Vector geographic information acquisition method and system based on remote sensing image

Abstract

The invention discloses a vector geographic information acquisition method and system based on a remote sensing image, and relates to the technical field of remote sensing image.The system adopts an unmanned aerial vehicle remote sensing technology to continuously capture geographic image information of a high mountain, efficient coverage of complex terrains is achieved, and the acquisition efficiency of geographic information is improved; the related environment data and the atmosphere situation data around the unmanned aerial vehicle are collected in real time according to different positions of the unmanned aerial vehicle, multi-aspect background information is provided for follow-up processing, and various environment factors in the geographic image acquisition process are considered; by calculating the visibility coefficient Njdx, the feasibility and availability of geographic image information acquisition can be further accurately evaluated; and a corresponding adjustment strategy is automatically made by comparing a preset visible threshold value Q with the visibility coefficient Njdx, so that the data accuracy and stability in the geographic image acquisition process are ensured.

Description

Technical Field

[0001] The present invention relates to the technical field of remote sensing images, and in particular to a method and system for collecting vector geographic information based on remote sensing images. Background Art

[0002] As a means of obtaining information about the earth's surface, remote sensing technology is widely used in agriculture, urban planning, resource management and other fields. In geographic information science and technology, vector data is an important form of describing geographical phenomena and geographic spatial relationships. Therefore, vector geographic information acquisition systems based on remote sensing images are widely used in spatial information processing and geographic data analysis. With the continuous development of drone technology, drone remote sensing has become one of the effective means of obtaining high-resolution geographic information.

[0003] However, when capturing geographic images of high mountains, as the drone continuously changes its altitude Gdz position, the surrounding environmental conditions will also change accordingly. In practical applications, the special terrain and climatic conditions in mountainous areas pose challenges to drone remote sensing. When the drone continuously adjusts its altitude Gdz position and inclination, it faces variable environmental factors such as atmospheric conditions, lighting conditions, and terrain slope, which are prone to offset and affect the precise collection of the final geographic image information, resulting in a certain error between the captured geographic image and the actual target, and may also cause fluctuations in image quality, affecting the accurate acquisition of geographic information. This problem is often ignored in traditional drone remote sensing, resulting in unsatisfactory accuracy and reliability of image acquisition. Summary of the invention

[0004] ( 一 ) Technical issues solved

[0005] In view of the deficiencies in the prior art, the present invention provides a method and system for collecting vector geographic information based on remote sensing images to solve the problems in the above-mentioned background technology.

[0006] (II) Technical solution

[0007] To achieve the above objectives, the present invention is implemented through the following technical solutions: a vector geographic information acquisition system based on remote sensing images, including a route planning module, a data acquisition module, a processing module, a condition analysis module, a vectorization module and a deviation comparison module;

[0008] The route planning module is used to continuously capture geographic image information of the mountains using UAV remote sensing technology, predetermine the route of the UAV to determine the geographical area of ​​the mountains that need to be captured, and when capturing geographic image information, adjust the height Gdz and inclination Qxd of the UAV in real time according to the slope trend of the mountains;

[0009] The data acquisition module is used to collect and record relevant environmental data information around the drone and relevant atmospheric situation data information in the atmosphere when the drone captures geographic image information, and generate a capture status data set;

[0010] The processing module is used to upload relevant environmental data information and relevant atmospheric situation data information to the capture state data set, and perform data preprocessing and feature extraction on them; and preprocess the continuous image frames in the geographic image information, remove noise, smooth the image, and perform geometric correction, and identify and extract effective features in the continuous image frames, and improve the image quality based on image enhancement technology to generate a geographic image data set;

[0011] The condition analysis module is used to perform machine analysis on the relevant data information in the capture state data set after feature extraction, obtain the atmospheric condition factor Dqyz and the environmental condition factor Hjyz, and associate the atmospheric condition factor Dqyz with the environmental condition factor Hjyz, and obtain the visibility coefficient Njdx after dimensionless processing. The visibility coefficient Njdx is obtained by the following formula:

[0012]

[0013] In the formula, F 1 Expressed as the proportionality coefficient of the atmospheric condition factor Dqyz, F 2 Expressed as the proportional coefficient of the environmental condition factor Hjyz, F 3 Expressed as the proportional coefficient of the slope Qxd, 0.06≤F 1 ≤0.26, 0.10≤F 2 ≤0.33, 0.20≤F 3 ≤0.41, and 0.45≤F 1 +F 2 +F 3 ≤1.0, P represents the first correction constant;

[0014] The vectorization module is used to convert the captured geographic image information into vector data and generate a vector layer to represent the geometric shapes and spatial relationships of different objects;

[0015] The deviation comparison module is used to obtain a preset visibility threshold Q based on the determined mountainous geographical area that needs to be captured, and compare and analyze the preset visibility threshold Q with the visibility coefficient Njdx to obtain the analysis result of the vector layer, and make corresponding adjustment strategies based on the analysis result.

