A method for evaluating population coverage capability of a monitoring station based on light remote sensing data

Abstract

The application discloses a kind of based on light remote sensing data's monitoring station population coverage capacity evaluation method, S1, the radio service needing to carry out radio monitoring station population coverage capacity evaluation, in the region to be evaluated, using electromagnetic field simulation or measurement method, combine topography and radio service features to calculate or measure coverage field intensity, obtain monitoring grid area field intensity and corresponding coordinate;The application relates to the technical field of radio management.This based on light remote sensing data's monitoring station population coverage capacity evaluation method, combine night light remote sensing data with monitoring area field intensity data, propose a kind of based on graph model and night light remote sensing data's radio monitoring station population coverage capacity evaluation method, it has practical significance to future radio monitoring network's monitoring coverage evaluation and planning design.

Description

Technical Field

[0001] The present invention relates to the technical field of radio management, and in particular to a method for evaluating the population coverage capability of a monitoring station based on light remote sensing data. Background Art

[0002] Due to the inherent complexity of radio monitoring network construction, there are still many issues to be resolved regarding how to evaluate and calculate the monitoring coverage of radio monitoring networks. Many experts have actively explored this issue. For example, Huang Ming et al. calculated the regional coverage of several typical radio services at fixed monitoring stations in my country and proposed an evaluation scheme for the regional coverage of VHF / UHF fixed monitoring stations. Based on this, Lu Qiannan et al. proposed an evaluation scheme for the regional coverage of fixed monitoring stations in my country's land border areas, taking into account the topography and landforms of border areas and the particularities of radio work in border areas. Zhang Yu et al. compared and analyzed the differences in monitoring regional coverage between Yunnan and Henan provinces, drawing many valuable conclusions. Han Peng et al. selected four frequency bands and conducted multiple experiments to propose a coverage area evaluation scheme for VHF / UHF fixed monitoring stations.

[0003] However, few scholars have addressed other aspects of radio monitoring coverage beyond national assessment standards. In fact, blindly pursuing full regional coverage of radio monitoring results in a waste of social resources and an imbalance in radio monitoring efforts. Radio monitoring should achieve deep coverage in areas with complex electromagnetic environments and continuous coverage in general. Because areas with complex electromagnetic environments often harbor dense populations and intense human activity, exploring methods for calculating the average population coverage of radio monitoring networks is crucial.

[0004] Nighttime light remote sensing data is a barometer of human socioeconomic activity, as it is strongly correlated with social statistics and urban indicators. Furthermore, nighttime light remote sensing data offers inherent advantages in terms of update frequency and spatial and temporal resolution. Therefore, this paper establishes a graphical model that correlates nighttime light remote sensing data with radio service reception field strength data, calculating the average population coverage of radio monitoring stations using an adjacency matrix. The proposed method for assessing the population coverage capability of radio monitoring stations has practical implications for future radio monitoring network monitoring coverage assessment and planning and design. Summary of the Invention

[0005] In view of the shortcomings of the existing technology, the present invention provides a method for evaluating the population coverage capability of a monitoring station based on light remote sensing data, which solves the problems raised in the above background technology.

[0006] To achieve the above objectives, the present invention is implemented through the following technical solutions: a method for evaluating the population coverage capability of a monitoring station based on light remote sensing data, specifically comprising the following steps:

[0007] S1. For radio services requiring population coverage assessment of radio monitoring stations, electromagnetic field simulation or measurement methods are used in the area to be assessed, combining topography and radio service characteristics to calculate or measure the coverage field strength, and obtain the field strength and corresponding coordinates of the grid points in the monitoring area.

[0008] S2. Preprocess the nighttime light remote sensing data: Use the administrative district vector map as a mask for cropping to obtain a nighttime light image of the study area. Then perform necessary georeferencing, projection conversion, and nearest neighbor resampling to align the nighttime light data grid coordinates with the field intensity value coordinates in step 1, thereby obtaining a nighttime light image of the area to be assessed that meets the requirements.

