A hierarchical slicing method for hand-drawn maps of agricultural, cultural, and tourism technology services

Abstract

The present invention relates to the field of map slicing technology, and discloses a hand-drawn map hierarchical slicing method for agricultural, cultural, and tourism technology services, comprising: obtaining a hand-drawn map of a target area, determining a minimum bounding rectangle covering the hand-drawn map, and obtaining the geographic coordinates of the vertices of the minimum bounding rectangle; performing feature point detection on the hand-drawn map to obtain a feature point distribution map; determining a zoom level, slicing the hand-drawn map, and determining the row and column numbers of each tile; calculating the first coordinate of each tile, and calculating the second coordinate based on the geographic coordinates; judging whether the range covered by the first coordinate is within the range covered by the second coordinate, and if so, calculating the pixel coordinates of the tile corresponding to the first coordinate in the hand-drawn map, otherwise, setting the tile corresponding to the first coordinate to blank; querying the feature points covered by the pixel coordinates in the feature distribution map, resampling the tiles corresponding to the pixel coordinates based on the feature points, and obtaining new tiles corresponding to each tile; and storing all new tiles according to the zoom level and the row and column numbers corresponding to each tile. The present invention can effectively improve the quality of hand-drawn map slicing; and at the same time reduce data storage pressure, network transmission pressure, and front-end rendering pressure for tile service applications.

Description

Technical Field

[0001] The present invention relates to the field of map slicing technology, and in particular to a hierarchical slicing method for hand-drawn maps for agricultural, cultural, and tourism technology services. Background Art

[0002] Hand-drawn maps are maps created by hand. Modern hand-drawn maps are a fusion of 2D maps and 3D painting. They visualize iconic landmarks like roads and buildings, transforming ordinary city maps into more engaging images. They are often used in brochure printing, exhibition board production, and electronic map guides. Hand-drawn maps are created by map designers using professional drawing software. The original map data is high-precision vector graphics and is voluminous. Online map services, however, often require high data volumes, high concurrency, and rapid response times, placing stringent demands on the efficient transmission and loading of hand-drawn maps.

[0003] In actual engineering applications, different manufacturers have proposed targeted map tiering optimization and slicing algorithms based on their own application scenarios and data conditions. Currently, mainstream map tiering and slicing solutions primarily target surveying and mapping geographic information data, such as satellite remote sensing imagery. These data are formatted as raster images and contain real-world photographs. These slicing algorithms use a fixed resampling algorithm to gradually reduce image resolution, enabling map slicing to effectively preserve the image's spectral characteristics at large scales with low storage overhead. However, hand-drawn maps differ significantly from satellite imagery, and traditional algorithms have numerous drawbacks when applied to hand-drawn map data: 1) Unlike raster imagery, hand-drawn maps are naturally vector data, with sharp boundaries and vibrant colors. Traditional resampling methods can blur text and image lines, making the map less legible. 2) Satellite remote sensing imagery faithfully reflects the actual landscape, without prioritizing content. However, hand-drawn maps highly abstract the regional geographic pattern and major surface elements, resulting in varying densities of elements across different regions. Traditional resampling methods cannot effectively handle non-uniformly distributed information, resulting in a lack of prominence for the main features of the map. 3) Hand-drawn map production requires artistic processing of detailed details, such as terrain outlines, simplified representations of buildings, and symbolized vegetation. Furthermore, to enhance visual impact, hand-drawn maps may require specially designed color and lighting effects, which are typically not necessary for satellite imagery tile services. Summary of the Invention

[0004] The purpose of the present invention is to overcome at least one of the problems mentioned above and provide a method for hierarchical slicing of hand-drawn maps for agricultural, cultural, tourism and technological services. The present invention can avoid the homogenization and low-quality problems of generated tiles in the existing technology by taking different treatments for different landforms, and effectively improve the quality of hand-drawn map slicing; at the same time, it ensures that the tiles retain details while effectively controlling and reducing the tile file size, thereby reducing data storage pressure, network transmission pressure and front-end rendering pressure for tile service applications.