[0016] Preferably, the route planning module includes a predetermined route unit and a real-time positioning unit;

[0017] The predetermined route unit is used to obtain and plan the route of the UAV remote sensing according to the geographical image information of the high mountain section to be obtained and the geographical location in the map;

[0018] The real-time positioning unit is used to continuously capture geographic image information of the side of the mountain according to the planned UAV flight route and the slope trend of the mountain, and to locate the position of the UAV on the mountain in real time, so as to obtain relevant environmental data information and relevant atmospheric situation data information around the UAV at different heights Gdz and inclinations Qxd.

[0019] Preferably, the data acquisition module includes a first data acquisition unit, a second data acquisition unit and a geographic image acquisition unit;

[0020] The first data acquisition unit is used to collect relevant atmospheric situation data information around the drone in real time according to the drone at different heights Gdz and inclinations Qxd, wherein the relevant atmospheric situation data information includes the pressure state in the atmosphere, the atmospheric transparency Tmdz, the water vapor concentration Szqn, the atmospheric turbulence state, the aerosol concentration, and the temperature difference Wdc and humidity difference generated by the drone at different heights Gdz;

[0021] The second data acquisition unit is used to collect relevant environmental data information around the drone in real time when the drone is at different heights Gdz and inclinations Qxd, wherein the relevant environmental data information includes wind speed Fsz, wind direction, particle volume Klwt, light intensity Gxqd and meteorological weather conditions;

[0022] The geographic image acquisition unit is used to use drone remote sensing to obtain continuous image frames of the side of the mountain to generate geographic image information, wherein the geographic image information includes the slope, slope direction, soil condition, geological structure, human activity area, water body distribution, and vegetation type and distribution data information of the mountain section to be acquired.

[0023] Preferably, the processing module includes a data preprocessing unit and an image enhancement unit;

[0024] The data preprocessing unit is used to detect and delete the repeatedly collected relevant environmental data information and relevant atmospheric situation data information to avoid the deviation of the analysis caused by the data duplication, and normalize the units by using the dimensionless processing technology;

[0025] The image enhancement unit is used to extract key feature information in continuous image frames through image enhancement technology, identify and analyze defective parts in the image, and select and adjust the difference between different areas in the image frame according to their characteristics.

[0026] Preferably, the high mountain segments to be acquired are imaged and a three-dimensional regional model is constructed based on UAV remote sensing technology, and spatial analysis technology is used in the three-dimensional regional model to distinguish the relevant environmental data information and relevant atmospheric situation data information acquired based on the different Gdz states of the UAV at different altitudes.

[0027] Preferably, the atmospheric transparency Tmdz and the water vapor concentration Szqn are correlated and dimensionlessly processed to obtain the atmospheric condition factor Dqyz, which is obtained by the following formula:

[0028]

[0029] In the formula, α and β are both proportional coefficients, Wdc is the temperature difference generated by the drone at different altitudes Gdz, Yqz is the pressure coefficient, and C is the second correction constant;

[0030] The condition threshold Z is set in advance, and the condition threshold Z is compared and analyzed with the atmospheric condition factor Dqyz to determine whether the drone needs to use multiple time series to capture the geographical image information of the mountain figure for multiple times. The analysis results are as follows:

[0031] If the atmospheric condition factor Dqyz is greater than or equal to the condition threshold Z, that is, Dqyz ≥ Z, it will be determined that the drone needs to use multiple time series to capture the geographical image information of the mountain to be acquired multiple times;

[0032] If the atmospheric condition factor Dqyz is less than the condition threshold Z, that is, Dqyz<Z, it will be determined that there is no need to use multiple time series for the UAV.

[0033] Preferably, the wind speed Fsz is associated with the light intensity Gxqd, and after dimensionless processing, the environmental condition factor Hjyz is obtained, and the environmental condition factor Hjyz is obtained by the following formula:

[0034]

[0035] Where Klwt represents the volume of particles, b 1 and b 2 Both are expressed as proportional coefficients, and g is expressed as the third correction constant.

[0036] Preferably, the vectorization module includes a target recognition unit and a vectorization processing unit;

[0037] The target recognition unit is used to recognize the types of different objects in the captured geographic image information, wherein the types of objects include buildings, roads, vegetation and pedestrian roads;

[0038] The vector processing unit is used to convert the geographic image information in the target recognition unit into vector data, generate high mountain vector geometry, so as to represent the shape and position of the high mountain surface.

[0039] Preferably, the preset visibility threshold Q is compared with the visibility coefficient Njdx to obtain the analysis result of the vector layer:

[0040] If the visibility coefficient Njdx is greater than the preset visibility threshold Q, it means that the high mountain geographical area currently captured by the drone remote sensing deviates from the high mountain figure to be acquired, and the captured geographical image information has a phenomenon of mis-shooting. At this time, a red warning notification will be triggered in time, the altitude Gdz and inclination Qxd of the drone will be adjusted, and continuous image capture will be performed at multiple time points;

[0041] If the visibility coefficient Njdx is equal to the preset visibility threshold Q, it means that the alpine geographical area currently captured by the UAV remote sensing is at the position of the alpine segment to be acquired, and no deviation occurs, and the capture operation continues at this time;

[0042] If the visibility coefficient Njdx is less than the preset visibility threshold Q, it means that the mountain geographical area currently captured by UAV remote sensing is in the position of the mountain segment to be acquired, but there is repeated image information in the continuously captured geographical image information. At this time, the processing module will be used to deduplicate the repeated image information.