[0009] S3. Taking the county as the minimum research statistical area, establish a population coverage map model of radio monitoring stations based on nighttime light remote sensing data, and store the field intensity data, light data, and corresponding grid coordinates obtained in steps 1 and 2 into a database based on the map model;

[0010] S4. Calculate an adjacency matrix associated with the field intensity data, nighttime light remote sensing data, and coordinate data based on the characteristics of the radio service and the graph model;

[0011] S5. Obtain the population coverage of radio monitoring stations based on adjacency matrix statistics.

[0012] Preferably, in said S3, the population coverage map model of the radio monitoring station based on nighttime light remote sensing data is:

[0013]

[0014] Where G t Represents the graphical model at time t, where t refers to the collection time of the selected nighttime light remote sensing data, V t is a node set, N = |V| is the number of nodes, the field strength data is described using a three-layer structure, including field strength node, service node, and frequency band node v. The lighting data is also described using a three-layer structure, E t is the edge set, M=|E| is the number of edges, X t It is used to represent the node attribute characteristics, edge attribute characteristics and adjacency matrix A. Since the model (1) uses a hierarchical structure to divide the field strength nodes into radio monitoring field strength nodes Radio Service Node and band nodes Therefore, there is a containment relationship between them, that is, Accordingly, the light data can be mapped to the field intensity data and divided into field intensity corresponding light nodes. Business corresponding lighting node and frequency band corresponding to the light node

[0015] Preferably, in said S4, in radio communication and broadcasting applications, since the spatial field strength is only greater than a certain threshold E min The user terminal can receive normally, so the frequency band node v III and the corresponding light node u III In addition to being geographically identical, the adjacency between two nodes must also satisfy the requirement that the spatial field strength is greater than E min , whose value is determined by the radio service attributes, radio wave propagation environment and user terminal reception characteristics. The adjacency matrix in S4 is:

[0016] A vu =[e 11 ,e 12 ,...e 1j ,...e 1m ;e 21 ,e 22 ,...e 2j ...e 2m ;...;e i1 ,e i2 ,...e ij ...e im ;e n1 ,e n2 ,...e nj ...e nm ] T (2)

[0017] Where, the adjacency matrix numbers [1,2,...i...,n] and [1,2,...j...,m] correspond to the frequency band nodes v III and light node u III The grid longitude and latitude, in the adjacency matrix A vu In, e ij =1,i=j,E≥E min Indicates the frequency band node v III and light node u III The longitude and latitude are the same and the field strength is greater than the threshold E min , so the frequency band node v III and light node u III There is an adjacency relationship between them, e ij =0,i=j,E<E min Indicates the frequency band node v III and light node u III The longitude and latitude are the same but the field strength is less than the threshold E min , so the frequency band node v III and light node u III There is no adjacency relationship between them, eij =0, i≠j indicates that the frequency band nodes v have different longitudes and latitudes III and light node u III There is no adjacency between them.

[0018] Preferably, in S4, since the light values ​​at different locations are different, and the larger the light value, the more population the corresponding area has, in order to more accurately characterize the population coverage capability of the radio monitoring station, this method defines an adjacency matrix with weights:

[0019]

[0020] Among them, w ij For adjacent element e ij The weight of the light node u i With field strength node v j Characterization of the coupling coordination between them.

[0021] Preferably, in S5, the population coverage of the radio monitoring station is calculated as follows: Among them, V L is the total light value of the light nodes in the study area, V l It is the total light value of the light nodes at the same position in the spatial grid whose field strength value is greater than or equal to the user receiver sensitivity.

