CN108229446B - Region delineation method and system - Google Patents
Region delineation method and system Download PDFInfo
- Publication number
- CN108229446B CN108229446B CN201810132892.9A CN201810132892A CN108229446B CN 108229446 B CN108229446 B CN 108229446B CN 201810132892 A CN201810132892 A CN 201810132892A CN 108229446 B CN108229446 B CN 108229446B
- Authority
- CN
- China
- Prior art keywords
- image
- analyzed
- file
- unit
- block
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V20/00—Scenes; Scene-specific elements
- G06V20/10—Terrestrial scenes
- G06V20/13—Satellite images
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F18/00—Pattern recognition
- G06F18/40—Software arrangements specially adapted for pattern recognition, e.g. user interfaces or toolboxes therefor
Landscapes
- Engineering & Computer Science (AREA)
- Physics & Mathematics (AREA)
- Theoretical Computer Science (AREA)
- General Physics & Mathematics (AREA)
- Computer Vision & Pattern Recognition (AREA)
- Artificial Intelligence (AREA)
- Bioinformatics & Computational Biology (AREA)
- Data Mining & Analysis (AREA)
- Evolutionary Biology (AREA)
- Evolutionary Computation (AREA)
- Bioinformatics & Cheminformatics (AREA)
- General Engineering & Computer Science (AREA)
- Life Sciences & Earth Sciences (AREA)
- Human Computer Interaction (AREA)
- Astronomy & Astrophysics (AREA)
- Remote Sensing (AREA)
- Multimedia (AREA)
- Image Analysis (AREA)
Abstract
The embodiment of the invention provides a region delineation method and a system, wherein the method comprises the following steps: acquiring an image to be analyzed of a research area, and preprocessing the image to be analyzed; establishing an analysis file, and analyzing the preprocessed image to be analyzed by using the analysis file so as to mark each element point in the image to be analyzed; establishing an evaluation index, and obtaining an evaluation result of each block contained in the image to be analyzed according to the evaluation index and the marking result of each element point in the image to be analyzed; performing area delineation according to the evaluation result of each block in the image to be analyzed; and generating a corresponding database and a corresponding data table according to the image information of the blocks contained in the circled area. According to the area delineation method, the areas meeting the requirements are obtained through element point marking, element point evaluation, block evaluation and the like, and compared with a traditional investigation method, the area delineation method is more convenient to process and more reliable in result.
Description
Technical Field
The invention relates to the technical field of hydrogeology, in particular to a region delineation method and a region delineation system.
Background
The traditional method for investigating underground water mainly comprises the following steps: water exploration by using hydrogeological survey materials, geophysical prospecting water exploration, drilling water exploration and the like. The traditional method is time-consuming and labor-consuming, and cannot realize large-area dynamic monitoring and evaluation due to the fact that control points are few and representativeness is poor, and due to the particularity of natural conditions of certain outdoor environments, such as high altitude hypoxia, severe environment, rare occurrence of people, high difficulty in field work and the like, the traditional method for investigating underground water cannot meet the requirements of hydrogeological investigation.
Disclosure of Invention
It is therefore an objective of the claimed invention to provide a method and system for area delineation to solve the above problems.
The preferred embodiment of the present invention provides a method for area delineation, which comprises:
acquiring an image to be analyzed of a research area, and preprocessing the image to be analyzed;
establishing an analysis file, and analyzing the preprocessed image to be analyzed by using the analysis file so as to mark each element point in the image to be analyzed;
establishing an evaluation index, and obtaining an evaluation result of each block contained in the image to be analyzed according to the evaluation index and the marking result of each element point in the image to be analyzed;
performing area delineation according to the evaluation result of each block in the image to be analyzed;
and generating a corresponding database and a corresponding data table according to the image information of the blocks contained in the circled area.
Further, the image to be analyzed is a remote sensing image, the remote sensing image comprises multispectral data and panchromatic band data, and the step of preprocessing the image to be analyzed comprises the following steps:
calling an L PS module in ERDAS software to respectively carry out orthorectification processing on the multispectral data and the panchromatic waveband data so as to obtain a multispectral orthography image map and a panchromatic orthography image map;
selecting a B4(R) waveband, a B3(G) waveband and a B2(B) waveband from the multispectral orthophoto map, and combining the B4(R) waveband, the B3(G) waveband and the B2(B) waveband;
carrying out fusion processing on the combined wave band and a panchromatic wave band in the panchromatic orthophoto map;
and stretching the image obtained after the fusion treatment to obtain a two-dimensional orthophoto map.
Further, the step of analyzing the preprocessed image to be analyzed by using the analysis file to mark each element point in the image to be analyzed includes:
calling a Catalog module in ArcGISI 10.3 software to establish a point file, a line file and a face file for image analysis;
respectively adapting the point file, the line file and the surface file to each element point in the preprocessed image to be analyzed;
marking each element point according to the adaptation result of each element point in the image to be analyzed and the point file, the line file and the surface file.
Further, the step of establishing an evaluation index and obtaining an evaluation result of each block included in the image to be analyzed according to the evaluation index and the marking result of each element point in the image to be analyzed includes:
establishing evaluation indexes, and setting different weight values for each evaluation index to obtain a weighted index model;
calling a Create Fishnet module in ArcGISI 10.3 software to divide the image to be analyzed into a plurality of blocks;
and aiming at each block, obtaining marking results of the element points contained in the block, and calculating the evaluation result of each element point according to the marking results and the weighting index model to obtain the evaluation result of the block.