[0043] Preferably, a method for collecting vector geographic information based on remote sensing images comprises the following steps:

[0044] Step 1: Use the UAV remote sensing technology to capture the image of the mountain to be acquired through the route planning module to obtain geographic image information, and when capturing the geographic image information, adjust the height Gdz and inclination Qxd of the UAV in real time according to the slope trend of the mountain;

[0045] Step 2: The data acquisition module collects relevant environmental data information around the drone and relevant atmospheric situation data information in the atmosphere according to the altitude Gdz of the drone, and generates a capture status data set;

[0046] Step 3: Preprocess the relevant data information in the capture state data set and extract features through the processing module, preprocess the continuous image frames in the geographic image information, identify and extract effective features in the continuous image frames, and improve the image quality based on image enhancement technology to generate a geographic image data set;

[0047] Step 4: Perform machine analysis on the relevant data information in the captured state data set after feature extraction through the condition analysis module to obtain the atmospheric condition factor Dqyz and the environmental condition factor Hjyz, and associate the atmospheric condition factor Dqyz with the environmental condition factor Hjyz, and obtain the visibility coefficient Njdx after dimensionless processing;

[0048] Step 5: Convert the captured geographic image information into vector data through a vectorization module and identify the types of different land features;

[0049] Step 6: Compare and analyze the preset visibility threshold Q with the visibility coefficient Njdx through the deviation comparison module, obtain the analysis result of the vector layer, and make corresponding adjustment strategies according to the analysis result.

[0050] (III) Beneficial effects

[0051] The present invention provides a method and system for collecting vector geographic information based on remote sensing images, which has the following beneficial effects:

[0052] (1) The system uses UAV remote sensing technology to continuously capture geographic image information of high mountains, achieve efficient coverage of complex terrain, and improve the efficiency of obtaining geographic information; and fully considers that as the position of the UAV changes, the relevant environmental data and atmospheric situation data around the UAV are collected in real time to provide multi-faceted background information for subsequent processing, taking into account various environmental factors in the process of acquiring geographic images; by calculating the visibility coefficient Njdx, it helps to further accurately evaluate the feasibility and availability of geographic image information collection; and by comparing the preset visibility threshold Q and the visibility coefficient Njdx, the corresponding adjustment strategy is automatically made to ensure the accuracy and stability of data in the process of geographic image collection. In short, compared with the existing technology, this system fully considers the dynamic changes of environmental conditions and performs real-time collection, thereby further accurately capturing geographic image information.

[0053] (2) In the prior art, spatial analysis technology is used in a three-dimensional regional model. The system can obtain relevant environmental data information and atmospheric situation data information according to the different altitudes Gdz of the drone, and distinguish them. This is convenient for detecting whether the drone will be affected by external factors when it is at different altitudes Gdz, causing the high mountain geographical area captured by drone remote sensing to deviate from the high mountain figure to be acquired, and the captured geographical image information has the phenomenon of mis-shooting. This provides the system with the ability to conduct in-depth analysis of geographical images; by pre-setting the condition threshold Z and comparing it with the atmospheric condition factor Dqyz, according to the analysis results, the system can determine whether it is necessary to use multiple time series, that is, whether it is necessary for the drone to capture multiple images of the high mountain figure to be acquired, so that it can respond to different environmental conditions more flexibly; by judging whether the atmospheric condition factor Dqyz reaches the set condition threshold Z, the system can decide whether to use multiple time series. If the atmospheric conditions are good, there is no need to capture multiple times, thereby improving the efficiency of image capture and further reducing the waste of resources and time. BRIEF DESCRIPTION OF THE DRAWINGS

[0054] Figure 1 It is a schematic diagram of a flow chart of a vector geographic information acquisition system based on remote sensing images of the present invention;

[0055] Figure 2 The present invention is a schematic diagram of the steps of a method for collecting vector geographic information based on remote sensing images. DETAILED DESCRIPTION

[0056] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. 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 creative work are within the scope of protection of the present invention.

[0057] As a means of obtaining information about the earth's surface, remote sensing technology is widely used in agriculture, urban planning, resource management and other fields. In geographic information science and technology, vector data is an important form of describing geographical phenomena and geographic spatial relationships. Therefore, vector geographic information acquisition systems based on remote sensing images are widely used in spatial information processing and geographic data analysis. With the continuous development of drone technology, drone remote sensing has become one of the effective means of obtaining high-resolution geographic information.

[0058] However, when capturing geographic images of high mountains, as the drone constantly changes its altitude Gdz position, the surrounding environmental conditions will also change accordingly. In practical applications, the special terrain and climatic conditions in mountainous areas pose challenges to drone remote sensing. When the drone constantly adjusts its altitude Gdz position and inclination, it faces variable environmental factors such as atmospheric conditions, lighting conditions, and terrain slope, which can easily cause deviations, resulting in certain errors between the captured geographic images and the actual targets. This may also cause fluctuations in image quality and affect the accurate acquisition of geographic information. This problem is often overlooked in traditional drone remote sensing, resulting in unsatisfactory accuracy and reliability of image acquisition.