[0005] In order to achieve the above-mentioned object, the present invention provides a method for hierarchical slicing of hand-drawn maps for agricultural, cultural, and tourism technology services, the method comprising:

[0006] Obtaining a hand-drawn map of a target area, determining a minimum bounding rectangle covering the hand-drawn map, and obtaining geographic coordinates of vertices of the minimum bounding rectangle;

[0007] Performing feature point detection on the hand-drawn map to obtain a feature point distribution map;

[0008] Determining a zoom level, slicing the hand-drawn map based on the zoom level and the geographic coordinates of the vertices, and determining row and column numbers of each tile;

[0009] Calculating the coordinates of the vertices of each tile under the Web Mercator projection to obtain a first coordinate, and calculating the coordinates of the geographic coordinates under the Web Mercator projection to obtain a second coordinate;

[0010] Determine whether the range covered by the first coordinate is within the range covered by the second coordinate; if so, calculate the pixel coordinates of the tile corresponding to the first coordinate in the hand-drawn map; otherwise, set the tile corresponding to the first coordinate to blank;

[0011] Querying the feature points covered by the pixel coordinates in the feature point distribution map, and resampling the tiles corresponding to the pixel coordinates based on the feature points to obtain new tiles corresponding to each tile;

[0012] All new tiles are stored according to the zoom level and the row and column numbers corresponding to each tile to complete the slicing.

[0013] Furthermore, the process of obtaining a hand-drawn map of the target area, determining a minimum bounding rectangle covering the hand-drawn map, and obtaining the geographic coordinates of the vertices of the minimum bounding rectangle includes:

[0014] (1) Obtain a satellite image of the target area, mark the locations with the same locations in the hand-drawn map and the satellite image, and obtain a set of mappings of points with the same name;

[0015] (2) Select any point from the set of homonymous point mappings, determine the pixel coordinates of the point on the hand-drawn map and the geographic coordinates of the point on the satellite image, and determine the initial Helmert transformation relationship between the pixel coordinates and the geographic coordinates based on the pixel coordinates and the geographic coordinates of the point;

[0016] (3) Substitute the other points in the same-name point mapping set into the initial Helmert transformation relationship one by one, adjust the error and parameters, and obtain the final Helmert transformation relationship;

[0017] (4) Substitute the pixels of the minimum bounding rectangle into the final Helmert transformation relationship to obtain the geographic coordinates of all pixels.

[0018] (5) Read the geographic coordinates of the four vertices of the minimum circumscribed rectangle from the geographic coordinates of all the pixel points.

[0019] Furthermore, the locations at the same position in the hand-drawn map and the satellite image are marked, wherein the points at the same position are selected from road intersections and / or turning points of land features.

[0020] Furthermore, the hand-drawn map is subjected to feature point detection to obtain a feature point distribution map, wherein the feature points include at least one of edge points, line inflection points, feature point categories and scale-invariant feature points.

[0021] The edge points are used to identify sharp boundaries in the hand-drawn map;

[0022] The line inflection points are used to identify areas where the lines in the hand-drawn map are significantly bent;

[0023] The scale-invariant feature points are points in the hand-drawn map that do not change according to the transformation conditions, wherein the transformation conditions include illumination, color, noise and affine transformation;

[0024] The feature points are used to distinguish different features, including house walls, forest vegetation, and water bodies.

[0025] Furthermore, slicing the hand-drawn map based on the zoom level and the geographic coordinates of the vertices and determining the row and column numbers of each tile includes: calculating the coordinates of the geographic coordinates of the vertices under the Web Mercator projection; calculating the spatial resolution of each tile based on the zoom level; and calculating the row and column numbers of each tile based on the coordinates of the geographic coordinates of the vertices under the Web Mercator projection and the spatial resolution of each tile.

[0026] Furthermore, the pixel coordinates of the tile corresponding to the first coordinates in the hand-drawn map are calculated in the following manner:

[0027]

[0028]

[0029] in, is the number of horizontal pixels of the original hand-drawn map, is the number of pixels in the vertical direction of the hand-drawn map, ( , ) is the coordinate of the upper left corner of tile T under the web Mercator projection, ( , ) is the Mercator projection coordinate of the upper left vertex of the hand-drawn map, ( , ) are the Mercator projection coordinates of the lower right vertex of the hand-drawn map.