Further, the step of performing area delineation according to the evaluation result of each block in the image to be analyzed includes:
sequencing the plurality of blocks in the image to be analyzed according to the evaluation result of each block in the image to be analyzed;
dividing the sorted blocks into a plurality of grades according to a preset grade division rule;
and performing area delineation according to the grade condition of each divided block.
Another preferred embodiment of the present invention provides an area delineation system, comprising:
the device comprises a preprocessing module, a storage module and a processing module, wherein the preprocessing module is used for acquiring an image to be analyzed of a research area and preprocessing the image to be analyzed;
the marking module is used for establishing an analysis file, and analyzing the preprocessed image to be analyzed by using the analysis file so as to mark each element point in the image to be analyzed;
the evaluation result acquisition module is used for establishing an evaluation index and obtaining the evaluation result of each block contained in the image to be analyzed according to the evaluation index and the marking result of each element point in the image to be analyzed;
the delineating module is used for performing area delineation according to the evaluation result of each block in the image to be analyzed;
and the generating module is used for generating a corresponding database and a corresponding data table according to the image information of the blocks contained in the circled area.
Furthermore, the image to be analyzed is a remote sensing image, the remote sensing image comprises multispectral data and panchromatic band data, and the preprocessing module comprises an orthorectification processing unit, a combination unit, a fusion unit and a stretching processing unit;
the orthographic correction processing unit is used for calling an L PS module in the ERDAS software to carry out orthographic correction processing on the multispectral data and the panchromatic waveband data respectively so as to obtain a multispectral orthographic image map and a panchromatic orthographic image map;
the combination unit is used for selecting a B4(R) waveband, a B3(G) waveband and a B2(B) waveband from the multispectral orthophoto map and combining the B4(R) waveband, the B3(G) waveband and the B2(B) waveband;
the fusion unit is used for fusing the combined wave band and a panchromatic wave band in the panchromatic ortho-image map;
and the stretching unit is used for stretching the image obtained after the fusion treatment to obtain a two-dimensional orthophoto map.
Further, the marking module comprises a file establishing unit, an adapting unit and a marking unit;
the file establishing unit is used for calling a Catalog module in ArcGIS10.3 software to establish a point file, a line file and a face file for image analysis;
the adaptation unit is used for respectively adapting each element point in the preprocessed image to be analyzed by using the point file, the line file and the surface file;
the marking unit is used for marking each element point according to the adaptation result of each element point in the image to be analyzed and the point file, the line file and the surface file.
Further, the evaluation result acquisition module comprises an index establishing unit, a block dividing unit and an evaluation result acquisition unit;
the index establishing unit is used for establishing evaluation indexes and setting different weight values for the evaluation indexes to obtain a weighted index model;
the block dividing unit is used for calling a Create Fishnet module in ArcGISI 10.3 software to divide the research area into a plurality of blocks;
the evaluation result obtaining unit is configured to obtain, for each block, a marking result of the element points included in the block, and calculate an evaluation result of each element point according to the marking result and the weighted index model to obtain an evaluation result of the block.
Further, the delineating module comprises a sorting unit, a grade dividing unit and a delineating unit;
the sorting unit is used for sorting the plurality of blocks in the image to be analyzed according to the evaluation result of each block in the image to be analyzed;
the grade division unit is used for dividing the sorted blocks into a plurality of grades according to a preset grade division rule;
and the delineating unit is used for performing area delineation according to the grade condition of each divided block.
According to the area delineation method and the area delineation system provided by the embodiment of the invention, the to-be-analyzed image of the research area is analyzed to mark each element point included in the to-be-analyzed image, and the established evaluation index is utilized to obtain the evaluation result of each element point by combining the marking result of each element point, so that the evaluation result of each block included in the to-be-analyzed image is obtained. Area delineation is performed according to the evaluation result of each block, so that areas which are helpful for investigation are obtained. According to the area delineation method, the areas meeting the requirements are obtained through element point marking, element point evaluation, block evaluation and the like, and compared with a traditional investigation method, the area delineation method is more convenient to process and more reliable in result.
In order to make the aforementioned and other objects, features and advantages of the present invention comprehensible, preferred embodiments accompanied with figures are described in detail below.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings needed to be used in the embodiments will be briefly described below, it should be understood that the following drawings only illustrate some embodiments of the present invention and therefore should not be considered as limiting the scope, and for those skilled in the art, other related drawings can be obtained according to the drawings without inventive efforts.
Fig. 1 is a block diagram of a region delineation apparatus according to a preferred embodiment of the present invention.
Fig. 2 is a flowchart of a region delineation method according to a preferred embodiment of the present invention.
Fig. 3 is a flowchart of the substeps of step S101 in fig. 2.
Fig. 4 is a flowchart of the substeps of step S102 in fig. 2.
Fig. 5 is a flowchart of the substeps of step S103 in fig. 2.
Fig. 6 is a flowchart of the substeps of step S104 in fig. 2.
Fig. 7 is a functional block diagram of an area delineation system according to an embodiment of the present invention.
