A heterogeneous layer contrast rendering system and method based on WebGIS

Abstract

This invention discloses a heterogeneous layer comparison rendering system and method based on WebGIS, belonging to the field of GIS data rendering technology. The invention collects, uniformly registers, and parses metadata from the original parameters of multi-source heterogeneous layers to obtain standardized layer information and construct a unified layer abstract model. It then performs heterogeneous adaptation and coordinate transformation on the unified model data to obtain unified spatial reference data. Based on the unified spatial reference data, it divides the viewport space and determines the viewport range and clipping region. It calculates the visible tile index based on the viewport range and clipping region, and performs scheduling, sorting, caching, and concurrency control on the visible tile set to obtain available tile data. Based on the available tile data, it performs GPU clipping rendering to obtain a clipped rendered image, implements multi-viewport synchronization constraints on the clipped rendered image, and outputs the final comparison rendering result.

Description

Technical Field

[0001] This invention relates to the field of GIS data rendering technology, specifically a heterogeneous layer comparison rendering system and method based on WebGIS. Background Technology

[0002] With the rapid development of Geographic Information System (GIS) technology, WebGIS platforms are widely used in various geographic data display scenarios, and the demand for comparative rendering of multi-source heterogeneous layers is becoming increasingly urgent. Multi-source heterogeneous layers typically come from different data sources, and their coordinate reference systems, resolutions, tile sizes, and other parameters vary significantly.

[0003] Existing technologies lack standardized processing methods for parameters of multi-source heterogeneous layers. They fail to normalize and uniformly register layer parameters, nor do they combine spatial boundary coordinates to calculate spatial features and construct a unified layer abstract model. This results in heterogeneous layers of different formats failing to achieve unified adaptation and hindering effective comparison and display. Furthermore, in the spatial adaptation process of heterogeneous layers, existing technologies lack a scientific spatial matching and resolution evaluation mechanism. They cannot accurately calculate spatial matching based on the coordinate deviation of corresponding points, spatial overlap rate, and layer diagonal length. They also fail to incorporate resolution consistency for data filtering, leading to biases in the selected spatial reference data. This, in turn, affects the accuracy of heterogeneous layer comparison rendering and fails to meet the requirements for high-precision comparison. In the tile scheduling and rendering stage, existing technologies do not filter and schedule tiles according to visibility weight, nor do they use dynamic pruning thresholds for GPU rendering. Furthermore, they lack an effective multi-viewport synchronization constraint mechanism, making it impossible to achieve accurate alignment of secondary viewport parameters based on the primary viewport. This results in low tile loading efficiency, redundant invalid fragments during rendering, and misalignment during multi-viewport comparison, affecting the smoothness and consistency of comparison rendering. Consequently, it is difficult to meet the high-efficiency and accurate requirements of WebGIS platforms for heterogeneous layer comparison rendering. Summary of the Invention

[0004] The purpose of this invention is to provide a heterogeneous layer comparison and rendering system and method based on WebGIS to solve the problems raised in the prior art.

[0005] To achieve the above objectives, the present invention provides the following technical solution: In a first aspect, the present invention provides a method for heterogeneous layer comparison and rendering based on WebGIS, comprising: Collect original parameters from multi-source heterogeneous layers, perform unified registration and metadata parsing to obtain standardized layer information; construct a unified layer abstract model based on the standardized layer information to obtain unified model data; Heterogeneous adaptation and coordinate unification transformation are performed on the unified model data to obtain unified spatial reference data; The viewport space is divided based on unified spatial reference data to determine the viewport range and clipping area. By combining the obtained viewport range and clipping region, the visible tile index is calculated to obtain the visible tile set; based on the visible tile set, scheduling sorting, cache determination and concurrency control are performed to obtain the available tile data; GPU clipping rendering is performed based on available tile data to obtain a clipped rendering image; multi-viewport synchronization constraints are applied to the clipped rendering image, and the final comparison rendering result is output.

[0006] In conjunction with the first aspect, in the first implementation of the first aspect of this application, the step of collecting the original parameters of multi-source heterogeneous layers, performing unified registration and metadata parsing, and obtaining standardized layer information includes: Collect raw parameters of multi-source heterogeneous layers, including layer space boundary coordinates, native resolution, tile size, and coordinate reference system; normalize and parse the collected raw parameters of multi-source heterogeneous layers, unifying the coordinate formats, resolution units, tile size formats, and coordinate reference system identifiers from different sources into the same standard format; uniformly register the raw parameters of multi-source heterogeneous layers that have completed normalization and parse, assign a unique identifier to each layer, and associate and store the unique identifier with the corresponding normalized raw parameters of multi-source heterogeneous layers. Multiply the horizontal and vertical differences in the four boundary coordinates of the layer space to obtain the original area of ​​the layer space; calculate the diagonal length of the layer space by using Euclidean distance from the four boundary coordinates of the layer space. The layer data, which includes the original area of ​​the layer space and the length of the layer space diagonal, will be normalized, uniformly registered, and used as standardized layer information.

