CN105718481A - Massive topographic data organization and release method - Google Patents
Massive topographic data organization and release method Download PDFInfo
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Abstract
The invention discloses a massive topographic data organization and release method, and relates to the technical field of processing and application of geographic information. The massive topographic data organization and release method is characterized by comprising the following steps of reading topographic data, unifying topographic data coordinates, selecting a topographic data range, establishing index information, resampling the topographic data, fusing the topographic data and releasing the topographic data, which form a complete process. The massive topographic data organization and release method has the superiority that the technical problems that organization structure construction of the massive topographic data can be convenient for updating, rapid retrieval and acquisition of the data and the like can be simultaneously solved. Meanwhile, images can be compressed, edge-matched and fused, a storage space is reduced, access efficiency is improved, and the massive topographic data organization and release method is convenient for updating and maintenance; the massive topographic data can be subjected to multi-platform data release and sharing; and safe, reliable, accurate and efficient data support is provided for deep application in different industries.
Description
Technical field
The present invention relates to geographic information processing and applied technical field, particularly to a kind of management based on geographic information data, image compression, edge fit and fusion, reduce memory space, improve access efficiency, it is easy to updating maintenance, a kind of massive terrain data tissue dissemination method of the efficient tissue of massive terrain data, management and issue.
Background technology
Geographical information technology (GeographicInformationSystem or Geo-Informationsystem, GIS) is also called " Geo-informatic Tupu technology " or " environment and resources information technology " sometimes.It is a kind of specific highly important Spatial Information Technology.It is under computer hardware and software technical support, the relevant geographic distribution data in earth top layer (including atmosphere) space all or in part be acquired, store, manage, computing, the technical method analyzing, be shown and described.And this technology can be applied in the Simulation of Building Roam in real estate domain, such as real estate virtual reality three-dimensional displays such as real estate are roamed, and community browses, and building is roamed, three-dimensional show house；Can being applied in urban planning, urban planning in planning field, city image is shown, digitalized city, urban digitalization project, Garden Planning, venue construction etc.；May be used for the publicity of the scenic spot of gardens scene in field, gardens, tourist attractions are developed, and topography and geomorphology shows, national park; Forest Park, Natural and Cultural Resource is protected, historical and cultural heritage record, garden landscape planning; venue is afforested, subdistrict greening, building view exhibition etc.；Can being industrial products in industrial design field, electronic product be shown；Game movie can realize animated show, game movie Film Animation etc.；In virtual reality studio, virtual reality stage, virtual commercial space, plays displaying and publicity, the effects such as auxiliary is sold, auxiliary office in the application of all entries such as reality environment performance.
From above practical application example it can be seen that, although the application of the every profession and trades such as data visualization varies, but solution, the core technology of its bottom is identical, finally data and information graphically will be changed, interactively present to user, therefore all use the tissue of mass data, management and release quickly.
Increasingly mature along with remote sensing satellite and digital photogrammetry technology, satellite remote sensing information is increasingly becoming a kind of significant data source in GIS, and remote sensing image data is as the important foundation data in country's digital city, " NSDI " is built role and also day by day strengthens.Under the burgeoning premise of image data application demand, day by day huge data are carried out effective management and use and becomes digital photogrammetry and field of remote sensing image processing problem in the urgent need to address.Particularly the massive image data of data organizational management, issue and management distribution is thus providing image information service to have more realistic meaning for various application such as territory planning, Mapping remote sensing technology, traffic, hydraulic and electric engineering, agricultural environmental protection.
Terrain data has the feature of magnanimity, and a general provincial high-resolution terrain data amount is up to 500-1000GB.Along with computer hardware capacity of memory device increases, the storage of mass data is achieved, but for massive terrains numerical control management and issue Chinese scholars also in further investigation the stage, OGC has formulated image information service interface, and has a website demonstrated；The magnanimity information issue capability of Microsoft's magnanimity operating capability and IIS in order to show its database management language SQLServer has issued the image database MierosoftTerraServer based on Internet.And it is domestic more single in data organization and administration and data publication.The dimensional topography tissue storage method of current main flow is to utilize quad-tree structure that DEM and DOM data are carried out piecemeal to index management terrain data.But in terrain blocks process, it is primarily present problems with:
1), multilamellar DOM resampling and visual fusion problem:
A, generally only one layer of DOM image of consideration and global context image, and DOM image by superposing (color of image form RGBA, 4 bytes of each pixel) after increasing transparent channel with global context image, the method adds internal memory undoubtedly.
B, do not account for other images, for instance history image, infrared image ..., autgmentability application is limited.
