KR100678395B1 - System and method for real time position correction of geometric information data using satellite and aerospace image - Google Patents

Abstract

A system and a method for correcting geometric information data in real-time with a satellite/aerospace image are provided to efficiently correct the geometric information data in real-time by correcting the real-time satellite/aerospace image, performing coordinate conversion, and correcting/storing the geometric information data corresponding to a position desired from a user. An image obtainer(11) obtains the satellite/aerospace image of a specific area. An image corrector(12) corrects the satellite/aerospace image through various processes. A digitizer(13) receives/digitizes the corrected satellite/aerospace image as spatial data. A coordinate converter(14) forms a digital map by converting coordinates of the digitized spatial data. A GPS(Global Positioning System) receiver(21) receives real-time position information through a GPS. A map display part(22) outputs a map image by the position information received through the GPS receiver. A location corrector(23) displays the data converted in the coordinate converter on the displayed map image and enables the user to correct/store the geometric information data corresponding to the desired position.

Description

System and method for real time position correction of geometric information data using satellite and aerospace image}

1 is a block diagram of a real-time position correction system of geographic information data using satellite image and aerial image according to an embodiment of the present invention.

2 is a flowchart illustrating a real-time position correction method of geographic information data using satellite image and aerial image according to an embodiment of the present invention.

3 is a flowchart illustrating a real-time update method of conventional geographic data.

Explanation of symbols on the main parts of the drawings

10: preprocessing unit 11: image acquisition unit

12: image correction unit 13: digitizing unit

14: coordinate conversion unit 20: real-time position correction unit

21: GPS receiver 22: map display

23: position correction unit 30: transmission unit

31: real-time location transmitter

The present invention relates to a Geographic Information System (GIS), and in particular, to correct and store the geospatial data corresponding to the point that the user wants to correct by calibrating and transforming the satellite image and the aerial image acquired in real time. Therefore, the present invention relates to a real-time position correction system and method for geospatial data using satellite and aerial images, which are suitable for performing efficient real-time position correction on geospatial data.

In general, the Geographic Information System (GIS) refers to a system for interpreting attribute information on a map using a computer. This is also called a map information system. The information handled varies, including human factors such as population density and land use, and natural environmental factors such as weather conditions and geology. It aims to process attribute information, interpret it for specific purposes, and support planning. Geographic information systems are used for various purposes such as urban planning, land management, and corporate sales strategy planning.

Thus, as a technique for updating the geographic information data of the conventional geographic information system in real time, there was a Republic of Korea Patent Office registration number 10-557747 ('real time update method of geographic information data)'.

3 is a flowchart illustrating a real-time update method of conventional geographic data.

Therefore, first, through the mobile terminal, the entire geographical information data of the feature included in the optimal path from the current location to the destination is received and stored in the geographical information data storage unit (ST11).

Next, position data on the current position is received from the satellite through the GPS receiver (ST12).

Next, the geographic information data corresponding to the unit cell area including the current position among all the geographic information data according to the position data is output through the graphic processor as a map image on the display unit, and the map data is received in real time by receiving the position data. The images are superimposed on the image (ST13).

At this time, if there is a modification to the feature output on the display unit during the movement of the user using the navigation system, the geo-information data corresponding to the point to be modified through the operation unit is loaded and modified (ST14).

However, these prior arts have limitations in not using satellite images and aerial images when performing real-time position correction.

Therefore, the present invention has been proposed to solve the above-mentioned general problems, and an object of the present invention is to correct the satellite image and the aerial image obtained in real time and coordinate transformation of the geography corresponding to the point that the user wants to correct. The present invention provides a real-time position correction system and method for geo-information data using satellite image and aerial image that can perform efficient real-time position correction on geo-information data by modifying and storing the information data.

Hereinafter, an embodiment according to the present invention, a real-time position correction system of geospatial data using satellite images and aerial images, and a method thereof, will be described with reference to the accompanying drawings.

1 is a block diagram of a real-time position correction system of geographic information data using satellite image and aerial image according to an embodiment of the present invention.

