CN108197328B - Automatic identification method for geographical national condition data change types - Google Patents
Automatic identification method for geographical national condition data change types Download PDFInfo
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Abstract
The invention relates to a method for automatically identifying geographical national condition data change types, which comprises the following steps: acquiring data to be processed, identifying the data type of the data, and acquiring the data conforming to the target data type; data preprocessing is carried out on data in a data processor; performing quality inspection on the preprocessed data according to the change detection requirement; setting the planar element tolerance and the linear element tolerance automatically identified by the geographical national condition data change information for the data qualified by the quality inspection; identifying planar elements, linear elements and point elements of the two-stage geographical national condition element data set; the planar elements, the linear elements and the point elements of the two-stage geographic national condition element data sets are overlapped in the same way, and the change information of the geographic national condition data is automatically identified; and outputting the geographical national condition data after the change information is automatically identified. By implementing the method for automatically identifying the change type of the geographical national condition data, the change information can be accurately filled, and the geographical national condition information can be efficiently acquired.
Description
Technical Field
The invention belongs to the technical field of geographic national condition monitoring, and particularly relates to an automatic identification method for a change type of geographic national condition data.
Background
Vector data change detection is an important content of space data change detection, and is an application technology for identifying and analyzing target changes at different time periods based on a computer image processing system. The existing vector data change detection technology faces many problems and difficulties which are difficult to solve, and researchers at home and abroad also carry out a great deal of research on the problems and the difficulties. By researching the relation between the spatial data change and the similarity, the Tangzhangliang and Yangbishen propose a spatial data change detection algorithm based on the similarity of linear ground objects, and realize the road data change discovery and extraction based on the recognition of the similarity of linear graphics. Aiming at the requirement of geographic information data change, such as Wanyuan and Lilin, a design scheme of a geographic information system for detecting the change of the geographic information data is provided, the change information among the geographic data in different periods can be detected, and the result shows that the system has higher accuracy in detecting the change of the geographic information data. The Xuwenxiang research makes a space feature code only related to elements, and the rapid change detection of various vector elements is realized based on the space feature code. The method comprises the steps of utilizing a triple change detection model to automatically detect detection results of 5 change types such as newly adding, disappearing, prolonging, shortening and deforming linear vector data, taking a road network in the region of the Odoku county and the Yushu county in Qinghai province as test data, obtaining a road network change detection result, and verifying the reasonability of an algorithm. Sunk and songying propose a geographic data increment updating strategy and method based on particle calculation to research the expression conditions and reasoning problems of geographic objects under both static scale state and dynamic scale state. The technical scheme is characterized in that a change detection overall scheme based on spatial matching is constructed by researching a change information detection technology and extracting and filtering related rules according to actual current problems and difficulties of data. The grandchild group further discusses and summarizes the change detection technology of vector space data and the application thereof in recent years from the aspect of multi-source vector data. The studies of the scholars still need to be improved in the efficiency and accuracy of identification in actual production, the types of the processed spatial data are relatively single, and the studies on the aspect of full-coverage area spatial data are hardly involved.
Disclosure of Invention
Aiming at the defects of the prior art, the invention provides a method for automatically identifying the change type of geographical national condition data, which comprises the following steps:
(1) acquiring data to be processed, identifying the data type of the data, acquiring data conforming to the target data type, and inputting the acquired data into a data processor;
(2) data preprocessing is carried out on data in a data processor;
(3) performing quality inspection on the preprocessed data according to the change detection requirement;
(4) setting the planar element tolerance and the linear element tolerance automatically identified by the geographical national condition data change information for the data qualified by the quality inspection;
(5) identifying a two-stage earth surface coverage classification data set and a geographical national condition element data set, identifying planar elements of the two-stage earth surface coverage classification data set according to spatial data types, and identifying planar elements, linear elements and point-shaped elements of the two-stage geographical national condition element data set according to spatial data types;
(6) superposing the planar elements of the two-stage earth surface coverage classification data set and the planar elements, linear elements and point elements of the two-stage geographic national condition element data set in the step (5) in the same way, and automatically identifying the change information of the geographic national condition data;
(7) and outputting the geographical national condition data after the change information is automatically identified.