2), DEM resampling and adjacent plot crack problem:
When adjacent plot is in different resolution level, Border sample point is misaligned, causes T crack occur.Conventional adjacent plot avoiding cracks method has point, method of adding some points.Going a method is skip some points on the border of the piecemeal of high-resolution not draw, and so can keep the seriality of adjacent piecemeal.The method of adding some points is exactly increase some summits on the piecemeal border of low resolution newly to keep continuous print purposes to reach two piecemeal summits.No matter it is increase newly to put or remove to put to be required for whole landform being traveled through and relevant piecemeal being re-started triangle subdivision, loses the independence of piecemeal, add the pressure of buffer memory, increase the complex nature of the problem, and then have influence on efficiency.
3), block data quickly puts problem in storage:
Terrain data classification piecemeal generates magnanimity three dimensional topographic data block record, and how quickly warehouse-in is the key issue issuing terrain data.Except the concurrently access of conventional data base itself, record batch insertion, multi-thread data release processing etc., emphasis need to reduce the read-write number of times of ground blocks of data.
4), self-defined clipping region and increment RELEASE PROBLEM:
Self-defined clipping region sometimes only need to process region (rectangle or polygon) interested and carries out being published to data base when referring to issue terrain data, and how solving the Multi-Resolution blocked processing of local irregularities's image is comparatively laborious thing.
And domestic related data delivery system is at the massive terrain data processing multi-scale, multiresolution, the request of data aspect efficiency comparison of multi-user is low, the aspect Shortcomings such as the motility of system, versatility and portability, the primary demand of user can not be met, say nothing of the increment to data and issue meeting of demand.
At present, can solve to build based on massive terrain data organizational structure to facilitate data to update and the technical problem such as quick-searching and acquisition but without a perfect method simultaneously；Simultaneously, it is possible to image compression, edge fit and fusion, reduce memory space, improve access efficiency, it is simple to updating maintenance, enable massive terrain data to carry out multi-platform data publication and to share；Good application for different industries provides safe and reliable, data supporting accurately and efficiently.
Summary of the invention
In order to solve the technical barrier existed in prior art, it is possible to solve to build based on massive terrain data organizational structure to facilitate data to update and the technical problem such as quick-searching and acquisition simultaneously；Simultaneously, it is possible to image compression, edge fit and fusion, reduce memory space, improve access efficiency, it is simple to updating maintenance, enable massive terrain data to carry out multi-platform data publication and to share；Good application for different industries provides safe and reliable, data supporting accurately and efficiently.
The embodiment of the present invention provides a kind of massive terrain data tissue dissemination method, comprises the steps:
Read terrain data: orthography and digital elevation image data are read out, a map sheet image, many map sheets image can be read in image reads simultaneously, the resolution of every width image can be different, and the scope of every width image is also repeatable, forms one layer, multilamellar terrain data；
Graphic data coordinate uniformly: judge that whether image geographic coordinate system is consistent, be then for further processing if the judgment is Yes, if NO, then its data coordinates be transformed under unified geographic coordinate system；
Choose terrain data scope: judge whether that the scope to image carries out entirety and chooses or carry out custom field and choose, choose just be for further processing as carried out entirety, choose as carried out custom field, carry out polygon scope judgement the image data intercepting within the scope of this and be for further processing:
Index information: first carry out physical block according to the entire scope of massive terrain data, terrestrial range after piecemeal is carried out classification piecemeal again and builds overall data structure, then the geographical coordinate position of base area graphic data determines its coordinated indexing position in overall data structure, namely indexes information；
Resampling terrain data: every piece of terrain data is carried out resampling process by the index information according to setting up；
Merge terrain data: if being provided with background layer in the multilamellar terrain data issued, then the terrain data after being processed by piecemeal is embedded in the block data that background layer scope is corresponding；The index information of piecemeal belonging to image data wherein can be determined by geographical coordinate position；
Issue terrain data: the terrain data after classification piecemeal and index information are stored in various types of data source.
A kind of massive terrain data tissue dissemination method, described the method also includes increment issuing steps, wherein:
Increment is issued: again issue new data in existing terrain source data in this data source, for the extension of local updating and the terrain data scope of terrain data；
Wherein, what described increment was issued concretely comprises the following steps:
1), obtain increment and issue the terrain information of data；
2), each plot is traveled through according to terrain information；
3) all terrain datas comprising this plot, are read in relief area；
4), incrementally blocks of data is stored in data source.
A kind of massive terrain data tissue dissemination method, the step of described reading terrain data is concretely: orthography and digital elevation image data are read out, in image reads, can read a picture layer image also can read the map overlay image a kind of, multiple in the image of history image, infrared image difference figure layer, and can to arrange one layer of terrain data therein be Background From Layer.
A kind of massive terrain data tissue dissemination method, described in choose concretely comprising the following steps of terrain data scope:
1), polygon scope is created: input polygon point set creates custom field；
2) scope of every piece of terrain data, is merged: the polygon scope that every piece of landform is arranged merged, generate a polygon range information；
3) polygon range information, is utilized to create buffer memory landform: by the terrain data storage in polygon to landform buffer memory.
