A vector spatio-temporal geographic data visualization system based on multi-source data fusion

Abstract

The present invention discloses a vector spatio-temporal geographic data visualization system based on multi-source data fusion, which relates to the technical field of geographic data visualization and improves the accuracy of geographic data display. The present invention associates and maps ground environmental data and remote sensing image data to a geographic data filling area, generates a regional remote sensing image according to the filling condition of the remote sensing image data in the geographic data filling area, further divides a number of characteristic image areas in the regional remote sensing image, and obtains the primary and secondary relevant data of each characteristic image area in the geographic data filling area, establishes a geographic visualization display space with the geographic data filling area as the base, sets a number of vector space blocks above the geographic data filling area, associates the corresponding vector space blocks according to the distribution of the characteristic image areas in the geographic data filling area, and inputs the geographic environment data associated with the characteristic image areas into the vector space blocks.

Description

Technical Field

[0001] The present invention relates to the technical field of geographic data visualization, and particularly to a vector spatio-temporal geographic data visualization system based on multi-source data fusion. Background Art

[0002] In the fields of geographic information science and remote sensing technology, accurately and efficiently collecting and analyzing geographic data is crucial for numerous applications such as urban planning, environmental monitoring, and disaster assessment. Traditional geographic data collection methods often rely on ground surveys or satellite remote sensing, which have certain limitations in terms of coverage, real-time nature, or level of detail.

[0003] With the rapid development of geographic information system (GIS) technology, the scale and complexity of spatio-temporal geographic data have been continuously increasing. Especially in the fields of urban management, ecological environment monitoring, and traffic management, multi-source, multi-dimensional, and multi-temporal geographic data has become an important supporting resource.

[0004] Existing geographic data visualization and display technologies have the following defects:

[0005] Insufficient data fusion ability: When existing systems process multi-source data, they usually adopt simple superposition or splicing methods, lacking in-depth analysis and fusion of the semantic relationships between data. Such simple processing methods are difficult to fully exploit the potential value of multi-source data, resulting in insufficient accuracy and integrity of the visualization results.

[0006] Insufficient interactivity and dynamics: Existing systems have limited functions in user interaction, and it is difficult for users to flexibly perform operations such as data filtering and spatio-temporal slice selection. In addition, the dynamic display function of the system is relatively simple and cannot provide real-time and dynamic visualization effects in complex scenarios, limiting its value in practical applications.

[0007] Therefore, a vector spatio-temporal geographic data visualization system based on multi-source data fusion is provided. Summary of the Invention

[0008] In order to solve the above technical problems, the purpose of the present invention is to provide a vector spatio-temporal geographic data visualization system based on multi-source data fusion.

[0009] In order to achieve the above purpose, the present invention provides the following technical solutions:

[0010] A vector spatio-temporal geographic data visualization system based on multi-source data fusion, including a control center, which is communicatively connected to a geographic data collection module, a vector spatio-temporal data analysis module, and a dynamic visualization display module;

[0011] The geographic data acquisition module is communicatively connected to a number of drones and ground data acquisition units, and flight routes and data storage pools are set for each drone. Then, during the flight of the drones along the flight routes, the drones communicate with the ground data acquisition units in real time. The drones store the collected remote sensing image data in the data storage pools according to the real-time communication results. At the same time, the ground data acquisition units collect the ground environment data at their locations.

[0012] The vector spatio-temporal data analysis module is used to set geographic data filling areas, and according to the storage form of the remote sensing image data in the data storage pools, map the ground environment data and the remote sensing image data to the geographic data filling areas. Regional remote sensing images are generated according to the filling status of the remote sensing image data in the geographic data filling areas. Then, a number of characteristic image areas are divided in the regional remote sensing images, and the primary and secondary relevant data of each characteristic image area are obtained in the geographic data filling areas.

[0013] The dynamic visualization display module is used to establish a geographic visualization display space based on the geographic data filling areas, and set a number of vector space blocks above the geographic data filling areas. The corresponding vector space blocks are associated according to the distribution of the characteristic image areas in the geographic data filling areas, and the geographic environment data associated with the characteristic image areas are input into the vector space blocks. Then, primary and secondary data display chains are set in the vector space blocks according to the primary and secondary relevant data of the characteristic image areas.