Further, in the step (1), the data to be processed comprises two different stages of data, namely geographical national condition background data and geographical national condition monitoring data; the geographical national condition background data and the geographical national condition monitoring data are standard framing data and arbitrary framing data; the target data types of the geographical national condition background data and the geographical national condition monitoring data are one or more of Shapefile with suffix, Personal Geodatabase with suffix mdb or File Geodatabase with suffix gdb.
Further, preprocessing the data to be processed in the step (2) according to the geographical national condition monitoring data, wherein the preprocessing comprises projection conversion and format conversion, and the projection conversion is used for adjusting a coordinate system of the geographical national condition background data to be consistent with a coordinate system of the geographical national condition monitoring data; the format conversion is used for converting the format of the geographical national condition background data into the format of the geographical national condition monitoring data.
Further, the change detection requirement in the step (3) means that the data set, the layer, the field, the graph and the attribute of the data are kept consistent; the quality inspection refers to the inspection of the consistency of the data set, the layer, the field, the graph and the attribute of the preprocessed data, and if the consistency is kept, the preprocessed data is judged to be qualified, otherwise, the preprocessed data is judged to be unqualified.
Further, in the step (5), the ground surface coverage classification data set comprises a planting land data set, a forest and grass coverage data set, a housing construction area data set, a railway and road data set, a structure data set, a manual pile-digging land data set, a desert and bare land data set and a water area data set; the geographic national condition element data set comprises a traffic network data set, a water area data set, a structure element data set, a geographic unit data set and a city and town comprehensive function unit data set; the spatial data types include planar surface coverage element data, planar geographic national condition element data, linear geographic national condition element data, and dot geographic national condition element data.
Further, the step (6) of automatically identifying the geographical national situation data change information comprises the following steps:
(1') when the data set is a ground surface coverage classification data set, automatically identifying ground surface coverage classification change information, comprising the following steps:
1-reading planar surface coverage layers from a background and surface coverage classification data set for monitoring geographical and national condition data respectively;
1- ② carrying out identity superposition analysis on the data of the two-stage planar surface coverage layer;
1-reading the planar intermediate data after the same superposition analysis one by one;
1-fourthly, the newborn baby is judged to be newborn by meeting the following conditions:
1-the extension and contraction are determined by satisfying any one of the conditions (2) and (3):
and 1-outputting the automatic identification data of the surface coverage change information if the last data is the last data, and otherwise, continuously repeating the steps of 1- - (c), 1-d and 1-c.
Further, the step (6) of automatically identifying the geographical national situation data change information further comprises the following steps:
(2') when the data set is a geographical national condition element data set and the spatial data type is planar geographical national condition element data, automatically identifying the planar geographical national condition element change information, comprising the following steps:
reading a planar geographic national condition map layer from the geographic national condition background data and the geographic national condition data of the geographic national condition monitoring data respectively;
2-step two, performing identity superposition analysis and reverse identity superposition analysis on the two-stage planar geographic national situation layer data;
2-reading the planar intermediate data after the same overlapping analysis and the reverse same overlapping analysis one by one;
2-the new born fish is judged to be new when the following conditions are met:
2-fifthly, the deletion is judged when the following conditions are met
Sixthly, any one satisfying the conditions (3) and (4) is determined as expansion and contraction:
2-seventhly, all judging attributes among fields except the planar geographic national condition elements which are judged to be new and deleted, and determining that the attributes except the fields of the layer are changed to be changed if the attributes are changed;
and 2-if the last data is the data, outputting the automatic identification data of the change information of the planar geographic national condition elements, and otherwise, continuously repeating the steps 2-third, 2-fourth, 2-fifth, 2-sixth and 2-seventh.
