CN109741446B - Method for dynamically generating fine coast terrain by three-dimensional digital earth - Google Patents
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Abstract
The invention discloses a method for dynamically generating fine coast terrains on a three-dimensional digital earth, and relates to the field of dynamically generating the fine coast terrains by the earth. The method comprises the following steps: s1: data acquisition and preprocessing; s2: carrying out coastline data extraction processing; s3: generating coastal terrain grid data; s4: generation of coast detail texture data. The invention is based on the existing terrain generating technology, utilizes satellite picture data, ground elevation data and coastline vector data, combines an innovative coastline high-precision terrain grid generating algorithm and a detail texture generating algorithm to obtain the coastline, the coast terrain grid and the coast detail texture with high precision, generates the three-dimensional digital earth coast terrain with precision and effect closer to the real environment, and can be widely applied to the fields of geographic information systems, simulation and the like.
Description
Technical Field
The invention relates to the field of dynamically generating fine coast terrains by earth, in particular to a method for dynamically generating fine coast terrains by three-dimensional digital earth.
Background
In recent years, due to various human causes and natural causes, greenhouse effect, i.e., global warming, has been developed on the earth. The global warming causes the glaciers to retreat and the sea level to rise, so that the global warming can be monitored to a certain extent by monitoring the rise of the sea level. Therefore, as global warming leads to an increase in sea level, people are more and more concerned about the change of coastline, so that a need arises for coastline analysis and presentation in a three-dimensional scene. However, for example, the popular google earth and osgearth at present cannot display the high-precision coastline, and only the satellite picture can be used as the coastline texture, so that the display effect is poor.
At present, some related technologies exist in a grid computing method for three-dimensional digital terrestrial terrain refinement, namely an Inverse Distance weighting method (IDW-Inverse Distance Weighted), and the effect is poor under the condition that the shape of a coastline is complex. The other method is a Spline with Barriers method, which is complex in calculation process and long in time consumption and cannot meet the requirement of generating high-precision coastal terrain in real time in a three-dimensional digital earth.
In this case, in order to prevent global warming and prevent adverse effects caused by global warming, a method capable of generating fine coastal landforms with high accuracy is required, which enables more accurate real-time monitoring of a coastline, and thus more accurate real-time monitoring of a sea level rise situation and a global warming situation.
Disclosure of Invention
The invention aims to: aiming at the problems in the prior art, the method for dynamically generating the fine coastal terrain on the three-dimensional digital earth is provided, the three-dimensional digital earth coastal terrain with the precision and effect closer to the real environment is generated by combining an innovative coastline high-precision terrain grid generation algorithm and a detail texture generation algorithm on the basis of the existing terrain generation technology, and the method can be widely applied to the fields of geographic information systems, simulation and the like.
The technical scheme adopted by the invention is as follows:
a method of three-dimensional digital earth dynamic generation of fine coastal terrain, characterized in that it comprises the steps of: s1: acquiring and preprocessing data, wherein the acquiring comprises the acquisition of satellite picture data, ground elevation data and coastline vector data, and the preprocessing of the satellite picture data, the ground elevation data and the coastline vector data is carried out; s2: coastline data extraction processing, namely processing and extracting coastline data by using satellite picture data, ground elevation data and coastline vector data; s3: generating coastal terrain grid data, namely utilizing the acquired ground elevation data to obtain elevation data of each point of coastal terrain through interpolation processing, so as to generate coastal terrain grid data; s4: generating coast detail texture data, wherein the generation comprises the steps of carrying out object information identification on satellite picture data, namely carrying out area identification on land, seawater and intersection areas at two sides of a coast line in the satellite picture data, and generating a coast type mask map by utilizing the information of the areas, wherein the data of the mask map reflects the detail textures of the area ranges of different types of coasts, and the mask map data correspondingly obtains the texture data of the area ranges of the different types of coasts; s5: the earth's coastal terrain is obtained using a terrain generation technique using coastline data, coastal terrain grid data, and coastal detail texture data.