[0007] In conjunction with the first aspect, in the second implementation of the first aspect of this application, the step of constructing a unified layer abstract model based on standardized layer information to obtain unified model data includes: Obtain standardized layer information, extract the spatial boundary coordinates, native resolution, tile size, and coordinate reference system of each layer; based on the spatial boundary coordinates of all layers, take the minimum longitude, minimum latitude, maximum longitude, and maximum latitude to construct a unified minimum bounding rectangle; By using a unified minimum bounding rectangle, unified native resolution, unified tile size, and unified coordinate reference system, the data of each layer is structured and organized to obtain unified model data.

[0008] In conjunction with the first aspect, in the third implementation of the first aspect of this application, the step of performing heterogeneous adaptation and coordinate unification transformation on the unified model data to obtain unified spatial reference data includes: Acquire unified model data and collect the coordinates of corresponding points between layers; transform the spatial coordinates of each layer in the unified model data to the same target coordinate reference system; calculate the coordinate deviation of a single set of corresponding points using Euclidean distance based on the coordinate difference before and after the transformation. Sum the coordinate deviations of all single-group corresponding points and divide by the total number of corresponding points to obtain the average coordinate deviation; calculate the spatial intersection range through the spatial extent of the two layers, take the area of ​​the spatial intersection range as the spatial intersection area, divide the spatial intersection area by the original spatial area of ​​the smaller of the two layers to obtain the spatial overlap rate; divide the average coordinate deviation by the length of the diagonal of the layer space to obtain the coordinate normalization deviation; subtract the coordinate normalization deviation from 1 to obtain the coordinate normalization overlap degree; multiply the spatial overlap rate and the coordinate normalization overlap degree to obtain the spatial matching degree. Divide the smaller native resolution value in the two layers by the larger native resolution value to obtain resolution consistency; use the layer data that has undergone unified coordinate transformation and whose spatial matching degree and resolution consistency meet the preset spatial threshold and preset resolution threshold respectively as unified spatial reference data.

[0009] In conjunction with the first aspect, in the fourth implementation of the first aspect of this application, the step of dividing the viewport space based on unified spatial reference data and determining the viewport range and clipping region includes: Acquire unified spatial reference data and collect the x-coordinates of the comparison mode and clipping line; divide the display space into a main viewport and a secondary viewport according to the comparison mode, and obtain the spatial range of the main viewport and the spatial range of the secondary viewport respectively; take the intersection of the spatial range of the main viewport and the spatial range of the secondary viewport to obtain the spatial intersection range, and take the area of ​​the spatial intersection range as the spatial intersection range area. Divide the area of ​​the spatial intersection range by the area of ​​the main viewport spatial range to obtain the viewport coverage ratio; calculate the coordinates of the center point of the main viewport based on the main viewport spatial range; and calculate the maximum effective distance of the viewport based on the diagonal length of the main viewport spatial range. Using the horizontal coordinate of the clipping line as the boundary, the spatial intersection area is divided into the clipping retention area and the clipping rejection area, thus obtaining the viewport range and the clipping area.

[0010] In conjunction with the first aspect, in the fifth implementation of the first aspect of this application, the calculation of the visible tile index based on the combined viewport range and clipping region to obtain the visible tile set includes: Obtain the viewport range and clipping area, and collect the tile size; divide the difference between the geographic x-coordinate within the viewport and the minimum x-coordinate of the main viewport by the tile size and round down to obtain the tile column number; divide the difference between the maximum y-coordinate of the main viewport and the geographic y-coordinate within the viewport by the tile size and round down to obtain the tile row number. The intersection of the tile's spatial extent and the clipping retention area is calculated, and the area of ​​this intersection is taken as the intersection area of ​​the tile and the clipping retention area. The intersection area of ​​the tile and the clipping retention area is divided by the complete area of ​​the tile to obtain the tile's visible proportion. The coordinates of the tile's center point are calculated based on the tile's spatial extent. Based on the coordinates of the main viewport center point and the tile's center point, the distance from the tile's center to the viewport center is calculated using Euclidean distance. The distance from the tile's center to the viewport center is divided by the maximum effective distance of the viewport to obtain the distance normalization deviation. The distance normalization deviation is subtracted from 1 to obtain the viewport center coincidence. The tile's visible proportion is multiplied by the viewport center coincidence to obtain the tile's visible weight. The tiles are filtered according to their visibility weight, and the sub-viewport tile indices are aligned with the main viewport tile index to obtain the set of visible tiles.

[0011] In conjunction with the first aspect, in the sixth implementation of the first aspect of this application, the step of performing scheduling sorting, cache determination, and concurrency control based on the visual tile set to obtain available tile data includes: Obtain the set of visible tiles, collect the system's maximum concurrency, the number of currently requested tiles, and the set of cached tiles; divide the intersection of the set of visible tiles and the set of cached tiles by the total number of visible tiles to obtain the cache hit rate; divide the number of currently requested tiles by the system's maximum concurrency to obtain the concurrency saturation. The visible tile set is sorted from high to low according to the tile visibility weight, the tile request priority is adjusted according to the cache hit rate, the number of simultaneous requests is controlled according to the concurrency saturation, the tile scheduling and loading are performed, and the loaded tiles are used as available tile data.