[0030] Furthermore, querying the feature point distribution map for the feature points covered by the pixel coordinates, and resampling the tiles corresponding to the pixel coordinates based on the feature points, specifically includes:

[0031] (1) Calculate the importance weight of the feature points contained in the tile corresponding to the pixel coordinates;

[0032] (2) If the importance weight is greater than 200, a high-fidelity resampling method is adopted for the tile corresponding to the pixel coordinate; otherwise, a low-fidelity resampling method is adopted for the tile corresponding to the pixel coordinate.

[0033] Furthermore, when calculating the importance weights of the feature points contained in the tile corresponding to the pixel coordinates, if the feature points are of multiple types, the importance weights are accumulated.

[0034] Furthermore, the high-fidelity resampling method is a trilinear interpolation resampling method, and after resampling, the tiles are sharpened using a Sobel operator.

[0035] Furthermore, the low-fidelity resampling method is a nearest neighbor resampling method.

[0036] Compared with the prior art, the present invention has the following beneficial effects:

[0037] The present invention first performs feature point detection on a hand-drawn map to obtain a feature point distribution map corresponding to the hand-drawn map, then divides the hand-drawn map according to the zoom level and the geographic coordinates of the vertices of the minimum circumscribed rectangle of the hand-drawn map to obtain a group of tiles and the row and column numbers corresponding to each tile, and then queries the feature points contained in each tile. Different resampling methods are adopted according to the feature points, thereby overcoming the problems of homogenized and low-quality tiles generated by traditional algorithms and significantly improving the quality of hand-drawn map slices; at the same time, the quality and size of the tiles are balanced to ensure that the tiles retain details while effectively controlling and reducing the tile file size, thereby reducing the data storage pressure, network transmission pressure, and front-end rendering pressure for tile service applications. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] Figure 1 This is a flowchart of a hand-drawn map hierarchical slicing method for agricultural, cultural, and tourism technology services according to Example 1 of the present invention;

[0039] Figure 2 This is a schematic diagram of a hand-drawn map of the target area of ​​Example 1 of the present invention;

[0040] Figure 3 is a calibration map of the target area in Example 1 of the present invention;

[0041] Figure 4 Schematic diagram of building and forest feature points in Example 1 of the present invention;

[0042] Figure 5 2 is a schematic diagram of a tile slice hierarchical division method according to embodiment 1 of the present invention;

[0043] Figure 6 This is a schematic diagram of slicing a hand-drawn map according to Example 1 of the present invention into tiles at levels 7-20;

[0044] Figure 7 4 is a sampling comparison diagram of the high-fidelity resampling method and the low-fidelity resampling method according to Example 1 of the present invention;

[0045] Figure 8 This is a framework diagram of a hand-drawn map hierarchical slicing method for agricultural, cultural, and tourism technology services in an embodiment of the present invention. DETAILED DESCRIPTION

[0046] The following embodiments of the present invention are described in further detail with reference to the accompanying drawings and examples. The following examples are used to illustrate the present invention but are not intended to limit the scope of the present invention.

[0047] In the description of the present invention, it should be noted that the terms "center," "longitudinal," "lateral," "upper," "lower," "front," "back," "left," "right," "vertical," "horizontal," "top," "bottom," "inner," and "outer" and the like, indicating orientations or positional relationships, are based on the orientations or positional relationships shown in the accompanying drawings and are intended solely to facilitate the description of the present invention and simplify the description. They are not intended to indicate or imply that the devices or components referred to must have a specific orientation, be constructed, or operate in a specific orientation. Therefore, they should not be construed as limiting the present invention. Furthermore, the terms "first," "second," and "third" are used for descriptive purposes only and should not be construed as indicating or implying relative importance.

[0048] In the description of the present invention, it should be noted that, unless otherwise expressly specified or limited, the terms "mounted," "connected," and "connected" should be understood in a broad sense. For example, they may refer to fixed, detachable, or integral connections; mechanical or electrical connections; direct or indirect connections through an intermediate medium; and internal communication between two components. Those skilled in the art will understand the specific meanings of the above terms in the present invention based on the specific circumstances.