[0014] Further, the process of real-time communication between the drones and the ground data acquisition units includes:

[0015] Set a communication detection period, and set device numbers for each ground data acquisition unit. Whenever a communication detection period starts, during the flight of each drone along the flight route over the target geographic area, the drone generates an air-ground communication signal according to its current position information and sends the air-ground communication signal to the ground data acquisition units within the drone's data acquisition range.

[0016] Whenever a ground data acquisition unit receives an air-ground communication signal within its data acquisition range, it synchronously generates a ground communication signal according to its geographic location information and sends the ground communication signal to the corresponding drone.

[0017] Further, the drone has a built-in data storage pool, and a data storage plane mapped according to the size of the drone's data acquisition range is set in the data storage pool.

[0018] Taking the drone flight direction as the positive direction, and according to the geographic location information recorded by the ground communication signals of each ground data acquisition unit and the current position of the drone, multiple data storage spaces are divided in the data storage plane.

[0019] Further, the acquisition process of geographical environment data and remote sensing image data includes:

[0020] During the flight of each unmanned aerial vehicle (UAV) along the flight route, the remote sensing data acquisition device continuously acquires the remote sensing image data within its data acquisition range, and stores the remote sensing image data in the data storage pool in real time. According to the ground data acquisition units corresponding to each data storage space, the remote sensing image data is segmented into several remote sensing image segments, and the corresponding ground data acquisition unit device numbers are marked for each remote sensing image segment.

[0021] At the same time, each ground data acquisition unit acquires a plurality of geographical environment data within its data acquisition range through various sensors.

[0022] Further, the process of dividing the characteristic image area includes:

[0023] A geographical data filling area is established according to the floor area and shape of the target geographical area. The remote sensing image data generated by each UAV at the same moment during the same cycle flight is filled into the geographical data filling area according to the position information of the UAV at the corresponding moment to obtain the regional remote sensing image at the corresponding moment.

[0024] At the same time, according to the device numbers carried in each remote sensing image segment of the remote sensing image data, part of the geographical environment data of the ground data acquisition unit with the corresponding device number at the corresponding moment is bound to the remote sensing image segment corresponding to the remote sensing image data.

[0025] For the regional remote sensing images at each moment, the pixel values of each pixel in the regional remote sensing image are obtained. Then, the Gaussian mixture model divides several characteristic image areas in the regional remote sensing image, and different event numbers are set for each characteristic image area. The characteristic image area consists of several adjacent or scattered pixels.

[0026] Further, the process of obtaining the primary and secondary correlation data of each characteristic image area includes:

[0027] The characteristic image areas in the regional remote sensing images at adjacent moments during the same cycle flight are matched with each other, and then the relative matching degree between the characteristic image areas in the regional remote sensing images at adjacent moments is obtained. Then, according to the relative matching degree between the characteristic image areas, the corresponding two characteristic image areas are set with an association annotation in the regional remote sensing images at the corresponding adjacent moments.

[0028] The geographical environment data associated with each characteristic image area is retrieved from the geographical data filling area, and then a two-dimensional coordinate system is established, and the other data in the geographical environment data that is not image data is mapped to the two-dimensional coordinate system in chronological order.

[0029] Obtain the change slope between the geographical environment data at adjacent moments, and then statistically calculate the total change slope of the geographical environment data associated with each feature image area under the same circular flight;

[0030] Set three slope change intervals, and then, according to which slope change interval the total change slope is located in, record the geographical environment data as irrelevant visualization data, sub-related visualization data or main-related visualization data.