A kind of massive terrain data tissue dissemination method, described resampling terrain data can be divided into DOM and DEM carries out image resampling process respectively:
Wherein:
Can process according to lowest resolution when DOM being carried out classification piecemeal resampling process, the data message after being sampled；
When considering the DEM value of adjacent plot at the same level sampled point when DEM carrying out classification piecemeal resampling and processing, first entirety carries out DEM resampling again to each sampled point assignment after piecemeal；When considering adjacent but different stage plot DEM sampling, formula (2* (2 can be passed through for crack treatment problem when eliminating gound-mappingn+ 1)-1) * (2* (2n+ 1)-1) carry out Multi-Resolution blocked processing, border takes the DEM elevation point value that the meansigma methods of consecutive points obtains the boundary point in sub-level plot.
A kind of massive terrain data tissue dissemination method, DOM can be carried out image resampling process by described resampling terrain data:
Wherein: DOM carries out image resampling process can be further:
1), according to landform classification block index information, each plot in the landform classification piecemeal of each image is traveled through；
2) each the image data in each plot, is read, it is thus achieved that the data message after resampling.
A kind of massive terrain data tissue dissemination method, DEM can be carried out image resampling process by described resampling terrain data:
Wherein: DEM carries out image resampling process can be further:
1), every grade of rectangular area is traveled through according to landform index data；
2) every grade of rectangle data, is read in memory array；
3), the square boundary coincidence point place point data corresponding with lower level of present level is replaced, it is ensured that endpoint data is consistent；
4), each plot in traversal current rectangle region；
5), according to plot index number, data are deposited to core buffer, until each ground blocks of data is all deposited to core buffer in every grade of region.
A kind of massive terrain data tissue dissemination method, DOM and DEM can be carried out image resampling process by described resampling terrain data: the further step of its process is:
1), by carrying out inlaying fusion with corresponding overall DOM blocks of data after DOM resampling；
2), DOM data acquisition carry out compression of images by self-defining compression factor, be effectively reduced data volume；
3), add multilamellar DOM data time, set up figure layer index information, plot store each figure layer DOM data respectively, the DOM image of equivalent layer when rendering, can be called according to actual needs；
4), add multi-DEMs data, carry out classification piecemeal also according to its coordinate range, it is determined that its index position in entire scope classification block data structure, namely set up classification block index information；
5) whole data structure index informations and whole terrain block data to data sources, are stored.
A kind of massive terrain data tissue dissemination method, concretely comprising the following steps of described fusion terrain data:
1), the data that each terrain data classification piecemeal resampling processes being deposited to core buffer, wherein each terrain data includes one layer of background terrain and multilamellar local landform；
2) internal storage data in each plot, after traversal classification piecemeal, and the graphic data partly in each plot is embedded in the internal storage data of corresponding background plot.
A kind of massive terrain data tissue dissemination method, described resampling terrain data DOM and DEM can be carried out image resampling process: the further step of its process is:
Multi-Resolution blocked processing can be carried out according to lowest resolution when DOM carries out Multi-Resolution blocked processing, obtain required index information.
A kind of massive terrain data tissue dissemination method, described issue terrain data the terrain data after classification piecemeal and index information are stored in various types of data source: its data source can for various relevant databases, file type data form.
As can be seen here: the method in the embodiment of the present invention can solve to build based on massive terrain data organizational structure to facilitate data to update and the technical problem such as quick-searching and acquisition simultaneously.Simultaneously, it is possible to image compression, edge fit and fusion, reduce memory space, improve access efficiency, it is simple to updating maintenance；Massive terrain data is enable to carry out multi-platform data publication and to share；Good application for different industries provides safe and reliable, data supporting accurately and efficiently.
Accompanying drawing explanation
The schematic flow sheet of the massive terrain data tissue dissemination method that Fig. 1 provides for embodiments of the invention 1；
The schematic flow sheet of the massive terrain data tissue dissemination method that Fig. 2 provides for embodiments of the invention 2；
The schematic flow sheet choosing terrain data scope step that Fig. 3 provides for embodiments of the invention；
One of schematic flow sheet of resampling terrain data that Fig. 4 provides for embodiments of the invention；
One of schematic flow sheet of resampling terrain data that Fig. 5 provides for embodiments of the invention；
One of schematic flow sheet of resampling terrain data that Fig. 6 provides for embodiments of the invention；
The schematic flow sheet merging terrain data that Fig. 7 provides for embodiments of the invention；
The schematic flow sheet that Fig. 8 issues for the increment that embodiments of the invention provide.
Detailed description of the invention
In order to make those skilled in the art be more fully understood that the present invention program, describing the present invention in detail below in conjunction with accompanying drawing and specific embodiment, illustrative examples and explanation in this present invention are used for explaining the present invention, but not as a limitation of the invention.