Further, the step (6) of automatically identifying the geographical national situation data change information further comprises the following steps:
(3') when the data set is a geographic national condition element data set and the spatial data type is linear geographic national condition element data, automatically identifying linear geographic national condition element change information, comprising the following steps:
3-reading linear geographical national condition layers from the geographical national condition background data and the geographical national condition data of the geographical national condition monitoring data respectively;
3-step two, performing identity superposition analysis and reverse identity superposition analysis on the linear geographic national condition layer data in the two phases;
3, reading linear intermediate data after the same-degree superposition analysis and the reverse same-degree superposition analysis one by one;
3-fourthly, judging the newborn baby to be new when the following conditions are met:
3-fifthly, the deletion is judged when the following conditions are met
3-sixthly, any one satisfying the conditions (3) and (4) is determined as expansion and contraction:
3-seventh, when the following four conditions are met, the segmentation is judged to be interrupted
a. The accessed geographic national condition background data is the same element
b. The update elements are spatially adjacent
c. Attribute unchanged
d. The sum of the lengths of the background data is equal to the sum of the lengths of the divided detection files
3-determining all the attributes among the fields except the linear geographic national conditions elements which are determined to be new and deleted, wherein if the attributes except the fields of the layers are changed, the attributes are determined to be changed;
3-ninthly, if the last data is, outputting linear geographical national condition element change information automatic identification data, otherwise, continuously repeating the steps of 3-third, 3-fourth, 3-fifth, 3-sixth, 3-seventh and 3-eighth;
further, the step (6) of automatically identifying the geographical national situation data change information further comprises the following steps:
(4') when the data set is a geographical national condition element data set and the spatial data type is punctiform geographical national condition element data, carrying out automatic identification on punctiform geographical national condition element change information, and comprising the following steps:
4-reading a dotted geographical national condition map layer from the geographical national condition background data and the geographical national condition data of the geographical national condition monitoring data respectively;
4-performing identity superposition analysis and reverse identity superposition analysis on the two-stage point geographical national condition layer data;
4-reading the dot-like intermediate data after the same-degree superposition analysis and the reverse same-degree superposition analysis one by one;
4-judging the CC _ to be new under the condition of identity superposition analysis:
4-judging that the CC < > CC _ is deleted under the condition of reverse identity superposition analysis;
4-except the point geographic national condition elements which are judged to be new and deleted, all the attribute judgment among the fields is carried out, and if the attribute change except the field of the layer is generated, the attribute change is determined;
and 4-seventhly, outputting point-like geographical national condition element change information automatic identification data if the last data is the last data, and otherwise, continuously repeating the steps 4- ③, 4-fourteen and 4-sixthly.
Further, the geographical national condition data after the automatic identification of the output change information in the step (7) includes a surface coverage classification data set and a geographical national condition element data set, wherein layers in the surface coverage classification data set are added with ChangeType fields, and layers in the geographical national condition element data set are added with ChangeType and ChangeAtt fields.
Has the advantages that:
the general survey and monitoring of geographical national conditions are important components of national condition research, including the general survey and monitoring of natural geographical national conditions, humanistic geographical national conditions, economic geographical national conditions and the like. The geographic national condition monitoring is carried out, the system comprehensively and dynamically continuously masters the natural and humanistic geographic element conditions, the development trend and the mutual relation of the earth surface of China, and the system has important significance for assisting the scientific decision and the scientific management of governments and promoting the deep fusion of surveying and mapping geographic information and the development of economic society. In the production of the geographic national condition monitoring data, the automatic identification method of the change type of the geographic national condition data can accurately fill the change information, thereby revealing the change characteristics of the geographic spatial information and efficiently acquiring the geographic national condition information.
Drawings
FIG. 1 is a general flow chart of the method for automatically identifying geographical national situation data change types of the present invention;
FIG. 2 is a flow chart of the automatic identification of the terrain coverage classification change information of the present invention;
FIG. 3 is a flow chart of the present invention for automatically identifying the change information of the geographical national condition elements;
FIG. 4 is a flow chart of the present invention for automatically identifying the change information of linear geographic national conditions elements;
fig. 5 is a flow chart of the automatic identification of the change information of the punctual geographical national conditions elements of the present invention.