[0012] In conjunction with the first aspect, in the seventh implementation of the first aspect of this application, the step of performing GPU cropping rendering based on available tile data to obtain a cropped rendered image includes: Obtain available tile data and clipping line x-coordinates, and collect the total GPU video memory; load the available tile data into the GPU, construct texture objects and vertex buffer objects respectively, and calculate the video memory usage of texture objects and vertex buffer objects; divide the sum of the video memory usage of texture objects and vertex buffer objects by the total GPU video memory to obtain the video memory usage rate; Subtract the visible tile ratio from 1 to get the invisible tile ratio. Multiply the invisible tile ratio by the tile size to get the invisible tile size. Add the invisible tile size to the clipping line x-coordinate to get the dynamic clipping threshold. Compare the fragment pixel x-coordinate with the dynamic clipping threshold. If the fragment pixel x-coordinate is greater than the dynamic clipping threshold, discard the fragment. Rendering and layer overlay are performed on the retained fragments to obtain the cropped rendered image.

[0013] In conjunction with the first aspect, in the eighth implementation of the first aspect of this application, the step of applying multi-viewport synchronization constraints to the cropped rendered image and outputting the final comparison rendering result includes: Obtain the cropped rendered image and extract the center point coordinates, native resolution, and cropping line coordinates of the main viewport and the secondary viewport. Using the center point coordinates, native resolution, and clipping line coordinates of the main viewport as a reference, the parameters corresponding to the secondary viewport are synchronized and aligned, and the aligned clipped rendering image is output as the final comparison rendering result.

[0014] Secondly, the present invention provides a heterogeneous layer comparison and rendering system based on WebGIS, comprising: Layer standardization and modeling module: includes a layer parameter acquisition and parsing unit, a layer spatial feature calculation unit, and a unified model construction unit; among them, the layer parameter acquisition and parsing unit collects and normalizes the original parameters of multi-source heterogeneous layers, and completes the unified registration of layers; the layer spatial feature calculation unit calculates the original spatial area and spatial diagonal length of the layer; the unified model construction unit constructs a unified minimum bounding rectangle based on the standardized information and generates unified model data. The unified spatial reference adaptation module includes a coordinate transformation unit, a spatial matching evaluation unit, a resolution consistency evaluation unit, and a unified reference filtering unit. The coordinate transformation unit transforms the spatial coordinates of each layer to the same target coordinate reference system. The spatial matching evaluation unit calculates the average coordinate deviation, spatial overlap rate, and spatial matching degree. The resolution consistency evaluation unit calculates the ratio of the original resolutions of two layers to obtain resolution consistency. The unified reference filtering unit filters layer data that meet threshold requirements to generate unified spatial reference data. The viewport segmentation and tile calculation module includes a viewport space segmentation unit, a visible tile index calculation unit, a tile visibility assessment unit, and a tile weight filtering unit. Specifically, the viewport space segmentation unit segments the primary and secondary viewports and calculates relevant parameters to determine the areas to be clipped and discarded. The visible tile index calculation unit calculates the tile row and column numbers based on the viewport range and tile size. The tile visibility assessment unit calculates the tile visibility ratio and the distance deviation from the tile center to the viewport center. The tile weight filtering unit calculates the tile visibility weights, filters and aligns the tiles to obtain a set of visible tiles. Tile scheduling and GPU rendering module: includes tile scheduling control unit, GPU memory statistics unit and dynamic clipping rendering unit; among them, tile scheduling control unit calculates cache hit rate and concurrency saturation, and schedules and loads available tile data; GPU memory statistics unit counts GPU memory usage and calculates memory usage rate; dynamic clipping rendering unit calculates dynamic clipping threshold and removes invalid fragments to complete GPU clipping rendering; Multi-viewport synchronous output module: includes multi-viewport synchronous constraint unit, used to align primary and secondary viewport parameters and output the final heterogeneous layer comparison rendering result.

[0015] Compared with the prior art, the beneficial effects of the present invention are: 1. This invention performs normalization analysis and unified registration of multi-source heterogeneous layer parameters, calculates spatial features by combining spatial boundary coordinates, and constructs a unified layer abstract model.

[0016] 2. This invention calculates spatial matching degree based on the coordinate deviation of corresponding points, spatial overlap rate and layer diagonal length, and obtains unified spatial reference data by combining resolution consistency screening.