Fig. 8 is a functional block diagram of a preprocessing module according to an embodiment of the present invention.
Fig. 9 is a functional block diagram of a marking module according to an embodiment of the present invention.
Fig. 10 is a functional block diagram of an evaluation result obtaining module according to an embodiment of the present invention.
Fig. 11 is a functional block diagram of a delineation module according to an embodiment of the present invention.
Icon: 100-area delineation equipment; 110-zone delineation system; 111-a pre-processing module; 1111-an orthorectification processing unit; 1112-a combining unit; 1113-fusion unit; 1114-a stretching treatment unit; 112-a labeling module; 1121-file creation unit; 1122-an adaptation unit; 1123-marking cells; 113-evaluation result acquisition module; 1131, an index establishing unit; 1132-block dividing unit; 1133, an evaluation result acquisition unit; 114-delineation module; 1141-a sorting unit; 1142-a level division unit; 1143-delineation unit; 115-a generating module; 120-a processor; 130-memory.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. The components of embodiments of the present invention generally described and illustrated in the figures herein may be arranged and designed in a wide variety of different configurations. Thus, the following detailed description of the embodiments of the present invention, presented in the figures, is not intended to limit the scope of the invention, as claimed, but is merely representative of selected embodiments of the invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments of the present invention without making any creative effort, shall fall within the protection scope of the present invention.
It should be noted that: like reference numbers and letters refer to like items in the following figures, and thus, once an item is defined in one figure, it need not be further defined and explained in subsequent figures. Meanwhile, in the description of the present invention, unless otherwise explicitly specified or limited, the terms "mounted," "disposed," and "connected" are to be construed broadly, e.g., as being fixedly connected, detachably connected, or integrally connected; can be mechanically or electrically connected; they may be connected directly or indirectly through intervening media, or they may be interconnected between two elements. The specific meanings of the above terms in the present invention can be understood in specific cases to those skilled in the art.
Fig. 1 is a block diagram of an area delineation apparatus 100 according to an embodiment of the present invention. In the present embodiment, the area delineation apparatus 100 comprises an area delineation system 110, a processor 120 and a memory 130. Wherein, the memory 130 is electrically connected with the processor 120 directly or indirectly to realize the data transmission or interaction. The area delineation system 110 includes at least one software function module that may be stored in the memory 130 in the form of software or firmware or solidified in the operating system of the area delineation device 100. The processor 120 is configured to execute an executable module stored in the memory 130, such as a software function module or a computer program included in the region delineation system 110, to perform region delineation on the image to be analyzed, so as to obtain a water exploration favorable region.
In this embodiment, the area delineation device 100 may be, but is not limited to, a terminal device with data and image processing capabilities, such as a personal computer, a notebook computer, and the like.
Fig. 2 is a schematic flowchart of an area delineation method applied to the area delineation apparatus 100 shown in fig. 1 according to an embodiment of the present invention. It should be noted that the method provided by the present embodiment is not limited by the sequence shown in fig. 2 and described below. The specific process shown in fig. 2 will be described in detail below.
Step S101, obtaining an image to be analyzed of a research area, and preprocessing the image to be analyzed.
In the underground water investigation research, the natural conditions of some research areas are severe, such as high seawave mountain areas in arid areas of Qinghai-Tibet plateau, so that the difficulty of carrying out field operations is large, therefore, the hydrogeology degree is very low, and the modern remote sensing technology is not easily limited by terrain conditions due to the presence, the macroscopicity and the timeliness thereof, so that the method has great superiority in the aspect of underground water investigation, and along with the improvement of the spatial resolution of the remote sensing image, the hydrogeology elements such as surface water, springs and underground overflow zones can be rapidly obtained in addition to the regional elements such as lithology, structure, terrain and landform.
In addition, digital elevation model data, basic geology of a research area, hydrogeology related invoking research result data and the like can be collected to serve as auxiliary materials for subsequent judgment of the water-rich area.
Referring to fig. 3, in the present embodiment, step S101 may include four sub-steps of step S1011, step S1012, step S1013, and step S1014.
Step S1011, calling an L PS module in the ERDAS software to respectively perform orthorectification processing on the multispectral data and the panchromatic waveband data so as to obtain a multispectral orthography image and a panchromatic orthography image.
Step S1012, selecting a B4(R) band, a B3(G) band, and a B2(B) band in the multispectral orthophoto map, and combining the B4(R) band, the B3(G) band, and the B2(B) band.
And step S1013, carrying out fusion processing on the combined wave band and the panchromatic wave band in the panchromatic ortho-image map.
In step S1014, the image obtained after the fusion process is stretched to obtain a two-dimensional orthophoto map.
In this embodiment, the image to be analyzed mainly includes a remote sensing image, where the remote sensing image includes multispectral data and panchromatic band data. In this example, a remote sensing image obtained by high score number one (GF-1) was used to investigate groundwater. After the image to be analyzed is obtained, the image to be analyzed needs to be preprocessed first, so that the subsequent analysis processing of the image is facilitated. The preprocessing of the remote sensing image mainly comprises orthorectification processing, wave band combination, wave band fusion, image local stretching processing and the like.
