Analysis of the Distribution Characteristics
and Influencing Factors of AdvertisingBillboards in Wuhan
Shaohua Wang, Aerospace Information Research Institute, China
Cheng Su, Aerospace Information Research Institute, China
Juanyuan Zhou, Lanzhou Jiaotong University, China
Xiao Li, Lanzhou Jiaotong University, China
Dachuan Xu, Lanzhou Jiaotong University, China
Wenyu Wei, Lanzhou Jiaotong University, China

Contents
1. Background and Significance
2. Methods
3. Results
4. Conclusion

01

Background and Significance1.Background and SignificanceBillboard
Placement

Surrounding Environment
Traffic Conditions
Target Audience……

ImprovedAdvertising Impactand Business Value

The optimization of billboard placement is greatly facilitated by an understandingof the current spatial distribution of existing billboards.
Traditional Methods

Spatial Analysis

Traditional methods relying on

The spatial analysis method cansubjective memory and experience

yield more specific andare prone to distortion over time,comprehensive analysis results

making them less reliable02

Methods

2.Methods
Study Area and Data
Table 1. Classification of impact factors

Figure 2: Spatial Distribution of Billboards inWuhan City

The comprehensive use of these data to select the location
can improve the exposure rate of billboards so that theadvertising effect can be as optimal as possible.
So, studying these influencing factors is crucial.

2.Methods
WorkflowØ Average Nearest Neighbor Method and Kernel
Density Analysis : investigate whether billboards
exhibit clustered distribution and the extent ofclusteringØ Standard Deviation Ellipse Analysis : examine
the directional distribution characteristics ofbillboards
Ø Hotspot and Coldspot Analysis : identify areas
with high and low concentrations of billboards
Ø Geodetector Analysis : explore the factors
influencing billboard distribution
Figure 1: The Research Framework of This
Article2.Methods
Geodetector

In this study, the Geodetector model is used to quantify the individual andinteractive effects of various influencing factors on the spatial distribution of
billboards in Wuhan City. It aims to reveal the primary influencing factors ofbillboard spatial distribution in Wuhan and the ways in which these factors interact.

The q-value falls within the range of [0,1],
indicating the magnitude of the impact of
this influencing factor on the spatial
distribution of billboards in Wuhan City.
A larger value indicates a greater impact.

03Results

3.Results
Spatial Analysis

Standard DeviationalEllipse

Average Nearest
Neighbor

Figure 3: Directional Distribution Analysis(Standard Error Ellipses)

Figure 4: The report on the average nearest
neighbor results
Figure 2: Spatial Distribution ofBillboards in Wuhan City

3.Results
Hot Spot Analysis and Kernel Density Analysis

Figure 5: Hotspot analysis

Figure 6: Kernel Density Analysis Chart

The hot spot analysis results show that thedistribution of billboards in Wuhan presents
an obvious hot spot aggregation pattern. Incontrast, the cold spots are distributed in aring pattern, mainly in the farther outerregions. The results of the kernel density
analysis show a unique multi-modal
pattern, indicating polarization.

3.Results
Geodetector

Figure 7: Interaction Detector Results

Bus Route Density (X3) > Number of Shared Bicycle
Returns per Kilometer Grid (X8) > Number of Shared
Bicycle Rentals per Kilometer Grid (X7) > Bus Stop
Density (X2) > Charging Station Density (X5) >Building Density (X6) > Road Density (X4) >Population Density (X1)•••

The spatial differentiation pattern of billboards in Wuhan
City is not controlled by a single factor but is the result of
the combined action of multiple factors.
Largest : Bus Route Density (X3) and Charging Station
Density (X5)
Smallest : Road Density (X4) and Population Density(X1)04Conclusion

4.Conclusion• By utilizing various spatial analysis methods, we explore the influence of different
factors on the spatial distribution of billboards.
• From the aforementioned analysis, it is evident that the optimal placement of billboards
should be closely associated with public transportation infrastructure and other relevantstructures.
• The methods and tools employed in this paper can serve as a reference for spatial
distribution analysis in other cities.
• This study has certain limitations, such as the failure to consider the impact ofcompetition between different types of billboards on their placement. In the future, wewill continue to improve and expand spatial analysis methods, focusing on delving
deeper into the spatial distribution patterns of billboards in Wuhan.
• This will provide more valuable insights for optimizing the placement of billboards.

Thank you for your listening!