[0022] Beneficial effects

[0023] The present invention provides a method for evaluating the population coverage capability of monitoring stations based on light remote sensing data. Compared with the existing technology, it has the following advantages:

[0024] This method for evaluating the population coverage capability of monitoring stations based on light remote sensing data combines light remote sensing data with field strength data of grid points in the monitoring space area. It proposes a method for evaluating the population coverage capability of radio monitoring stations based on a graphical model and nighttime light remote sensing data. This method has practical significance for the monitoring coverage evaluation and planning and design of future radio monitoring networks. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] Figure 1 This is a schematic diagram of a method for evaluating the population coverage capability of a monitoring station based on light remote sensing data according to the present invention. DETAILED DESCRIPTION

[0026] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0027] Figure 1 In the figure, the right side shows remote sensing data of nighttime lights in a specific area, and the left side shows calculated or measured regional spatial field strength data. Regional spatial field strength is divided into a top-down hierarchy, including the field strength level, service node level, and frequency band node level. This facilitates the management of population coverage data. For example, the broadcast service node includes modulation methods such as FM radio, analog television broadcast, and digital television broadcast. FM radio operates in the 87-108 MHz band and has multiple FM radio stations. Data is constructed from the bottom up during acquisition.

[0028] See also Figure 1 The present invention provides two technical solutions: a method for evaluating the population coverage capability of a monitoring station based on light remote sensing data, specifically including the following embodiments:

[0029] Example 1:

[0030] Without considering the light intensity weight, the population monitoring coverage of the radio monitoring station in Wuhua District, Kunming City for the 100MHz FM radio station was calculated.

[0031] Step 1: Simulate the field strength coverage of the monitoring station, taking into account terrain factors. The main simulation parameters used are: monitoring station coordinates 25.04361, 102.70723, transmission frequency 100 MHz, transmission bandwidth 300 kHz, equivalent isotropic radiated power 50 dBW, peak power 40 dBW, antenna gain 10 dBi, transmitter height above ground 70 m, receiving bandwidth 150 kHz, sensitivity -72 dBm, impedance 50 ohms, signal-to-interference ratio 45 dB, signal-to-noise ratio 45 dB, noise figure 5 dB, and receiver height above ground 70 m.

[0032] Step 2: Use the 2020 average light data of NPP-VIIRS and crop it with the vector map of Wuhua District, Kunming City as a mask to obtain the night light image of the study area. Then perform necessary georeferencing, projection conversion, and resampling using the nearest neighbor method to align the light data coordinates with the field intensity value coordinates in step 1 to obtain a night light image of the area to be evaluated that meets the requirements.

[0033] Step 3: Taking Wuhua District of Kunming City as the research area, establish a population coverage model of radio monitoring stations based on nighttime light remote sensing data. t =(V t ,E t ,X t ), the field strength nodes are divided into radio monitoring field strength nodes using a hierarchical structure Radio Service Node and band nodes Therefore, there is a containment relationship between them, that is, Accordingly, the light data can be mapped to the field intensity data and divided into field intensity corresponding light nodes. Business corresponding lighting node and frequency band corresponding to the light node According to the graphical model, the field intensity data, nighttime light remote sensing data and corresponding grid coordinates obtained in steps one and two are stored in the database.

[0034] Step 4: Establish an adjacency matrix that associates field intensity data, nighttime light remote sensing data, and coordinate data. vu =[e 11 ,e 12 ,...e 1j ,...e 1m ;e 21 ,e 22 ,...e 2j ...e 2m ;...;e i1 ,e i2 ,...e ij ...e im ;e n1 ,e n2 ,...e nj ...e nm ] T

[0035] Where, the adjacency matrix numbers [1,2,...i...,n] and [1,2,...j...,m] correspond to the frequency band nodes v III and light node u III The grid longitude and latitude of . In the adjacency matrix A vu In, e ij =1,i=j,E≥E min Indicates the frequency band node v III and light node u III The longitude and latitude are the same and the field strength is greater than the threshold E min , so the frequency band node v III and light node u III There is an adjacency relationship between them; ij =0,i=j,E<E min Indicates the frequency band node v III and light node u III The longitude and latitude are the same but the field strength is less than the threshold E min , so the frequency band node v III and light node u III There is no adjacency relationship between them; ij =0, i≠j indicates that the frequency band nodes v have different longitudes and latitudesIII and light node u III There is no adjacency between them.