In this embodiment, a L PS module in ERDAS software can be called to perform orthorectification processing on a remote sensing image, wherein the ERDAS software is remote sensing professional processing software, and the multispectral data and the panchromatic band data are respectively subjected to orthorectification processing by adopting a method of 'DEM + RFM + GCP' ('digital elevation model + rational function model + ground control point') under a L PS module.
After the multispectral ortho-shadowgraph corresponding to the multispectral ortho-shadowgraph is obtained by performing ortho-rectification on the multispectral data, the B4(R) wave band, the B3(G) wave band and the B2(B) wave band in the multispectral ortho-shadowgraph can be extracted. And combining the B4(R) band, the B3(G) band, and the B2(B) band to obtain a combined band. And then the combined wave band and the panchromatic wave band in the panchromatic ortho-image map are subjected to fusion processing. The panscharp algorithm can be used for the fusion process. And finally, performing local stretching treatment on the image obtained after the fusion treatment to manufacture a two-dimensional orthophoto map.
Optionally, in this embodiment, an ArcInfo-ArcScene software platform may be further used to realize stereoscopic observation of three-dimensional topographic features and geographic elements of the research area by superimposing DEM (digital elevation model) data of the research area on the basis of the prepared two-dimensional orthophoto map.
Step S102, establishing an analysis file, and analyzing the preprocessed image to be analyzed by using the analysis file so as to mark each element point in the image to be analyzed.
Referring to fig. 4, in the present embodiment, the step S102 may include three sub-steps of step S1021, step S1022 and step S1023.
Step S1021, calling a Catalog module in ArcGIS10.3 software to establish a point file, a line file and a face file for image analysis.
Step S1022, the point file, the line file, and the surface file are respectively adapted to each pixel point in the preprocessed image to be analyzed.
And step S1023, marking each element point according to the adaptation result of each element point in the image to be analyzed and the point file, the line file and the surface file respectively.
In the embodiment, the analysis processing of the image to be analyzed mainly analyzes the geological features of each element in the image to be analyzed, such as the lithology of the stratum, the geological structure, the surface water system, the spring and spring group, the underground water overflow zone and the like.
The Catalog module in ArcGISI 10.3 software can be utilized to create Point (Point) files, line (Polyline) files, and surface (Polygon) files of the translation vectors. The point file mainly explains the characteristics of the springs and the spring groups, the line file mainly explains fractures, linear rivers, underground water overflow zones and the like, and the surface file mainly explains the characteristics of stratums, surface rivers, lakes, glaciers and the like. That is, the created point file contains the characteristics of the remote sensing elements of the springs and the spring groups, and the point file can be used for adapting to each element point in the image to be analyzed, and the obtained element points which can be successfully adapted to the point file are the element points which are characterized as the springs or the spring groups. Similarly, the established line file comprises the characteristics of remote sensing elements such as fractures, linear rivers, underground water overflow zones and the like, and the line file can be adapted to all element points in the image to be analyzed, so that the element points which can be successfully adapted to the line file are the element points which are characterized as fractures, linear rivers or underground water overflow zones. The established surface file comprises the characteristics of remote sensing elements such as stratum, surface river, lake, glacier and the like, and the surface file can be used for adapting to all element points in the image to be analyzed, so that the element points which can be successfully adapted to the surface file are the element points which are characterized as the stratum, the surface river, the lake and the glacier.
In this embodiment, a Create Features module in the arcgis10.3 software may be used to mark the element points according to the fitting results of the point file, the line file and the surface file respectively, so as to distinguish the element points representing different geological Features.
Step S103, establishing an evaluation index, and obtaining the evaluation result of each block included in the image to be analyzed according to the evaluation index and the marking result of each element point in the image to be analyzed.
Referring to fig. 5, in the present embodiment, step S103 may include three substeps, i.e., step S1031, step S1032 and step S1033.
And step S1031, establishing evaluation indexes, and setting different weight values for each evaluation index to obtain a weighted index model.
Step S1032, a Create Fishnet module in ArcGISI 10.3 software is called to divide the image to be analyzed into a plurality of blocks.
Step S1033, for each block, obtaining a marking result of the element points included in the block, and calculating an evaluation result of each element point according to the marking result and the weighted index model to obtain an evaluation result of the block.
Through the steps, each element point in the image to be analyzed can be marked to determine geological information represented by each element point, such as stratigraphic lithology, geological structure, surface water system, spring and spring group, underground water overflow zone and the like.
In this embodiment, an evaluation criterion needs to be established to determine which regions in the image to be analyzed are the water-rich regions that are favorable for water exploration. Optionally, an evaluation index is established, which is established based on the geological information characterized by the element points, for example, the evaluation index may be a spring group characteristic, a groundwater overflow zone characteristic, a planar river characteristic, and the like. The area delineation by using the single evaluation index is inaccurate, so that different weight values can be set for each evaluation index according to a certain rule to form a weighting index model, and the image to be analyzed is evaluated by using the weighting index model.
In this embodiment, a Create fisher module in the arcgis10.3 software is called to divide the grid, so as to divide the image to be analyzed into a plurality of blocks. It will be appreciated that each block includes a plurality of element points, and therefore the geological information represented by the element points constitutes the geological information of the block.