The method for dynamically generating the fine coastal terrain by the three-dimensional digital earth is characterized in that the method S2 specifically comprises the following steps: s2.1: tracking an edge line of the satellite picture data by using an edge detection algorithm to extract a coastline, and connecting the results by processing of a morphological (expansion and corrosion) algorithm to obtain a continuous coastline, wherein coastline result data A is obtained at the moment; s2.2: calibrating the coastline by using the transition characteristics of the coastlines of different coastline types in the satellite picture data on the brightness of the picture to obtain coastline result data B; s2.3: generating contour line data by utilizing the elevation data, and comparing the contour line data with a coastline elevation value to obtain coastline result data C; s2.4: using the coastline data in the existing coastline vector data as coastline result data D; s2.5: the coastline result data A, B, C, D is processed to obtain final coastline result data E.
The method for dynamically generating the fine coastal terrain by the three-dimensional digital earth is characterized by comprising the following steps S2.5: and obtaining final coastline result data E after weighting addition processing is carried out on the coastline result data A, B, C, D, wherein the calculation formula is as follows: e = w A A+w B B+w C C+w D D。
The method for dynamically generating the fine coast terrain by the three-dimensional digital earth is characterized in that in the step S4, object information identification is carried out on satellite picture data, specifically, the identification of the coast ground covering details and the coastline is carried out on the satellite picture data based on an image identification technology.
The method for dynamically generating the fine coastal landforms by using the three-dimensional digital earth is characterized in that in step S4, coastal type mask maps are generated by using the information of the areas, wherein the determination of the areas of different types of coasts in the mask maps also needs to combine with elevation data, height gradients are calculated by using contour lines calculated by the elevation data, and mask maps determined by the areas of different types of coasts can be obtained by using the differences of the different types of coasts on the height gradients and combining the information of the areas.
The method for dynamically generating the fine coast land forms by the three-dimensional digital earth is characterized in that mask map data in the method step S4 are mapped to obtain coast detail texture data, wherein the mapping relationship between the mask map and the texture data of different types of coast region ranges is that one mask map corresponds to the texture data of one type of coast region range.
The method for dynamically generating the fine coastal terrain by the three-dimensional digital earth is characterized in that the object information identification specific steps are as follows: s4.1: graying the satellite picture data; s4.2: standardizing the color space of the input satellite picture data by adopting a Gamma correction method; s4.3: calculating the gradient of each pixel of the satellite picture data; s4.4: dividing the satellite picture data into a plurality of image units, and counting a gradient direction histogram of each image unit to form directional gradient histogram feature description data of each image unit; s4.5: forming a plurality of adjacent image units into an image block, and connecting the directional gradient histogram feature description data of all the image units in the image block in series to obtain the directional gradient histogram feature description data of the image block; s4.6: connecting the directional gradient histogram feature description data of all image blocks in the satellite picture data in series to obtain directional gradient histogram feature description data of the satellite picture data; s4.7: and performing content identification on the satellite picture data according to the directional gradient histogram feature description data of the satellite picture data by using the CNN graph classification model.
The method for dynamically generating the fine coast terrain by the three-dimensional digital earth is characterized in that the data preprocessing in the method step S1 comprises the following steps: registering and fusing the satellite picture data to obtain color image data, and performing geometric correction and projection correction on the data by using a known control point; the elevation data is processed through interpolation, the problem of data loopholes possibly caused by objective factors is solved, and the elevation data is kept consistent with a satellite picture data coordinate system through coordinate conversion.
In summary, due to the adoption of the technical scheme, the invention has the beneficial effects that:
1. according to the method for dynamically generating the fine coastline terrain by using the three-dimensional digital earth, provided by the invention, the coastline data is obtained by processing and extracting the satellite picture data, the ground elevation data and the coastline vector data, so that more accurate coastline data can be obtained.
2. According to the method for dynamically generating the fine coastal terrain by the three-dimensional digital earth, provided by the invention, the ground elevation data are subjected to interpolation processing to obtain the elevation values of the known points and other unknown points in the original ground elevation data in the coastal terrain grid to be generated, so that the coastal high-precision terrain grid is obtained.
