Fixed point method for land management measurement

Abstract

The invention relates to the technical field of land management measurement, in particular to a point fixing method for land management measurement. A fixed point method for land management measurement comprises the following steps: SS01, arranging piles disorderly, ramming points of a plurality of initial piles on a to-be-measured land by adopting ramming equipment, arranging the points of the plurality of initial piles in a set state, and arranging a total station at an approximate central position of a to-be-managed land measurement area; performing primary parameter measurement on the initial pile by using a total station in a set measurement mode to obtain a primary calibration parameter set; the land management measurement fixed point method has the beneficial effects that the fixed point identification and accurate point deviation caused by weather, luminosity and color deviation in the flight process can be overcome during measurement, so that the land fixed point precision is improved in an auxiliary manner; moreover, the method can achieve the batch recognition of the feature points of the land, and achieves the multi-parameter comparison type auxiliary point determination.

Description

Technical Field

[0001] The invention relates to the technical field of land management measurement, in particular to a fixed-point method for land management measurement. Background Art

[0002] In the process of measuring the land, it is necessary to mark and fix points on the land. In the prior art, a patent document with publication number CN117647234B discloses a land management measurement point fixer, including a shell, the bottom of the shell is symmetrically fixedly connected with two base plates, the surfaces of the two base plates are fixedly connected with brackets, the end surfaces of the two brackets are respectively fixedly installed with a first conveying chain and a second conveying chain, and the first conveying chain and the second conveying chain match, and the interior of the shell is fixedly connected with a support plate.

[0003] In the above-mentioned device, the pressure block inserts the benchmark into the soil at the fixed point mark to achieve land management positioning, but the above-mentioned positioning method adopts walking positioning, which leads to low positioning efficiency, and the above-mentioned positioning method is not suitable for large-scale land measurement. Although some methods that use aerial means to achieve land management have appeared in the prior art, the existing aerial measurement method is not convenient for reducing the fixed point recognition and confirmation deviation caused by weather, light intensity, and color deviation during the aerial image acquisition process during land measurement, and is not convenient for improving the land's fixed point and confirmation accuracy. In addition, the existing fixed point method is not convenient for realizing the subsequent prediction of land deformation after land measurement and the deviation management and predictive correction of offset after the initial fixed point of the land.

[0004] Based on this, the present invention provides a fixed-point method for land management measurement to solve the problems raised in the above-mentioned background technology. Summary of the invention

[0005] The present invention aims at the technical problems existing in the prior art and provides a fixed-point method for land management surveying to solve the problems that the existing aerial surveying methods are not convenient for reducing the fixed-point identification and confirmation deviations caused by weather, luminosity and color deviations in the process of aerial image acquisition during land surveying, and are subsequently not convenient for improving the land fixed-point and confirmation accuracy. In addition, the existing fixed-point methods are not convenient for realizing the subsequent prediction of land deformation after land surveying and the deviation management and predictive correction of offset after the initial land fixed-pointing.