As shown therein, an image acquisition unit 11 for acquiring satellite and aerial images of a predetermined area; The satellite image acquired by the image acquisition unit 11, pre-processing to remove the electromagnetic noise and correction of errors, emphasis processing to enhance the image quality of the image, thematic analysis processing to perform thematic analysis of the image, extract the surface information Perform post-processing to correct satellite images, and use it for quantitative analysis processing to determine the position, size, and shape of the aerial image obtained by the image acquisition unit 11, and information including resources and environment. An image correction unit 12 performing correction on the aerial image by performing qualitative analysis processing; A digitizing unit 13 for receiving the satellite image and the aerial image corrected by the image correcting unit 12 and digitizing the spatial data; A coordinate transformation unit 14 for transforming the digitized spatial data by the digitizing unit 13 to form a numerical map; A GPS receiver 21 for receiving real-time location information through a GPS (Global Positioning System); A map display unit 22 outputting a map image based on the location information received through the GPS receiver 21; Coordinate transformed data of the satellite image and the aerial image received in real time by the coordinate conversion unit 13 is displayed on the map image output by the map display unit 22, and whether the user corresponds to a point to be corrected. A position correction unit 23 for correcting and storing logical information data; A real-time position transmitter 31 for correcting the position correction unit 23 and transmitting the stored geo information data to a geo information providing server so that the position correction of the geo information data is performed and reflected in the geo information providing server. Characterized in that configured.

2 is a flowchart illustrating a real-time position correction method of geographic information data using satellite image and aerial image according to an embodiment of the present invention.

As shown therein, a first step ST1 of acquiring satellite image and aerial image of a predetermined area; The satellite image acquired after the first step, the pre-processing to remove the electromagnetic noise and correct the error, the emphasis processing to enhance the image quality of the image, thematic analysis to perform thematic analysis of the image, the post-processing to extract the information of the ground surface To perform satellite image correction, perform quantitative analysis to determine position, size and shape of the aerial image acquired in the first step, and perform qualitative analysis to be used for information survey including resources and environment. Performing a correction on the aerial image (ST2); A third step (ST3) of digitizing the satellite image and the aerial image corrected in the second step with spatial data; A fourth step (ST4) of forming a numerical map by coordinate transformation of the digitized spatial data in the third step; A fifth step ST5 of receiving real-time location information through GPS; A sixth step ST6 of outputting a map image based on the location information received in the fifth step; In the fourth step, the coordinate-converted data of the satellite image and the aerial image are displayed on the map image output in the sixth step, and the user can modify and store the geographic data corresponding to the point to be corrected. A seventh step ST7; And an eighth step (ST8) for correcting the position of the geographic information data in the geographic information providing server by transmitting the stored geographic information data modified in the seventh step to the geographic information providing server. It is done.

Referring to the accompanying drawings, a preferred embodiment of a system for real-time position correction of geospatial data using satellite images and aerial images and a method thereof according to the present invention configured as described above will be described in detail. In the following description of the present invention, detailed descriptions of well-known functions or configurations will be omitted if it is determined that the detailed description of the present invention may unnecessarily obscure the subject matter of the present invention. In addition, terms to be described below are terms defined in consideration of functions in the present invention, which may vary according to intention or precedent of a user or an operator, and thus, the meaning of each term should be interpreted based on the contents throughout the present specification. will be.

First, the present invention is to perform efficient real-time position correction for geospatial data by modifying and storing geospatial data corresponding to the point that the user wants to correct by calibrating and transforming the satellite image and aerial image acquired in real time. will be.

To this end, the image acquisition unit 11 of the preprocessing unit 10 acquires satellite image and aerial image of a predetermined area (ST1).

In addition, the image correction unit 12 performs thematic analysis on the satellite image acquired by the image acquisition unit 11, preprocessing to remove electromagnetic noise and correcting errors, emphasis processing to enhance the image quality, and subjective analysis of the image. Performs post-processing to extract the information on the surface of the earth's surface to perform satellite image correction, and to determine the position, size, and shape of the aerial image acquired by the image acquisition unit 11, resources and environment. Qualitative analysis is used to investigate the information, including the correction of the aerial image.

In this case, the satellite image is a digital wave form that detects electromagnetic energy reflected or radiated by an object of the earth by a detector mounted on a satellite, and records it in digital form. The image correction unit 12 processes the data to obtain information about the object or phenomenon. . In this case, the image correction unit 12 analyzes satellite images obtained not only in the visible light region but also in the infrared and ultraviolet light regions, and divides the information into a plurality of wavelength bands to obtain various analysis using the spectral characteristics of the geographic information. Can be done.

In order to make the satellite image data that can be used in the GIS, the image correction unit 12 undergoes a complicated process.