3. The method for dynamically generating the fine coast terrain by the three-dimensional digital earth provided by the invention has the advantages that the satellite picture data is subjected to image recognition, and the land, the seawater and the region of the intersection part at the two sides of the coastline are subjected to region marking and recognition, so that the coast high-precision detail texture is obtained.
4. The method for dynamically generating the fine coastal landform by the three-dimensional digital earth utilizes the existing landform generation technology and combines an innovative coastline high-precision landform grid generation algorithm and a detail texture generation algorithm to generate the earth coastal landform with precision and effect closer to a real environment.
Detailed Description
In order to make the technical solutions of the present invention better understood, the following description is provided clearly and completely, and other similar embodiments obtained by those skilled in the art without creative efforts shall fall within the protection scope of the present application based on the embodiments in the present application.
Example 1
A method for three-dimensional digital earth dynamic generation of fine coastal terrain, characterized in that it comprises the following steps: s1: acquiring and preprocessing data, wherein the acquiring comprises the acquisition of satellite picture data, ground elevation data and coastline vector data, and the preprocessing of the satellite picture data, the ground elevation data and the coastline vector data is carried out; s2: coastline data extraction processing, namely processing and extracting coastline data by using satellite picture data, ground elevation data and coastline vector data; s3: generating coastal terrain grid data, namely utilizing the acquired ground elevation data to obtain elevation data of each point of coastal terrain through interpolation processing, so as to generate coastal terrain grid data; s4: generating coast detail texture data, wherein the generation comprises the steps of carrying out object information identification on satellite picture data, namely carrying out area identification on land, seawater and intersection areas at two sides of a coast line in the satellite picture data, and generating a coast type mask map by utilizing the information of the areas, wherein the data of the mask map reflects the detail textures of the area ranges of different types of coasts, and the mask map data correspondingly obtains the texture data of the area ranges of the different types of coasts; s5: the earth's coastal terrain is obtained using a terrain generation technique using coastline data, coastal terrain grid data, and coastal detail texture data.
In the third step of the invention, the known point elevation value and other unknown point elevation values in the original ground elevation data in the coastal terrain grid to be generated are obtained by utilizing the interpolation processing of the ground elevation data, thereby obtaining the coastal high-precision terrain grid.
The method for dynamically generating the fine coast terrain by the three-dimensional digital earth is characterized in that the method comprises the following specific steps of S2: s2.1: tracking an edge line of the satellite picture data by using an edge detection algorithm to extract a coastline, and connecting results by processing of a morphology (expansion and corrosion) algorithm to obtain a continuous coastline, wherein coastline result data A is obtained at the moment; s2.2: calibrating the coastline by using the transition characteristics of the coastlines of different coastline types in the satellite picture data on the brightness of the picture to obtain coastline result data B; s2.3: generating contour line data by utilizing the elevation data, and comparing the contour line data with a coastline elevation value to obtain coastline result data C; s2.4: using the coastline data in the existing coastline vector data as coastline result data D; s2.5: coastline result data A, B, C, D is processed to obtain final coastline result data E.
The method for dynamically generating the fine coastal terrain by the three-dimensional digital earth is characterized by comprising the following steps S2.5: and obtaining final coastline result data E after weighting addition processing is carried out on the coastline result data A, B, C, D, wherein the calculation formula is as follows: e = w A A+w B B+w C C+w D D。
In the invention, the coastline data is obtained by processing and extracting the satellite picture data, the ground elevation data and the coastline vector data, so that more accurate coastline data can be obtained.
The method for dynamically generating the fine coastal terrain by using the three-dimensional digital earth is characterized in that in the step S4, object information identification is carried out on satellite picture data, specifically, coastal ground coverage details and coastlines are identified on the satellite picture data based on an image identification technology.
The method for dynamically generating the fine coastal landforms by the three-dimensional digital earth is characterized in that in step S4, a coastal type mask map is generated by using the information of the area, wherein the determination of the areas of different types of coasts in the mask map also needs to be combined with elevation data, the height gradient is calculated by using contour lines calculated by the elevation data, the difference of the different types of coasts on the height gradient is used, and meanwhile, the mask map determined by the areas of the different types of coasts can be obtained by combining the information of the areas.