[0036] Step 5: Calculate the population coverage of radio monitoring stations based on the graph model and adjacency matrix. The calculation of the population coverage of radio monitoring stations is: R p =V l ÷V L , where V L is the total light value of the light nodes in the study area, V l It is the total light value of the light nodes at the same grid position whose field strength value is greater than or equal to the user's FM radio receiver sensitivity of 48dB (μv / m). The calculation result is R p =44.40%

[0037] Example 2

[0038] Taking the light intensity weight into consideration, the population monitoring coverage of the radio monitoring station in Wuhua District, Kunming City for the 100MHz FM radio station was calculated.

[0039] Step 1: Simulate the radio monitoring station's field strength coverage, taking terrain factors into account. The main simulation parameters used are: monitoring station coordinates 25.04361, 102.70723, transmit frequency 100 MHz, transmit bandwidth 300 kHz, equivalent isotropic radiated power 50 dBW, peak power 40 dBW, antenna gain 10 dBi, transmitter height 70 m, receiving bandwidth 150 kHz, sensitivity -72 dBm, impedance 50 ohms, signal-to-noise ratio 45 dB, noise figure 5 dB, and receiver height 70 m.

[0040] Step 2: Use the 2020 average light data of NPP-VIIRS and crop it with the vector map of Wuhua District, Kunming City as a mask to obtain the night light image of the study area. Then perform necessary georeferencing, projection conversion, and resampling using the nearest neighbor method to align the night light data coordinates with the field intensity value grid coordinates in step 1 to obtain a night light image of the area to be evaluated that meets the requirements.

[0041] Step 3: Taking Wuhua District of Kunming City as the research area, establish a population coverage model of radio monitoring stations based on nighttime light remote sensing data. t =(V t ,E t ,X t ), the field strength nodes are divided into radio monitoring field strength nodes using a hierarchical structure Radio Service Node and band nodes Therefore, there is a containment relationship between them, that is, Accordingly, the light remote sensing data is corresponded with the field strength data, and is divided into field strength corresponding light nodes Business corresponding light nodes And frequency band corresponding light nodes According to the graph model, the field strength data, the night light remote sensing data and the corresponding coordinates obtained in steps one and two are stored in a database.

[0042] Step four: an adjacency matrix of the association of the field strength data, the night light remote sensing data and the grid coordinate data is established.

[0043] In the formula, the adjacency matrix numbers [1, 2,..., i,..., n] and [1, 2,..., j,..., m] respectively correspond to the grid longitude and latitude of the frequency band node v III and the light node u III In the adjacency matrix A vu , e ij =1, i=j, E≥E min indicates that the longitude and latitude of the frequency band node v III and the light node u III are the same and the field strength is greater than the threshold E min , so there is an adjacency between the frequency band node v III and the light node u III ; e ij =0, i=j, E<E min indicates that the longitude and latitude of the frequency band node v III and the light node u III are the same but the field strength is less than the threshold E min , so there is no adjacency between the frequency band node v III and the light node u III ; e ij =0, i≠j indicates that there is no adjacency between the frequency band node v III and the light node u III with different longitude and latitude. Wherein w ij is the weight of the adjacency element e ij , which is characterized by the coupling coordination between the light node u i and the field strength node v j , and the following coupling coordination model is used to calculate the weight:

[0044] When n=2, and assuming maxU i =U2, the coupling coordination model is simplified as: So the calculation method of the weight w ij of the adjacency element e ij is as follows: Assuming max(u i,v j )=u i , the weight calculation expression is simplified as follows:

[0045]

[0046] Step 5: Calculate the population coverage of radio monitoring stations based on the graph model and adjacency matrix. The calculation of the population coverage of radio monitoring stations is: R p =V l ÷V L , where V L is the total light value of the light nodes in the study area, V l The field strength value is greater than or equal to the user's FM radio receiver sensitivity 48dB (μv / m) corresponding to the total light value of the light node at the same location. The calculation result is R p =92.50%, and the contents not described in detail in this specification belong to the prior art known to those skilled in the art.