And aiming at each block in the image to be analyzed, obtaining the element points contained in the block. And evaluating the element points according to the marking results of the element points and the established weighted index model to obtain the evaluation results of the element points. And averaging the evaluation results corresponding to the plurality of element points in the block to obtain the evaluation result of the whole block. The evaluation result represents the water source condition of the area, and the higher the value of the evaluation result is, the more abundant the water source of the block is.
And step S104, performing area delineation according to the evaluation result of each block in the image to be analyzed.
Referring to fig. 6, in the present embodiment, the step S104 may include three substeps, i.e., a step S1041, a step S1042, and a step S1043.
Step S1041, sorting the plurality of blocks in the image to be analyzed according to the size of the evaluation result of each block in the image to be analyzed.
Step S1042, divide the sorted blocks into a plurality of levels according to a preset level division rule.
And step S1043, performing area delineation according to the grade condition of each divided block.
After the evaluation results of the blocks in the research area are obtained through the steps, namely the abundant condition of the water source is obtained, the water source area can be defined by integrating the evaluation results of the blocks in the research area. Alternatively, the plurality of blocks may be sorted according to the size of the evaluation result of each block in the image to be analyzed. According to a preset grade division rule, for example, all the blocks are divided into a preset number of grades, and the plurality of blocks after being sorted are divided into a plurality of grades. Alternatively, the higher the value of the evaluation result of the block included in the higher rank, the more abundant the water source condition in the blocks.
It should be understood that when the water source area is defined, if the block is the smallest unit, the defined area may include a plurality of blocks, and the blocks may be adjacent or non-adjacent, and the main evaluation criterion is the numerical size of the evaluation result of the block. In this embodiment, a block with the top grade after the ranking may be defined as a water finding favorable area, or a block with the top two grades including the ranked grade may be defined as a water finding favorable area.
Step S105, a corresponding database and a corresponding data table are generated according to the image information of the blocks included in the circled area.
In this embodiment, after the favorable water-finding area is defined, the information of the defined block may be sorted and output or stored, so as to be referred to. Optionally, image information of the circled block is generated into a corresponding database and data table, and the image information may include the geographic location of the block, geological information of each element point in the block, and the like.
Referring to fig. 7, a functional block diagram of a region delineation system 110 applied to the region delineation apparatus 100 according to an embodiment of the present invention is shown. The area delineation system 110 includes a preprocessing module 111, a marking module 112, an evaluation result obtaining module 113, a delineation module 114, and a generation module 115.
The preprocessing module 111 is configured to acquire an image to be analyzed of a research area and preprocess the image to be analyzed. The preprocessing module 111 can be used to execute step S101 shown in fig. 2, and the detailed description of step S101 can be referred to for a specific operation method.
The marking module 112 is configured to create an analysis file, and analyze the preprocessed image to be analyzed by using the analysis file, so as to mark each element point in the image to be analyzed. The marking module 112 can be used to execute step S102 shown in fig. 2, and the detailed description of step S102 can be referred to for a specific operation method.
The evaluation result obtaining module 113 is configured to establish an evaluation index, and obtain an evaluation result of each block included in the image to be analyzed according to the evaluation index and the marking result of each element point in the image to be analyzed. The evaluation result obtaining module 113 may be configured to execute step S103 shown in fig. 2, and the detailed description of step S103 may be referred to for a specific operation method.
The delineating module 114 is configured to perform area delineation according to an evaluation result of each block in the image to be analyzed. The delineating module 114 can be used to execute step S104 shown in fig. 2, and the detailed operation method can refer to the detailed description of step S104.
The generating module 115 is configured to generate a corresponding database and a corresponding data table according to the image information of the blocks included in the circled area. The generating module 115 may be configured to execute step S105 shown in fig. 2, and the detailed description of step S105 may be referred to for a specific operation method.
In this embodiment, the image to be analyzed is a remote sensing image, the remote sensing image includes multispectral data and panchromatic band data, please refer to fig. 8, and the preprocessing module 111 includes an orthorectification processing unit 1111, a combining unit 1112, a fusion unit 1113, and a stretching processing unit 1114.
The ortho-rectification processing unit 1111 is configured to invoke an L PS module in the ERDAS software to perform ortho-rectification on the multispectral data and the panchromatic waveband data respectively to obtain a multispectral ortho-image map and a panchromatic ortho-image map, the ortho-rectification processing unit 1111 may be configured to perform step S1011 shown in fig. 3, and the detailed operation method may refer to the detailed description of step S1011.
The combining unit 1112 is configured to select a B4(R) band, a B3(G) band, and a B2(B) band in the multispectral orthophoto map, and combine the B4(R) band, the B3(G) band, and the B2(B) band. The combining unit 1112 can be configured to perform step S1012 shown in fig. 3, and the detailed description of step S1012 can be referred to for a specific operation method.
The fusion unit 1113 is configured to perform fusion processing on the combined wavelength band and the panchromatic wavelength band in the panchromatic ortho-image map. The fusing unit 1113 may be configured to perform step S1013 shown in fig. 3, and the detailed description of step S1013 may be referred to for a specific operation method.
The stretching processing unit 1114 is configured to stretch the image obtained after the fusion processing to obtain a two-dimensional orthophoto map. The stretching processing unit 1114 can be used to execute step S1014 shown in fig. 3, and the detailed operation method can refer to the detailed description of step S1014.