[0006] The technical solution of the present invention to solve the above technical problems is as follows: A fixed-point method for land management measurement comprises the following steps: SS01, random pile arrangement, using pile tamping equipment to tamp multiple initial pile points on the land to be measured, multiple initial pile points are arranged in a set state, and a total station is installed at the approximate center of the land measurement area to be managed; SS02, primary calibration parameter acquisition, using the total station to set the measurement mode to measure the initial pile parameters to obtain a calibration parameter set; SS03, image acquisition, preset drone, install data acquisition equipment on the drone, and the drone acquires multiple image sets with set aerial photography parameters; SS04, correction modeling, superimpose multiple image sets obtained in step SS03 and import them into Smart3D Capture software, and perform atmospheric correction, data degradation correction, dark area correction and replacement, and pixel-by-pixel RGB value correction and replacement in sequence, and finally generate a 3D real scene model with no dark area, no atmospheric distortion and no color difference after multiple corrections; SS05, measurement coordinate system establishment, establish a spatial coordinate system in the corrected three-dimensional real scene model, when establishing the spatial coordinate system, take the center point of the total station in step SS01 as the origin, the origin has the GPS position information corresponding to the origin, and calibrate and establish the coordinate value based on the primary data set of the total station during a measurement. After the spatial coordinate system is assigned, each coordinate value corresponds to a GPS value; SS06. Acquisition of the basic value of the management model: N hours after the first calibration parameter acquisition, the second calibration parameter acquisition is performed according to the measurement mode of the total station during the first calibration parameter acquisition. After the second calibration parameter acquisition, the displacement of the positioning pile during the first calibration parameter acquisition relative to the second calibration parameter acquisition is recorded, and then the average offset of the reference pile caused by weather, time and land settlement is measured. After the average offset of the reference pile is calculated, the average offset of the initial pile per hour is calculated. After the average offset of the initial pile per hour is obtained, the basic establishment value of the positioning pile position prediction management model is obtained; SS07, the establishment of fixed-point positioning piles, using the spatial coordinate system established in step SS05 as a reference for land measurement, through land measurement, obtain the characteristic points of the land to be managed, the GPS location information of the characteristic points, and the distance difference, height difference and angle value of each characteristic point relative to each initial pile. After the above parameter values ​​are obtained, calculate the time difference when the positioning pile is established relative to the reference pile and the total amount of offset caused by the time difference. After the total amount of offset and parameter values ​​are obtained, the subsequent multiple positioning piles can be accurately established in combination with the positions of multiple initial piles; SS08, establishment of a prediction model for the correction of the management of positioning piles. After step SS07, a prediction management model for the positioning pile positions is established based on the average hourly displacement of the initial piles obtained in step SS06. After the prediction management model for the positioning pile positions is established, the total displacement of the specified positioning piles at each real-time time is obtained at that time and the real-time correction of the positioning pile displacement parameters is realized.

[0007] The beneficial effects of the present invention are: This fixed-point method can utilize the drone aerial measurement mode to realize batch rapid and precise positioning and subsequent batch establishment of fixed-point stakes in the process of land management. Through the realization of the above-mentioned batch positioning and precise stake positioning, the positioning efficiency and positioning accuracy of this land fixed-point method can be effectively improved. At the same time, this land management measurement fixed-point method can overcome the fixed-point identification and confirmation deviations caused by weather, luminosity, and color deviations during the flight process during measurement, and then assist in improving the land fixed-point accuracy. This land fixed-point method can also realize batch identification of land feature points and multi-parameter comparison-assisted confirmation. At the same time, this positioning method can also realize subsequent batch management of land fixed points and correct the offset differences of land fixed points caused by land subsidence, geological factors and weather factors in real time.

[0008] Based on the above technical solution, the present invention can also be improved as follows.

[0009] Furthermore, in the SS01 step, a unique digital code is provided on the top of each of the initial piles, the three-dimensional specifications of each of the initial piles are different, an RFID chip is pre-embedded in each of the initial piles, and each of the RFID chips stores unique coding information corresponding to the initial pile. The RFID chip can read information through an external reader, and after the external reader reads the coding information of the RFID chip, it can automatically obtain the three-dimensional specification parameters, coding identification, full-color image under standard light intensity of the initial pile, and GPS assignment calibration information of the initial pile by the land data management platform.

[0010] Furthermore, when the initial piles are arranged, the distances between the initial piles are different, the distances between the initial piles are ≥8m, and the specification parameters of the initial piles and the positioning piles are the same.

[0011] Furthermore, in the SS02 step, when the total station is used for measurement, a land data management platform is pre-established. The land data management platform is linked to the data acquisition equipment in real time through wireless data transmission. The following measurement parameters are used when the total station is used for measurement. When measuring, the total station is used to collect three-dimensional specification parameters of M initial piles, where M≥3. The three-dimensional specification parameters include the height, width and length of the initial piles. When collecting, the distance values ​​and mutual angles between the two initial piles among the M initial piles are recorded. The above data collected by the total station are packaged into a calibration parameter set, which is transmitted to the land data management platform in real time.