First of all, images received from satellites include scattering and reflection in the atmosphere between the satellite and the surface, systematic noises that occur regularly, and accidental noises that occur due to the characteristics of space. So the collected satellite image data is the pre-treatment is required to remove the geometric errors or radial errors caused by the satellite and the earth's movement and shaking of the sensor, the atmospheric conditions. Therefore, in the pretreatment process, radial correction and geometric correction are performed. Radiation correction corrects for the influence of minute differences in sensitivity between detectors and for the effect of solar altitude when mosaicing data observed at different times. Radiation error correction techniques can be easily used in most image processing software. In addition, satellite images have geometric distortions and errors, so the position must be corrected to match the map coordinate system of the ground. Therefore, the geometric correction is to correct the effects of the earth's rotational influence and the earth curvature at the time of data acquisition to be the same as the projection of a general map. The geometric distortion of the satellite image can be represented by the difference between the coordinates of each pixel in the image and the coordinates of the object in the map coordinate system. In order to perform the geometric correction to correct the geometric distortion, the ground control points ( Ground Control Point (GOP) is selected, image coordinates and ground coordinates for ground control points are obtained, and the conversion equation between the two coordinates is set and corrected. As a conversion equation, an affine conversion equation, which is primarily a linear expression, may be used. When a target area is large, a second or higher order polynomial may be used. At this time, pixel resampling is performed.

In addition, the image correction unit 12 performs an emphasis process for enhancing the image quality of the image for better information acquisition through the satellite image. This enhances the readability of the image in order to enhance the readability of the image, thereby improving the visual readability of the image, and facilitates subsequent analysis and classification. This is accomplished by techniques such as contrast extension, contrast stretching, inter-pixel filtering, and inter-image computation. There are many ways to emphasize the image. Thus, the contrast expansion method gives a visual emphasis on the monitor screen and does not change the data value itself. In the segmentation processing method that emphasizes the shade by dividing the density of the image, it is easy to distinguish the boundary by emphasizing only the image having a certain density in the image that appears from the light color to the dark tone to make the difference of the density stand out from the surrounding objects. have. In addition, a contrast stretching method may be used to amplify a low brightness image so that the highest density corresponds to white and the lowest density corresponds to black so that the image quality is clearly displayed. . Another method is to extract edges or edges by making the edges stand out by highlighting the difference of shades by referring to the surrounding pixel values for each pixel by using filtering technique between adjacent pixels. It is also possible to use an extraction method and an inter-image calculation method for constructing image data by performing calculation processing on two or more band data.

In addition, the image correction unit 12 performs a subject-specific analysis step on the image. This is to analyze the highlighted data into selected themes. For example, images of landscapes include various land cover elements (various types of vegetation and characteristics of land use). In thematic analysis, these different types of cover are divided into different thematic maps and grouped together for statistical analysis. This allows us to find common themes from the raster cell. Thematic maps are maps showing the spatial distribution of scientific and social data, such as climate, vegetation, geology, and trade. These thematic maps are focused on providing information about spatial differences and regional diversity on specific topics, and represent spatial distribution patterns on certain phenomena. Therefore, thematic maps can be classified into geological maps, forest maps, soil maps, land use maps, precipitation maps, temperature maps, population distribution maps, economic maps, tourist maps, traffic maps, and city planning maps. The selection of themes is unlimited and is often used to compare regional characteristics of natural, socio / economic, historical / cultural phenomena.

In addition, the image corrector 12 performs a post-processing process for extracting information on the ground surface. This post-treatment categorizes subjects into distinct categories, for example, vegetation theme maps from total land cover (forests, farmland, barren land), community levels (leaves, conifers), and area of individual species. Can be classified as Supervised classification and unsupervised classification can be used to extract such information from the surface of the earth. Supervised classification is a method of extracting an object, such as the characteristic of the pixel, based on the value when the electromagnetic wave characteristic of the object to be determined is known or the pixel at the representative position is made clear. Here, the pixels used as the reference for the determination are defined as a training field for each item, and data for each item is input to form the reference for the discrimination. Based on this, which item each pixel belongs to is identified by arithmetic discrimination method (maximum likelihood method, average distance comparison method, shortest distance method, nearest Lean method, etc.) to be included in the nearest item. If any reference material is not similar enough to be satisfied, it is treated as unknown. The results of supervised classification are strongly influenced by the reference sheet, so selection of the reference sheet is very important. Therefore, the classification accuracy should be verified through on-site investigation on the classified results, which can be carried out by trial and error repetitive analysis method. In general, the maximum likelihood method is known to have the highest classification accuracy, so it can be mainly used. The maximum likelihood method sets the probability density function from the average value and the covariance matrix of the practice area for each item, and classifies it as the most probable item. Unsupervised classification can also be used in the absence of terrestrial references to refer to, by analyzing the data on the computer itself. By non-supervised classification, similar groups are categorized using the spectral characteristics of objects. Clustering methods for forming different clusters include sequential clustering, statistical clustering, ISODATA (International Organization for Standardization Data), RGB (red, green, blue) clustering. The computer randomly sets the center of each cluster and iterates and classifies until it finds the best center.