The method for dynamically generating the fine coast land forms by the three-dimensional digital earth is characterized in that mask map data in the method step S4 are mapped to obtain coast detail texture data, wherein the mapping relationship between the mask map and the texture data of different types of coast region ranges is that one mask map corresponds to the texture data of one type of coast region range.
In the invention, satellite picture data is used for image recognition, the land, seawater and intersection areas at two sides of a coastline are subjected to area marking and recognition, and high-precision coast detail texture data is obtained by combining elevation data.
The method for dynamically generating the fine coast terrain by the three-dimensional digital earth is characterized in that the object information identification specifically comprises the following steps: s4.1: graying the satellite picture data; s4.2: standardizing the color space of the input satellite picture data by adopting a Gamma correction method; s4.3: calculating the gradient of each pixel of the satellite picture data; s4.4: dividing the satellite picture data into a plurality of image units, and counting a gradient direction histogram of each image unit to form directional gradient histogram feature description data of each image unit; s4.5: forming a plurality of adjacent image units into an image block, and connecting the directional gradient histogram feature description data of all the image units in the image block in series to obtain the directional gradient histogram feature description data of the image block; s4.6: connecting the directional gradient histogram feature description data of all image blocks in the satellite picture data in series to obtain directional gradient histogram feature description data of the satellite picture data; s4.7: and performing content identification on the satellite picture data according to the directional gradient histogram feature description data of the satellite picture data by using the CNN graphic classification model.
The method for dynamically generating the fine coast terrain by the three-dimensional digital earth is characterized in that the data preprocessing in the method step S1 comprises the following steps: registering and fusing the satellite picture data to obtain color image data, and performing geometric correction and projection correction on the data by using a known control point; the elevation data is processed through interpolation, the problem of data loopholes possibly caused by objective factors is solved, and the elevation data is kept consistent with a satellite picture data coordinate system through coordinate conversion.
The invention utilizes the existing terrain generating technology and combines the innovative coastline high-precision terrain grid generating algorithm and the detail texture generating algorithm to generate the three-dimensional digital earth coastline terrain with the precision and the effect closer to the real environment. In the step S1, the data preprocessing is performed to perform the interpolation processing of the elevation data so as to smooth the data, and the main purpose is to ensure the integrity of the coastal grid and ensure that no data hole exists in the elevation data grid during the subsequent processing. The emphasis of the interpolation processing of the elevation data in the step S3 is to perform refinement processing on the coastal elevation grid, different from the interpolation processing of the data preprocessing in the step S1, the interpolation processing of the elevation data in the step S3 uses a specific interpolation processing process to obtain more accurate interpolation points, and the coastal terrain grid with high precision is ensured to be obtained.
Example 2
The invention provides a method for establishing and presenting effects including seawater and fine coasts in a three-dimensional digital planet, which comprises the steps of data acquisition, coastline extraction treatment, coastline type (four types of bedrock, sand, gravel and artificial) mask generation, ocean and land grid fine three-dimensional modeling and rendering.
Step 1. Data acquisition
The method comprises the steps of shooting a high-resolution and high-precision satellite picture through a high-resolution remote sensing satellite, obtaining ground elevation information through satellite-borne equipment, and processing all data in an existing coastline vector database to serve as input of subsequent steps.
The treatment specifically comprises the following steps:
the satellite picture data is registered and fused to obtain high-precision color image data, and the data is subjected to geometric correction and projection correction by utilizing a known control point.
The problem of data loopholes possibly caused by objective factors is solved after high-number data are subjected to interpolation processing, and the high-number data are kept consistent with a satellite picture coordinate system through coordinate conversion.
The existing coastline vector database data is rich and perfect in continuous coastline extraction, and a high-quality coastline vector database is formed through continuous updating.
And carrying out coordinate transformation on the three data, unifying coordinate systems and adopting a consistent space coordinate system.