Embodiment 1:
The schematic flow sheet of a kind of massive terrain data tissue dissemination method that Fig. 1 provides for the present embodiment.As it is shown in figure 1, a kind of massive terrain data tissue dissemination method, comprise the steps:
A kind of massive terrain data tissue dissemination method, it is characterised in that comprise the steps:
Read terrain data: orthography and digital elevation image data are read out, a map sheet image, many map sheets image can be read in image reads simultaneously, the resolution of every width image can be different, and the scope of every width image is also repeatable, forms one layer, multilamellar terrain data；
Graphic data coordinate uniformly: judge that whether image geographic coordinate system is consistent, be then for further processing if the judgment is Yes, if NO, then its data coordinates be transformed under unified geographic coordinate system；
Choose terrain data scope: judge whether that the scope to image carries out entirety and chooses or carry out custom field and choose, choose just be for further processing as carried out entirety, choose as carried out custom field, carry out polygon scope judgement the image data intercepting within the scope of this and be for further processing:
Index information: first carry out physical block according to the entire scope of massive terrain data, terrestrial range after piecemeal is carried out classification piecemeal again and builds overall data structure, then the geographical coordinate position of base area graphic data determines its coordinated indexing position in overall data structure, namely indexes information；
Resampling terrain data: every piece of terrain data is carried out resampling process by the index information according to setting up；
Merge terrain data: if being provided with background layer in the multilamellar terrain data issued, then the terrain data after being processed by piecemeal is embedded in the block data that background layer scope is corresponding；The index information of piecemeal belonging to image data wherein can be determined by geographical coordinate position；
Issue terrain data: the terrain data after classification piecemeal and index information are stored in various types of data source.
The step of described reading terrain data is concretely in a particular embodiment: orthography and digital elevation image data are read out, in image reads, can read a picture layer image also can read the map overlay image a kind of, multiple in the image of history image, infrared image difference figure layer, and can to arrange one layer of terrain data therein be Background From Layer.
A kind of massive terrain data tissue dissemination method as shown in Figure 3, chooses concretely comprising the following steps of terrain data scope:
1), polygon scope is created: input polygon point set creates custom field；
2) scope of every piece of terrain data, is merged: the polygon scope that every piece of landform is arranged merged, generate a polygon range information；
3) polygon range information, is utilized to create buffer memory landform: by the terrain data storage in polygon to landform buffer memory.
Described resampling terrain data can be divided into DOM and DEM carries out image resampling process respectively in a particular embodiment:
Wherein:
Can process according to lowest resolution when DOM being carried out classification piecemeal resampling process, the data message after being sampled；
When considering the DEM value of adjacent plot at the same level sampled point when DEM carrying out classification piecemeal resampling and processing, first entirety carries out DEM resampling again to each sampled point assignment after piecemeal；When considering adjacent but different stage plot DEM sampling, formula (2* (2 can be passed through for crack treatment problem when eliminating gound-mappingn+ 1)-1) * (2* (2n+ 1)-1) carry out Multi-Resolution blocked processing, border takes the DEM elevation point value that the meansigma methods of consecutive points obtains the boundary point in sub-level plot.
A kind of massive terrain data tissue dissemination method as shown in Figure 4, DOM can be carried out image resampling process by described resampling terrain data:
Wherein: DOM carries out image resampling process can be further:
1), according to landform classification block index information, each plot in the landform classification piecemeal of each image is traveled through；
2) each the image data in each plot, is read, it is thus achieved that the data message after resampling.
A kind of massive terrain data tissue dissemination method as shown in Figure 5, DEM can be carried out image resampling process by described resampling terrain data:
Wherein: DEM carries out image resampling process can be further:
1), every grade of rectangular area is traveled through according to landform index data；
2) every grade of rectangle data, is read in memory array；
3), the square boundary coincidence point place point data corresponding with lower level of present level is replaced, it is ensured that endpoint data is consistent；
4), each plot in traversal current rectangle region；
5), according to plot index number, data are deposited to core buffer, until each ground blocks of data is all deposited to core buffer in every grade of region.
A kind of massive terrain data tissue dissemination method as shown in Figure 6, DOM and DEM can be carried out image resampling process by described resampling terrain data: the further step of its process is:
1), by carrying out inlaying fusion with corresponding overall DOM blocks of data after DOM resampling；
2), DOM data acquisition carry out compression of images by self-defining compression factor, DOM data after compression update overall block data, are effectively reduced data volume；
3), add multilamellar DOM data time, set up figure layer index information, plot store each figure layer DOM data respectively, the DOM image of equivalent layer when rendering, can be called according to actual needs；
4), add multi-DEMs data, carry out classification piecemeal also according to its coordinate range, it is determined that its index position in entire scope classification block data structure, namely set up classification block index information；
5) whole data structure index informations and whole terrain block data to data sources, are stored.
A kind of massive terrain data tissue dissemination method as shown in Figure 7, concretely comprising the following steps of described fusion terrain data:
1), the data that each terrain data classification piecemeal resampling processes being deposited to core buffer, wherein each terrain data includes one layer of background terrain and multilamellar local landform；
2) internal storage data in each plot, after traversal classification piecemeal, and the graphic data partly in each plot is embedded in the internal storage data of corresponding background plot.