In addition, the image correction unit 12 properly analyzes the characteristics of various objects obtained from the aerial image according to the purpose, and analyzes based on this to obtain information on the shape, geology, vegetation, soil, etc. of the object. Aerial photographs can be read directly from aerial photographs such as paddy fields, field divisions, road pavement, vegetation, etc., as in topographic maps, or inductive or deductive methods from indirect observations such as geological readings. You can determine and correct the necessary information. The aerial photograph reading is to determine the characteristics of objects such as roads, railways, rivers, houses, geology, and forests, which were photographed in the photographic image.

Thus, the image correction unit 12 performs quantitative analysis and qualitative analysis for reading the aerial image. That is, quantitative aerial image reading that determines position, size, and shape, and qualitative aerial image reading which are used to investigate information such as resources and environment are performed.

When reading the aerial image, the size, shape, shadow, tone, texture, and pattern of the photo image are analyzed as basic elements, and the correlation, Additional combinations of factors such as vertical exaggeration can be read. Here, hypersensitivity means that the height of the three-dimensional image obtained by stereoscopic view of the aerial image is protruding, the relief is severe, the valley is deeper than the actual, and the slope is more urgent than the actual slope. This over-examination exaggerates the ups and downs of the surface, so it is considered to be considered for terrain reading in flat areas and terrain reading in slopes (ST2).
Thus, the size and shape of the aerial image are very important factors in the reading, and the size refers to the three-dimensional and planar width or length of a single shape or a single hue, and the shape refers to the outline, composition, arrangement and general shape of an object or a target. It means. The actual size of the picture can be calculated using the photographing nose and the focal length of the camera lens. Because aerial images are images taken from just above the ground surface, they are generally different from the side view from the ground, so they should be read in the form of when viewed vertically.
Shading is also an important factor in aerial photographic readings when reading features such as tall towers and terrains that are difficult to contrast with ambient tones. When reading aerial photographs, the direction of light rays matches the direction of sunlight during shooting, and a three-dimensional effect is obtained from the relationship between shadows. Read south while looking up. In general, however, shadows in aerial photographs interfere with detailed readings, so that aerial photographs should be taken with altitude set appropriately for aerial photographs.
On the other hand, the color tone of aerial photographs is mainly due to the reflectance of sunlight, and is used to determine objects such as vegetation disturbances. In black and white photography, color and contrast are recorded in a single tone from white to black. The color of the aerial photo is also influenced by the subject's position and angle with respect to the sun, the timing and weather of shooting, the sensitivity of the film, the nature of the filter, the processing of the print, and the type of photo paper. In this way, since the color tone changes in various ways even for the same object, the aerial photograph is read with emphasis on the difference in color tone rather than the absolute value of the concentration of the aerial photograph. In particular, when the scale of aerial photographs is small, details cannot be known accurately through stereoscopic vision, so the importance of color tone is more prominent in reading. Compared to black-and-white photographs, white-to-black hue is a single color tone, while natural-color photographs reproduce the color of an object as it is.
The texture of aerial photographs shows the detail and roughness of the image name in which various elements such as size, shadow, shape, and hue are gathered together, and it is a minute hue change in which a small object set that is difficult to identify in each state is displayed. . The representation of the texture is divided into rough or dense, bumpy or flat, and the scale of the texture varies depending on the scale.
The spatial arrangement of vegetation, topography, or surface tones that appear on aerial photographs is called shape. Many objects, artificial or natural, have a basic shape of repetition or relevance to aid in reading. In addition, the structure, properties, types, uses, etc. of the object can be read by the arrangement thereof. For example, the shape of the water system, the scale and layout of the plant, etc. can be easily read.
In addition, identifying which images relate to the surrounding images is important in aerial photograph reading. Since one shape is generally associated with the surrounding image, it may be difficult to read correctly without looking at only one particular image and considering the relation to the other photograph. In particular, when the scale of aerial photographs is small and it is difficult to observe each photograph, the relationship between objects should be used.
In addition, the height of the three-dimensional image obtained by stereoscopic view of the aerial photo is projected higher and more undulating, and the valley is deeper than the actual, and the slope is more urgent than the actual slope. This hypersensitivity changes due to the focal length, redundancy, etc. of the lens used for reading. Excessiveness is a result of exaggerated surface ups and downs, which helps greatly in reading terrain in low and flat areas, while avoiding misjudgment because slopes are more urgent than they actually are.