[0049] Furthermore, in the description of the present invention, unless otherwise specified, “plurality” means two or more.

[0050] Example 1

[0051] like Figure 1 As shown, a hand-drawn map hierarchical slicing method for agricultural, cultural, and tourism technology services in a preferred embodiment of the present invention includes:

[0052] S1: Obtain a hand-drawn map of the target area, determine the minimum bounding rectangle covering the hand-drawn map, and obtain the geographic coordinates of the vertices of the minimum bounding rectangle;

[0053] In one possible embodiment, a hand-drawn map of the target area is Figure 2 As shown, it can be seen Figure 2 This is an agricultural area map, which mainly includes farmland, trees, crops, and houses. Specifically, S1 includes:

[0054] (1) Obtain a satellite image of the target area, mark the locations with the same location in the hand-drawn map and the satellite image, and obtain a set of mappings of points with the same name. In this embodiment, the locations with the same location are road intersections and / or corners of land features. The marking results are shown in Figure 3 ;

[0055] (2) Select any point from the set of homonymous point mappings, determine the pixel coordinates of the point in the hand-drawn map and the geographic coordinates of the point in the satellite image, and determine the initial Helmert transformation relationship between the pixel coordinates and the geographic coordinates based on the pixel coordinates and the geographic coordinates of the point. Specifically, let the pixel coordinates of the point be The geographic coordinates of the point with the same name on the satellite image are , based on these two coordinates, the initial Helmert transformation relationship can be determined as follows:

[0056] ;

[0057] (3) Substitute the other points in the same-name point mapping set into the initial Helmert transformation relationship one by one, adjust the error and parameters, and obtain the final Helmert transformation relationship. Specifically, the final Helmert transformation relationship is:

[0058] ;

[0059] (4) Substitute the pixels of the minimum bounding rectangle into the final Helmert transformation relationship to obtain the geographic coordinates of all pixels.

[0060] (5) Read the geographical coordinates of the four vertices of the minimum bounding rectangle from the geographical coordinates of all the pixel points. Specifically, read the geographical coordinates of the four vertices of the minimum bounding rectangle, which are recorded as , the geographic coordinates of the minimum enclosing rectangle are:

[0061]

[0062] S2: Detect feature points on the hand-drawn map to obtain a feature point distribution map;

[0063] In one feasible embodiment, feature point detection is performed on the hand-drawn map to obtain a feature point distribution map. Feature points include edge points, line inflection points, feature points of landform categories, and scale-invariant feature points. Different feature points can be used to extract features from different elements in the hand-drawn map, specifically:

[0064] Edge points are used to identify sharp boundaries in the hand-drawn map, such as hand-drawn lines, strokes, color block mutation areas, etc. This embodiment uses the Sobel edge detection algorithm to extract edge points;

[0065] Line inflection points are used to identify areas where lines in the hand-drawn map are significantly bent, such as road intersections, building eaves and corners, and text. This embodiment uses the Harris corner detection algorithm to extract feature points.

[0066] Scale-invariant feature points are points in the hand-drawn map that do not change according to the transformation conditions, including illumination, color, noise, and affine transformation. In this embodiment, the SIFT operator is used to detect scale-invariant feature points.

[0067] Feature points are used to distinguish different features, including house walls, forest vegetation and water bodies. This embodiment uses the K-means clustering algorithm to classify pixels. The schematic diagram of building and forest feature points is shown in the figure. Figure 4 shown.

[0068] S3: Determine the zoom level, slice the hand-drawn map based on the zoom level and the geographic coordinates of the vertex, and determine the row and column numbers of each tile;

[0069] In a feasible embodiment, the hand-drawn map is divided into levels according to the tile grid. The tile grid is defined as: in the EPSG:3857 plane coordinate system, the global scope is projected as a rectangle of equal width and height, with the 0th level tile representing the global scope, and each level tile is divided into four equal parts into the next level tile, with a maximum of 24 levels. For details, see Figure 5 The hand-drawn map of this embodiment is sliced ​​into 7-20 levels of tiles. Figure 6 The user end sends a data request to the backend based on the map view range and the current zoom level. Assuming that the longitude range of the frontend current view is [lon1, lon2], the latitude range is [lat1, lat2], and the zoom level is z, the corresponding tile request format is as follows:

[0070] [BaseURL] / getTile?minX=[lon1]&minY=[lat1]&maxX=[lon2]&maxY=[lat2]&level=[z]&fromat=PNG.