Detailed Description
In order to make the purpose and technical solution of the embodiments of the present invention clearer, the technical solution of the embodiments of the present invention will be clearly and completely described below with reference to the drawings of the embodiments of the present invention. It is to be understood that the embodiments described are only a few embodiments of the present invention, and not all embodiments. All other embodiments, which can be derived by a person skilled in the art from the described embodiments of the invention without any inventive step, are within the scope of protection of the invention.
It will be understood by those skilled in the art that, unless otherwise defined, all terms (including technical and scientific terms) used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs. It will be further understood that terms, such as those defined in commonly used dictionaries, should be interpreted as having a meaning that is consistent with their meaning in the context of the prior art and will not be interpreted in an idealized or overly formal sense unless expressly so defined herein.
Introduction of the related algorithm:
stacking analysis: overlay analysis is one of the common means for extracting spatial implicit information in geographic information systems. Unlike position query, a new layer can be generated by overlay analysis, and part of the elements of the input layer will be divided by the boundaries of the overlay layer. The new data layers generated by the superposition analysis integrate all attributes of the original two or more layer elements, so that not only is a new spatial relationship generated, but also the attribute relationships of all the layers are updated. The vector layer overlay analysis mainly comprises overlay intersection, overlay summation, difference division overlay, identity overlay and updating overlay.
The identical superposition analysis is to carry out polygon superposition, and the output layer is to reserve all polygons with one input layer as a control boundary. The process of the identity superposition analysis operation is to delete elements outside the boundary of the input image layer by taking the input image layer as a control boundary, reserve elements inside the boundary, and simultaneously carry out polygon superposition operation on the elements inside the boundary.
The invention relates to a method for automatically identifying geographical national condition data change types, which comprises the following steps:
(1) acquiring data to be processed, identifying the data type of the data, acquiring data conforming to the target data type, and inputting the acquired data into a data processor;
(2) data preprocessing is carried out on data in a data processor;
(3) performing quality inspection on the preprocessed data according to the change detection requirement;
(4) setting the planar element tolerance and the linear element tolerance automatically identified by the geographical national condition data change information for the data qualified by the quality inspection;
(5) identifying a two-stage earth surface coverage classification data set and a geographical national condition element data set, identifying planar elements of the two-stage earth surface coverage classification data set according to spatial data types, and identifying planar elements, linear elements and point-shaped elements of the two-stage geographical national condition element data set according to spatial data types;
(6) superposing the planar elements of the two-stage earth surface coverage classification data set and the planar elements, linear elements and point elements of the two-stage geographic national condition element data set in the step (5) in the same way, and automatically identifying the change information of the geographic national condition data;
(7) and outputting the geographical national condition data after the change information is automatically identified.
The geographical national condition background data in the above steps is historical geographical national condition data acquired before, and the geographical national condition monitoring data is data acquired after being compared with the geographical national condition background data.
In the step (1), the data to be processed comprises two different stages of data of geographical national condition background data and geographical national condition monitoring data; the geographical national condition background data and the geographical national condition monitoring data are standard framing data and arbitrary framing data; the target data types of the geographical national condition background data and the geographical national condition monitoring data are one or more of Shapefile with suffix, Personal Geodatabase with suffix mdb or File Geodatabase with suffix gdb.
Preprocessing the data to be processed in the step (2) according to the geographical national condition monitoring data, wherein the preprocessing comprises projection conversion and format conversion, and the projection conversion is used for adjusting the coordinate system of the geographical national condition background data to be consistent with the coordinate system of the geographical national condition monitoring data; the format conversion is used for converting the format of the geographical national condition background data into the format of the geographical national condition monitoring data.
The change detection requirement in the step (3) means that the data set, the layer, the field, the graph and the attribute of the data are kept consistent; the quality inspection refers to the inspection of the consistency of the data set, the layer, the field, the graph and the attribute of the preprocessed data, and if the consistency is kept, the preprocessed data is judged to be qualified, otherwise, the preprocessed data is judged to be unqualified.