Referring to fig. 9, in the present embodiment, the marking module 112 includes a file creating unit 1121, an adapting unit 1122, and a marking unit 1123.
The file creating unit 1121 is configured to call a Catalog module in the arcgis10.3 software to create a point file, a line file, and a face file for image analysis. The file creating unit 1121 can be used to execute step S1021 shown in fig. 4, and the detailed operation method can refer to the detailed description of step S1021.
The adapting unit 1122 is configured to adapt each element point in the preprocessed image to be analyzed by using the point file, the line file, and the surface file. The adapting unit 1122 can be used to execute step S1022 shown in fig. 4, and the detailed operation method can refer to the detailed description of step S1022.
The marking unit 1123 is configured to mark each element point according to an adaptation result of each element point in the image to be analyzed with the point file, the line file, and the surface file. The marking unit 1123 can be used to execute step S1023 shown in fig. 4, and the detailed description of step S1023 can be referred to for a specific operation method.
Referring to fig. 10, in the present embodiment, the evaluation result obtaining module 113 includes an index establishing unit 1131, a block dividing unit 1132 and an evaluation result obtaining unit 1133.
The index establishing unit 1131 is configured to establish evaluation indexes, and set different weight values for each of the evaluation indexes to obtain a weighted index model. The index establishing unit 1131 may be configured to execute step S1031 shown in fig. 5, and a detailed description of the specific operation method may refer to step S1031.
The block dividing unit 1132 is configured to call a Create fisher module in the arcgis10.3 software to divide the research area into a plurality of blocks. The partition unit 1132 may be configured to perform step S1032 shown in fig. 5, and the detailed operation method may refer to the detailed description of step S1032.
The evaluation result obtaining unit 1133 is configured to obtain, for each block, a marking result of the element points included in the block, and calculate an evaluation result of each element point according to the marking result and the weighted index model to obtain an evaluation result of the block. The evaluation result obtaining unit 1133 can be used to execute step S1033 shown in fig. 5, and the detailed description of the step S1033 can be referred to for a specific operation method.
Referring to fig. 11, in the present embodiment, the delineation module 114 includes a sorting unit 1141, a level dividing unit 1142, and a delineation unit 1143.
The sorting unit 1141 is configured to sort the plurality of blocks in the image to be analyzed according to the evaluation result of each block in the image to be analyzed. The sorting unit 1141 may be configured to execute step S1041 shown in fig. 6, and the detailed description of the step S1041 may be referred to for a specific operation method.
The level dividing unit 1142 is configured to divide the sorted multiple blocks into multiple levels according to a preset level dividing rule. The level dividing unit 1142 may be used to execute step S1042 shown in fig. 6, and the detailed description of step S1042 may be referred to for a specific operation method.
The delineating unit 1143 is configured to perform area delineation according to the grade of each divided block. The delineating unit 1143 may be configured to perform step S1043 shown in fig. 6, and the detailed description of the step S1043 may be referred to for a specific operation method.
In summary, embodiments of the present invention provide a method and a system for area delineation, in which an image to be analyzed of a research area is analyzed to mark each element point included in the image, and an evaluation result of each element point is obtained by using an established evaluation index and combining the marking result of each element point, so as to obtain an evaluation result of each block included in the image to be analyzed. Area delineation is performed according to the evaluation result of each block, so that areas which are helpful for investigation are obtained. According to the area delineation method, the areas meeting the requirements are obtained through element point marking, element point evaluation, block evaluation and the like, and compared with a traditional investigation method, the area delineation method is more convenient to process and more reliable in result.
In the embodiments provided in the present application, it should be understood that the disclosed apparatus and method may be implemented in other ways. The apparatus embodiments described above are merely illustrative and, for example, the flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of apparatus, methods and computer program products according to embodiments of the present invention. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
It should be noted that, in this document, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other identical elements in a process, method, article, or apparatus that comprises the element.
The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention, and various modifications and changes may be made by those skilled in the art. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention. It should be noted that: like reference numbers and letters refer to like items in the following figures, and thus, once an item is defined in one figure, it need not be further defined and explained in subsequent figures.
The above description is only for the specific embodiments of the present invention, but the scope of the present invention is not limited thereto, and any person skilled in the art can easily conceive of the changes or substitutions within the technical scope of the present invention, and all the changes or substitutions should be covered within the scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the appended claims.