[0059] Example 1

[0060] See also Figure 1 ,The present invention provides a vector geographic information acquisition system based on remote sensing images, including a route planning module, a data acquisition module, a processing module, a condition analysis module, a vectorization module and a deviation comparison module;

[0061] The route planning module is used to continuously capture geographic image information of the mountains using UAV remote sensing technology, predetermine the route of the UAV to determine the geographical area of ​​the mountains that need to be captured, and when capturing geographic image information, adjust the height Gdz and inclination Qxd of the UAV in real time according to the slope trend of the mountains;

[0062] The data acquisition module is used to collect and record relevant environmental data information around the drone and relevant atmospheric situation data information in the atmosphere when the drone captures geographic image information, and generate a capture status data set;

[0063] The processing module is used to upload relevant environmental data information and relevant atmospheric situation data information to the capture state data set, and perform data preprocessing and feature extraction on them; and preprocess the continuous image frames in the geographic image information, remove noise, smooth the image, and perform geometric correction, and identify and extract effective features in the continuous image frames, and improve the image quality based on image enhancement technology to generate a geographic image data set;

[0064] The condition analysis module is used to perform machine analysis on the relevant data information in the capture state data set after feature extraction, obtain the atmospheric condition factor Dqyz and the environmental condition factor Hjyz, and associate the atmospheric condition factor Dqyz with the environmental condition factor Hjyz, and obtain the visibility coefficient Njdx after dimensionless processing. The visibility coefficient Njdx is obtained by the following formula:

[0065]

[0066] In the formula, F1 Expressed as the proportionality coefficient of the atmospheric condition factor Dqyz, F 2 Expressed as the proportional coefficient of the environmental condition factor Hjyz, F 3 Expressed as the proportional coefficient of the slope Qxd, 0.06≤F 1 ≤0.26, 0.10≤F 2 ≤0.33, 0.20≤F 3 ≤0.41, and 0.45≤F 1 +F 2 +F 3 ≤1.0, P represents the first correction constant;

[0067] The vectorization module is used to convert the captured geographic image information into vector data and generate a vector layer to represent the geometric shapes and spatial relationships of different objects;

[0068] The deviation comparison module is used to obtain a preset visibility threshold Q based on the determined mountainous geographical area that needs to be captured, and compare and analyze the preset visibility threshold Q with the visibility coefficient Njdx to obtain the analysis result of the vector layer, and make corresponding adjustment strategies based on the analysis result.

[0069] During the operation of this system, through the route planning module, the system can use UAV remote sensing technology to continuously capture geographic image information of high mountains; the real-time control mechanism in the route planning module dynamically adjusts the height Gdz and inclination Qxd of the UAV according to the slope trend of the mountain, ensuring that accurate geographic image information is obtained under different terrain conditions; the data acquisition module can collect relevant environmental data and atmospheric situation data around the UAV, providing multi-faceted background information for subsequent processing, taking into account various environmental factors in the process of geographic image acquisition; by calculating the visibility coefficient Njdx, it helps to further accurately evaluate the feasibility and availability of geographic image information acquisition; and by comparing the preset visibility threshold Q and the visibility coefficient Njdx, it automatically makes corresponding adjustment strategies to ensure data accuracy and stability during the geographic image acquisition process.

[0070] Example 2

[0071] Please refer to Figure 1 ,Specifically: the route planning module includes a predetermined route unit and a real-time positioning unit;

[0072] The predetermined route unit is used to obtain and plan the route of the UAV remote sensing according to the geographical image information of the high mountain section to be obtained and the geographical location in the map;

[0073] The real-time positioning unit is used to continuously capture geographic image information of the side of the mountain according to the planned UAV flight route and the slope trend of the mountain, and to locate the position of the UAV on the mountain in real time, so as to obtain relevant environmental data information and relevant atmospheric situation data information around the UAV at different heights Gdz and inclinations Qxd.

[0074] The data acquisition module includes a first data acquisition unit, a second data acquisition unit and a geographic image acquisition unit;

[0075] The first data acquisition unit is used to collect relevant atmospheric situation data information around the drone in real time according to the drone at different heights Gdz and inclinations Qxd, wherein the relevant atmospheric situation data information includes the pressure state in the atmosphere, the atmospheric transparency Tmdz, the water vapor concentration Szqn, the atmospheric turbulence state, the aerosol concentration, and the temperature difference Wdc and humidity difference generated by the drone at different heights Gdz;

[0076] The second data acquisition unit is used to collect relevant environmental data information around the drone in real time when the drone is at different heights Gdz and inclinations Qxd, wherein the relevant environmental data information includes wind speed Fsz, wind direction, particle volume Klwt, light intensity Gxqd and meteorological weather conditions;

[0077] The geographic image acquisition unit is used to use drone remote sensing to obtain continuous image frames of the side of the mountain to generate geographic image information, wherein the geographic image information includes the slope, slope direction, soil condition, geological structure, human activity area, water body distribution, and vegetation type and distribution data information of the mountain section to be acquired.

