CN108536829B - A method of it improving aerial survey of unmanned aerial vehicle data and generates tile map efficiency - Google Patents
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Abstract
The present invention relates to a kind of methods that raising aerial survey of unmanned aerial vehicle data generate tile map efficiency, it is characterised in that including the following contents: passing through the aerophotogrammetry data in unmanned plane acquisition tasks region；General assignment is uniformly divided into several subtasks according to aerophotogrammetry data and allocation of computer, and exports all subtask marks；Obtained subtask is submitted to identify to hadoop cluster；Tile map is generated according to obtained subtask parallel processing aerophotogrammetry data；The tile of tile map is encoded, and the tile after coding is uploaded to establish in the library hbase and is indexed.The present invention can be widely applied in tile map generation.
Description
Technical Field
The invention relates to a method for improving the efficiency of generating a tile map by aerial survey data of an unmanned aerial vehicle, and relates to the technical field of tile maps.
Background
With the continuous progress of remote sensing technology, remote sensing data increasingly permeate human daily life, such as topographic mapping, digital earth, plant monitoring and the like. The demand of various industries on remote sensing data is continuously increased, the remote sensing data acquisition means is relatively insufficient, the unmanned aerial vehicle remote sensing technology becomes one of the main remote sensing technologies with lower operation cost and simple and convenient operation application, and the technology can acquire high-resolution image data in county and regional ranges. High-resolution image data can generate larger-scale data, and the visualization work of a large-scale raster data set at the present stage usually needs a large amount of preprocessing time, which is mainly consumed in the stages of image splicing, pyramid tile generation and the like. Tile technologies are used in geographic information systems such as ArcGIS, MapGIS and Mapnik and geographic information processing libraries to improve the map service efficiency, but the existing tile generation method for large-scale image data can only generate tiles one by one, the larger the data volume of aerial survey data is, the larger the calculated amount of the existing method is, the lower the efficiency of generating a tile map is, and the existing method is far from being adapted to the trend that the scale of the current aerial survey data set is increasing.
Disclosure of Invention
In order to solve the problem that the efficiency of tile generation is low in the traditional method, the invention provides a method for improving the efficiency of tile map generation of aerial survey data of an unmanned aerial vehicle.
In order to achieve the purpose, the invention adopts the following technical scheme: a method for improving tile map generation efficiency of aerial survey data of an unmanned aerial vehicle is characterized by comprising the following steps: acquiring aerial survey data of a task area through an unmanned aerial vehicle; uniformly dividing the total task into a plurality of subtasks according to the aerial survey data and the computer configuration, and outputting all subtask identifications; submitting the subtask identifier to the hadoop cluster; parallel processing aerial survey data according to the obtained subtasks to generate a tile map; and coding the tiles of the tile map, and uploading the coded tiles to the hbase library to establish an index.
Further, the specific process of uniformly dividing the total task into a plurality of subtasks according to the aerial survey data and the computer configuration and outputting all subtask identifications is as follows:
1) calculating the horizontal and vertical values of the starting tile and the ending tile of each layer of tiles according to the latitude and longitude range of the known picture and the preset number of the layers of the tiles;
2) calculating the total tile number according to the starting tile and the ending tile of each layer;
3) calculating the task number through the computer configuration;
4) and calculating each subtask identifier according to the aerial survey data and the number of tasks.
Further, the specific process of 4) calculating each subtask identifier according to the aerial survey data and the number of tasks is as follows:
4.1) inputting aerial survey data of the unmanned aerial vehicle;
4.2) calculating the number of the tiles required to be generated by the subtask, wherein the calculation formula is as follows:
wherein h represents the total number of tiles from the starting layer to the ending layer, n represents the number of the tasks obtained by the previous calculation, d represents the number of the tiles of each subtask, and the number of the tiles of the last subtask is smaller than d because d needs to be rounded up;
4.3) obtaining the task number of the subtask;
4.4) taking the first tile of the minimum layer as the start tile of the task 1, traversing according to the row first to obtain d tiles from the start tile to the back as the tiles to be processed by the task 1, if the cumulative total number of the tiles at the end of the row is less than d, continuing to accumulate from the start point of the next row, if the cumulative total number of the tiles at the end of the row is less than d, continuing to accumulate from the start tile of the next layer until d tiles are accumulated, taking the d-th tile as the end tile of the task, taking the next tile after the end tile as the start tile of the next task, obtaining the end point of the next task according to the rule, and so on to obtain the start point and the end point of all tasks, and if the number of the last task is less than d, directly determining the end tile of the last task as the last tile of the maximum layer;
4.5) output the subtask identification, i.e. the identification of the start tile and the end tile: [ "number of layers" - "lateral axis value" - "longitudinal axis value" ].