[0012] Furthermore, in the SS03 step, the data acquisition equipment includes a GPS locator, a three-dimensional laser scanner and a spectrometer. Before the aerial photography parameters are executed, the scope of the land to be measured is obtained in advance. After the scope of the land to be measured is obtained, the aerial photography trajectory of the drone is formulated. After the aerial photography trajectory is formulated, the automatic time interval during shooting is set. A mixed direct and side shooting method is adopted during aerial photography. When shooting directly, the angle between the acquisition angle of the data acquisition equipment and the fuselage is 90°, and when shooting sideways, the angle between the acquisition angle of the data acquisition equipment and the fuselage is 45°. When shooting aerial photography, a multi-time series acquisition plan is formulated, and each time series corresponds to a collection time period. The collection time period of each time series is different, and a unified aerial photography parameter is used in each time series. Finally, the data acquisition equipment obtains image sets in multiple different time series.

[0013] Furthermore, in the SS03 step, after each aerial image is acquired, each image file in the image set corresponds to the GPS location information, time information, spectral parameter information and aerial angle information bound when the image is acquired.

[0014] Furthermore, in the SS04 step, during atmospheric correction, a histogram adjustment method and a dark target method are used to eliminate image distortion caused by atmospheric influence in the image set. In the SS04 step, during data degradation correction, a linear discriminant analysis method is used to reduce the spectral wavenumber and data volume of the hyperspectral image. After the image sets obtained under multiple time series are superimposed and imported into the Smart3DCapture software, the brightness correction module obtains the luminance of the image set under each time series and the spectral parameters corresponding to each image. After the luminance of the image set under each time series and the spectral parameters corresponding to each image are obtained, the dark area correction replacement module identifies the dark area in each image set and the image pixel points below the set brightness value. After the dark area in each image set and the image pixel points below the set brightness value are identified, the dark area correction replacement module selects the corresponding image pixel points in other image sets that meet the luminance value to perform equipotential replacement on the selected dark area pixel points, so that the three-dimensional model generated by Smart3DCapture has no dark area when viewed at any angle and can observe all land features of the three-dimensional model without blind spots and intuitively.

[0015] Further, in the SS04 step, the RGB value of each pixel in the full-color image of the positioning pile under the standard light intensity of the positioning pile is identified by image recognition software and an image recognition algorithm, and multiple pixels are classified for the same color according to the color type classification method. After the classification is completed, the RGB value corresponding to each color is recorded, and the RGB value in the full-color image of the positioning pile under the standard light intensity is used as the calibration value. After the calibration value is obtained, the positioning pile acquisition image in each image set is identified by image recognition software and an image recognition algorithm. After the positioning pile acquisition image is recognized, the RGB value of each pixel in the positioning pile acquisition image is obtained. After the RGB value of each pixel is obtained, the multiple pixels are classified for the same color according to the color type classification method. After the classification is completed, the RGB value corresponding to each color is recorded, and the calibrated RGB value is used to replace the RGB value of each corresponding color in the positioning pile acquisition image. After the RGB value of each pixel is corrected, a three-dimensional model with real color saturation and high simulation is finally obtained.

[0016] Furthermore, in the step SS07, the acquired land feature points include four corner points of the land, multiple land edge points, land geomorphic feature points, land identification reference points and land center points, and in the step SS06, N≥5.

[0017] Furthermore, in the SS08 step, after the real-time offset and offset parameters of the positioning pile are corrected, the land data management platform synchronizes the corrected parameters, and after the reader reads the RFID chip code of the positioning pile, it quickly obtains the land feature point type of the positioning pile, the GPS historical position table calibrated with time value, and the GPS position prediction table calibrated with time value. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] Figure 1 A schematic diagram of the flow structure of a fixed-point method for land management measurement according to the present invention; Figure 2 A schematic diagram of the steps of the fixed-point method for land management measurement of the present invention; Figure 3 It is a schematic diagram of the process structure of step SS04 of the present invention. DETAILED DESCRIPTION

[0019] The principles and features of the present invention are described below in conjunction with the accompanying drawings. The examples given are only used to explain the present invention and are not used to limit the scope of the present invention.