In a particular embodiment described resampling terrain data DOM and DEM can be carried out image resampling process: the further step of its process is:
Multi-Resolution blocked processing can be carried out according to lowest resolution when DOM carries out Multi-Resolution blocked processing, obtain required index information.
In a particular embodiment described issue terrain data the terrain data after classification piecemeal and index information are stored in various types of data source: its data source can be various relevant databases, file type data form.
With the example of a details aspect more specifically, this technology is described in detail below.
A kind of massive terrain data tissue dissemination method, mainly include reading terrain data, uniformly graphic data coordinate, choose terrain data scope, index information, resampling terrain data, merge terrain data, issue the processes such as terrain data, specifically comprise the following steps that
Read terrain data: choosing the global DEM image terrain data as a setting that resolution is the global DOM image of 2048x1024,2700x1350, the orthography that resolution is 5001x4001 and the digital elevation image that resolution is 1251x1001 of choosing Tianjin map sheet 408-105-16 are read out as graphic data partly.
Graphic data coordinate uniformly: globally graphic data default coordinate system is WGS84；The terrain data coordinate system of map sheet 408-105-16 is Tianjin 90 coordinate system；Two-layer terrain data coordinate system is inconsistent, and owing to WGS84 coordinate system is world coordinate system, in order to process conveniently, the present embodiment graphic data will transfer WGS84 coordinate system to partly.
Choose terrain data scope: determine image capturing range to be processed, if view picture local image is involved in warehouse-in, proceeds next step data and process；If carrying out custom field to choose, local image being chosen polygon point set and creates custom field, can once choose polygon point set, also polygon point set can repeatedly be chosen, after selection range, polygon scope point set is merged, generate a polygon range information, and in the terrain data storage in polygon to landform buffer memory, will then carry out next step data process.
Index information: first according to geographical transit square degree scope (-180 ° ~ 180 ° ,-90 ° ~ 90 °), Background From Layer being carried out physical block, piecemeal number is num.In order to briefly describe implementation, average for background terrain scope piecemeal is 8 pieces by the present embodiment, then every piece is all square.Terrestrial range after piecemeal is carried out quaternary tree classification piecemeal (can also otherwise piecemeal) again and builds overall data structure (level=0,1,2 ...), all there are 4 sub-plot in every grade of plot, every sub-plot coordinate in its current level is (row, col).The such as 0 sub-block coordinates of level respectively (0,0), (1,0), (0,1), (1,1), the sub-block coordinates of 1 level respectively (0,0), (1,0), (2,0), (3,0), (0,1), (2,1), (3,1), (0,2), (1,2), (3,2), (0,3) ..., thus set up overall data structure.Then the geographical coordinate position according to graphic data partly determines its coordinated indexing position (num, level, row, col) in overall data structure, finally indexes information TerrainIndex.
Resampling terrain data: the resampling carrying out (num, level, row, col) Block-terrain data according to the index information TerrainIndex of landform processes and stores TerrainBlock.Concrete operations are as follows: can determine that the local image of 5001x4001 may finally be divided into 17 classifications according to lowest resolution 256x256 when local terrain data carrying out classification piecemeal resampling and processing, then each block data is processed, the data message after being sampled.When considering the DEM value of adjacent plot at the same level sampled point when local terrain data being carried out classification piecemeal resampling and processing, first local terrain data entirety is carried out DEM resampling and obtains each sampled point DEM value again to each sampled point assignment after piecemeal；When considering adjacent but different stage plot DEM sampling, formula (2* (2 can be adopted for crack treatment problem when eliminating gound-mappingn+ 1)-1) * (2* (2+1)-1) determines sampled point resolution, the present embodiment take the resolution of 9*9 carry out Multi-Resolution blocked processing (n can according to precision need carry out value), and parent boundary of land block takes the meansigma methods DEM elevation point value as the boundary point in its sub-level plot of consecutive points.Then, according to landform classification block index information TerrainIndex, travel through each plot in the landform classification piecemeal of each layer terrain data, read the data of each the DOM image 256*256 in each plot, it is thus achieved that the data message after resampling.When processing DEM, assignment be put accordingly to L+1 level by the square boundary point DEM value of current L level, ensure that each classification piecemeal boundary point sampled data value is consistent, according to plot index number (num, level, row, col) data are deposited to terrain data relief area, until each ground blocks of data is all deposited to terrain data relief area in every grade of region.
Merge terrain data: travel through the data cached of each plot after classification piecemeal, geographical coordinate position some classification Block-terrain data known according to local image had not only comprised graphic data but also comprise background terrain data partly, and now then the graphic data partly of this piecemeal is mapped to the image data forming the final 256*256 of this piecemeal in the block data source that background terrain data are corresponding according to geographic coordinate information.