[0078] In this embodiment, the real-time positioning unit continuously captures geographic image information of the side of the mountain according to the planned route and the slope trend of the mountain, and simultaneously locates the position of the UAV on the mountain in real time, providing accurate position information for subsequent data collection, and acquiring corresponding relevant environmental data information and relevant atmospheric situation data information according to different position information; and according to the first data collection unit, the second data collection unit and the geographic image collection unit, the relevant atmospheric situation data, environmental data and geographic image information around the UAV are respectively collected in real time, providing multi-dimensional and high-quality geographic information for subsequent processing, so as to facilitate subsequent judgment on whether the mountain geographical area captured by UAV remote sensing deviates from the mountain body to be acquired.

[0079] Example 3

[0080] Please refer to Figure 1 ,Specifically: the processing module includes a data preprocessing unit and an image enhancement unit;

[0081] The data preprocessing unit is used to detect and delete the repeatedly collected relevant environmental data information and relevant atmospheric situation data information to avoid the deviation of the analysis caused by the data duplication, and normalize the units by using the dimensionless processing technology;

[0082] The image enhancement unit is used to extract key feature information in continuous image frames through image enhancement technology, identify and analyze defective parts in the image, and select and adjust the degree of difference between different areas in the image frame according to their characteristics, which helps to eliminate noise in the image, improve the clarity and contrast of the image, make the geographic image data clearer and easier to analyze, thereby improving the accuracy of extracting geographic information.

[0083] In this embodiment, the data preprocessing unit further reduces the potential deviation caused by data duplication to the analysis by detecting and deleting repeatedly collected relevant environmental data and atmospheric situation data, thereby further improving the accuracy and consistency of the data; at the same time, the unit normalization using dimensionless processing technology helps to eliminate the interference caused by different dimensions and improves the comparability and consistency of the data; after data preprocessing and image enhancement, the data is more analyzable and interpretable, which helps the subsequent condition analysis module to more accurately obtain the atmospheric condition factor Dqyz and the environmental condition factor Hjyz, thereby improving the accurate calculation of the visibility coefficient Njdx and providing a more reliable data foundation for geographic information collection.

[0084] Example 4

[0085] Please refer to Figure 1 Specifically: Based on the UAV remote sensing technology, the high mountain sections to be acquired are imaged and a three-dimensional regional model is constructed. Spatial analysis technology is used in the three-dimensional regional model to distinguish the relevant environmental data information and relevant atmospheric situation data information obtained according to the different Gdz states of the UAV at different altitudes.

[0086] Among them, spatial analysis technology is used to process relevant environmental data information and relevant atmospheric situation data information obtained by UAVs at different altitudes and Gdz states to distinguish and establish three-dimensional regional models, and includes geographic information systems to process geographic data, identify land object types, and analyze terrain, etc., so as to more comprehensively utilize and understand the collected geographic image information.

[0087] The atmospheric transparency Tmdz and the water vapor concentration Szqn are correlated and dimensionlessly processed to obtain the atmospheric condition factor Dqyz, which is obtained by the following formula:

[0088]

[0089] In the formula, α and β are both proportional coefficients, Wdc is the temperature difference generated by the drone at different altitudes Gdz, Yqz is the pressure coefficient, and C is the second correction constant;

[0090] The above-mentioned atmospheric transparency Tmdz is measured by using a transmissometer or an optical conductivity meter. The transmissometer can measure the attenuation of light when passing through the atmosphere, thereby indirectly reflecting the transparency. The reduction in transparency may cause the signal strength received by the UAV remote sensing to decrease, thereby affecting the quality of the image.

[0091] The water vapor concentration Szqn is measured by a water vapor detector or a water vapor measuring instrument;

[0092] The temperature difference Wdc generated by the drone at different altitudes Gdz is collected and obtained through the temperature sensor;

[0093] The pressure coefficient Yqz is collected and obtained through the pressure sensor;

[0094] The condition threshold Z is set in advance, and the condition threshold Z is compared and analyzed with the atmospheric condition factor Dqyz to determine whether the drone needs to use multiple time series to capture the geographical image information of the mountain figure for multiple times. The analysis results are as follows:

[0095] If the atmospheric condition factor Dqyz is greater than or equal to the condition threshold Z, that is, Dqyz ≥ Z, it indicates that the current external environment may affect the captured geographic image phenomenon. At this time, it will be determined that the drone needs to use multiple time series to capture the geographic image information of the mountain figure for multiple times;

[0096] If the atmospheric condition factor Dqyz is less than the condition threshold Z, that is, Dqyz<Z, it will be determined that there is no need to use multiple time series for the UAV.

[0097] In this embodiment, by pre-setting the condition threshold Z and comparing it with the atmospheric condition factor Dqyz, according to the analysis results, the system can determine whether it is necessary to adopt multiple time series, that is, whether the drone is required to capture multiple images of the high mountain figure to be acquired, so that it can respond to different environmental conditions more flexibly; by determining whether the atmospheric condition factor Dqyz reaches the set condition threshold Z, the system can decide whether to adopt multiple time series.

[0098] Example 5

[0099] Please refer to Figure 1 Specifically, the wind speed Fsz is associated with the light intensity Gxqd, and after dimensionless processing, the environmental condition factor Hjyz is obtained. The environmental condition factor Hjyz is obtained by the following formula:

[0100]

[0101] Where Klwt represents the volume of particles, b 1 and b 2 Both are expressed as proportional coefficients, and g is expressed as the third correction constant.