[0047] It should be noted that, in this document, relational terms such as first and second, etc., are used only to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations. Moreover, the terms "comprises," "comprising," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that includes a list of elements includes not only those elements but also other elements not explicitly listed, or elements inherent to such process, method, article, or apparatus.

[0048] While embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions, and variations may be made to these embodiments without departing from the principles and spirit of the invention, and that the scope of the invention is defined by the appended claims and their equivalents.

Claims

1. A method for evaluating the population coverage capability of monitoring stations based on light remote sensing data, characterized by: The specific steps include: S1. For radio services requiring population coverage assessment of radio monitoring stations, electromagnetic field simulation or measurement methods are used in the area to be assessed, combining topography and radio service characteristics to calculate or measure the coverage field strength, and obtain the field strength and corresponding coordinates of the grid points in the monitoring area. S2. Preprocess the nighttime light remote sensing data: Use the administrative district vector map as a mask for cropping to obtain a nighttime light image of the study area. Then perform necessary georeferencing, projection conversion, and nearest neighbor resampling to align the nighttime light data grid coordinates with the field intensity value coordinates in step 1, thereby obtaining a nighttime light image of the area to be assessed that meets the requirements. S3. Taking the county as the minimum research statistical area, establish a population coverage map model of radio monitoring stations based on nighttime light remote sensing data, and store the field intensity data, light data, and corresponding grid coordinates obtained in steps 1 and 2 into a database based on the map model; S4. Calculate an adjacency matrix associated with the field intensity data, nighttime light remote sensing data, and coordinate data based on the characteristics of the radio service and the graph model; S5. Obtain the population coverage rate of the radio monitoring station according to the adjacency matrix statistics. In S3, the population coverage map model of the radio monitoring station based on the nighttime light remote sensing data is: (1) Where, Represents the graphical model at time t, where t refers to the collection time of the selected nighttime light remote sensing data. It is a node set. The field intensity data is described by a three-layer structure. The light data is also described by a three-layer structure. is an edge set, Used to represent node attribute features, edge attribute features and adjacency matrix , since the model (1) uses a hierarchical structure to divide the field strength nodes into radio monitoring field strength nodes , Radio Service Node and band nodes , so there is a containment relationship between them, that is ; Accordingly, the light data can be matched with the field intensity data, and the light nodes can be divided into field intensity corresponding light nodes , business corresponding lighting node and frequency band corresponding to the light node , ; In S5, the population coverage rate of radio monitoring stations is calculated as: ,in, is the total light value of the light nodes in the study area, It is the total light value of the light nodes at the same grid position whose field strength value is greater than or equal to the user receiver sensitivity.

2. The method for evaluating the population coverage capability of a monitoring station based on light remote sensing data according to claim 1, characterized in that: In the above S4, in radio communication and broadcasting applications, since the spatial field strength is only greater than a certain threshold field strength value, The user terminal can receive normally, so the frequency band node and the corresponding light nodes In addition to the same geographic grid position, the adjacency between two nodes must also satisfy the spatial field strength greater than , whose value is determined by the radio service attributes, radio wave propagation environment and user terminal reception characteristics. The adjacency matrix in S4 is: (2) Where, the adjacency matrix number is and Corresponding to frequency band nodes and light nodes The grid longitude and latitude, in the adjacency matrix middle, Indicates frequency band node and light nodes The longitude and latitude are the same and the field strength is greater than the threshold , so the frequency band node and light nodes There is an adjacency relationship between them. Indicates frequency band node and light nodes The latitude and longitude are the same but the field strength is less than the threshold , so the frequency band node and light nodes There is no adjacency relationship between them. Indicates frequency band nodes with different longitudes and latitudes and light nodes There is no adjacency between them.

3. The method for evaluating the population coverage capability of a monitoring station based on light remote sensing data according to claim 2, characterized in that: In S4, since the light values ​​at different locations are different, and the larger the light value, the more population the corresponding area has, in order to more accurately characterize the population coverage capability of the radio monitoring station, this method defines an adjacency matrix with weights: (3) in, For adjacent elements The weight of the light node Field strength node Characterization of the coupling coordination between them.

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