Issue terrain data: select data source types, the present embodiment selects Firedird data base, newdata library file, such as TianJin, by in index information table in landform index information TerrainIndex write into Databasce, whole Block-terrain data TerrainBlock are written in the tables of data of plot.
Embodiment 2:
The schematic flow sheet of a kind of massive terrain data tissue dissemination method that Fig. 2 provides for the present embodiment.As it is shown in figure 1, a kind of massive terrain data tissue dissemination method, comprise the steps:
A kind of massive terrain data tissue dissemination method, it is characterised in that comprise the steps:
Read terrain data: orthography and digital elevation image data are read out, a map sheet image, many map sheets image can be read in image reads simultaneously, the resolution of every width image can be different, and the scope of every width image is also repeatable, forms one layer, multilamellar terrain data；
Graphic data coordinate uniformly: judge that whether image geographic coordinate system is consistent, be then for further processing if the judgment is Yes, if NO, then its data coordinates be transformed under unified geographic coordinate system；
Choose terrain data scope: judge whether that the scope to image carries out entirety and chooses or carry out custom field and choose, choose just be for further processing as carried out entirety, choose as carried out custom field, carry out polygon scope judgement the image data intercepting within the scope of this and be for further processing:
Index information: first carry out physical block according to the entire scope of massive terrain data, terrestrial range after piecemeal is carried out classification piecemeal again and builds overall data structure, then the geographical coordinate position of base area graphic data determines its coordinated indexing position in overall data structure, namely indexes information；
Resampling terrain data: every piece of terrain data is carried out resampling process by the index information according to setting up；
Merge terrain data: if being provided with background layer in the multilamellar terrain data issued, then the terrain data after being processed by piecemeal is embedded in the block data that background layer scope is corresponding；The index information of piecemeal belonging to image data wherein can be determined by geographical coordinate position；
Issue terrain data: the terrain data after classification piecemeal and index information are stored in various types of data source.
Increment is issued: again issue new data in existing terrain source data in this data source, for the extension of local updating and the terrain data scope of terrain data.
The step of described reading terrain data is concretely in a particular embodiment: orthography and digital elevation image data are read out, in image reads, can read a picture layer image also can read the map overlay image a kind of, multiple in the image of history image, infrared image difference figure layer, and can to arrange one layer of terrain data therein be Background From Layer.
A kind of massive terrain data tissue dissemination method as shown in Figure 3, described in choose concretely comprising the following steps of terrain data scope:
1), polygon scope is created: input polygon point set creates custom field；
2) scope of every piece of terrain data, is merged: the polygon scope that every piece of landform is arranged merged, generate a polygon range information；
3) polygon range information, is utilized to create buffer memory landform: by the terrain data storage in polygon to landform buffer memory.
Described resampling terrain data can be divided into DOM and DEM carries out image resampling process respectively in a particular embodiment:
Wherein:
Can process according to lowest resolution when DOM being carried out classification piecemeal resampling process, the data message after being sampled；
When considering the DEM value of adjacent plot at the same level sampled point when DEM carrying out classification piecemeal resampling and processing, first entirety carries out DEM resampling again to each sampled point assignment after piecemeal；When considering adjacent but different stage plot DEM sampling, formula (2* (2 can be passed through for crack treatment problem when eliminating gound-mappingn+ 1)-1) * (2* (2n+ 1)-1) carry out Multi-Resolution blocked processing, border takes the DEM elevation point value that the meansigma methods of consecutive points obtains the boundary point in sub-level plot.
A kind of massive terrain data tissue dissemination method as shown in Figure 4, DOM can be carried out image resampling process by described resampling terrain data:
Wherein: DOM carries out image resampling process can be further:
1), according to landform classification block index information, each plot in the landform classification piecemeal of each image is traveled through；
2) each the image data in each plot, is read, it is thus achieved that the data message after resampling.
A kind of massive terrain data tissue dissemination method as shown in Figure 5, DEM can be carried out image resampling process by described resampling terrain data:
Wherein: DEM carries out image resampling process can be further:
1), every grade of rectangular area is traveled through according to landform index data；
2) every grade of rectangle data, is read in memory array；
3), the square boundary coincidence point place point data corresponding with lower level of present level is replaced, it is ensured that endpoint data is consistent；
4), each plot in traversal current rectangle region；
5), according to plot index number, data are deposited to core buffer, until each ground blocks of data is all deposited to core buffer in every grade of region.
A kind of massive terrain data tissue dissemination method as shown in Figure 6, DOM and DEM can be carried out image resampling process by described resampling terrain data: the further step of its process is:
1), by carrying out inlaying fusion with corresponding overall DOM blocks of data after DOM resampling；
2), DOM data acquisition carry out compression of images by self-defining compression factor, DOM data after compression update overall block data, are effectively reduced data volume；
3), add multilamellar DOM data time, set up figure layer index information, plot store each figure layer DOM data respectively, the DOM image of equivalent layer when rendering, can be called according to actual needs；
4), add multi-DEMs data, carry out classification piecemeal also according to its coordinate range, it is determined that its index position in entire scope classification block data structure, namely set up classification block index information；
5) whole data structure index informations and whole terrain block data to data sources, are stored.