The symbol used for judging the tolerance in the step (4) is defined as: ARC is area tolerance and CRC is length tolerance; CC is a geographical national condition classification code of background data, and CC _ is a classification code of monitoring geographical national condition data; area is the area of the post-shape data processed based on the identity stacking analysis technique, and area _ is the area of the post-shape data processed based on the reverse identity stacking analysis technique; shape _ Area is the Area of monitoring Area-shaped data, and Shape _ Ar _1 is the Area of background Area-shaped data; pIPeline.Length is the length of the linear data processed based on the identity stacking analysis technique, and pIPeline.Length _ is the length of the linear data processed based on the reverse identity stacking analysis technique; shape _ Leng1 is the monitor line length and Shape _ Le _1 is the background line length.
In the step (5), the ground surface coverage classification data set comprises a planting land data set, a forest and grass coverage data set, a housing construction area data set, a railway and road data set, a structure data set, a manual pile-digging land data set, a desert and bare land data set and a water area data set; the geographic national condition element data set comprises a traffic network data set, a water area data set, a structure element data set, a geographic unit data set and a city and town comprehensive function unit data set; the spatial data types include planar surface coverage element data, planar geographic national condition element data, linear geographic national condition element data, and dot geographic national condition element data.
By taking data in basic geographic national condition monitoring data technical regulation (GQJC 01-2017) as standard data, planar elements in a two-phase surface coverage classification data set, planar elements in a geographic national condition element data set, linear elements in the geographic national condition element data set and dotted elements in the geographic national condition element data set are sequentially identified. And sequentially comparing and judging the planar elements in the two-stage earth surface coverage classification data set, the planar elements in the geographic national condition element data set, the linear elements in the geographic national condition element data set and the point elements in the geographic national condition element data set with the standard data.
The step (6) of automatically identifying the change information of the geographical national situation data comprises the following steps:
(1') when the data set is a ground surface coverage classification data set, automatically identifying ground surface coverage classification change information, comprising the following steps:
1-reading planar surface coverage layers from a background and surface coverage classification data set for monitoring geographical and national condition data respectively;
1- ② carrying out identity superposition analysis on the data of the two-stage planar surface coverage layer;
1-reading the planar intermediate data after the same superposition analysis one by one;
1-fourthly, the newborn baby is judged to be newborn by meeting the following conditions:
1-the extension and contraction are determined by satisfying any one of the conditions (2) and (3):
and 1-outputting the automatic identification data of the surface coverage change information if the last data is the last data, and otherwise, continuously repeating the steps of 1- - (c), 1-d and 1-c.
The step (6) of automatically identifying the geographical national situation data change information further comprises the following steps:
(2') when the data set is a geographical national condition element data set and the spatial data type is planar geographical national condition element data, automatically identifying the planar geographical national condition element change information, comprising the following steps:
reading a planar geographic national condition map layer from the geographic national condition background data and the geographic national condition data of the geographic national condition monitoring data respectively;
2-step two, performing identity superposition analysis and reverse identity superposition analysis on the two-stage planar geographic national situation layer data;
2-reading the planar intermediate data after the same overlapping analysis and the reverse same overlapping analysis one by one;
2-the new born fish is judged to be new when the following conditions are met:
2-fifthly, the deletion is judged when the following conditions are met
Sixthly, any one satisfying the conditions (3) and (4) is determined as expansion and contraction:
2-seventhly, all judging attributes among fields except the planar geographic national condition elements which are judged to be new and deleted, and determining that the attributes except the fields of the layer are changed to be changed if the attributes are changed;
and 2-if the last data is the data, outputting the automatic identification data of the change information of the planar geographic national condition elements, and otherwise, continuously repeating the steps 2-third, 2-fourth, 2-fifth, 2-sixth and 2-seventh.
