daoli

District

15-minute

accessibility

0.34 0.68

Population

coverage

78.93 92.34

As can be seen from Table 2, the accessibility of

medical facilities in Daoli District is 0.68, and that

in Nangang District is 0.34. The accessibility of

Nangang District is nearly twice that of Daoli

District. In terms of the population coverage of

medical facilities within 15 minutes, the population

coverage rate of Daoli District is 92.34%, and that of

Nangang District is 78.93%. The population

coverage rate of Daoli District is about 15

percentage points higher than that of Nangang

District.

PMBDA 2022 - International Conference on Public Management and Big Data Analysis

Table 3: Accessibility of commercial facilities and

population coverage.

index Nangang

District

Daoli

District

15-minute

accessibilit

9.19 3.31

Population

covera

98.25 99.24

As can be seen from Table 3, the accessibility of

commercial facilities in Daoli District is 3.31, and

that in Nangang District is 9.19. The accessibility of

commercial facilities in Daoli District is less than

half that in Nangang District. The accessibility of

the Nangang district is nearly twice that of the Daoli

District. From the perspective of the population

coverage within 15 minutes of commercial facilities,

the population coverage rate of Daoli District is

99.24%, and that of Nangang District is 98.25%.

The gap between the two is not very large.

Table 4: Accessibility of cultural and sports facilities and

population coverage.

index Nangang

District

Daoli

District

15-minute

accessibilit

0.81 0.40

Population coverage 74.95 93.31

As can be seen from Table 4, the accessibility of

cultural and sports facilities in Daoli District is 0.40,

and that in Nangang District is 74.95, twice that in

Daoli District. The accessibility of Daoli District is

lower than that of Nangang District. However, due

to the large internal differences in Nangang District,

the value of most areas is 0, so the accessibility of

recreational and sports facilities is spatially high in

the middle and low on the two sides.

Table 5: Accessibility of park facilities and population

coverage.

index

Nangang

District

Daoli

District

15-minute

accessibilit

2.09 2.84

Population coverage 93.78 97.94

As can be seen from Table 5, the accessibility of

park facilities in Daoli District is 2.84, and that in

Nangang District is 2.09. The accessibility of Daoli

District is about 1.3 times that of Nangang District.

In terms of population coverage rate, Daoli District

is 97.94, and Nangang District is 93.78. The

population coverage rate of Daoli District is about 4%

higher than that of Nangang District.

4.3 Comparative Analysis

Figure 1: Comparison of accessibility and population

coverage of various facilities.

According to Figure 1, the 15-minute accessibility

and population coverage of commercial, park, and

educational facilities are relatively high. The

15-minute accessibility of cultural, sports, and

medical facilities is less than 85% of the population,

and the accessibility is less than 0.8, indicating that

there is room for optimization of the spatial layout

of cultural, sports, and medical facilities.

5 CONCLUSION

Five types of representative public service facilities

in the study area were selected in the text, and their

grid analysis was carried out by using tools. The

data showed that if the accessibility was greater than

0, it meant that the residents represented by the grid

units were within 15 minutes of the public service

facilities. Further analysis shows that there are

14632 (62.49%) grid data that can use five types of

public facilities within 15 minutes in the study area,

and 2181930 (73.58%) people can reach five types

of public service facilities within a 15-minute life

circle through the conversion of grid units and

population data.

Based on the above analysis, the following three

conclusions are drawn: 1) The accessibility and

population coverage of education facilities,

commercial facilities, and park facilities are

reasonable, and the population distribution is

relatively matched. However, the layout of medical

facilities and cultural and sports facilities is

contradictory to the population distribution, and

there is still a large space for improvement in the

spatial layout. 2) The special spatial distribution of

different public facilities can be seen through the

grid data. On the whole, the accessibility presents a

Accessibility and Population Matching Analysis of Public Service Facilities Based on the Gaussian Mobile Search Method

spatial layout of "high in the middle and low on both

sides". 3) The overall data of 15-minute accessibility

of public facilities are good, with nearly 80% of

residents within its range, and the overall spatial

distribution is reasonable. But there are still some

people who cannot fully enjoy high-quality public

service facilities.

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