[0020] The present invention provides the following preferred embodiments like Figure 1-Figure 3 As shown, a fixed-point method for land management measurement includes the following steps: SS01, random pile arrangement, using pile tamping equipment to tamp multiple initial pile points on the land to be measured, multiple initial pile points are arranged in a set state, and a total station is installed at the approximate center of the land measurement area to be managed; In step SS01, each initial pile is provided with a unique digital code at the top; When the initial piles are laid out, the distance between the two initial piles is different, and the distance between the two initial piles is ≥8m. The specification parameters of the initial piles and the positioning piles are the same; Uniquely numbered to facilitate visual identification of each initial pile; The three-dimensional specifications of each initial pile are different. An RFID chip is pre-embedded in each initial pile. Each RFID chip stores the unique coding information corresponding to the initial pile. The RFID chip can read information through an external reader. After the external reader reads the coding information of the RFID chip, it can automatically obtain the three-dimensional specification parameters, coding identification, full-color image under standard light intensity of the initial pile and the GPS assignment calibration information of the land data management platform for the initial pile.

[0021] SS02, primary calibration parameter acquisition, using the total station to set the measurement mode to measure the initial pile parameters to obtain a calibration parameter set; In step SS02, when the total station is used for measurement, a land data management platform is pre-established, and the land data management platform is linked to the data acquisition equipment in real time through wireless data transmission. The following measurement parameters are used when the total station is used for measurement. When measuring, the total station is used to collect the three-dimensional specification parameters of M initial piles, M≥3; The three-dimensional specification parameters include the height, width and length of the initial piles. When collecting, the distance and angle between the two initial piles among the M initial piles are recorded; The above data collected by the total station are packaged into a calibration parameter set, and the calibration parameter set is transmitted to the land data management platform in real time; SS03, image acquisition, preset drone, install data acquisition equipment on the drone, and the drone acquires multiple image sets with set aerial photography parameters; In step SS03, the data acquisition equipment includes a GPS locator, a three-dimensional laser scanner and a spectrometer. Before the aerial photography parameters are executed, the scope of the land to be measured is obtained in advance. After the scope of the land to be measured is obtained, the aerial photography trajectory of the drone is formulated. After the aerial photography trajectory is formulated, the automatic time interval during shooting is set; Aerial photography uses a mixed shooting method of direct shooting and side shooting. When shooting directly, the angle between the data acquisition device and the fuselage is 90°, and when shooting sideways, the angle between the data acquisition device and the fuselage is 45°. When taking aerial photos, a multi-time series acquisition plan is formulated. Each time series corresponds to a collection time period, and the collection time period of each time series is different. The same aerial photography parameters are used in each time sequence, and finally the data acquisition device obtains multiple sets of images in different time sequences; In step SS03, after each aerial image is acquired, each image file in the image set corresponds to the GPS location information, time information, spectral parameter information and aerial angle information bound when the image is acquired; SS04, correction modeling, superimpose multiple image sets obtained in step SS03 and import them into Smart3DCapture software, and perform atmospheric correction, data degradation correction, dark area correction and replacement, and pixel-by-pixel RGB value correction and replacement in sequence, and finally generate a 3D real scene model with no dark area, no atmospheric distortion and no color difference after multiple corrections; Through the brightness correction, spectrum correction and color correction in the SS04 step, the deviation of fixed point identification and confirmation caused by weather, light intensity and color deviation during the flight process can be overcome, thereby assisting in improving the accuracy of land fixed point; In step SS04, after the image sets obtained in multiple time sequences are superimposed and imported into the Smart3DCapture software, the brightness correction module obtains the luminance of the image set in each time sequence and the spectral parameters corresponding to each image. After the luminance of the image set in each time sequence and the spectral parameters corresponding to each image are obtained, the dark area correction and replacement module identifies the dark areas in each image set and the image pixels below the set brightness value. After the dark areas in each image set and the image pixels below the set brightness value are identified, the dark area correction and replacement module selects the corresponding image pixels in other image sets that meet the luminance values ​​to perform equipotential replacement on the selected dark area pixels. Finally, the three-dimensional model generated by Smart3DCapture has no dark areas when viewed at any angle, and all land features of the three-dimensional model can be observed without blind spots and intuitively.