A kind of massive terrain data tissue dissemination method as shown in Figure 7, concretely comprising the following steps of described fusion terrain data:
1), the data that each terrain data classification piecemeal resampling processes being deposited to core buffer, wherein each terrain data includes one layer of background terrain and multilamellar local landform；
2) internal storage data in each plot, after traversal classification piecemeal, and the graphic data partly in each plot is embedded in the internal storage data of corresponding background plot.
In a particular embodiment described resampling terrain data DOM and DEM can be carried out image resampling process: the further step of its process is:
Multi-Resolution blocked processing can be carried out according to lowest resolution when DOM carries out Multi-Resolution blocked processing, obtain required index information.
In a particular embodiment described issue terrain data the terrain data after classification piecemeal and index information are stored in various types of data source: its data source can be various relevant databases, file type data form.
A kind of massive terrain data tissue dissemination method as shown in Figure 8, wherein, what described increment was issued concretely comprises the following steps:
Wherein, what described increment was issued concretely comprises the following steps:
1), obtain increment and issue the terrain information of data；
2), each plot is traveled through according to terrain information；
3) all terrain datas comprising this plot, are read in relief area；
4), incrementally blocks of data is stored in data source.
With the example of a details aspect more specifically, this technology is described in detail below.
Elapsing over time, graphic data there may be change or needs to expand warehouse-in terrain data scope partly, it is necessary to again put in storage by the terrain data after updating.Increment now can be adopted to issue, the data plot of only more new change in pre-existing topography data base, it is not necessary to the cost plenty of time is again issued and generates new data file, and handling process is consistent with embodiment 1, specifically comprises the following steps that
1), obtain increment and issue the information of terrain data: on embodiment 1 basis, add DOM and the DEM of new graphic data 408-105-17 partly, set up the classification block index information of this incrementally graphic data, and carry out embodiment 1 mesorelief data resampling, fusion etc. and process and generate this increment and issue image classification Block-terrain data.
2), travel through each plot according to terrain information: the classification block index information according to incrementally graphic data, travel through each plot.
3) all terrain datas comprising current plot, are read in relief area: read and comprise current (num, level, row, col) all terrain datas in plot are in extra buffer, are written in the relief area in current plot by each layer terrain data of relief area after resampling, fusion, compression etc. process.
4), the data in the block buffer of current position are written in data source: current plot (num, level, row, col) data in relief area are written in embodiment 1 data with existing storehouse TianJin, if data base has existed this plot, then updating former data with this plot new data, if do not deposited, this ground blocks of data being added in data base.
The advantage of patent of the present invention is in that: the method in the embodiment of the present invention can solve to build based on massive terrain data organizational structure to facilitate data to update and the technical problem such as quick-searching and acquisition simultaneously.Simultaneously, it is possible to image compression, edge fit and fusion, reduce memory space, improve access efficiency, it is simple to updating maintenance；Massive terrain data is enable to carry out multi-platform data publication and to share；Good application for different industries provides safe and reliable, data supporting accurately and efficiently.
Although depicting the embodiment of the present invention by embodiment, it will be appreciated by the skilled addressee that the present invention has many deformation and is varied without departing from the spirit of the present invention, it is desirable to appended claim includes these deformation and is varied without departing from the spirit of the present invention.
Claims (11)
1. a massive terrain data tissue dissemination method, it is characterised in that comprise the steps:
Read terrain data: orthography and digital elevation image data are read out, a map sheet image, many map sheets image can be read in image reads simultaneously, the resolution of every width image can be different, and the scope of every width image is also repeatable, forms one layer, multilamellar terrain data；
Graphic data coordinate uniformly: judge that whether image geographic coordinate system is consistent, be then for further processing if the judgment is Yes, if NO, then its data coordinates be transformed under unified geographic coordinate system；
Choose terrain data scope: judge whether that the scope to image carries out entirety and chooses or carry out custom field and choose, choose just be for further processing as carried out entirety, choose as carried out custom field, carry out polygon scope judgement the image data intercepting within the scope of this and be for further processing:
Index information: first carry out physical block according to the entire scope of massive terrain data, terrestrial range after piecemeal is carried out classification piecemeal again and builds overall data structure, then the geographical coordinate position of base area graphic data determines its coordinated indexing position in overall data structure, namely indexes information；
Resampling terrain data: every piece of terrain data is carried out resampling process by the index information according to setting up；
Merge terrain data: if being provided with background layer in the multilamellar terrain data issued, then the terrain data after being processed by piecemeal is embedded in the block data that background layer scope is corresponding；The index information of piecemeal belonging to image data wherein can be determined by geographical coordinate position；
Issue terrain data: the terrain data after classification piecemeal and index information are stored in various types of data source.