[0017] 3. This invention filters tiles according to their visibility weight and performs scheduled loading, uses dynamic pruning thresholds for GPU rendering, and achieves multi-viewport parameter synchronization and alignment based on the main viewport. Attached Figure Description

[0018] Figure 1 This is a schematic diagram illustrating the steps of a heterogeneous layer comparison and rendering method based on WebGIS according to the present invention; Figure 2 This is a flowchart of a heterogeneous layer comparison and rendering method based on WebGIS according to the present invention. Figure 3 This is a system structure diagram of a heterogeneous layer comparison and rendering system based on WebGIS according to the present invention. Detailed Implementation

[0019] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0020] Example: Figures 1-3 As shown, the present invention provides a technical solution. like Figure 1 A schematic diagram illustrating the steps of a heterogeneous layer comparison and rendering method based on WebGIS is shown. This invention provides a heterogeneous layer comparison and rendering method based on WebGIS, comprising: Step S100: Collect the original parameters of the multi-source heterogeneous layers, perform unified registration and metadata parsing to obtain standardized layer information; construct a unified layer abstract model based on the standardized layer information to obtain unified model data; Specifically, the process involves collecting raw parameters from multi-source heterogeneous layers, including the layer space coordinates, native resolution, tile size, and coordinate reference system; normalizing and parsing the collected raw parameters from the multi-source heterogeneous layers, unifying the coordinate formats, resolution units, tile size formats, and coordinate reference system identifiers from different sources into the same standard format; and uniformly registering the normalized raw parameters from the multi-source heterogeneous layers, assigning a unique identifier to each layer, and associating and storing the unique identifier with the corresponding normalized raw parameters from the multi-source heterogeneous layers. Multiply the horizontal and vertical differences in the four boundary coordinates of the layer space to obtain the original area S of the layer space. The formula is: ; Where, x max and x min These represent the maximum and minimum longitude values ​​of the four cardinal coordinates in the layer space, y max and y min These represent the maximum and minimum latitude values ​​of the four cardinal coordinates of the layer space, respectively. The diagonal length L of the layer space is obtained by calculating the four boundary coordinates of the layer space using Euclidean distance. The formula is: ; The layer data, which includes the original area of ​​the layer space and the length of the layer space diagonal, will be normalized, uniformly registered, and used as standardized layer information.

[0021] Obtain standardized layer information, extract the spatial boundary coordinates, native resolution, tile size, and coordinate reference system of each layer; based on the spatial boundary coordinates of all layers, take the minimum longitude, minimum latitude, maximum longitude, and maximum latitude to construct a unified minimum bounding rectangle; By using a unified minimum bounding rectangle, unified native resolution, unified tile size, and unified coordinate reference system, the data of each layer is structured and organized to obtain unified model data.

[0022] Step S200: Perform heterogeneous adaptation and coordinate unification transformation on the unified model data to obtain unified spatial reference data; Specifically, the process involves acquiring unified model data and collecting the coordinates of corresponding points across layers; transforming the spatial coordinates of each layer in the unified model data to the same target coordinate reference system; and calculating the coordinate deviation d of a single set of corresponding points using Euclidean distance based on the coordinate difference before and after the transformation. i The formula is: ; Where, Δx i and Δy i This represents the difference between the x-axis and y-axis coordinates of points before and after the transformation. Sum the coordinate deviations of all individual points of the same type, and divide by the total number of points of the same type to obtain the average coordinate deviation. The formula is: ; Where n is the total number of points with the same name; The spatial intersection range is calculated by examining the spatial extent of the two layers. The area of ​​this spatial intersection range is taken as the spatial intersection area. The spatial intersection area is then divided by the smaller original spatial area of ​​the two layers to obtain the spatial overlap rate R. s The formula is: ; in, S1 represents the area of ​​the intersection of the two layer spaces, and S2 represents the original space areas of the two layers, respectively. Divide the average coordinate deviation by the diagonal length of the layer space to obtain the coordinate normalization deviation; subtract the coordinate normalization deviation from 1 to obtain the coordinate normalization overlap; multiply the spatial overlap rate by the coordinate normalization overlap to obtain the spatial matching degree M. s The formula is: ; in, R is the average coordinate deviation, L is the length of the diagonal in the layer space, and R is the average coordinate deviation. s Spatial overlap rate; Divide the smaller native resolution value in both layers by the larger native resolution value to obtain the resolution consistency R. r The formula is: ; Where r1 and r2 are the native resolutions of the two layers, respectively; Layer data that has undergone unified coordinate transformation and whose spatial matching degree and resolution consistency meet the preset spatial threshold and preset resolution threshold respectively are used as unified spatial reference data.

[0023] Step S300: Divide the viewport space based on unified spatial reference data, and determine the viewport range and clipping area; Specifically, obtain unified spatial reference data, collect the contrast mode and clipping line x-coordinate; divide the display space into main viewport and secondary viewport according to the contrast mode, and obtain the main viewport spatial range and secondary viewport spatial range respectively; take the intersection of the main viewport spatial range and secondary viewport spatial range to obtain the spatial intersection range, and take the area of ​​the spatial intersection range as the spatial intersection range area. Divide the area of ​​the spatial intersection range by the area of ​​the main viewport spatial range to obtain the viewport coverage ratio; calculate the coordinates of the center point of the main viewport based on the main viewport spatial range; and calculate the maximum effective distance of the viewport based on the diagonal length of the main viewport spatial range. Using the horizontal coordinate of the clipping line as the boundary, the spatial intersection area is divided into the clipping retention area and the clipping rejection area, thus obtaining the viewport range and the clipping area.