[0022] In step SS04, the RGB value of each pixel in the full-color image of the positioning pile under the standard light intensity of the positioning pile is identified by image recognition software and image recognition algorithm, and multiple pixels are classified for the same color according to the color type classification method. After the classification is completed, the RGB value corresponding to each color is recorded, and the RGB value in the full-color image of the positioning pile under the standard light intensity is used as the calibration value. After the calibration value is obtained, the positioning pile acquisition image in each image set is identified by image recognition software and image recognition algorithm. After the positioning pile acquisition image is recognized, the RGB value of each pixel in the positioning pile acquisition image is obtained. After the RGB value of each pixel is obtained, the multiple pixels are classified for the same color according to the color type classification method. After the classification is completed, the RGB value corresponding to each color is recorded, and the RGB value of each corresponding color in the positioning pile acquisition image is replaced by the calibrated RGB value. After the RGB value of each pixel is corrected, a three-dimensional model with real color and high simulation is finally obtained; SS05, measurement coordinate system establishment, establish a spatial coordinate system in the corrected three-dimensional real scene model, when establishing the spatial coordinate system, take the center point of the total station in step SS01 as the origin, the origin has the GPS position information corresponding to the origin, and calibrate and establish the coordinate value based on the primary data set of the total station during a measurement. After the spatial coordinate system is assigned, each coordinate value corresponds to a GPS value; SS06. Acquisition of the basic value of the management model: N hours after the first calibration parameter acquisition, the second calibration parameter acquisition is performed according to the measurement mode of the total station during the first calibration parameter acquisition. After the second calibration parameter acquisition, the displacement of the positioning pile during the first calibration parameter acquisition relative to the second calibration parameter acquisition is recorded, and then the average offset of the reference pile caused by weather, time and land settlement is measured. After the average offset of the reference pile is calculated, the average offset of the initial pile per hour is calculated. After the average offset of the initial pile per hour is obtained, the basic establishment value of the positioning pile position prediction management model is obtained; SS07, the establishment of fixed-point positioning piles, using the spatial coordinate system established in step SS05 as a reference for land measurement, through land measurement, obtain the characteristic points of the land to be managed, the GPS location information of the characteristic points, and the distance difference, height difference and angle value of each characteristic point relative to each initial pile. After the above parameter values ​​are obtained, calculate the time difference when the positioning pile is established relative to the reference pile and the total amount of offset caused by the time difference. After the total amount of offset and parameter values ​​are obtained, the subsequent multiple positioning piles can be accurately established in combination with the positions of multiple initial piles; In step SS07, the acquired land feature points include four corner points of land, multiple land edge points, land geomorphic feature points, land identification reference points and land center points. In step SS06, N≥5; Through the SS07 step, multi-parameter comparison-assisted point determination is then achieved; SS08, establishment of a prediction model for the management and correction of positioning piles. After step SS07, a prediction management model for the positioning pile positions is established based on the average displacement of the initial piles per hour obtained in step SS06. After the prediction management model for the positioning pile positions is established, the total displacement of the designated positioning piles at each real-time time is obtained and the real-time correction of the displacement parameters of the positioning piles is realized. In step SS08, after the real-time offset and offset parameters of the positioning pile are corrected, the land data management platform synchronizes the corrected parameters. After the reader reads the RFID chip code of the positioning pile, it quickly obtains the land feature point type of the positioning pile, the GPS historical position table calibrated with time value, and the GPS position prediction table calibrated with time value.