[0031] Further, the process of inputting the geographical environment data associated with the feature image area into the vector space block includes:

[0032] Whenever the vector spatio-temporal data parsing module receives the data from the geographical data acquisition module, it automatically updates the geographical data filling area and synchronizes the updated geographical data filling area to the dynamic visualization display module;

[0033] Whenever the dynamic visualization display module receives the geographical data filling area, according to the pixel distribution of each feature image area in the geographical data filling area, it automatically renders the vector space block at the corresponding position in the geographical visualization display space, and inputs the geographical environment data associated with the corresponding position in the geographical data filling area into the vector space block;

[0034] Furthermore, the vector space block generates a primary and secondary data display chain according to the received data. The primary and secondary data display chain consists of num data nodes, and the data nodes are divided into primary data nodes, secondary data nodes and irrelevant data nodes;

[0035] Furthermore, input the irrelevant visualization data, sub-related visualization data or main-related visualization data of the feature image area into the primary data node, secondary data node and irrelevant data node respectively. num is a natural number greater than 0, representing the total number of types of geographical environment data.

[0036] Further, the vector space block can be associated with different feature image areas at different times. When displaying the position changes of the vector space blocks associated with different feature image areas at each moment, the types of primary and secondary visualization data displayed by the vector space block at the original position change. That is, when the user browses the geographical visualization display space through the time slider, the types of data displayed by each vector space block change dynamically, and the types of data defaultly displayed by the vector space blocks corresponding to the same feature image area are the same.

[0037] Compared with the prior art, the beneficial effects of the present invention are:

[0038] 1. The present invention sets flight routes and data storage pools for each drone. During the flight of the drone along the flight route, real-time communication is established between the drone and the ground data collection unit. The drone stores the collected remote sensing image data in the data storage pool according to the real-time communication results, realizing the real-time communication and data storage mechanism, ensuring the timely update and processing of data, facilitating real-time monitoring and response to environmental changes, and laying a foundation for subsequent data fusion of remote sensing image data and geographical environment data.

[0039] 2. The present invention improves the accuracy and detail of geographical data display by associating and mapping remote sensing image data with ground environment data. At the same time, by establishing a geographical visualization display space and a vector space block, geographical data can be intuitively displayed, facilitating user understanding and decision-making. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] Figure 1 is a schematic diagram of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0041] To further elaborate on the technical means and effects adopted by the present invention to achieve the predetermined invention purpose, the following, in conjunction with the accompanying drawings and preferred embodiments, details the specific embodiments, structures, features, and their effects of the present invention as follows.

[0042] As Figure 1 shown, a vector spatio-temporal geographical data visualization system based on multi-source data fusion includes a control center, and the control center is communicatively connected to a geographical data collection module, a vector spatio-temporal data analysis module, and a dynamic visualization display module;

[0043] The geographical data collection module is communicatively connected to a number of drones and a ground data collection unit, and sets flight routes and data storage pools for each drone. During the flight of the drone along the flight route, real-time communication is established between the drone and the ground data collection unit. The drone stores the collected remote sensing image data in the data storage pool according to the real-time communication results. At the same time, the ground data collection unit collects the ground environment data at its location;

[0044] The vector spatio-temporal data analysis module is used to set geographical data filling areas, and according to the storage form of the remote sensing image data in the data storage pool, associate and map the ground environment data and the remote sensing image data to the geographical data filling areas, generate regional remote sensing images according to the filling status of the remote sensing image data in the geographical data filling areas, and then divide a number of characteristic image areas in the regional remote sensing images, and obtain the primary and secondary related data of each characteristic image area in the geographical data filling areas;

[0045] The dynamic visualization display module is used to establish a geographic visualization display space based on the geographic data filling area, set a number of vector space blocks above the geographic data filling area, associate the corresponding vector space blocks according to the distribution of the feature image area in the geographic data filling area, input the geographic environment data associated with the feature image area into the vector space blocks, and then set the primary and secondary data display chains in the vector space blocks according to the primary and secondary relevant data of the feature image area.