[0102] The wind speed Fsz is collected and acquired by a wind speed sensor, a hot wire wind speed sensor or an ultrasonic wind speed sensor, and provides information about the direction and intensity of the wind;

[0103] The light intensity Gxqd is collected and obtained through a light intensity sensor.

[0104] The particle volume Klwt is measured by lidar or laser scattering instrument, which uses a laser beam to emit into the atmosphere and measures the scattered light to estimate the concentration and volume of the particles.

[0105] The vectorization module includes a target recognition unit and a vectorization processing unit;

[0106] The target recognition unit is used to recognize the types of different objects in the captured geographic image information, wherein the types of objects include buildings, roads, vegetation and pedestrian roads;

[0107] The vector processing unit is used to convert the geographic image information in the target recognition unit into vector data, generate high mountain vector geometry to represent the shape and position of the high mountain surface, and provide high-precision spatial data for geographic information.

[0108] Compare and analyze the preset visibility threshold Q with the visibility coefficient Njdx to obtain the analysis result of the vector layer:

[0109] If the visibility coefficient Njdx is greater than the preset visibility threshold Q, it means that the high mountain geographical area currently captured by the drone remote sensing has deviated from the high mountain figure to be acquired, and the captured geographical image information has the phenomenon of mis-shooting. At this time, a red warning notification will be triggered in time, indicating that the currently captured geographical image information may have the phenomenon of deviation and mis-shooting. Adjust the height Gdz and inclination Qxd of the drone, and perform continuous image capture at multiple time points to obtain more comprehensive and clear data;

[0110] If the visibility coefficient Njdx is equal to the preset visibility threshold Q, it means that the alpine geographical area currently captured by the UAV remote sensing is at the position of the alpine segment to be acquired, and no deviation occurs, and the capture operation continues at this time;

[0111] If the visibility coefficient Njdx is less than the preset visibility threshold Q, it means that the alpine geographical area currently captured by UAV remote sensing is in the position of the alpine part to be acquired, but there is repeated image information in the continuously captured geographic image information. At this time, the processing module will be used to deduplicate the repeated image information, which will help optimize the geographic image information, reduce the interference of repeated information on subsequent analysis, and improve data utilization efficiency.

[0112] In this embodiment, the target recognition unit further realizes the intelligent classification of the features by identifying the types of different features in the captured geographic image, such as buildings, roads and vegetation; the vectorization processing unit converts the information of these features into vector data, generates mountain vector geometry, and thus better represents the shape and position of the mountain surface; by comparing and analyzing the preset visibility threshold Q with the visibility coefficient Njdx, the system can determine whether the currently captured mountain geographical area deviates from the mountain segment position to be acquired, and obtain the analysis results. In different situations, the system adopts different strategies, such as red warning notification, continuous image capture and deduplication operations, to further ensure the accuracy and completeness of the geographic image.

[0113] Example 6

[0114] Please refer to Figure 1 and Figure 2 ,Specifically: A vector geographic information acquisition method based on remote sensing images, comprising the following steps,

[0115] Step 1: Use the UAV remote sensing technology to capture the image of the mountain to be acquired through the route planning module to obtain geographic image information, and when capturing the geographic image information, adjust the height Gdz and inclination Qxd of the UAV in real time according to the slope trend of the mountain;

[0116] Step 2: The data acquisition module collects relevant environmental data information around the drone and relevant atmospheric situation data information in the atmosphere according to the altitude Gdz of the drone, and generates a capture status data set;

[0117] Step 3: Preprocess the relevant data information in the capture state data set and extract features through the processing module, preprocess the continuous image frames in the geographic image information, identify and extract effective features in the continuous image frames, and improve the image quality based on image enhancement technology to generate a geographic image data set;

[0118] Step 4: Perform machine analysis on the relevant data information in the captured state data set after feature extraction through the condition analysis module to obtain the atmospheric condition factor Dqyz and the environmental condition factor Hjyz, and associate the atmospheric condition factor Dqyz with the environmental condition factor Hjyz, and obtain the visibility coefficient Njdx after dimensionless processing;

[0119] Step 5: Convert the captured geographic image information into vector data through a vectorization module and identify the types of different land features;

[0120] Step 6: Compare and analyze the preset visibility threshold Q with the visibility coefficient Njdx through the deviation comparison module, obtain the analysis result of the vector layer, and make corresponding adjustment strategies according to the analysis result.

[0121] In this embodiment, combined with the contents of steps one to six, the route of the UAV is first planned to determine the position of the high mountain segment to be acquired, and then, according to the image capture process of the UAV, relevant environmental data information and relevant atmospheric situation data information are collected, and the visibility coefficient Njdx is obtained through the condition analysis module. Finally, through comparative analysis, it is determined whether the strategy needs to be adjusted.