[0023] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims

1. A method for fixed-point measurement for land management, characterized in that: The following steps are involved: SS01, random pile arrangement, using pile tamping equipment to tamp multiple initial pile points on the land to be measured, multiple initial pile points are arranged in a set state, and a total station is installed at the approximate center of the land measurement area to be managed; SS02, primary calibration parameter acquisition, using the total station to set the measurement mode to measure the initial pile parameters to obtain a calibration parameter set; SS03, image acquisition, preset drone, install data acquisition equipment on the drone, and the drone acquires multiple image sets with set aerial photography parameters; SS04, correction modeling, superimpose multiple image sets obtained in step SS03 and import them into Smart3DCapture software, and perform atmospheric correction, data degradation correction, dark area correction and replacement, and pixel-by-pixel RGB value correction and replacement in sequence, and finally generate a 3D real scene model with no dark area, no atmospheric distortion and no color difference after multiple corrections; SS05, measurement coordinate system establishment, establish a spatial coordinate system in the corrected three-dimensional real scene model, when establishing the spatial coordinate system, take the center point of the total station in step SS01 as the origin, the origin has the GPS position information corresponding to the origin, and calibrate and establish the coordinate value based on the primary data set of the total station during a measurement. After the spatial coordinate system is assigned, each coordinate value corresponds to a GPS value; SS06. Acquisition of the basic value of the management model: N hours after the first calibration parameter acquisition, the second calibration parameter acquisition is performed according to the measurement mode of the total station during the first calibration parameter acquisition. After the second calibration parameter acquisition, the displacement of the positioning pile during the first calibration parameter acquisition relative to the second calibration parameter acquisition is recorded, and then the average offset of the reference pile caused by weather, time and land settlement is measured. After the average offset of the reference pile is calculated, the average offset of the initial pile per hour is calculated. After the average offset of the initial pile per hour is obtained, the basic establishment value of the positioning pile position prediction management model is obtained; SS07, the establishment of fixed-point positioning piles, using the spatial coordinate system established in step SS05 as a reference for land measurement, through land measurement, obtain the characteristic points of the land to be managed, the GPS location information of the characteristic points, and the distance difference, height difference and angle value of each characteristic point relative to each initial pile. After the above parameter values ​​are obtained, calculate the time difference when the positioning pile is established relative to the reference pile and the total amount of offset caused by the time difference. After the total amount of offset and parameter values ​​are obtained, the subsequent multiple positioning piles can be accurately established in combination with the positions of multiple initial piles; SS08, establishment of a prediction model for the correction of the management of positioning piles. After step SS07, a prediction management model for the positioning pile positions is established based on the average hourly displacement of the initial piles obtained in step SS06. After the prediction management model for the positioning pile positions is established, the total displacement of the specified positioning piles at each real-time time is obtained at that time and the real-time correction of the positioning pile displacement parameters is realized.

2. A method for land management surveying according to claim 1, characterized in that: In the SS01 step, each of the initial piles is provided with a unique digital code on the top, each of the initial piles has different three-dimensional specifications, each of the initial piles is pre-embedded with an RFID chip, each of the RFID chips stores unique coding information corresponding to the initial pile, and the RFID chip can read information through an external reader. After the external reader reads the coding information of the RFID chip, it can automatically obtain the three-dimensional specification parameters, coding identification, full-color image under standard light intensity of the initial pile, and GPS assignment calibration information of the initial pile by the land data management platform.

3. A method for land management surveying according to claim 2, characterized in that: When the initial piles are arranged, the distances between the initial piles are different, the distances between the initial piles are ≥8m, and the specification parameters of the initial piles and the positioning piles are the same.

4. A method for land management surveying according to claim 3, characterized in that: In the SS02 step, when the total station is used for measurement, a land data management platform is pre-established. The land data management platform is linked to the data acquisition equipment in real time through wireless data transmission. The following measurement parameters are used when the total station is used for measurement. When measuring, the total station is used to collect three-dimensional specification parameters of M initial piles, where M≥3. The three-dimensional specification parameters include the height, width and length of the initial piles. When collecting, the distance values ​​and mutual angles between the two initial piles among the M initial piles are recorded. The above data collected by the total station are packaged into a calibration parameter set, which is transmitted to the land data management platform in real time.