[0046] Further, the working principle of the present invention is illustrated by the following embodiments:

[0047] The geographic data acquisition module is communicatively connected to n drones and m ground data acquisition units, and different numbers a1, a2,..., a n , b1, b2,..., b m are set for each drone and ground data acquisition unit respectively, where n and m are natural numbers greater than 0;

[0048] The drones are equipped with GPS positioning devices, signal transmission devices, and remote sensing data acquisition devices;

[0049] The ground data acquisition unit consists of a GPS positioning device, multiple sensors, and a signal transmission device, and each ground data acquisition unit is installed in the target geographic area, and the types of sensors are, for example, temperature sensors, humidity sensors, infrared detectors, etc.;

[0050] It should be noted that the drones and the ground data acquisition units are both set with fixed data acquisition ranges, and there is partial overlap between the data acquisition ranges of adjacent ground data acquisition units. The area formed by the data acquisition ranges of all ground data acquisition units in the target geographic area is larger than the area of the target geographic area, and the flight speeds of each drone are the same;

[0051] The geographic data acquisition module sets different device numbers for each drone and ground data acquisition unit, such as a154648, etc.;

[0052] Different flight starting points and flight ending points are set for each drone, and a flight route is set with the radius length of the data acquisition range of the drone as the flight route width, so that the drone flies in a loop between the flight starting point and the flight ending point along the flight route, so that the drone can traverse the entire target geographic area during each loop flight. It should be noted that the flight heights of each drone are the same, and there will be no collision between them during the flight along the flight route, and at the same moment, the data acquisition ranges of each drone cover the entire target geographic area;

[0053] A communication detection period is set, and the time length of the communication detection period is generally 10 ms;

[0054] Whenever a communication detection cycle starts, during the flight of each drone along the flight route over the target geographical area, the drone generates an air-ground communication signal based on its current position information and sends the air-ground communication signal to the ground data acquisition unit within the data acquisition range of the drone;

[0055] Whenever the ground data acquisition unit receives the air-ground communication signal within its data acquisition range, it synchronously generates a ground communication signal based on its geographical position information and sends the ground communication signal to the corresponding drone;

[0056] The drone is built-in with a data storage pool, and a data storage plane mapped according to the size of the drone's data acquisition range is set in the data storage pool;

[0057] Taking the flight direction of the drone as the positive direction, and based on the geographical position information recorded by the ground communication signals of each ground data acquisition unit and the current position of the drone, multiple data storage spaces are divided on the data storage plane, where the area size of each data storage space is inversely proportional to the distance between the ground data acquisition unit corresponding to each ground communication signal and the drone.

[0058] Further, during the flight of each drone along the flight route, the remote sensing data acquisition device continuously acquires remote sensing image data within its data acquisition range, and stores the remote sensing image data in the data storage pool in real time, and divides the remote sensing image data into several remote sensing image segments according to the ground data acquisition units corresponding to each data storage space, and labels the device numbers of the corresponding ground data acquisition units for each remote sensing image segment;

[0059] At the same time, each ground data acquisition unit acquires a plurality of geographical environment data within its data acquisition range through various sensors, and the geographical environment data is, for example, a regional heat distribution map and a regional humidity distribution map;

[0060] Whenever each drone completes a round of flight, each drone and the ground data acquisition unit upload the data they acquire to the geographical data acquisition module. Then, after the geographical data acquisition module labels the corresponding drone numbers or device numbers for each item of data, all the data is sent to the vector spatio-temporal data analysis module.

[0061] Further, the vector spatio-temporal data analysis module establishes a geographical data filling area according to the occupied area and the occupied shape of the target geographical area, and fills the remote sensing image data generated by each drone at the same moment during the same round of flight into the geographical data filling area according to the position information of the drone at the corresponding moment to obtain the regional remote sensing image at the corresponding moment;

[0062] At the same time, according to the equipment number in each remote sensing image segment of the remote sensing image data, part of the geographical environment data of the ground data acquisition unit with the corresponding equipment number at the corresponding moment is bound to the remote sensing image segment corresponding to the remote sensing image data;

[0063] A time slider is set for the geographic data filling area, and the remote sensing image data and geographic environment data generated at each moment are bound to the time slider, so that the remote sensing image data and geographic environment data are synchronously displayed and changed in the time dimension as the time slider scrolls;

[0064] For the regional remote sensing image at each moment, the pixel value of each pixel in the regional remote sensing image is obtained, and then the Gaussian mixture model divides a number of characteristic image areas in the regional remote sensing image, and a different event number is set for each characteristic image area. The characteristic image area is composed of a number of adjacent or scattered pixels.