Step 2, coastline extraction treatment
The main characteristic that the two sides of the coastline in the satellite picture are obvious in comparison is utilized, the coastline is extracted by tracking the edge line through an edge detection algorithm, the results are connected through processing of a morphology (expansion and corrosion) algorithm, the continuous coastline is obtained, and a coastline result A is obtained at the moment. And calibrating the coastline by using the transition characteristics of the coastlines of different coastline types in the satellite picture on the brightness of the picture to obtain a coastline result B. And generating contour line data by using the fine elevation data, and comparing the contour line data with the elevation value of the coastline to obtain a coastline result C. The existing coastline vector database data is used as result D. And performing weighted addition processing on the four coastline result data to obtain a final coastline result E. The calculation formula is as follows:
E＝w A A+w B B+w C C+w D D
wherein: w is a A Represents the weight, w, of the result A B Weight, w, of the result B C Represents the weight, w, of the result C D Represents the weight of the result D, and w A +w B +w C +w D ＝1。
Step 3, generating a coast high-precision terrain grid
Since the grid accuracy of the three-dimensional numbers cannot reach the accuracy required by the coastline, the coastline within the viewpoint range needs to be subjected to fine interpolation processing. The method comprises the following specific steps:
1. constructing a variation function c (h) according to the elevation point and distance data in the viewpoint range, wherein the variation function only depends on the elevation h separating the elevation and the distance data and does not depend on the specific geographical longitude and latitude positions (x, y), and obtaining:
2. calculating the half-variance r of the elevation points i and j of the coastal terrain by using a formula i,j And then constructing a semivariance matrix.
3. According to the weight coefficient of the estimation quantity, taking the elevation point v as an example, the estimation variance formula which is satisfied by the terrain elevation value variation quantity of the coastal area is as follows:
in the formula: c i,j Representing the covariance of the known coastline grid elevation points i and j.
4. The elevation variables of the land form of the coastal land form satisfy the intrinsic hypothesis, and a new variation function equation set of the land form elevation points of the coastal land form can be obtained by utilizing the relation r (h) = C (0) -C (h) of the covariance function and the variation function:
in the formula: r is i,j Representing the half-variance of the elevation points i and j.
5. Solving the weight coefficient obtained by the equation set and the value of the coast terrain elevation point to be generated, and simultaneously obtaining an interpolation error, wherein the interpolation error is expressed by a matrix form as follows:
Kγ＝D
in the formula:
k is a matrix formed by the semivariances of the elevation sample points, and D is a vector formed by the distance value between the point v to be estimated and the known elevation point and a constant 1.
The estimation of the unknown elevation height point v in the fine coastal grid is as follows:
the vector D of the original known elevation point and other unknown elevation points in the coastline grid can be obtained, the weight coefficient and the estimation variance of the elevation points are obtained according to a formula, and the estimation elevations and the estimation variances of the elevation points at all positions in the coastline fine grid can be obtained through iterative circulation.
Step 4, generating the coast high-precision detail texture
After the coastal terrain mesh refinement processing is carried out, object information identification is carried out on the satellite picture, namely whether the image contains certain objects or not is judged, and the positions and the sizes of the objects are required to be marked during detection. Namely, the type object range of the land part of the four types (bedrock, sand, gravel and artificial) coastline types is identified, and a corresponding type mask map is generated. According to the position of the coastline mark, the land, the sea water and the area of the intersection part at two sides of the coastline in the satellite picture are marked by areas, a coastline type mask map is generated by utilizing the information of the areas, and different texture effects can be rendered in real time during rendering.
For a basement rock type coast, the sea water area is darker in color, the land is lighter in color, the intersection part is narrow, and the generated mask area is a narrow strip-shaped area along the coastline. For the gravel type coast, the color of the seawater area is obviously contrasted with that of the land area, the intersection part is slightly wide, and the gravel area extends towards the land and the sea along the coastline to a certain extent respectively and is represented as a slightly wide belt-shaped area along the coastline. For sandy coasts, the land extends into the sea more than partially, as indicated by the larger light areas on the satellite picture, and the sandy areas extend along the shoreline to a greater extent into the land and sea, respectively, as indicated by the wider areas along the shoreline. Artificial type coasts are similar to gravel type coasts.