2. a kind of massive terrain data tissue dissemination method according to claim 1, it is characterised in that described the method also includes increment issuing steps, wherein:
Increment is issued: again issue new data in existing terrain source data in this data source, for the extension of local updating and the terrain data scope of terrain data；
Wherein, what described increment was issued concretely comprises the following steps:
1), obtain increment and issue the terrain information of data；
2), each plot is traveled through according to terrain information；
3) all terrain datas comprising this plot, are read in relief area；
4), incrementally blocks of data is stored in data source.
3. a kind of massive terrain data tissue dissemination method according to claim 1, it is characterized in that, the step of described reading terrain data is concretely: orthography and digital elevation image data are read out, in image reads, can read a picture layer image also can read the map overlay image a kind of, multiple in the image of history image, infrared image difference figure layer, and can to arrange one layer of terrain data therein be Background From Layer.
4. a kind of massive terrain data tissue dissemination method according to claim 1, it is characterised in that described in choose concretely comprising the following steps of terrain data scope:
1), polygon scope is created: input polygon point set creates custom field；
2) scope of every piece of terrain data, is merged: the polygon scope that every piece of landform is arranged merged, generate a polygon range information；
3) polygon range information, is utilized to create buffer memory landform: by the terrain data storage in polygon to landform buffer memory.
5. a kind of massive terrain data tissue dissemination method according to claim 1, it is characterised in that described resampling terrain data can be divided into DOM and DEM carries out image resampling process respectively:
Wherein:
Can process according to lowest resolution when DOM being carried out classification piecemeal resampling process, the data message after being sampled；
When considering the DEM value of adjacent plot at the same level sampled point when DEM carrying out classification piecemeal resampling and processing, first entirety carries out DEM resampling again to each sampled point assignment after piecemeal；When considering adjacent but different stage plot DEM sampling, formula (2* (2 can be passed through for crack treatment problem when eliminating gound-mappingn+ 1)-1) * (2* (2n+ 1)-1) carry out Multi-Resolution blocked processing, border takes the DEM elevation point value that the meansigma methods of consecutive points obtains the boundary point in sub-level plot.
6. a kind of massive terrain data tissue dissemination method according to claim 1, it is characterised in that DOM can be carried out image resampling process by described resampling terrain data:
Wherein: DOM carries out image resampling process can be further:
1), according to landform classification block index information, each plot in the landform classification piecemeal of each image is traveled through；
2) each the image data in each plot, is read, it is thus achieved that the data message after resampling.
7. a kind of massive terrain data tissue dissemination method according to claim 1, it is characterised in that DEM can be carried out image resampling process by described resampling terrain data:
Wherein: DEM carries out image resampling process can be further:
1), every grade of rectangular area is traveled through according to landform index data；
2) every grade of rectangle data, is read in memory array；
3), the square boundary coincidence point place point data corresponding with lower level of present level is replaced, it is ensured that endpoint data is consistent；
4), each plot in traversal current rectangle region；
5), according to plot index number, data are deposited to core buffer, until each ground blocks of data is all deposited to core buffer in every grade of region.
8. a kind of massive terrain data tissue dissemination method according to claim 1, it is characterised in that DOM and DEM can be carried out image resampling process by described resampling terrain data: the further step of its process is:
1), by carrying out inlaying fusion with corresponding overall DOM blocks of data after DOM resampling；
2), DOM data acquisition carry out compression of images by self-defining compression factor, be effectively reduced data volume；
3), add multilamellar DOM data time, set up figure layer index information, plot store each figure layer DOM data respectively, the DOM image of equivalent layer when rendering, can be called according to actual needs；
4), add multi-DEMs data, carry out classification piecemeal also according to its coordinate range, it is determined that its index position in entire scope classification block data structure, namely set up classification block index information；
5) whole data structure index informations and whole terrain block data to data sources, are stored.
9. a kind of massive terrain data tissue dissemination method according to claim 1, it is characterised in that concretely comprising the following steps of described fusion terrain data:
1), the data that each terrain data classification piecemeal resampling processes being deposited to core buffer, wherein each terrain data includes one layer of background terrain and multilamellar local landform；
2) internal storage data in each plot, after traversal classification piecemeal, and the graphic data partly in each plot is embedded in the internal storage data of corresponding background plot.
10. a kind of massive terrain data tissue dissemination method according to claim 1,5,6,7,8, it is characterised in that described resampling terrain data DOM and DEM can be carried out image resampling process: the further step of its process is:
Multi-Resolution blocked processing can be carried out according to lowest resolution when DOM carries out Multi-Resolution blocked processing, obtain required index information.
11. according to a kind of massive terrain data tissue dissemination method described in claim 1, it is characterized in that, described issue terrain data the terrain data after classification piecemeal and index information are stored in various types of data source: its data source can be various relevant databases, file type data form.
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