[0065] Furthermore, firstly, the characteristic image regions in the remote sensing images of the adjacent time regions under the same cyclic flight are matched with each other, and then the relative matching degree between the characteristic image regions in the remote sensing images of the adjacent time regions is obtained. The relative matching degree obtaining process includes:

[0066] For any two feature image areas of regional remote sensing images at adjacent times, firstly, one of the feature image areas is selected as the comparison feature image area, and the other feature image area is overlapped and matched starting from the first pixel of the comparison image area. According to the overlap matching, the pixel difference between the pixels at the overlapping position is obtained to see whether it is less than or equal to the pixel difference threshold. If it is less than or equal to the result, then the matching number is recorded once, otherwise no operation is performed;

[0067] Counting and selecting the maximum number of matching times as the first relative matching number, dividing the first relative matching number by the total number of pixels in another feature image region, and then obtaining a first matching degree, and then using another feature image region as a comparison feature image region to repeat the above process of obtaining the matching degree, comparing the two obtained matching degrees, and then selecting the maximum matching degree as the relative matching degree corresponding to the two feature image regions;

[0068] Set a relative matching threshold. If the relative matching degree of a feature image region in the two regional remote sensing images is greater than or equal to the relative matching threshold, then the corresponding feature image region matching combination is recorded. Otherwise, the corresponding feature image region matching combination is discarded.

[0069] Arrange the matching combinations of the remaining characteristic image regions in descending order of relative matching degree. First, according to the matching combination of the characteristic image region with the largest relative matching degree, set associated annotations for the corresponding two characteristic image regions in the remote sensing images of the corresponding adjacent time regions, and eliminate the remaining matching combinations of the characteristic image regions with the above two characteristic image regions. Then, according to the remaining matching combination of the characteristic image region with the largest relative matching degree, set associated annotations for the corresponding two characteristic image regions in the remote sensing images of the corresponding adjacent time regions, and so on, until all the remaining matching combinations of the characteristic image regions are eliminated.

[0070] Further, retrieve the geographical environment data associated with each characteristic image region from the geographical data filling area, and then establish a two-dimensional coordinate system. Map the other data in the geographical environment data that is not image data to the two-dimensional coordinate system in chronological order;

[0071] Obtain the change slope between the geographical environment data at adjacent times, and then calculate the total value of the change slopes of the geographical environment data associated with each characteristic image region during the same cyclic flight;

[0072] Set three slope change intervals: [0, α), [α, γ], and (γ, ∞). For the geographical environment data with the total change slope value in the slope change interval [0, α), it is recorded as irrelevant visualization data;

[0073] For the geographical environment data with the total change slope value in the slope change interval [α, γ], it is recorded as sub-related visualization data;

[0074] For the geographical environment data with the total change slope value in the slope change interval (γ, ∞), it is recorded as main-related visualization data;

[0075] For the geographical environment data whose data type is image data, obtain the total pixel value difference between the geographical environment data at adjacent times, and set three threshold intervals similar to the slope change intervals. Then, according to which interval the total pixel value difference is in, record the geographical environment data whose data type is image data as irrelevant visualization data, sub-related visualization data, or main-related visualization data.

[0076] Further, the dynamic visualization module establishes a geographical visualization space. The geographical visualization space is based on the geographical data filling area, and several vector space blocks of the same size are divided above the geographical data filling area;

[0077] Whenever the vector spatio-temporal data parsing module receives the data from the geographical data acquisition module, it automatically updates the geographical data filling area and synchronizes the updated geographical data filling area to the dynamic visualization module;

[0078] Whenever the dynamic visualization display module receives a geographical data filling area, according to the pixel distribution of each feature image area in the geographical data filling area, it automatically renders the vector space blocks at the corresponding positions in the geographical visualization display space, and inputs the geographical environment data associated with the corresponding positions in the geographical data filling area into the vector space blocks;

[0079] Furthermore, the vector space block generates a primary and secondary data display chain according to the received data. The primary and secondary data display chain consists of num data nodes, and the data nodes are divided into primary data nodes, secondary data nodes, and irrelevant data nodes;