[0122] Example:

[0123] Data collection: atmospheric transparency Tmdz is 95%; water vapor concentration Szqn is 68%; the temperature difference Wdc generated by the drone at different altitudes Gdz is 12; the pressure coefficient Yqz is 6.2; α is 0.25; β is 0.37; C is 0.5; wind speed Fsz is 16; light intensity Gxqd is 26; particle volume Klwt is 2.3; b 1 is 0.15; b 2 is 0.49; g is 0.35; the inclination Qxd is 64%; F 1 0.20; F 2 0.30; F 3 =0.21; P =0.89;

[0124] With the above data, the following calculations can be performed:

[0125] Atmospheric Condition Factor

[0126] Environmental Condition Factors

[0127] Visibility coefficient

[0128] If the preset visibility threshold Q is 10, the visibility coefficient Njdx is greater than the preset visibility threshold Q, indicating that the high mountain geographical area currently captured by UAV remote sensing deviates from the high mountain figure to be acquired, and the captured geographical image information has the phenomenon of mis-shooting. At this time, a red warning notification will be triggered in time, the height Gdz and inclination Qxd of the UAV will be adjusted, and continuous image capture will be performed at multiple time points.

[0129] Although 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 the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A vector geographic information acquisition system based on remote sensing images, characterized in that: It includes route planning module, data acquisition module, processing module, condition analysis module, vectorization module and deviation comparison module; The route planning module is used to continuously capture geographic image information of the mountains using UAV remote sensing technology, predetermine the route of the UAV to determine the geographical area of ​​the mountains that need to be captured, and when capturing geographic image information, adjust the height Gdz and inclination Qxd of the UAV in real time according to the slope trend of the mountains; The data acquisition module is used to collect and record relevant environmental data information around the drone and relevant atmospheric situation data information in the atmosphere when the drone captures geographic image information, and generate a capture status data set; The processing module is used to upload relevant environmental data information and relevant atmospheric situation data information to the capture state data set, and perform data preprocessing and feature extraction on them; And pre-process the continuous image frames in the geographic image information, remove noise, smooth the image, and perform geometric correction, and identify and extract effective features in the continuous image frames, and improve the image quality based on image enhancement technology to generate a geographic image data set; The condition analysis module is used to perform machine analysis on the relevant data information in the capture state data set after feature extraction, obtain the atmospheric condition factor Dqyz and the environmental condition factor Hjyz, and associate the atmospheric condition factor Dqyz with the environmental condition factor Hjyz, and obtain the visibility coefficient Njdx after dimensionless processing. The visibility coefficient Njdx is obtained by the following formula: Wherein, F1 represents the proportional coefficient of the atmospheric condition factor Dqyz, F2 represents the proportional coefficient of the environmental condition factor Hjyz, F3 represents the proportional coefficient of the inclination Qxd, 0.06≤F1≤0.26, 0.10≤F2≤0.33, 0.20≤F3≤0.41, and 0.45≤F1+F2+F3≤1.0, and P represents the first correction constant; The vectorization module is used to convert the captured geographic image information into vector data and generate a vector layer to represent the geometric shapes and spatial relationships of different objects; The deviation comparison module is used to obtain a preset visibility threshold Q based on the determined mountainous geographical area that needs to be captured, and compare and analyze the preset visibility threshold Q with the visibility coefficient Njdx to obtain the analysis result of the vector layer, and make corresponding adjustment strategies based on the analysis result.

2. The vector geographic information acquisition system based on remote sensing images according to claim 1 is characterized by: The route planning module includes a predetermined route unit and a real-time positioning unit; The predetermined route unit is used to obtain and plan the route of the UAV remote sensing according to the geographical image information of the high mountain section to be obtained and the geographical location in the map; The real-time positioning unit is used to continuously capture geographic image information of the side of the mountain according to the planned UAV flight route and the slope trend of the mountain, and to locate the position of the UAV on the mountain in real time, so as to obtain relevant environmental data information and relevant atmospheric situation data information around the UAV at different heights Gdz and inclinations Qxd.

3. The vector geographic information acquisition system based on remote sensing images according to claim 2 is characterized in that: The data acquisition module includes a first data acquisition unit, a second data acquisition unit and a geographic image acquisition unit; The first data acquisition unit is used to collect relevant atmospheric situation data information around the drone in real time according to the drone at different heights Gdz and inclinations Qxd, wherein the relevant atmospheric situation data information includes the pressure state in the atmosphere, the atmospheric transparency Tmdz, the water vapor concentration Szqn, the atmospheric turbulence state, the aerosol concentration, and the temperature difference Wdc and humidity difference generated by the drone at different heights Gdz; The second data acquisition unit is used to collect relevant environmental data information around the drone in real time when the drone is at different heights Gdz and inclinations Qxd, wherein the relevant environmental data information includes wind speed Fsz, wind direction, particle volume Klwt, light intensity Gxqd and meteorological weather conditions; The geographic image acquisition unit is used to use drone remote sensing to obtain continuous image frames of the side of the mountain to generate geographic image information, wherein the geographic image information includes the slope, slope direction, soil condition, geological structure, human activity area, water body distribution, and vegetation type and distribution data information of the mountain section to be acquired.

4. The vector geographic information acquisition system based on remote sensing images according to claim 3 is characterized by: The processing module includes a data preprocessing unit and an image enhancement unit; The data preprocessing unit is used to detect and delete the repeatedly collected relevant environmental data information and relevant atmospheric situation data information to avoid the deviation of the analysis caused by the data duplication, and normalize the units by using the dimensionless processing technology; The image enhancement unit is used to extract key feature information in continuous image frames through image enhancement technology, identify and analyze defective parts in the image, and select and adjust the difference between different areas in the image frame according to their characteristics.