Further, submitting the subtask identifier to the hadoop cluster specifically includes: modifying the pretreatment class of hadoop: the preprocessing class takes the format of [ "task id", "start tile" + "end tile" ] as the identifier of a subtask, and the hadoop cluster outputs the key value pair with the subtask identifier through the inputFormat class as the input of a parallel stage task.
Further, the tile map generated by parallel processing of the aerial survey data according to the obtained subtasks specifically comprises: and in the parallel stage, calling the mapnik library transplanted to the hadoop according to the input subtask identifier to generate all tiles within the subtask identifier range.
Further, the image processing function of mapnik is transplanted to hadoop, and the specific steps are as follows: modifying a file system in the mapnik library, so that the modified mapnik library directly operates the hadoop file system, and in the process of operating the hadoop file system, using a hadoop short circuit reading function which bypasses dataode to directly read data so as to improve the reading speed; and using the streaming function of hadoop, and using the modified mapnik library through a c + + program in the hadoop parallel stage.
Further, the tiles of the tile map are encoded using a hilbert encoding algorithm.
Further, the user uploads the encoded tile map to the hbase library through the c + + program by using thrift, and the stored row key format is as follows: "layer" - "Hilbert-coded value", which is the content of the corresponding tile.
Due to the adoption of the technical scheme, the invention has the following advantages: 1. according to the tile map generation method, the tile map is generated in a parallel computing mode by utilizing the parallel computing function of the mapreduce module in the hadoop cluster, the computing time is effectively reduced, in the parallel stage, subtasks are reasonably divided according to aerial survey data and cluster configuration, and cluster resources are fully utilized to further improve the tile generating efficiency. 2. The method transplants the c + + open source library mapnik into the hadoop cluster, and operates the hadoop file system by calling the mapnik library. 3. The invention utilizes the hadoop streaming technology to complete the parallel stage of hadoop through a c + + program, thereby effectively solving the problem that java-based hadoop and c + + language-based mapnik are incompatible. 4. According to the configuration of the cluster, the invention equally divides the total task into a plurality of subtasks, and distributes tasks with reasonable calculation amount to each computer in the cluster, thereby fully utilizing the performance of the cluster and having the technical effect of improving the parallel calculation efficiency. 5. The invention utilizes the thrift technology to operate the hbase through the c + + program, and the operation is convenient. The method can be widely applied to the tile map.
Drawings
FIG. 1 is a flow chart of a method of improving the efficiency of tile map generation by aerial survey data of an unmanned aerial vehicle according to the present invention;
FIG. 2 is a flowchart of hadoop clustering operation in the method for improving the efficiency of generating a tile map from aerial survey data of an unmanned aerial vehicle according to the present invention;
fig. 3 is a flowchart of a task allocation process in the method for improving the efficiency of generating the tile map from the aerial survey data of the unmanned aerial vehicle according to the present invention.
Detailed Description
The present invention is described in detail below with reference to the attached drawings. It is to be understood, however, that the drawings are provided solely for the purposes of promoting an understanding of the invention and that they are not to be construed as limiting the invention.
Interpretation of terms: hadoop is an open-source distributed system architecture and can be applied to development of distributed programs; mapreduce is a programming model for parallel operation of large-scale data sets, and hadoop has mapreduce function; hdfs is a hadoop distributed file system; hbase is a distributed, column-oriented open source database that utilizes hdfs composition file storage systems; mapnik is an open source tool kit for developing GIS application programs, and the core of the mapnik is a c + + shared library; hadoop streaming allows a user to operate mapreduce in a multilingual environment; thrift provides a c + + interface to operate hbase.