[0080] Furthermore, the irrelevant visualization data, sub-related visualization data, or primary-related visualization data of the feature image area are respectively input into the primary data node, secondary data node, and irrelevant data node. The primary data node is located at the top layer of the primary and secondary data display chain and is default displayed. The secondary data node and the irrelevant data node are successively located at the second layer and the third layer of the primary and secondary data display chain. The user can change the displayed data by clicking on the vector space block. num is a natural number greater than 0, representing the total number of types of geographical environment data;

[0081] The vector space block can be associated with different feature image areas at different times. When showing the position changes of the vector space blocks associated with different feature image areas at each time, the types of primary and secondary visualization data displayed by the vector space block at the original position change. That is, when the user browses the geographical visualization display space through the time slider, the types of data displayed by each vector space block change dynamically, and the types of data default displayed by the vector space blocks corresponding to the same feature image area are the same.

[0082] The above is only a preferred embodiment of the present invention and does not impose any form of limitation on the present invention. Although the present invention has been disclosed above with a preferred embodiment, it is not intended to limit the present invention. Any person skilled in the art can make some changes or modifications to the above-disclosed technical content to obtain equivalent embodiments with equivalent changes, but as long as the technical content of the present invention is not departed from, any brief modifications, equivalent changes, and modifications made to the above embodiments based on the technical essence of the present invention still fall within the scope of the technical solution of the present invention.

Claims

1. A vector spatio-temporal geographic data visualization system based on multi-source data fusion, including a control center, characterized in that, The control center is communicatively connected to a geographic data acquisition module, a vector spatio-temporal data parsing module, and a dynamic visualization display module; The geographic data acquisition module is communicatively connected to a number of unmanned aerial vehicles (UAVs) and a ground data acquisition unit. Flight routes and data storage pools are set for each UAV. During the flight of the UAVs along the flight routes, real-time communication is enabled between the UAVs and the ground data acquisition unit. The UAVs store the collected remote sensing image data in the data storage pools according to the real-time communication results. At the same time, the ground data acquisition unit collects the ground environment data at its location; The vector spatio-temporal data parsing module is used to set geographic data filling areas, and according to the storage form of the remote sensing image data in the data storage pools, map the ground environment data and the remote sensing image data to the geographic data filling areas in an associated manner. Regional remote sensing images are generated according to the filling status of the remote sensing image data in the geographic data filling areas. Then, a number of characteristic image areas are divided in the regional remote sensing images, and the primary and secondary relevant data of each characteristic image area are obtained in the geographic data filling areas; The dynamic visualization display module is used to establish a geographic visualization display space based on the geographic data filling areas, and set a number of vector space blocks above the geographic data filling areas. Corresponding vector space blocks are associated according to the distribution of the characteristic image areas in the geographic data filling areas, and the geographic environment data associated with the characteristic image areas are input into the vector space blocks. Then, a primary and secondary data display chain is set in the vector space blocks according to the primary and secondary relevant data of the characteristic image areas; The process of obtaining the primary and secondary relevant data of each characteristic image area includes: Matching each characteristic image area in the regional remote sensing images at adjacent times during the same cycle of flight, thereby obtaining the relative matching degree between each characteristic image area in the regional remote sensing images at adjacent times. Corresponding two characteristic image areas are set with associated markings in the regional remote sensing images at the corresponding adjacent times according to the relative matching degree between each characteristic image area; Retrieve the geographic environment data associated with each characteristic image area from the geographic data filling areas, and then establish a two-dimensional coordinate system, and map the other data in the geographic environment data that are not image data to the two-dimensional coordinate system in chronological order; Obtain the change slope between the geographic environment data at adjacent times, and then statistically calculate the total change slope value of the geographic environment data associated with each characteristic image area during the same cycle of flight; Set three slope change intervals, and then record the geographic environment data as irrelevant visualization data, secondary relevant visualization data, or primary relevant visualization data according to which slope change interval the total change slope value is located in; 2. The vector spatio-temporal geographic data visualization system based on multi-source data fusion according to claim 1, characterized in that, The process of real-time communication between the UAVs and the ground data acquisition unit includes: Device numbers are set for each ground data acquisition unit. During the flight of each UAV in the upper area of the target geography along the flight route, the UAV generates an air-ground communication signal according to its current position information and sends the air-ground communication signal to the ground data acquisition units within the data acquisition range of the UAV; Whenever the ground data acquisition unit receives the air-ground communication signal within its data acquisition range, it synchronously generates a ground communication signal based on its geographical location information and sends the ground communication signal to the corresponding unmanned aerial vehicle (UAV).