5. A method for land management surveying according to claim 1, characterized in that: In the SS03 step, the data acquisition equipment includes a GPS locator, a three-dimensional laser scanner and a spectrometer. Before the aerial photography parameters are executed, the scope of the land to be measured is obtained in advance. After the scope of the land to be measured is obtained, the aerial photography trajectory of the drone is formulated. After the aerial photography trajectory is formulated, the automatic time interval during shooting is set. A mixed shooting method of direct shooting and side shooting is adopted during aerial photography. The angle between the acquisition angle of the data acquisition equipment and the fuselage is 90° during direct shooting, and the angle between the acquisition angle of the data acquisition equipment and the fuselage is 45° during side shooting. During aerial photography, a multi-time series acquisition plan is formulated, and each time series corresponds to a collection time period. The collection time periods of each time series are different. A unified aerial photography parameter is adopted in each time series, and finally the data acquisition equipment obtains a plurality of image sets in different time series. In the SS04 step, during atmospheric correction, the histogram adjustment method and the dark target method are used to eliminate the image distortion caused by the atmospheric influence in the image set. In the SS04 step, during data degradation correction, the linear discriminant analysis method is used to reduce the spectral wave number and data volume of the hyperspectral image. After the image sets obtained under multiple time series are superimposed and imported into the Smart3DCapture software, the brightness correction module obtains the luminance of the image set under each time series and the spectral parameters corresponding to each image. After the luminance of the image set under each time series and the spectral parameters corresponding to each image are obtained, the dark area correction replacement module identifies the dark area in each image set and the image pixel points below the set brightness value. After the dark area in each image set and the image pixel points below the set brightness value are identified, the dark area correction replacement module selects the corresponding image pixel points in other image sets that meet the luminance value to perform equipotential replacement on the selected dark area pixel points, so that the three-dimensional model generated by Smart3DCapture does not have a dark area when viewed at any angle, and all land features of the three-dimensional model can be observed without blind spots and intuitively. In the SS04 step, the RGB value of each pixel in the full-color image of the positioning pile under the standard light intensity of the positioning pile is identified by image recognition software and image recognition algorithm, and multiple pixels are classified for the same color according to the color type classification method. After the classification is completed, the RGB value corresponding to each color is recorded, and the RGB value in the full-color image of the positioning pile under the standard light intensity is used as the calibration value. After the calibration value is obtained, the positioning pile acquisition image in each image set is identified by image recognition software and image recognition algorithm. After the positioning pile acquisition image is recognized, the RGB value of each pixel in the positioning pile acquisition image is obtained. After the RGB value of each pixel is obtained, the multiple pixels are classified for the same color according to the color type classification method. After the classification is completed, the RGB value corresponding to each color is recorded, and the RGB value of each corresponding color in the positioning pile acquisition image is replaced by the calibrated RGB value. After the RGB value of each pixel is corrected, a three-dimensional model with real color saturation and high simulation is finally obtained.

6. A method for land management surveying according to claim 5, characterized in that: In the SS03 step, after each aerial image is acquired, each image file in the image set corresponds to the GPS position information, time information, spectral parameter information and aerial angle information bound when the image is acquired.

7. A method for land management surveying according to claim 1, characterized in that: In the SS07 step, the acquired land feature points include four corner points of the land, multiple land edge points, land geomorphic feature points, land identification reference points and land center points. In the SS06 step, N≥5.

8. A method for land management surveying according to claim 7, characterized in that: In the SS08 step, after the real-time offset and offset parameters of the positioning pile are corrected, the land data management platform synchronizes the corrected parameters, and after the reader reads the RFID chip code of the positioning pile, it quickly obtains the land feature point type of the positioning pile, the GPS historical position table calibrated with time value, and the GPS position prediction table calibrated with time value.

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