As shown in fig. 1 and fig. 2, the method for improving the efficiency of generating the tile map by the aerial survey data of the unmanned aerial vehicle provided by the invention comprises the following steps:
1. gather the aerial survey data of task area through unmanned aerial vehicle, specifically do: an unmanned aerial vehicle task is set, aerial survey data of a task area are collected through an unmanned aerial vehicle, and a tiff format file is generated through OpenDroneMap on the collected aerial survey data to serve as source data.
2. Uniformly dividing the total task into a plurality of subtasks according to aerial survey data and computer configuration, and outputting all subtask identifications, wherein the specific process is as follows:
1) and calculating the horizontal and vertical values of the start tile and the end tile of each layer of tiles according to the latitude and longitude range of the known picture and the preset number of layers of tiles (such as 17-23 layers).
N＝2z；
Wherein,the method comprises the following steps of representing rounding operation, wherein z represents the number of tile layers, N represents the number of tiles in a line of the z-th layer in an input longitude and latitude range, x and y respectively represent horizontal and vertical values of the tiles, lon represents longitude, and lat represents latitude. For example, the input latitude and longitude are: +118.716 degrees and +30.2878 degrees, if the number of tile layers is 17, the horizontal and vertical values of the output tiles are respectively: x is 108759 and y is 53955.
2) And calculating the total tile number according to the starting tile and the ending tile of each layer. The concrete formula is as follows:
D(z)＝(X1(z)-X0(z)+1)*(Y1(z)-Y0(z)+1)；
and a is0≤a1，
Wherein z represents the number of tile layers, D (z) represents the total number of tiles in the known latitude and longitude range of the z-th layer picture, and X0And Y0Denotes the horizontal and vertical values of the starting tile, X1And Y1Indicates the horizontal and vertical values of the end tile, a0And a1Indicating a preset start and end layer, h indicates the number a0Layer to a1Total number of layer tiles.
3) And calculating the task number through the computer configuration.
The number of map tasks simultaneously performed by the cluster is related to the number of nodes and the cpu, and the specific calculation formula is as follows:
m＝d*k；
wherein d represents the number of map tasks (the number of the dual cores is 2) simultaneously operated by each node, k represents the number of nodes used for parallel computation, and m represents the number of map tasks simultaneously performed by the cluster.
In the process of calculating the task number, it is required to ensure that the content processed by each task cannot be too small, so the minimum number of pictures processed by each task is set, the maximum task number can be calculated by dividing the total number of pictures by the minimum number of pictures, and the finally obtained task number is the maximum value which is within the maximum task number and meets the multiple of the map task number, and the specific calculation formula is as follows:
q＝h/p；
wherein, p represents the minimum tile number processed by each task, h represents the total tile number, q represents the maximum allowable task number, n represents the finally calculated task number, and m represents the map task number simultaneously performed by the cluster.
4) As shown in fig. 2 and 3, each subtask identifier is calculated according to the aerial survey data and the number of tasks, and the specific process is as follows:
4.1) inputting aerial survey data of the unmanned aerial vehicle;
4.2) calculating the number of the tiles required to be generated by the subtask, wherein the calculation formula is as follows:
wherein h represents the total number of tiles from the starting layer to the ending layer, n represents the number of the tasks obtained by the previous calculation, d represents the number of the tiles of each subtask, and the number of the tiles of the last subtask is smaller than d because d needs to be rounded up.
4.3) obtaining the task number of the subtask, and if 48 subtasks are obtained through calculation, numbering the subtasks from 1 to 48;
4.4) taking the first tile of the minimum layer as the start tile of the task 1, traversing according to the row first to obtain d tiles from the start tile to the back as the tiles to be processed by the task 1, if the cumulative total of the tiles at the end of the row is less than d, continuing to accumulate from the start point of the next row, if the cumulative total of the tiles at the end of the row is less than d, continuing to accumulate from the start tile of the next layer until d tiles are accumulated, taking the d-th tile as the end tile of the task, taking the next tile after the end tile as the start tile of the next task, obtaining the end point of the next task according to the rule, and so on, obtaining the start point and the end point of all the tasks. Since the last task has a tile number smaller than d, the end tile of the last task is directly defined as the last tile of the largest layer.
4.5) output the subtask identification, i.e. the identification of the start tile and the end tile: [ "number of layers" - "lateral axis value" - "longitudinal axis value" ].