[0071] Suppose the geographic coordinates of a point are ,in represents longitude, Represents latitude. Convert it to Web Mercator projection coordinates (WebMercatorX, WebMercatorY) as follows:

[0072] (1) Longitude Convert to WebMercatorX:

[0073]

[0074] in is the radius of the Earth, ;

[0075] (2) Convert latitude to radians. The conversion formula is:

[0076]

[0077] (3) Convert to WebMercatorY:

[0078]

[0079] According to the above conversion method, the longitudes of the upper left and lower right of the map view range are 、 ,latitude 、 , we can know the coordinate range of the view range under the Web Mercator projection, which is recorded as [WebMercatorX1, WebMercatorX2], [WebMercatorY1, WebMercatorY2].

[0080] Assuming the current zoom level is level, according to the tile partitioning rules in S3, the spatial resolution of each tile at the current level is:

[0081]

[0082] Where C is the circumference of the earth, C= , R is the image resolution of each tile, the default is 512 pixels.

[0083] Based on the Mercator projection coordinates and tile spatial resolution, the row and column numbers of the tile to which the projection coordinates belong at the current zoom level (that is, the number of the tile covering the coordinate point) can be calculated:

[0084]

[0085] Substitute the coordinates of the current map view range under the Web Mercator projection into the formula to obtain the tile number list corresponding to the current view range, which is recorded as , .

[0086] S4: Calculate the coordinates of the vertex of each tile under the Web Mercator projection to obtain the first coordinate, calculate the coordinates of the geographic coordinates under the Web Mercator projection to obtain the second coordinate;

[0087] In a feasible embodiment, suppose a tile T is numbered , then the coordinates of the upper left corner of the tile in the Web Mercator projection are:

[0088]

[0089] Similarly, the coordinates of the lower right corner vertex of the tile under the Web Mercator projection are:

[0090]

[0091] The above coordinates are also the first coordinates. According to the above projection coordinate transformation method, the original hand-drawn image longitude and latitude coordinates can be converted into Mercator projection coordinates, which can be expressed as:

[0092]

[0093]

[0094] in, is the Mercator projection coordinate of the upper left vertex of the hand-drawn map, The Mercator projection coordinates for the lower right vertex of the hand-drawn map.

[0095] S5: Determine whether the range covered by the first coordinate is within the range covered by the second coordinate. If so, calculate the pixel coordinates of the tile corresponding to the first coordinate in the hand-drawn map. Otherwise, set the tile corresponding to the first coordinate to blank.

[0096] In a feasible embodiment, the coordinates of the tile vertices are compared with the coordinates of the vertices of the original image. If the tile coverage is outside the original image, the tile content is empty. Otherwise, the pixel coordinates of the tile vertex in the original hand-drawn image are calculated. Taking the upper left corner vertex as an example, the calculation method is as follows:

[0097]

[0098] in is the number of horizontal pixels of the original hand-drawn map, The number of vertical pixels of the hand-drawn map.

[0099] S6: Query the feature points covered by the pixel coordinates in the feature distribution map, resample the tiles corresponding to the pixel coordinates based on the feature points, and obtain new tiles corresponding to each tile;

[0100] In a feasible embodiment, a corresponding resampling strategy is selected based on the category and distribution of feature points. For areas with a small image area but dense distribution of feature points (such as buildings, roads, artificial surfaces, etc.), a high-fidelity resampling method (trilinear interpolation) is used, and sharpening is performed after interpolation to ensure that the image lines are clear and visible. For areas with a large image area but sparse distribution of feature points (such as natural surfaces, trees and vegetation, etc.), a low-fidelity fast resampling method (nearest neighbor sampling) is used to improve image processing speed. The specific resampling method is as follows:

[0101] (1) According to the feature point type defined in S2, define the importance weight of each type of feature point; the feature point importance weight is as follows:

[0102]

[0103] (2) For each tile, traverse all the feature points it contains, query the feature point type and accumulate the importance weight, and finally obtain the tile importance weight. If a feature point has multiple types, the importance weight is accumulated (for example, a point is both a feature point on a building and a line inflection point).