Further, the step (6) of automatically identifying the geographical national situation data change information further comprises the following steps:
(3') when the data set is a geographic national condition element data set and the spatial data type is linear geographic national condition element data, automatically identifying linear geographic national condition element change information, comprising the following steps:
3-reading linear geographical national condition layers from the geographical national condition background data and the geographical national condition data of the geographical national condition monitoring data respectively;
3-step two, performing identity superposition analysis and reverse identity superposition analysis on the linear geographic national condition layer data in the two phases;
3, reading linear intermediate data after the same-degree superposition analysis and the reverse same-degree superposition analysis one by one;
3-fourthly, judging the newborn baby to be new when the following conditions are met:
3-fifthly, the deletion is judged when the following conditions are met
3-sixthly, any one satisfying the conditions (3) and (4) is determined as expansion and contraction:
3-seventh, when the following four conditions are met, the segmentation is judged to be interrupted
a. The accessed geographic national condition background data is the same element
b. The update elements are spatially adjacent
c. Attribute unchanged
d. The sum of the lengths of the background data is equal to the sum of the lengths of the divided detection files
3-determining all the attributes among the fields except the linear geographic national conditions elements which are determined to be new and deleted, wherein if the attributes except the fields of the layers are changed, the attributes are determined to be changed;
3-ninthly, if the last data is, outputting linear geographical national condition element change information automatic identification data, otherwise, continuously repeating the steps of 3-third, 3-fourth, 3-fifth, 3-sixth, 3-seventh and 3-eighth;
the step (6) of automatically identifying the geographical national situation data change information further comprises the following steps:
(4') when the data set is a geographical national condition element data set and the spatial data type is punctiform geographical national condition element data, carrying out automatic identification on punctiform geographical national condition element change information, and comprising the following steps:
4-reading a dotted geographical national condition map layer from the geographical national condition background data and the geographical national condition data of the geographical national condition monitoring data respectively;
4-performing identity superposition analysis and reverse identity superposition analysis on the two-stage point geographical national condition layer data;
4-reading the dot-like intermediate data after the same-degree superposition analysis and the reverse same-degree superposition analysis one by one;
4-judging the CC _ to be new under the condition of identity superposition analysis:
4-judging that the CC < > CC _ is deleted under the condition of reverse identity superposition analysis;
4-except the point geographic national condition elements which are judged to be new and deleted, all the attribute judgment among the fields is carried out, and if the attribute change except the field of the layer is generated, the attribute change is determined;
and 4-seventhly, outputting point-like geographical national condition element change information automatic identification data if the last data is the last data, and otherwise, continuously repeating the steps 4- ③, 4-fourteen and 4-sixthly.
The geographical national condition data after the automatic identification of the output change information in the step (7) comprise a ground surface coverage classification data set and a geographical national condition element data set, wherein layers in the ground surface coverage classification data set are added with ChangeType fields, and layers in the geographical national condition element data set are added with ChangeType and ChangeAtt fields.
The general attribute item definitions of the fields in step (7) are shown in tables 1 and 2 below:
TABLE 1 surface coverage Classification Change information generic Attribute item definition
TABLE 2 general Attribute item definition for geographic national conditions element Change information
The above are merely embodiments of the present invention, which are described in detail and with particularity, and therefore should not be construed as limiting the scope of the invention. It should be noted that, for those skilled in the art, various changes and modifications can be made without departing from the spirit of the present invention, and these changes and modifications are within the scope of the present invention.