[0024] Step S400: Combine the obtained viewport range and clipping region to calculate the visible tile index and obtain the visible tile set; perform scheduling sorting, cache determination and concurrency control based on the visible tile set to obtain available tile data; Specifically, obtain the viewport range and clipping area, and collect the tile size; divide the difference between the geographic horizontal coordinate within the viewport and the minimum horizontal coordinate of the main viewport by the tile size and round down to obtain the tile column number; divide the difference between the maximum vertical coordinate of the main viewport and the geographic vertical coordinate within the viewport by the tile size and round down to obtain the tile row number. The intersection of the tile's spatial extent and the cut-out retention area is calculated, and the area of ​​this intersection is taken as the intersection area of ​​the tile and the cut-out retention area. The intersection area of ​​the tile and the cut-out retention area is divided by the complete area of ​​the tile to obtain the visible proportion R of the tile. v The coordinates of the tile center point are calculated based on the tile's spatial range. Then, the distance d from the tile center to the viewport center is calculated using Euclidean distance, based on the coordinates of the main viewport center point and the tile center point. t Divide the distance from the tile center to the viewport center by the maximum effective viewport distance to obtain the distance normalization bias; subtract the distance normalization bias from 1 to obtain the viewport center coincidence; multiply the tile visibility ratio by the viewport center coincidence to obtain the tile visibility weight W. t The formula is: ; Among them, R v d represents the visible proportion of the tiles. t D is the distance from the center of the tile to the center of the viewport. max This represents the maximum effective viewing distance. The tiles are filtered according to their visibility weight, and the sub-viewport tile indices are aligned with the main viewport tile index to obtain the set of visible tiles.

[0025] Obtain the set of visible tiles, collect the system's maximum concurrency, the number of currently requested tiles, and the set of cached tiles; divide the intersection of the set of visible tiles and the set of cached tiles by the total number of visible tiles to obtain the cache hit rate; divide the number of currently requested tiles by the system's maximum concurrency to obtain the concurrency saturation. The visible tile set is sorted from high to low according to the tile visibility weight, the tile request priority is adjusted according to the cache hit rate, the number of simultaneous requests is controlled according to the concurrency saturation, the tile scheduling and loading are performed, and the loaded tiles are used as available tile data.

[0026] Step S500: Perform GPU clipping rendering based on available tile data to obtain a clipped rendering image; apply multi-viewport synchronization constraints to the clipped rendering image and output the final comparison rendering result.

[0027] Specifically, the process involves acquiring available tile data and clipping line x-coordinates, and collecting the total GPU memory usage. The available tile data is then loaded onto the GPU, and texture objects and vertex buffer objects are constructed separately. The memory usage of the texture objects and vertex buffer objects is then calculated. Finally, the sum of the memory usage of the texture objects and vertex buffer objects is divided by the total GPU memory to obtain the memory usage rate U. gpu The formula is: ; Among them, V tex V represents the video memory usage of texture objects. vbo V represents the video memory usage of the vertex buffer object. total Total GPU video memory; Subtracting the visible tile ratio from 1 yields the invisible tile ratio. Multiplying the invisible tile ratio by the tile size gives the invisible tile size. Adding the invisible tile size to the x-coordinate of the trimming line gives the dynamic trimming threshold T. c The formula is: ; Where, x c R is the x-coordinate of the clipping line. v s represents the visible proportion of the tiles. t For tile dimensions; In the vertex shader, the geographic coordinates of the vertex are passed to the fragment shader. After interpolation, the geographic x-coordinates of each fragment are obtained. The geographic x-coordinates are compared with the dynamic clipping threshold. When the geographic x-coordinates are greater than the dynamic clipping threshold, the fragments are discarded. Rendering and layer overlay are performed on the retained fragments to obtain the cropped rendered image.

[0028] Obtain the cropped rendered image and extract the center point coordinates, native resolution, and cropping line coordinates of the main viewport and the secondary viewport. Using the center point coordinates, native resolution, and clipping line coordinates of the main viewport as a reference, the parameters corresponding to the secondary viewport are synchronized and aligned, and the aligned clipped rendering image is output as the final comparison rendering result.