For example: the initial longitude and latitude of the aerial survey data is as follows: +118.716 degrees, +30.2878 degrees, the end longitude and latitude is: +118.725 degrees and +30.2803 degrees, the total number of tiles produced is 908910, the number of tasks is 48, and then the starting tile of the first subtask with the tile format of [ "number of layers" - "lateral axis value" - "longitudinal axis value" ] can be obtained according to fig. 3 as: [ 17-108759-: [ 23-69660762- > 3453196], the start tile of the second subtask is: [ 23-69660763- > 3453196], the end tile is: 23-69660708-3453286, the identity of other subtasks may be obtained similarly. The cluster resources can be fully utilized by distributing reasonable subtasks to the computers in the cluster for calculation, and the calculation efficiency is improved.
3. Submitting the obtained subtask identifier to a hadoop cluster;
as shown in fig. 2, the submitting subtask identification needs to modify the preprocessing class in the hadoop cluster, and the steps specifically include:
modifying the pretreatment class of hadoop: InputFormat, the preprocessing class is in the format of [ "task id", "start tile" + "end tile" ] as an identifier of a subtask.
The hadoop cluster outputs the key value pair with the subtask identification through the InputFormat class as the input of the parallel stage task, and the data volume processed by the subtask can be planned in a user-defined mode by modifying the related function of the class.
4. Parallel processing aerial survey data according to the obtained subtasks to generate a tile map;
in the parallel stage, according to an input subtask identifier, calling a mapnik library transplanted to the hadoop to generate all tiles within the subtask identifier range, wherein mapreduce in the hadoop is a high-performance parallel computing frame based on a cluster, and can automatically complete parallel processing of computing tasks, and is one of divide and conquer methods. The mapnik encapsulates the function of processing image data to generate a tile map, and the image processing function of the mapnik can be well transplanted to hadoop by utilizing the open source of the mapnik, and the specific steps are as follows:
modifying a file system in the mapnik library to enable the modified mapnik library to directly operate a hadoop file system, wherein a short-circuit reading function (short-circuit) of the hadoop is used in the process of operating the hadoop file system, and the short-circuit reading function bypasses dataode to directly read data, so that the reading speed is improved;
and using the streaming function of hadoop, and using the modified mapnik library through a c + + program in the hadoop parallel stage.
From the above description, streaming provides a multi-language environment to support hadoop parallel computation, and makes mapnik library and hadoop compatible with each other.
5. And coding the tiles, and uploading the coded tiles to the hbase library to establish indexes.
The invention adopts a Hilbert coding algorithm to code the processed tiles, and the c + + codes in the specific Hilbert coding process are as follows:
the Hilbert space filling curve can map data without good sequence in a high-dimensional space to a one-dimensional space, and adjacent objects passing through the Hilbert coding space can be stored together, so that the locality of the data is ensured, the I/O time is reduced, and the read-write efficiency of the data is improved.
Uploading the encoded tile data to an hbase library to establish an index, wherein the specific process comprises the following steps:
the user uploads the coded tile map to the hbase library through the c + + program by using thrift, and the stored row key format is as follows: "layer" - "Hilbert coded value", the value is the content of the corresponding tile. thrift lets the user operate hbase through c + + language, which makes mapnik and hbase compatible with each other.
In summary, the method for improving the efficiency of generating the tile map by the aerial survey data of the unmanned aerial vehicle firstly allocates tasks to hadoop clusters according to the input aerial survey data of the unmanned aerial vehicle and cluster configuration, then processes the aerial survey data on the clusters in parallel to generate the tile map, improves the generation efficiency of the tile map, and finally encodes and uploads the tile data to the hbase library. In the aspect of compatibility of the image processing library mapnik and the hadoop, the hadoop file system can be directly operated by modifying the bottom operating system of the mapnik library. The c + + program can call the mapnik library for image processing during mapreduce by using the streaming function of hadoop, and the user can operate hbase by using thrift with the c + + program. The invention also uses Hilbert code as the row key for storing tile data, thereby ensuring the locality of data, reducing I/O time and improving the efficiency of hbase indexing.
While the preferred embodiments of the present invention have been illustrated and described, it will be understood by those skilled in the art that various changes in form and details may be made therein without departing from the spirit and scope of the invention as defined in the appended claims.