The digitizing unit 13 receives the satellite image and the aerial image corrected by the image correcting unit 12 and digitizes the spatial data. Such digitizing can be built with a raster data model or a vector data model (ST3). Here, the raster data model refers to representing an object in the real world as a set of minimum maping units called grids, cells, or pixels. For raster data structures, the cell is the minimum size that represents the shape of the object. Thus, raster data represented by regular spatial arrangement is a structure that divides the entire surface into unit cells of a certain size, inputs attribute values into each cell, stores them, and operates. Therefore, each cell stores an image of an object given by "1" or "0" according to the presence or absence of information, and location information can be automatically determined by rows and columns. In addition, the vector data model expresses various objects or phenomena in the real world using points, lines, and polygons. The vector data structure indicates the geographical position of objects in directions and sizes. In the vector data model, objects are designed by their geographic location and attributes. For example, an oil well is represented by a single point coordinate (x, y) and a label, and the pipeline is a linear representation of the beginning node (x, y), the ending node (x, y) and the label. Can be. The refinery can also be represented by a polycon that includes a set of point coordinates (x, y) and a label.

In addition, when the digitizing unit 13 performs digitizing, various types of errors occur in the data. In other words, after the closed polygon is digitized, an error occurs in which a silver polygon is generated. This is because a silver polygon is formed when two polygons are in contact with one boundary line, and thus the digitization cannot be precisely digitized when the boundary line is digitized twice. In addition, an overshoot that ends the line past the intersection, or an undershoot where the line does not meet the reverse point, and a spike occurs when the two lines meet at the intersection. In addition, various types of errors occur in the formation of polygons. For example, if the polygon is not closed, if the label is doubled, if the label is missing from a polygon contained within another polygon, such as a lake, and if the boundary of the adjacent polygon is digitized twice, etc. There is this. The digitizing unit 13 corrects the various errors generated in this way so that the digitizing data can be automatically corrected (ST3).
Thus, undershoot or overshoot is an error in which two lines fall outside or fall short of the target point. To correct this, increase or decrease the length of the line segment. Select the wrong segment, then drag it to the intersection or target segment and run the fix that connects it properly.
Also, in the case of label errors, the label input of polygons can be pasted during or after digitizing, with some polygons having no label, multiple labels, or incorrect labeling. So you can select the wrong label, delete it, add it, or move it into place to fix it.
In addition, in the case of overlapping lines, when the input content is complicated, the same line may be input twice. If the lines are duplicated like this, the error can be easily corrected by removing one line.
Also, in the case of silver polygons, the formation of silver polygons occurs when digitizing in a complex map, and the way to correct them depends on the error that occurs. Sometimes polygons can be removed by shifting the position properly so that they don't overlap, or they can be corrected by removing the vertices that make up the incorrectly entered line segments that form the polygon.

Then, the coordinate conversion unit 14 coordinate-converts the spatial data digitized by the digitizing unit 13 to form a numerical map. Here, a map is a projection of a three-dimensional earth in a two-dimensional plane, and the shape, area, distance, direction, etc. are already deformed in this projection process. Thus, the coordinate conversion unit 14 performs a task of matching the coordinates of the data input through the digitizing unit 13 to the coordinate system of the real world (ST4).
The most important thing in these coordinate transformations is to define the registration point or reference point that is the basis of the coordinate transformation. In general, at least four or more tick marks must be determined at the beginning of the digitizing operation, and the positions of other objects are recognized as coordinates based on the reference point coordinates. Therefore, the larger the number of reference points, the better, and most importantly, the coordinate values of the reference points should be measured accurately and precisely.
Thus, an affine transform using a linear transform and a conformal transform using a secondary transform can be used. Basically, three processes occur: translation, rotation, and scale change.
The transformation is the movement of all or part of the object to another location on the Cartesian coordinate plane, by adding or subtracting the coordinates required for the object's X and Y coordinates (X '= X + Tx, Y' = Y + Ty).
Scale changes can be used when you need to compare maps with different scales or produce results at different scales. In this case, it is multiplied by the scale factor (sx, sy) which is the rate of change of scale (X '= X * sx, Y' = Y * sy).
Rotation can be used during projection and backprojection, using trigonometric functions. In other words, if the angle to be rotated is θ, the sum is multiplied by multiplying cosθ by the X coordinate and sinθ by the Y coordinate (X '= Xcosθ + Ysinθ, Y' = -Xcosθ + Ysinθ).