[0029] like Figure 2 The flowchart of a heterogeneous layer comparison and rendering method based on WebGIS is shown. This invention provides a heterogeneous layer comparison and rendering method based on WebGIS, comprising: After the process starts, it first enters the layer standardization and model construction stage. The original parameters of the multi-source heterogeneous layers are collected, normalized, parsed, and uniformly registered. The original spatial area and diagonal length of the layers are calculated to form standardized layer information. Then, a unified minimum bounding rectangle is constructed based on the standardized layer information to structure the layer data and obtain unified model data. Next, it enters the spatial reference unified adaptation stage. The unified model data is used to collect corresponding points and perform unified coordinate transformation. The coordinate deviation, spatial overlap rate, spatial matching degree, and resolution consistency are calculated in sequence, and it is determined whether the preset threshold requirements are met. If not, the coordinate transformation and matching calculation are re-performed. If the threshold is met, unified spatial reference data is generated. Next, the viewport segmentation and tile processing stage begins. Based on unified spatial reference data, the main viewport and secondary viewport are segmented, and the clipping retention and culling areas are determined. Tile filtering and index alignment are completed by calculating tile visibility ratio, viewport center overlap, and tile visibility weight, resulting in a set of visible tiles. Then, the tile scheduling and GPU rendering stage begins. Based on the set of visible tiles, cache hit rate and concurrent saturation are calculated. Tile scheduling and loading are performed according to tile visibility weight to obtain available tile data. GPU memory usage is then statistically analyzed based on the available tile data, a dynamic clipping threshold is calculated, and invalid fragments are removed. Valid fragments are rendered and layered to obtain a clipped rendered image. Finally, the multi-viewport synchronous output stage begins. Relevant parameters of the main and secondary viewports are extracted, and the secondary viewport parameters are synchronously aligned using the main viewport as a reference. The final heterogeneous layer comparison rendering result is output, completing the process.

[0030] like Figure 3 The system architecture diagram of a heterogeneous layer comparison and rendering system based on WebGIS is shown. This invention provides a heterogeneous layer comparison and rendering system based on WebGIS, comprising: Layer standardization and modeling module: includes a layer parameter acquisition and parsing unit, a layer spatial feature calculation unit, and a unified model construction unit; among them, the layer parameter acquisition and parsing unit collects and normalizes the original parameters of multi-source heterogeneous layers, and completes the unified registration of layers; the layer spatial feature calculation unit calculates the original spatial area and spatial diagonal length of the layer; the unified model construction unit constructs a unified minimum bounding rectangle based on the standardized information and generates unified model data. The unified spatial reference adaptation module includes a coordinate transformation unit, a spatial matching evaluation unit, a resolution consistency evaluation unit, and a unified reference filtering unit. The coordinate transformation unit transforms the spatial coordinates of each layer to the same target coordinate reference system. The spatial matching evaluation unit calculates the average coordinate deviation, spatial overlap rate, and spatial matching degree. The resolution consistency evaluation unit calculates the ratio of the original resolutions of two layers to obtain resolution consistency. The unified reference filtering unit filters layer data that meet threshold requirements to generate unified spatial reference data. The viewport segmentation and tile calculation module includes a viewport space segmentation unit, a visible tile index calculation unit, a tile visibility assessment unit, and a tile weight filtering unit. Specifically, the viewport space segmentation unit segments the primary and secondary viewports and calculates relevant parameters to determine the areas to be clipped and discarded. The visible tile index calculation unit calculates the tile row and column numbers based on the viewport range and tile size. The tile visibility assessment unit calculates the tile visibility ratio and the distance deviation from the tile center to the viewport center. The tile weight filtering unit calculates the tile visibility weights, filters and aligns the tiles to obtain a set of visible tiles. Tile scheduling and GPU rendering module: includes tile scheduling control unit, GPU memory statistics unit and dynamic clipping rendering unit; among them, tile scheduling control unit calculates cache hit rate and concurrency saturation, and schedules and loads available tile data; GPU memory statistics unit counts GPU memory usage and calculates memory usage rate; dynamic clipping rendering unit calculates dynamic clipping threshold and removes invalid fragments to complete GPU clipping rendering; Multi-viewport synchronous output module: includes multi-viewport synchronous constraint unit, used to align primary and secondary viewport parameters and output the final heterogeneous layer comparison rendering result.

[0031] It will be apparent to those skilled in the art that the present invention is not limited to the details of the exemplary embodiments described above, and that the invention can be implemented in other specific forms without departing from its spirit or essential characteristics. Therefore, the embodiments should be considered in all respects as exemplary and non-limiting, and the scope of the invention is defined by the appended claims rather than the foregoing description. Thus, all variations falling within the meaning and scope of equivalents of the claims are intended to be included within the present invention. No reference numerals in the claims should be construed as limiting the scope of the claims.

Claims

1. A WebGIS-based heterogeneous layer contrast rendering method, characterized in that, include: Collect original parameters of multi-source heterogeneous layers, perform unified registration and metadata parsing to obtain standardized layer information; A unified layer abstract model is constructed based on standardized layer information to obtain unified model data; Heterogeneous adaptation and coordinate unification transformation are performed on the unified model data to obtain unified spatial reference data; The viewport space is divided based on unified spatial reference data to determine the viewport range and clipping area. By combining the obtained viewport range and clipping area, the visible tile index is calculated to obtain the set of visible tiles; Based on the set of visible tiles, scheduling, caching, and concurrency control are performed to obtain available tile data; GPU cropping rendering is performed based on available tile data to obtain a cropped rendering image; Apply multi-viewport synchronization constraints to the cropped and rendered image, and output the final comparison rendering result.