The mask area range determination of different types of coasts also needs to be combined with elevation data, height gradients are calculated by utilizing contour lines calculated by the elevation data, and final area ranges are calculated by utilizing the difference of four types of coasts of bedrock, sand, gravel and manpower on the height gradients. The gradient calculation formula is as follows:
wherein p and q represent gradient values in the x direction and the y direction, respectively.
The specific implementation steps are as follows:
1. satellite picture content identification
Based on an image recognition technology, covers such as vegetation and sand and stones and a coastline are recognized on a high-precision satellite picture, and a final result is stored in a form of a mask map. The detailed process is as follows:
1.1 graying the image.
1.2 the Gamma correction method is adopted to standardize the color space of the input image, so as to adjust the contrast of the image, reduce the influence caused by the local shadow and illumination change of the image and inhibit the interference of noise.
Gamma compression formula:
I(x,y)＝I(x,y) gamma
1.3 calculate the gradient of each pixel of the image, mainly for the purpose of capturing contour information, while further attenuating the interference of illumination.
The gradient of pixel point (x, y) in the image is:
G x (x,y)＝H(x+1,y)-H(x-1,y)
G y (x,y)＝H(x,y+1)-H(x,y-1)
in the formula G x (x,y),G y (x, y), H (x, y) respectively represents the horizontal gradient, the vertical gradient and the pixel value at the pixel point (x, y) in the input image, and the gradient magnitude value and the gradient direction at the pixel point (x, y) are respectively:
first using [ -1,0,1]The gradient operator performs convolution operation on the original image to obtain gradient component gradscalx in the x direction, and then [1,0-1] T And performing convolution operation on the original image by the gradient operator to obtain a gradient component gradsignal in the y direction, and then calculating the gradient size and the gradient direction of the pixel point by using the formula.
1.4, dividing the image into small cells, and counting the gradient histogram of each cell to form the descriptor of each cell.
1.5, forming a block by a plurality of cells, and connecting the feature descriptors of all the cells in the block in series to obtain the HOG feature descriptor of the block.
1.6, connecting all block HOG feature descriptors in the image in series to obtain an image HOG feature descriptor, which is the final feature vector for classification.
1.7 the final result is identified and classified using CNN techniques.
2. Mask generation
And obtaining mask maps determined by the areas of different types of coasts by using the results of object identification and classification and combining elevation data.
3. Superimposed texture
Different mask maps respectively correspond to different detail texture types, the superposition proportion of each detail texture can be controlled through components, and finally, the superposed coastal terrain detail texture is obtained.
Step 5, generating the earth coast landform
The earth's coastal terrain is obtained using a terrain generation technique using coastline data, coastal terrain grid data, and coastal detail texture data.
All of the features disclosed in this specification, or all of the steps in any method or process so disclosed, may be combined in any combination, except combinations of features and/or steps that are mutually exclusive. Any feature disclosed in this specification (including any accompanying claims, abstract) may be replaced by alternative features serving equivalent or similar purposes, unless expressly stated otherwise. That is, unless expressly stated otherwise, each feature is only an example of a generic series of equivalent or similar features.
The invention is not limited to the foregoing embodiments. The invention extends to any novel feature or any novel combination of features disclosed in this specification and any novel method or process steps or any novel combination of features disclosed.
Claims (8)
1. A method for three-dimensional digital earth dynamic generation of fine coastal terrain, characterized in that it comprises the following steps:
s1: acquiring and preprocessing data, wherein the acquiring comprises acquiring satellite picture data, ground elevation data and coastline vector data, and the preprocessing comprises preprocessing the satellite picture data, the ground elevation data and the coastline vector data;
s2: coastline data extraction processing, namely processing and extracting coastline data by using satellite picture data, ground elevation data and coastline vector data;
s3: generating coastal terrain grid data, namely utilizing the acquired ground elevation data to obtain elevation data of each point of coastal terrain through interpolation processing, so as to generate coastal terrain grid data;
s4: generating coast detail texture data, wherein the generation comprises the steps of carrying out object information identification on satellite picture data, namely carrying out area identification on land, seawater and intersection areas at two sides of a coast line in the satellite picture data, and generating a coast type mask map by utilizing the information of the areas, wherein the data of the mask map reflects the detail textures of the area ranges of different types of coasts, and the mask map data correspondingly obtains the texture data of the area ranges of the different types of coasts;
s5: the earth's coastal terrain is obtained using a terrain generation technique using coastline data, coastal terrain grid data, and coastal detail texture data.