5. The vector geographic information acquisition system based on remote sensing images according to claim 4 is characterized in that: Based on the UAV remote sensing technology, the high mountain sections to be acquired are imaged and a three-dimensional regional model is constructed. Spatial analysis technology is used in the three-dimensional regional model to distinguish the relevant environmental data information and relevant atmospheric situation data information obtained according to the different Gdz states of the UAV at different altitudes.

6. The vector geographic information acquisition system based on remote sensing images according to claim 5 is characterized by: The atmospheric transparency Tmdz and the water vapor concentration Szqn are correlated and dimensionlessly processed to obtain the atmospheric condition factor Dqyz, which is obtained by the following formula: In the formula, α and β are both proportional coefficients, Wdc is the temperature difference generated by the drone at different altitudes Gdz, Yqz is the pressure coefficient, and C is the second correction constant; The condition threshold Z is preset, and the condition threshold Z is compared and analyzed with the atmospheric condition factor Dqyz to determine whether the drone needs to use multiple time series to capture the geographical image information of the mountain figure for multiple times. The analysis results are as follows: If the atmospheric condition factor Dqyz is greater than or equal to the condition threshold Z, that is, Dqyz ≥ Z, it will be determined that the drone needs to use multiple time series to capture the geographical image information of the mountain to be acquired multiple times; If the atmospheric condition factor Dqyz is less than the condition threshold Z, that is, Dqyz<Z, it will be determined that there is no need to use multiple time series for the UAV.

7. The vector geographic information acquisition system based on remote sensing images according to claim 6 is characterized by: The wind speed Fsz is associated with the light intensity Gxqd, and after dimensionless processing, the environmental condition factor Hjyz is obtained. The environmental condition factor Hjyz is obtained by the following formula: Wherein, Klwt represents the volume of the particle, b1 and b2 represent proportional coefficients, and g represents the third correction constant.

8. The vector geographic information acquisition system based on remote sensing images according to claim 7 is characterized in that: The vectorization module includes a target recognition unit and a vectorization processing unit; The target recognition unit is used to recognize the types of different objects in the captured geographic image information, wherein the types of objects include buildings, roads, vegetation and pedestrian roads; The vector processing unit is used to convert the geographic image information in the target recognition unit into vector data, generate high mountain vector geometry, so as to represent the shape and position of the high mountain surface.

9. The vector geographic information acquisition system based on remote sensing images according to claim 8 is characterized in that: Compare and analyze the preset visibility threshold Q with the visibility coefficient Njdx to obtain the analysis result of the vector layer: If the visibility coefficient Njdx is greater than the preset visibility threshold Q, it means that the high mountain geographical area currently captured by the drone remote sensing deviates from the high mountain figure to be acquired, and the captured geographical image information has a phenomenon of mis-shooting. At this time, a red warning notification will be triggered in time, the altitude Gdz and inclination Qxd of the drone will be adjusted, and continuous image capture will be performed at multiple time points; If the visibility coefficient Njdx is equal to the preset visibility threshold Q, it means that the alpine geographical area currently captured by the UAV remote sensing is at the position of the alpine segment to be acquired, and no deviation occurs, and the capture operation continues at this time; If the visibility coefficient Njdx is less than the preset visibility threshold Q, it means that the mountain geographical area currently captured by UAV remote sensing is in the position of the mountain segment to be acquired, but there is repeated image information in the continuously captured geographical image information. At this time, the processing module will be used to deduplicate the repeated image information.

10. A method for collecting vector geographic information based on remote sensing images, comprising a system for collecting vector geographic information based on remote sensing images as claimed in any one of claims 1 to 9, characterized in that: The following steps are included: Step 1: Use the UAV remote sensing technology to capture the image of the mountain to be acquired through the route planning module to obtain geographic image information, and when capturing the geographic image information, adjust the height Gdz and inclination Qxd of the UAV in real time according to the slope trend of the mountain; Step 2: The data acquisition module collects relevant environmental data information around the drone and relevant atmospheric situation data information in the atmosphere according to the altitude Gdz of the drone, and generates a capture status data set; Step 3: Preprocess the relevant data information in the capture state data set and extract features through the processing module, preprocess the continuous image frames in the geographic image information, identify and extract effective features in the continuous image frames, and improve the image quality based on image enhancement technology to generate a geographic image data set; Step 4: Perform machine analysis on the relevant data information in the captured state data set after feature extraction through the condition analysis module to obtain the atmospheric condition factor Dqyz and the environmental condition factor Hjyz, and associate the atmospheric condition factor Dqyz with the environmental condition factor Hjyz, and obtain the visibility coefficient Njdx after dimensionless processing; Step 5: Convert the captured geographic image information into vector data through a vectorization module and identify the types of different land features; Step 6: Compare and analyze the preset visibility threshold Q with the visibility coefficient Njdx through the deviation comparison module, obtain the analysis result of the vector layer, and make corresponding adjustment strategies according to the analysis result.

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