Claims (6)
1. A method for improving tile map generation efficiency of aerial survey data of an unmanned aerial vehicle is characterized by comprising the following steps:
acquiring aerial survey data of a task area through an unmanned aerial vehicle;
the method comprises the following specific processes of uniformly dividing a total task into a plurality of subtasks according to aerial survey data and computer configuration and outputting all subtask identifications:
1) calculating the horizontal and vertical values of the starting tile and the ending tile of each layer of tiles according to the latitude and longitude range of the known picture and the preset number of the layers of the tiles;
2) calculating the total tile number according to the starting tile and the ending tile of each layer;
3) calculating the task number through the computer configuration;
4) calculating each subtask identifier according to the aerial survey data and the number of tasks, and the specific process is as follows:
4.1) inputting aerial survey data of the unmanned aerial vehicle;
4.2) calculating the number of the tiles required to be generated by the subtask, wherein the calculation formula is as follows:
wherein h represents the total number of tiles from the starting layer to the ending layer, n represents the number of the tasks obtained by the previous calculation, d represents the number of the tiles of each subtask, and the number of the tiles of the last subtask is smaller than d because d needs to be rounded up;
4.3) obtaining the task number of the subtask;
4.4) taking the first tile in the minimum layer as the start tile of task 1, traversing according to row priority to obtain d tiles from the start tile to the back as the tiles to be processed by task 1, if the cumulative total of the tiles at the end of the row is less than d, continuing to accumulate from the start point of the next row, if the cumulative total of the tiles at the end of the row is less than d, continuing to accumulate from the start tile of the next layer until d tiles are accumulated, taking the d-th tile as the end tile of the task, taking the next tile after the end tile as the start tile of the next task, and obtaining the end point of the next task according to the rule, wherein the rule is specifically: traversing the new start tile according to rows preferentially to obtain d tiles from the start tile to the back as tiles to be processed by a task 2, if the cumulative total number of the tiles is less than d to the end of the row, continuing to accumulate from the start point of the next row, if the cumulative total number of the tiles is less than d to the end of the row, continuing to accumulate from the start tile of the next layer until d tiles are accumulated, taking the d-th tile as the end tile of the task, taking the next tile of the end tile as the start tile of the next task, repeating the steps to obtain the start point and the end point of all the tasks, and directly determining the end tile of the last task as the last tile of the largest layer because the number of the tiles is less than d;
4.5) output the subtask identification, i.e. the identification of the start tile and the end tile: [ "number of layers" - "lateral axis value" - "longitudinal axis value" ]; submitting the subtask identifier to the hadoop cluster;
parallel processing aerial survey data according to the obtained subtasks to generate a tile map;
and coding the tiles of the tile map, and uploading the coded tiles to the hbase library to establish an index.
2. The method of claim 1, wherein submitting the subtask identifier to the hadoop cluster specifically is: modifying the pretreatment class of hadoop: the preprocessing class takes the format of [ "task id", "start tile" + "end tile" ] as the identifier of a subtask, and the Hadoop cluster outputs the key value pair with the subtask identifier through the inputFormat class as the input of a parallel stage task.
3. The method according to claim 1, wherein the tile map generation by parallel processing of the aerial survey data according to the obtained subtasks is specifically: and in the parallel stage, calling the mapnik library transplanted to the hadoop according to the input subtask identifier to generate all tiles within the subtask identifier range.
4. The method according to claim 3, wherein the image processing function of mapnik is transplanted to hadoop by the following steps:
modifying a file system in the mapnik library, so that the modified mapnik library directly operates the hadoop file system, and in the process of operating the hadoop file system, using a hadoop short circuit reading function which bypasses dataode to directly read data so as to improve the reading speed;
and using the streaming function of hadoop, and using the modified mapnik library through a c + + program in the hadoop parallel stage.
5. The method of claim 1, wherein the tiles of the tile map are encoded using a hilbert coding algorithm.
6. The method of claim 5, wherein the user uploads the encoded tile map to the hbase library using thrift through the c + + program, and the stored row key format is: "layer" - "Hilbert-coded value", which is the content of the corresponding tile.
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| CN112802177A (en) * | 2020-12-31 | 2021-05-14 | 广州极飞科技股份有限公司 | Processing method and device of aerial survey data, electronic equipment and storage medium |
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