Claims (6)
1. A method of zone delineation, the method comprising:
acquiring an image to be analyzed of a research area, and preprocessing the image to be analyzed;
establishing an analysis file, and analyzing and processing the preprocessed image to be analyzed by using the analysis file so as to mark each element point in the image to be analyzed, wherein the element points comprise element points representing stratum lithology, geological structure, surface water system, spring group and underground water overflow zone;
establishing an evaluation index, and obtaining an evaluation result of each block contained in the image to be analyzed according to the evaluation index and the marking result of each element point in the image to be analyzed;
performing area delineation according to the evaluation result of each block in the image to be analyzed;
generating a corresponding database and a corresponding data table according to the image information of the blocks contained in the circled area;
the image to be analyzed is a remote sensing image, the remote sensing image comprises multispectral data and panchromatic waveband data, and the step of preprocessing the image to be analyzed comprises the following steps of:
calling an L PS module in ERDAS software to respectively carry out orthorectification processing on the multispectral data and the panchromatic waveband data so as to obtain a multispectral orthography image map and a panchromatic orthography image map;
selecting a B4(R) waveband, a B3(G) waveband and a B2(B) waveband from the multispectral orthophoto map, and combining the B4(R) waveband, the B3(G) waveband and the B2(B) waveband;
carrying out fusion processing on the combined wave band and a panchromatic wave band in the panchromatic orthophoto map;
stretching the image obtained after the fusion treatment to obtain a two-dimensional orthophoto map;
the step of establishing an evaluation index and obtaining the evaluation result of each block included in the image to be analyzed according to the evaluation index and the marking result of each element point in the image to be analyzed includes:
establishing evaluation indexes, and setting different weight values for each evaluation index to obtain a weighted index model; calling a Create Fishnet module in ArcGISI 10.3 software to divide the image to be analyzed into a plurality of blocks; and aiming at each block, obtaining marking results of the element points contained in the block, and calculating the evaluation result of each element point according to the marking results and the weighting index model to obtain the evaluation result of the block.
2. The area delineation method of claim 1 wherein the step of analyzing the preprocessed image to be analyzed with the analysis file to mark each element point in the image to be analyzed comprises:
calling a Catalog module in ArcGISI 10.3 software to establish a point file, a line file and a face file for image analysis;
respectively adapting the point file, the line file and the surface file to each element point in the preprocessed image to be analyzed;
marking each element point according to the adaptation result of each element point in the image to be analyzed and the point file, the line file and the surface file.
3. The area delineation method according to claim 1, wherein the step of area delineation according to the evaluation result of each block in the image to be analyzed comprises:
sequencing the plurality of blocks in the image to be analyzed according to the evaluation result of each block in the image to be analyzed;
dividing the sorted blocks into a plurality of grades according to a preset grade division rule;
and performing area delineation according to the grade condition of each divided block.
4. An area delineation system, the system comprising:
the device comprises a preprocessing module, a storage module and a processing module, wherein the preprocessing module is used for acquiring an image to be analyzed of a research area and preprocessing the image to be analyzed;
the marking module is used for establishing an analysis file, analyzing and processing the preprocessed image to be analyzed by utilizing the analysis file so as to mark each element point in the image to be analyzed, wherein the element points comprise element points representing the lithology of a stratum, a geological structure, an earth surface water system, springs, spring groups and an underground water overflow zone;
the evaluation result acquisition module is used for establishing an evaluation index and obtaining the evaluation result of each block contained in the image to be analyzed according to the evaluation index and the marking result of each element point in the image to be analyzed;
the delineating module is used for performing area delineation according to the evaluation result of each block in the image to be analyzed;
the generating module is used for generating a corresponding database and a corresponding data table according to the image information of the blocks contained in the circled area;
the image to be analyzed is a remote sensing image, the remote sensing image comprises multispectral data and panchromatic waveband data, and the preprocessing module comprises an orthorectification processing unit, a combination unit, a fusion unit and a stretching processing unit;
the orthographic correction processing unit is used for calling an L PS module in the ERDAS software to carry out orthographic correction processing on the multispectral data and the panchromatic waveband data respectively so as to obtain a multispectral orthographic image map and a panchromatic orthographic image map;
the combination unit is used for selecting a B4(R) waveband, a B3(G) waveband and a B2(B) waveband from the multispectral orthophoto map and combining the B4(R) waveband, the B3(G) waveband and the B2(B) waveband;
the fusion unit is used for fusing the combined wave band and a panchromatic wave band in the panchromatic ortho-image map;
the stretching processing unit is used for stretching the image obtained after the fusion processing to obtain a two-dimensional orthophoto map;
the evaluation result acquisition module comprises an index establishing unit, a block dividing unit and an evaluation result acquisition unit;
the index establishing unit is used for establishing evaluation indexes and setting different weight values for the evaluation indexes to obtain a weighted index model; the block dividing unit is used for calling a Create Fishnet module in ArcGISI 10.3 software to divide the research area into a plurality of blocks; the evaluation result obtaining unit is configured to obtain, for each block, a marking result of the element points included in the block, and calculate an evaluation result of each element point according to the marking result and the weighted index model to obtain an evaluation result of the block.
5. The zone delineation system of claim 4 wherein the labeling module comprises a file creation unit, an adaptation unit, and a labeling unit;
the file establishing unit is used for calling a Catalog module in ArcGIS10.3 software to establish a point file, a line file and a face file for image analysis;
the adaptation unit is used for respectively adapting each element point in the preprocessed image to be analyzed by using the point file, the line file and the surface file;
the marking unit is used for marking each element point according to the adaptation result of each element point in the image to be analyzed and the point file, the line file and the surface file.