2. The heterogeneous layer comparison and rendering method based on WebGIS according to claim 1, characterized in that, The process involves collecting original parameters from multi-source heterogeneous layers, performing unified registration and metadata parsing, to obtain standardized layer information, including: Collect raw parameters of multi-source heterogeneous layers, including layer space boundary coordinates, native resolution, tile size, and coordinate reference system; normalize and parse the collected raw parameters of multi-source heterogeneous layers, unifying the coordinate format, resolution unit, tile size format, and coordinate reference system identifier of different sources into the same standard format; uniformly register the raw parameters of multi-source heterogeneous layers that have completed normalization and parse, assign a unique identifier to each layer, and associate and store the unique identifier with the corresponding normalized raw parameters of multi-source heterogeneous layers; Multiply the horizontal and vertical differences in the four boundary coordinates of the layer space to obtain the original area of ​​the layer space; calculate the diagonal length of the layer space by using Euclidean distance from the four boundary coordinates of the layer space. The layer data, which includes the original area of ​​the layer space and the length of the layer space diagonal, will be normalized, uniformly registered, and used as standardized layer information.

3. The heterogeneous layer comparison and rendering method based on WebGIS according to claim 1, characterized in that, The process of constructing a unified layer abstract model based on standardized layer information to obtain unified model data includes: Obtain standardized layer information, extract the spatial boundary coordinates, native resolution, tile size, and coordinate reference system of each layer; based on the spatial boundary coordinates of all layers, take the minimum longitude, minimum latitude, maximum longitude, and maximum latitude to construct a unified minimum bounding rectangle; By using a unified minimum bounding rectangle, unified native resolution, unified tile size, and unified coordinate reference system, the data of each layer is structured and organized to obtain unified model data.

4. The heterogeneous layer comparison and rendering method based on WebGIS according to claim 1, characterized in that, The process of performing heterogeneous adaptation and coordinate unification transformation on unified model data to obtain unified spatial reference data includes: Acquire unified model data and collect the coordinates of corresponding points between layers; transform the spatial coordinates of each layer in the unified model data to the same target coordinate reference system; calculate the coordinate deviation of a single set of corresponding points using Euclidean distance based on the coordinate difference before and after the transformation. Sum the coordinate deviations of all single-group corresponding points and divide by the total number of corresponding points to obtain the average coordinate deviation; calculate the spatial intersection range through the spatial extent of the two layers, take the area of ​​the spatial intersection range as the spatial intersection area, divide the spatial intersection area by the original spatial area of ​​the smaller of the two layers to obtain the spatial overlap rate; divide the average coordinate deviation by the length of the diagonal of the layer space to obtain the coordinate normalization deviation; subtract the coordinate normalization deviation from 1 to obtain the coordinate normalization overlap degree; multiply the spatial overlap rate and the coordinate normalization overlap degree to obtain the spatial matching degree. Divide the smaller native resolution value in the two layers by the larger native resolution value to obtain resolution consistency; use the layer data that has undergone unified coordinate transformation and whose spatial matching degree and resolution consistency meet the preset spatial threshold and preset resolution threshold respectively as unified spatial reference data.

5. The heterogeneous layer comparison and rendering method based on WebGIS according to claim 1, characterized in that, The process of dividing the viewport space based on unified spatial reference data and determining the viewport range and clipping region includes: Acquire unified spatial reference data and collect the x-coordinates of the comparison mode and clipping line; divide the display space into a main viewport and a secondary viewport according to the comparison mode, and obtain the spatial range of the main viewport and the spatial range of the secondary viewport respectively; take the intersection of the spatial range of the main viewport and the spatial range of the secondary viewport to obtain the spatial intersection range, and take the area of ​​the spatial intersection range as the spatial intersection range area. Divide the area of ​​the spatial intersection range by the area of ​​the main viewport spatial range to obtain the viewport coverage ratio; calculate the coordinates of the center point of the main viewport based on the main viewport spatial range; and calculate the maximum effective distance of the viewport based on the diagonal length of the main viewport spatial range. Using the horizontal coordinate of the clipping line as the boundary, the spatial intersection area is divided into the clipping retention area and the clipping rejection area, thus obtaining the viewport range and the clipping area.

6. The heterogeneous layer comparison and rendering method based on WebGIS according to claim 1, characterized in that, The combined viewport extent and clipping region are used to calculate the visible tile index, resulting in a set of visible tiles, including: Obtain the viewport range and clipping area, and collect the tile size; divide the difference between the geographic x-coordinate within the viewport and the minimum x-coordinate of the main viewport by the tile size and round down to obtain the tile column number; divide the difference between the maximum y-coordinate of the main viewport and the geographic y-coordinate within the viewport by the tile size and round down to obtain the tile row number. The intersection of the tile's spatial extent and the clipping retention area is calculated, and the area of ​​this intersection is taken as the intersection area of ​​the tile and the clipping retention area. The intersection area of ​​the tile and the clipping retention area is divided by the complete area of ​​the tile to obtain the tile's visible proportion. The coordinates of the tile's center point are calculated based on the tile's spatial extent. Based on the coordinates of the main viewport center point and the tile's center point, the distance from the tile's center to the viewport center is calculated using Euclidean distance. The distance from the tile's center to the viewport center is divided by the maximum effective distance of the viewport to obtain the distance normalization deviation. The distance normalization deviation is subtracted from 1 to obtain the viewport center coincidence. The tile's visible proportion is multiplied by the viewport center coincidence to obtain the tile's visible weight. The tiles are filtered according to their visibility weight, and the sub-viewport tile indices are aligned with the main viewport tile index to obtain the set of visible tiles.