[0104] (3) Set the tile importance threshold. When the tile importance weight exceeds 200, it is considered an important tile and uses the trilinear interpolation resampling method and the Sobel operator for sharpening to retain the image details to the greatest extent. When the tile importance weight is less than 200, it is considered an ordinary tile and uses the nearest neighbor sampling method to increase the resampling speed. The comparison of the two resampling methods is as follows Figure 7 .

[0105] S7: Store all new tiles according to the zoom level and the row and column numbers corresponding to each tile to complete the slicing.

[0106] Example 2

[0107] This example verifies the superiority of the method proposed in Example 1. The performance of the method in Example 1 is compared with the traditional method. The comparison results are as follows:

[0108]

[0109] The superiority of the method of the present invention can be seen from the above table.

[0110] Example 3

[0111] An embodiment of the present invention also provides a computer-readable storage medium, on which is stored a computer program for a hand-drawn map hierarchical slicing method for agricultural, cultural, tourism and technology services. When the computer program for the hand-drawn map hierarchical slicing method for agricultural, cultural, tourism and technology services is processed, the steps of the hand-drawn map hierarchical slicing method for agricultural, cultural, tourism and technology services are implemented.

[0112] In summary, the embodiments of the present invention provide a hierarchical slicing method for hand-drawn maps for agricultural, cultural, and tourism technology services. This method first detects feature points on the hand-drawn map to obtain a corresponding feature point distribution map. The hand-drawn map is then sliced ​​based on the zoom level and the geographic coordinates of the vertices of the hand-drawn map's minimum bounding rectangle, obtaining a set of tiles and the row and column numbers corresponding to each tile. The method then queries the feature points contained within each tile and employs different resampling methods based on the feature points. This overcomes the homogenization and low-quality tile generation issues of traditional algorithms, significantly improving the quality of hand-drawn map slicing. It also balances tile quality and size, ensuring that tiles retain detail while effectively controlling and reducing tile file size, thus reducing data storage, network transmission, and front-end rendering pressures for tile service applications.

[0113] The above is only a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and substitutions can be made without departing from the technical principles of the present invention. These improvements and substitutions should also be regarded as the scope of protection of the present invention.

Claims

1. A hand-drawn map hierarchical slicing method for agricultural, cultural, tourism and technology services, characterized in that: The method comprises the following steps: Obtaining a hand-drawn map of a target area, determining a minimum bounding rectangle covering the hand-drawn map, and obtaining geographic coordinates of vertices of the minimum bounding rectangle; Performing feature point detection on the hand-drawn map to obtain a feature point distribution map; Determining a zoom level, slicing the hand-drawn map based on the zoom level and the geographic coordinates of the vertices, and determining row and column numbers of each tile; Calculating the coordinates of the vertices of each tile under the Web Mercator projection to obtain a first coordinate, and calculating the coordinates of the geographic coordinates under the Web Mercator projection to obtain a second coordinate; Determine whether the range covered by the first coordinate is within the range covered by the second coordinate; if so, calculate the pixel coordinates of the tile corresponding to the first coordinate in the hand-drawn map; otherwise, set the tile corresponding to the first coordinate to blank; Querying the feature points covered by the pixel coordinates in the feature point distribution map, and resampling the tiles corresponding to the pixel coordinates based on the feature points to obtain new tiles corresponding to each tile; All new tiles are stored according to the zoom level and the row and column numbers corresponding to each tile to complete the slicing.