On the other hand, the GPS receiver 21 in the real-time position correction unit 20 receives the real-time position information through the GPS (ST5).

Then, the map display unit 22 outputs a map image based on the location information received through the GPS receiver 21 (ST6).

The position correction unit 23 displays coordinate converted data for the satellite image and the aerial image received in real time from the coordinate conversion unit 13 on the map image output by the map display unit 22, and is corrected by the user. The geospatial data corresponding to the desired point can be modified and stored (ST7).

Then, the real-time position transmitter 31 of the transmitter 30 corrects the position correction unit 23 and transmits the stored geo information data to the geo information providing server, thereby performing the position correction of the geo information data on the geo information providing server. To be reflected (ST8).

As described above, the present invention performs efficient real-time position correction for the geospatial data by correcting and storing the geospatial data and the aerial image by correcting and transforming the geospatial data corresponding to the point to be corrected by the user. will be.

As described above, the real-time position correction system and method of geospatial data using the satellite image and the aerial image according to the present invention to correct the satellite image and the aerial image obtained in real time and coordinate transformation by the user to modify By modifying and storing the geospatial data corresponding to the point, it is possible to perform efficient real-time position correction on the geospatial data.

Although the above has been described as being limited to the preferred embodiment of the present invention, the present invention is not limited thereto and various changes, modifications, and equivalents may be used. Therefore, the present invention can be applied by appropriately modifying the above embodiments, it will be obvious that such application also belongs to the scope of the present invention based on the technical idea described in the claims below.

Claims (2)

An image acquisition unit 11 for acquiring satellite and aerial images of a predetermined region; The satellite image acquired by the image acquisition unit 11, pre-processing to remove the electromagnetic noise and correction of errors, emphasis processing to enhance the image quality of the image, thematic analysis processing to perform thematic analysis of the image, extract the surface information Perform post-processing to correct satellite images, and use it for quantitative analysis processing to determine the position, size, and shape of the aerial image obtained by the image acquisition unit 11, and information including resources and environment. An image correction unit 12 performing correction on the aerial image by performing qualitative analysis processing; A digitizing unit 13 for receiving the satellite image and the aerial image corrected by the image correcting unit 12 and digitizing the spatial data; A coordinate transformation unit 14 for transforming the digitized spatial data by the digitizing unit 13 to form a numerical map; A GPS receiver 21 for receiving real-time location information through GPS; A map display unit 22 outputting a map image based on the location information received through the GPS receiver 21; Coordinate-converted data of the satellite image and the aerial image received in real time by the coordinate conversion unit 13 is displayed on the map image output by the map display unit 22, and the geography corresponding to the point to be corrected by the user A position corrector 23 for correcting and storing the information data; A real-time position transmitter 31 for correcting the position correction unit 23 and transmitting the stored geo information data to a geo information providing server so that the position correction of the geo information data is performed and reflected in the geo information providing server. Real-time position correction system of geographic information data using satellite image and aerial image, characterized in that the configuration. A first step (ST1) of acquiring satellite and aerial images of a predetermined area; The satellite image acquired after the first step, the pre-processing to remove the electromagnetic noise and correct the error, the emphasis processing to enhance the image quality of the image, thematic analysis to perform thematic analysis of the image, the post-processing to extract the information of the ground surface To perform satellite image correction, perform quantitative analysis to determine position, size and shape of the aerial image acquired in the first step, and perform qualitative analysis to be used for information survey including resources and environment. Performing a correction on the aerial image (ST2); A third step (ST3) of digitizing the satellite image and the aerial image corrected in the second step with spatial data; A fourth step (ST4) of forming a numerical map by coordinate transformation of the digitized spatial data in the third step; A fifth step ST5 of receiving real-time location information through GPS; A sixth step ST6 of outputting a map image based on the location information received in the fifth step; Displaying coordinate converted data of the satellite image and the aerial image on the map image output in the sixth step, and allowing the user to modify and store geographic data corresponding to a point to be corrected. 7 steps ST7; And performing an eighth step (ST8) in which the location information of the geographical information data is performed and reflected by the geographical information providing server by transmitting the stored geographical information data to the geographical information providing server in the seventh step. Real-time position correction method of geographic data using satellite image and aerial image.

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