7. The heterogeneous layer comparison and rendering method based on WebGIS according to claim 1, characterized in that, The process of performing scheduling, sorting, caching, and concurrency control based on the visual tile set to obtain available tile data includes: Obtain the set of visible tiles, collect the system's maximum concurrency, the number of currently requested tiles, and the set of cached tiles; divide the intersection of the set of visible tiles and the set of cached tiles by the total number of visible tiles to obtain the cache hit rate; divide the number of currently requested tiles by the system's maximum concurrency to obtain the concurrency saturation. The visible tile set is sorted from high to low according to the tile visibility weight, the tile request priority is adjusted according to the cache hit rate, the number of simultaneous requests is controlled according to the concurrency saturation, the tile scheduling and loading are performed, and the loaded tiles are used as available tile data.

8. The heterogeneous layer comparison and rendering method based on WebGIS according to claim 1, characterized in that, The process of performing GPU cropping rendering based on available tile data to obtain a cropped rendered image includes: Obtain available tile data and clipping line x-coordinates, and collect the total GPU video memory; load the available tile data into the GPU, construct texture objects and vertex buffer objects respectively, and calculate the video memory usage of texture objects and vertex buffer objects; divide the sum of the video memory usage of texture objects and vertex buffer objects by the total GPU video memory to obtain the video memory usage rate; Subtract the visible tile ratio from 1 to get the invisible tile ratio. Multiply the invisible tile ratio by the tile size to get the invisible tile size. Add the invisible tile size to the clipping line x-coordinate to get the dynamic clipping threshold. Compare the fragment pixel x-coordinate with the dynamic clipping threshold. If the fragment pixel x-coordinate is greater than the dynamic clipping threshold, discard the fragment. Rendering and layer overlay are performed on the retained fragments to obtain the cropped rendered image.

9. A heterogeneous layer comparison and rendering method based on WebGIS according to claim 1, characterized in that, The process of applying multi-viewport synchronization constraints to the cropped and rendered image and outputting the final comparison rendering result includes: Obtain the cropped rendered image and extract the center point coordinates, native resolution, and cropping line coordinates of the main viewport and the secondary viewport. Using the center point coordinates, native resolution, and clipping line coordinates of the main viewport as a reference, the parameters corresponding to the secondary viewport are synchronized and aligned, and the aligned clipped rendering image is output as the final comparison rendering result.

10. A heterogeneous layer comparison and rendering system based on WebGIS, using the heterogeneous layer comparison and rendering method based on WebGIS according to any one of claims 1-9, characterized in that, include: Layer standardization and modeling module: includes a layer parameter acquisition and parsing unit, a layer spatial feature calculation unit, and a unified model construction unit; among them, the layer parameter acquisition and parsing unit collects and normalizes the original parameters of multi-source heterogeneous layers, and completes the unified registration of layers; the layer spatial feature calculation unit calculates the original spatial area and spatial diagonal length of the layer; the unified model construction unit constructs a unified minimum bounding rectangle based on the standardized information and generates unified model data. The unified spatial reference adaptation module includes a coordinate transformation unit, a spatial matching evaluation unit, a resolution consistency evaluation unit, and a unified reference filtering unit. The coordinate transformation unit transforms the spatial coordinates of each layer to the same target coordinate reference system. The spatial matching evaluation unit calculates the average coordinate deviation, spatial overlap rate, and spatial matching degree. The resolution consistency evaluation unit calculates the ratio of the original resolutions of two layers to obtain resolution consistency. The unified reference filtering unit filters layer data that meet threshold requirements to generate unified spatial reference data. The viewport segmentation and tile calculation module includes a viewport space segmentation unit, a visible tile index calculation unit, a tile visibility assessment unit, and a tile weight filtering unit. Specifically, the viewport space segmentation unit segments the primary and secondary viewports and calculates relevant parameters to determine the areas to be clipped and discarded. The visible tile index calculation unit calculates the tile row and column numbers based on the viewport range and tile size. The tile visibility assessment unit calculates the tile visibility ratio and the distance deviation from the tile center to the viewport center. The tile weight filtering unit calculates the tile visibility weights, filters and aligns the tiles to obtain a set of visible tiles. Tile scheduling and GPU rendering module: includes tile scheduling control unit, GPU memory statistics unit and dynamic clipping rendering unit; among them, tile scheduling control unit calculates cache hit rate and concurrency saturation, and schedules and loads available tile data; GPU memory statistics unit counts GPU memory usage and calculates memory usage rate; dynamic clipping rendering unit calculates dynamic clipping threshold and removes invalid fragments to complete GPU clipping rendering; Multi-viewport synchronous output module: includes multi-viewport synchronous constraint unit, used to align primary and secondary viewport parameters and output the final heterogeneous layer comparison rendering result.

Images