Claims (9)
1. The automatic identification method for the change types of the geographical national situation data is characterized by comprising the following steps of:
(1) acquiring data to be processed, identifying the data type of the data, acquiring data conforming to a target data type, and inputting the acquired data conforming to the target data type into a data processor;
(2) data preprocessing is carried out on data in a data processor;
(3) performing quality inspection on the preprocessed data according to the change detection requirement;
(4) setting the planar element tolerance and the linear element tolerance automatically identified by the geographical national condition data change information for the data qualified by the quality inspection;
(5) identifying a two-stage earth surface coverage classification data set and a two-stage geographical national condition element data set, identifying a planar element of the two-stage earth surface coverage classification data set according to a spatial data type, and identifying a planar element, a linear element and a point element of the two-stage geographical national condition element data set according to a spatial data type;
(6) superposing the planar elements of the two-stage earth surface coverage classification data set and the planar elements, linear elements and point elements of the two-stage geographic national condition element data set in the step (5) in the same way, and automatically identifying the change information of the geographic national condition data;
the method for automatically identifying the geographical national situation data change information comprises the following steps:
(1') when the data set is a ground surface coverage classification data set, automatically identifying ground surface coverage classification change information, comprising the following steps:
1-reading a planar ground surface coverage layer from ground surface coverage classification data sets of geographical national condition background data and geographical national condition monitoring data respectively;
1- ② carrying out identity superposition analysis on the data of the two-stage planar surface coverage layer;
1-reading the planar intermediate data after the same superposition analysis one by one;
1-4, the condition that the following (1) is satisfied is preferentially judged as new:
1-the extension and contraction are determined by satisfying any one of the conditions (2) and (3):
1-outputting the automatic identification data of the earth surface coverage change information if the last data is the data, otherwise, continuously repeating the steps of 1-three, 1-four and 1-five;
wherein, ARC is area tolerance, CC is a geographical national condition classification code of background data, and CC _ is a classification code of monitoring geographical national condition data; CC < > CC _ is that CC is not equal to CC _; area is the area of processing the shape data behind based on the same overlapping analysis technique, area is the area of processing the shape data behind based on the reverse same overlapping analysis technique; shape _ Area is the Area of monitoring planar data, Shape _ Ar _1 is the Area of background planar data, and Math.abs () is the absolute value of the parameter in the bracket;
(7) and outputting the geographical national condition data after the change information is automatically identified.
2. The method for automatically identifying the geographical national situation data change type according to claim 1, wherein in the step (1), the data to be processed comprises two different data, namely geographical national situation background data and geographical national situation monitoring data; the geographical national condition background data and the geographical national condition monitoring data are standard framing data and arbitrary framing data respectively; the target data types of the geographical national condition background data and the geographical national condition monitoring data are one or more of Shapefile with suffix, Personal Geodatabase with suffix mdb or File Geodatabase with suffix gdb.
3. The method according to claim 2, wherein the data to be processed in the step (2) is preprocessed according to the geographical national condition monitoring data, and the preprocessing comprises projection conversion and format conversion, wherein the projection conversion is used for adjusting the coordinate system of the geographical national condition background data to be consistent with the coordinate system of the geographical national condition monitoring data; the format conversion is used for converting the format of the geographical national condition background data into the format of the geographical national condition monitoring data.
4. The method for automatically identifying geographical national situation data change types according to claim 1, wherein the change detection requirement in step (3) means that data sets, layers, fields, graphs and attributes of the data are kept consistent; the quality inspection refers to the inspection of the consistency of the data set, the layer, the field, the graph and the attribute of the preprocessed data, and if the consistency is kept, the preprocessed data is judged to be qualified, otherwise, the preprocessed data is judged to be unqualified.
5. The method according to claim 1, wherein in step (5), the surface coverage classification data set comprises a planted land data set, a forest and grass coverage data set, a housing construction area data set, a railway and road data set, a structure data set, a manual pile-digging land data set, a desert and bare land data set and a water area data set; the geographic national condition element data set comprises a traffic network data set, a water area data set, a structure element data set, a geographic unit data set and a city and town comprehensive function unit data set; the spatial data types include planar surface coverage element data, planar geographic national condition element data, linear geographic national condition element data, and dot geographic national condition element data.
6. The method for automatically identifying geographical national condition data change types according to claim 1, wherein the step (6) of automatically identifying geographical national condition data change information further comprises the steps of:
(2') when the data set is a geographical national condition element data set and the spatial data type is a planar geographical national condition element data, automatically identifying the planar geographical national condition element change information, comprising the following steps:
reading a planar geographic national condition map layer from the geographic national condition background data and the geographic national condition data of the geographic national condition monitoring data respectively;
2-performing identity superposition analysis and reverse identity superposition analysis on the two-stage planar geographic national condition layer data;
2-reading the planar intermediate data after the same overlapping analysis and the reverse same overlapping analysis one by one;
2-4, meeting the following condition (4) to judge that the fish is new:
2-fifthly, the deletion is judged when the following (5) condition is met
Sixthly, any one satisfying the conditions (6) and (7) is determined as expansion and contraction:
2-seventhly, all judging attributes among fields except the planar geographic national condition elements which are judged to be new and deleted, and determining that the attributes except the fields of the layer are changed to be changed if the attributes are changed;
and 2-if the last data is the data, outputting the automatic identification data of the change information of the planar geographic national condition elements, and otherwise, continuously repeating the steps 2-third, 2-fourth, 2-fifth, 2-sixth and 2-seventh.