2. The method for three-dimensional digital earth dynamic generation of fine coastal topography as claimed in claim 1, wherein said method step S2 is embodied by the steps of:
s2.1: tracking an edge line of the satellite picture data by using an edge detection algorithm to extract a coastline, and connecting results through processing of a morphological algorithm to obtain a continuous coastline, wherein coastline result data A are obtained at the moment;
s2.2: calibrating the coastline by using the transition characteristics of the coastlines of different coastline types in the satellite picture data on the brightness of the picture to obtain coastline result data B;
s2.3: generating contour line data by utilizing the elevation data, and comparing the contour line data with a coastline elevation value to obtain coastline result data C;
s2.4: using the coastline data in the existing coastline vector data as coastline result data D;
s2.5: the coastline result data A, B, C, D is processed to obtain final coastline result data E.
3. The method for the dynamic generation of fine coastal topography by three-dimensional digital earth according to claim 2, characterized in that said method step S2.5 is in particular: and obtaining final coastline result data E after weighting addition processing is carried out on the coastline result data A, B, C, D, wherein the calculation formula is as follows: e = w A A+w B B+w C C+w D D；
Wherein: w is a A Represents the weight, w, of the result A B Represents the weight, w, of the result B C Represents the weight, w, of the result C D Representing the weight of the result D.
4. The method for three-dimensional digital earth dynamic generation of fine coastal landform as claimed in claim 1, wherein in step S4, the satellite picture data is subject to object information recognition, specifically, recognition of coastal ground coverage details and coastline is performed on the satellite picture data based on image recognition technology.
5. The method as claimed in claim 1, wherein the information of the area is used to generate a coast-type mask map in step S4, wherein the determination of the area of different types of coasts in the mask map further requires the combination of elevation data, the height gradient is calculated by using contour lines calculated from the elevation data, the difference of the height gradient between different types of coasts is used, and the mask map determined by the area of different types of coasts is obtained by combining the information of the area.
6. The method as claimed in claim 1, wherein the mask map data in step S4 are mapped to obtain coastal detail texture data, wherein the mapping relationship between the mask map and the texture data of different types of coastal region areas is that one mask map corresponds to the texture data of one type of coastal region area.
7. The method for dynamically generating fine coastal topography by three-dimensional digital earth as claimed in claim 4, wherein said object information identification comprises the specific steps of:
s4.1: graying the satellite picture data; s4.2: standardizing the color space of the input satellite picture data by adopting a Gamma correction method; s4.3: calculating the gradient of each pixel of the satellite picture data; s4.4: dividing the satellite picture data into a plurality of image units, and counting a gradient direction histogram of each image unit to form directional gradient histogram feature description data of each image unit; s4.5: forming a plurality of adjacent image units into an image block, and connecting the directional gradient histogram feature description data of all the image units in the image block in series to obtain the directional gradient histogram feature description data of the image block; s4.6: connecting the directional gradient histogram feature description data of all image blocks in the satellite picture data in series to obtain directional gradient histogram feature description data of the satellite picture data; s4.7: and performing content identification on the satellite picture data according to the directional gradient histogram feature description data of the satellite picture data by using the CNN graph classification model.
8. The method for three-dimensional digital earth dynamic generation of fine coastal topography as claimed in claim 1, wherein said data preprocessing in method step S1 comprises: registering and fusing the satellite picture data to obtain color image data, and performing geometric correction and projection correction on the data by using a known control point; the elevation data is processed through interpolation, the problem of data loopholes possibly caused by objective factors is solved, and the elevation data is kept consistent with a satellite picture data coordinate system through coordinate conversion.
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