2. A hand-drawn map hierarchical slicing method for agricultural, cultural, tourism and technology services according to claim 1, characterized in that: The process of obtaining a hand-drawn map of the target area, determining a minimum bounding rectangle covering the hand-drawn map, and obtaining the geographic coordinates of the vertices of the minimum bounding rectangle includes: (1) Obtain a satellite image of the target area, mark the locations with the same locations in the hand-drawn map and the satellite image, and obtain a set of mappings of points with the same name; (2) Select any point from the set of homonymous point mappings, determine the pixel coordinates of the point on the hand-drawn map and the geographic coordinates of the point on the satellite image, and determine the initial Helmert transformation relationship between the pixel coordinates and the geographic coordinates based on the pixel coordinates and the geographic coordinates of the point; (3) Substitute the other points in the same-name point mapping set into the initial Helmert transformation relationship one by one, adjust the error and parameters, and obtain the final Helmert transformation relationship; (4) Substitute the pixels of the minimum bounding rectangle into the final Helmert transformation relationship to obtain the geographic coordinates of all pixels. (5) Read the geographic coordinates of the four vertices of the minimum circumscribed rectangle from the geographic coordinates of all the pixel points.

3. The method for hierarchical slicing of hand-drawn maps for agricultural, cultural, tourism and technology services according to claim 2 is characterized in that: Mark the same locations in the hand-drawn map and the satellite image, wherein the same locations are selected from road intersections and / or turning points of land features.

4. A hand-drawn map hierarchical slicing method for agricultural, cultural and tourism technology services according to claim 1, wherein The characteristics are, The feature point detection is performed on the hand-drawn map to obtain a feature point distribution map, wherein the feature points include at least one of edge points, line inflection points, feature point categories and scale-invariant feature points. The edge points are used to identify sharp boundaries in the hand-drawn map; The line inflection points are used to identify areas where the lines in the hand-drawn map are significantly bent; The scale-invariant feature points are points in the hand-drawn map that do not change according to the transformation conditions, wherein the transformation conditions include illumination, color, noise and affine transformation; The feature points are used to distinguish different features, including house walls, forest vegetation, and water bodies.

5. A hand-drawn map hierarchical slicing method for agricultural, cultural and tourism technology services according to claim 1, wherein The characteristics are, The slicing of the hand-drawn map based on the zoom level and the geographic coordinates of the vertices, and determining the row and column numbers of each tile, includes: calculating the coordinates of the geographic coordinates of the vertices under the Web Mercator projection; calculating the spatial resolution of each tile based on the zoom level; and calculating the row and column numbers of each tile based on the coordinates of the geographic coordinates of the vertices under the Web Mercator projection and the spatial resolution of each tile.

6. A hand-drawn map hierarchical slicing method for agricultural, cultural and tourism technology services according to claim 1, wherein The characteristic is that the pixel coordinates of the tile corresponding to the first coordinate are calculated in the hand-drawn map in the following manner: in, is the number of horizontal pixels of the original hand-drawn map, is the number of pixels in the vertical direction of the hand-drawn map, ( , ) is the coordinate of the upper left corner of tile T under the web Mercator projection, ( , ) is the Mercator projection coordinate of the upper left vertex of the hand-drawn map, ( , ) are the Mercator projection coordinates of the lower right vertex of the hand-drawn map.

7. A hand-drawn map hierarchical slicing method for agricultural, cultural and tourism technology services according to claim 1, wherein The characteristics are, Querying the feature point covered by the pixel coordinates in the feature point distribution map, and resampling the tiles corresponding to the pixel coordinates based on the feature points, specifically including: (1) Calculate the importance weight of the feature points contained in the tile corresponding to the pixel coordinates; (2) If the importance weight is greater than 200, a high-fidelity resampling method is adopted for the tile corresponding to the pixel coordinate; otherwise, a low-fidelity resampling method is adopted for the tile corresponding to the pixel coordinate.

8. A hand-drawn map hierarchical slicing method for agricultural, cultural, and tourism technology services according to claim 7, wherein The characteristic is that, when calculating the importance weights of the feature points contained in the tile corresponding to the pixel coordinates, if the feature points have multiple types, the importance weights are accumulated.

9. A hand-drawn map hierarchical slicing method for agricultural, cultural and tourism technology services according to claim 7, wherein The method is characterized in that the high-fidelity resampling method is a trilinear interpolation resampling method, and after resampling, the Sobel operator is used to sharpen the tiles.

10. A hand-drawn map hierarchical slicing method for agricultural, cultural, tourism and technology services according to claim 7, It is characterized by: The low-fidelity resampling method is a nearest neighbor resampling method.

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