7. The method for automatically identifying geographical national condition data change types according to claim 1, wherein the step (6) of automatically identifying geographical national condition data change information further comprises the steps of:
(3') when the data set is the geographic national condition element data set and the spatial data type is linear geographic national condition element data, the method comprises the following steps:
3-reading linear geographical national condition layers from the geographical national condition background data and the geographical national condition data of the geographical national condition monitoring data respectively;
3-performing identity superposition analysis and reverse identity superposition analysis on the two-stage linear geographic national condition layer data;
3, reading linear intermediate data after the same-degree superposition analysis and the reverse same-degree superposition analysis one by one;
3-4, meeting the following (8) condition to judge that the fish is new:
3-fifthly, the deletion is judged when the following (9) condition is met
3-sixthly, any one satisfying the conditions (10) and (11) is determined as expansion and contraction:
and 3-seventh, when the following four conditions of a, b, c and d are met, the segmentation is judged to be interrupted:
a. the accessed geographic national condition background data is the same element;
b. the update elements are spatially adjacent;
c. the attribute is unchanged;
d. the length sum of the background data of the geographical national conditions is equal to the length sum of the segmented detection files;
3-determining all the attributes among the fields except the linear geographic national conditions elements which are determined to be new and deleted, wherein if the attributes except the fields of the layers are changed, the attributes are determined to be changed;
3-ninthly, if the last data is, outputting linear geographical national condition element change information automatic identification data, otherwise, continuously repeating the steps of 3-third, 3-fourth, 3-fifth, 3-sixth, 3-seventh and 3-eighth;
wherein CRC is the length tolerance; pIPeline.Length is the length of the linear data processed based on the identity stacking analysis technique, and pIPeline.Length _ is the length of the linear data processed based on the reverse identity stacking analysis technique; shape _ Leng1 is the monitor line length and Shape _ Le _1 is the background line length.
8. The method for automatically identifying geographical national condition data change types according to claim 1, wherein the step (6) of automatically identifying geographical national condition data change information further comprises the steps of:
(4') when the data set is a geographical national condition element data set and the spatial data type is punctiform geographical national condition element data, carrying out automatic identification on punctiform geographical national condition element change information, and comprising the following steps:
4-reading a dotted geographical national condition map layer from the geographical national condition background data and the geographical national condition data of the geographical national condition monitoring data respectively;
4-performing identity superposition analysis and reverse identity superposition analysis on the two-stage point-like geographical national condition layer data;
4-reading the dot-like intermediate data after the same-degree superposition analysis and the reverse same-degree superposition analysis one by one;
4-judging the CC _ to be new under the condition of identity superposition analysis:
4-judging that the CC < > CC _ is deleted under the condition of reverse identity superposition analysis;
4-except the point geographic national condition elements which are judged to be new and deleted, all the attribute judgment among the fields is carried out, and if the attribute change except the field of the layer is generated, the attribute change is determined;
and 4-seventhly, outputting point-like geographical national condition element change information automatic identification data if the last data is the last data, and otherwise, continuously repeating the steps 4- ③, 4-fourteen and 4-sixthly.
9. The method as claimed in claim 1, wherein the geographical national conditions data after the automatic identification of the variation type of the geographical national conditions data output in step (7) comprises a surface coverage classification data set and a geographical national conditions element data set, wherein layers in the surface coverage classification data set are added with ChangeType fields, and layers in the geographical national conditions element data set are added with ChangeType and ChangeAtt fields.
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