3. A vector spatio-temporal geographic data visualization system based on multi-source data fusion according to claim 1, characterized in that, The UAV is built-in with a data storage pool, and a data storage plane mapped according to the size of the UAV data acquisition range is set in the data storage pool; Taking the UAV flight direction as the positive direction, and based on the geographical location information recorded by the ground communication signals of each ground data acquisition unit and the current position of the UAV, multiple data storage spaces are divided in the data storage plane.

4. A vector spatio-temporal geographic data visualization system based on multi-source data fusion according to claim 2, characterized in that, The acquisition process of geographical environment data and remote sensing image data includes: During the flight of each UAV along the flight route, the remote sensing image data within its data acquisition range is continuously acquired through the remote sensing data acquisition device, and the remote sensing image data is stored in the data storage pool in real time. And according to the ground data acquisition unit corresponding to each data storage space, the remote sensing image data is segmented into several remote sensing image segments, and the equipment numbers of the corresponding ground data acquisition units are marked on each remote sensing image segment. Each ground data acquisition unit acquires a plurality of geographical environment data within its data acquisition range through various sensors.

5. A vector spatio-temporal geographic data visualization system based on multi-source data fusion according to claim 4, characterized in that, The process of dividing the characteristic image area includes: A geographical data filling area is established according to the floor area and occupied shape of the target geographical area, and the remote sensing image data generated by each UAV at the same moment during the same round of cyclic flight is filled into the geographical data filling area according to the position information of the UAV at the corresponding moment, so as to obtain the regional remote sensing image at the corresponding moment; At the same time, according to the equipment numbers carried in each remote sensing image segment of the remote sensing image data, a part of the geographical environment data of the ground data acquisition unit with the corresponding equipment number at the corresponding moment is bound to the remote sensing image segment corresponding to the remote sensing image data; For the regional remote sensing images at each moment, the pixel values of each pixel in the regional remote sensing image are obtained, and then the Gaussian mixture model divides several characteristic image areas in the regional remote sensing image.

6. The vector spatio-temporal geographic data visualization system based on multi-source data fusion according to claim 5, wherein, The process of inputting the geographical environment data associated with the characteristic image area into the vector space block includes: Whenever the vector spatio-temporal data analysis module receives the data from the geographical data acquisition module, it automatically updates the geographical data filling area and synchronizes the updated geographical data filling area to the dynamic visualization display module; Whenever the dynamic visualization display module receives the geographical data filling area, according to the pixel distribution of each characteristic image area in the geographical data filling area, it automatically renders the vector space blocks at the corresponding positions in the geographical visualization display space, and inputs the geographical environment data associated with the corresponding positions in the geographical data filling area into the vector space blocks; Furthermore, the vector space block generates a primary and secondary data display chain according to the received data. The primary and secondary data display chain consists of num data nodes, and the data nodes are divided into primary data nodes, secondary data nodes and irrelevant data nodes; Furthermore, the irrelevant visualization data, sub-relevant visualization data, or main-relevant visualization data in the feature image region are respectively input into the main data node, the sub-data node, and the irrelevant data node, where num is a natural number greater than 0, representing the total number of types of geographical environment data.

7. A vector spatio-temporal geographic data visualization system based on multi-source data fusion according to claim 6, characterized in that, The vector space blocks are respectively associated with different feature image regions at different times, and when showing the position changes of the vector space blocks associated with different feature image regions at each time, the types of primary and secondary visualization data shown by the vector space blocks at the original positions change.

Images