6. The area delineation system of claim 4 wherein the delineation module comprises a ranking unit, a ranking unit and a delineation unit;
the sorting unit is used for sorting the plurality of blocks in the image to be analyzed according to the evaluation result of each block in the image to be analyzed;
the grade division unit is used for dividing the sorted blocks into a plurality of grades according to a preset grade division rule;
and the delineating unit is used for performing area delineation according to the grade condition of each divided block.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201810132892.9A CN108229446B (en) | 2018-02-09 | 2018-02-09 | Region delineation method and system |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201810132892.9A CN108229446B (en) | 2018-02-09 | 2018-02-09 | Region delineation method and system |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN108229446A CN108229446A (en) | 2018-06-29 |
| CN108229446B true CN108229446B (en) | 2020-07-24 |
Family
ID=62661321
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201810132892.9A Active CN108229446B (en) | 2018-02-09 | 2018-02-09 | Region delineation method and system |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN108229446B (en) |
Families Citing this family (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109063711B (en) * | 2018-07-06 | 2021-10-29 | 中科星图股份有限公司 | Satellite image orthorectification algorithm based on LLTS framework |
| US10339424B1 (en) * | 2019-01-22 | 2019-07-02 | StradVision, Inc. | Method and device of neural network operations using a grid generator for converting modes according to classes of areas to satisfy level 4 of autonomous vehicles |
| US10311336B1 (en) * | 2019-01-22 | 2019-06-04 | StradVision, Inc. | Method and device of neural network operations using a grid generator for converting modes according to classes of areas to satisfy level 4 of autonomous vehicles |
Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102707332A (en) * | 2012-05-11 | 2012-10-03 | 北京科技大学 | Interpretation and evaluation method for reservoir area engineering geological survey |
| CN103106655A (en) * | 2013-01-15 | 2013-05-15 | 中国科学院遥感与数字地球研究所 | Construction site unsupervised extraction method based on remote-sensing image |
| CN105046592A (en) * | 2015-08-25 | 2015-11-11 | 徐光来 | Plain area water system characteristic evaluation method based on ArcGIS (Geographic Information System) |
-
2018
- 2018-02-09 CN CN201810132892.9A patent/CN108229446B/en active Active
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102707332A (en) * | 2012-05-11 | 2012-10-03 | 北京科技大学 | Interpretation and evaluation method for reservoir area engineering geological survey |
| CN103106655A (en) * | 2013-01-15 | 2013-05-15 | 中国科学院遥感与数字地球研究所 | Construction site unsupervised extraction method based on remote-sensing image |
| CN105046592A (en) * | 2015-08-25 | 2015-11-11 | 徐光来 | Plain area water system characteristic evaluation method based on ArcGIS (Geographic Information System) |
Non-Patent Citations (1)
| Title |
|---|
| 利用遥感等手段圈定紫金山铜金矿床外围找矿有利区;李明;《国土资源遥感》;20120315(第1期);第137-142页 * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN108229446A (en) | 2018-06-29 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Dong et al. | LiDAR remote sensing and applications | |
| Harris et al. | Predictive lithological mapping of Canada's North using Random Forest classification applied to geophysical and geochemical data | |
| McKay et al. | Comparison of the data-driven random forests model and a knowledge-driven method for mineral prospectivity mapping: A case study for gold deposits around the Huritz Group and Nueltin Suite, Nunavut, Canada | |
| Giasson et al. | Decision trees for digital soil mapping on subtropical basaltic steeplands | |
| Lemoine et al. | Testing the applicability of correlations between topographic slope and VS 30 for Europe | |
| Guitet et al. | Landform and landscape mapping, French Guiana (South america) | |
| CN101918864B (en) | Geophysical data processing systems | |
| Abdullah et al. | Remote sensing and geographic information system for fault segments mapping a study from Taiz area, Yemen | |
| CN108229446B (en) | Region delineation method and system | |
| Song et al. | Potential of ensemble learning to improve tree-based classifiers for landslide susceptibility mapping | |
| Abuzied et al. | Spatial prediction of landslide-susceptible zones in El-Qaá area, Egypt, using an integrated approach based on GIS statistical analysis | |
| Clubb et al. | Clustering river profiles to classify geomorphic domains | |
| Samy et al. | Application of terrain analysis to the mapping and spatial pattern analysis of subsurface geological fractures of Kuala Lumpur limestone bedrock, Malaysia | |
| de Oliveira Andrades-Filho et al. | Mapping Neogene and Quaternary sedimentary deposits in northeastern Brazil by integrating geophysics, remote sensing and geological field data | |
| Elhag | Consideration of landsat-8 Spectral band combination in typical mediterranean forest classification in Halkidiki, Greece | |
| Eberle et al. | Integrated data analysis for mineral exploration: A case study of clustering satellite imagery, airborne gamma-ray, and regional geochemical data suites | |
| Chen et al. | Research on the improvement of single tree segmentation algorithm based on airborne LiDAR point cloud | |
| Sengar et al. | Liquefaction identification using class-based sensor independent approach based on single pixel classification after 2001 Bhuj, India earthquake | |
| Elmahdy et al. | Automated detection of lineaments express geological linear features of a tropical region using topographic fabric grain algorithm and the SRTM DEM | |
| Wills et al. | Predictive modelling of fossil-bearing locality distributions in the Elliot Formation (Upper Triassic–Lower Jurassic), South Africa, using a combined multivariate and spatial statistical analyses of present-day environmental data | |
| Fournillon et al. | Characterization of karstic networks by automatic extraction of geometrical and topological parameters: comparison between observations and stochastic simulations | |
| Chen et al. | A one-class-classifier-based negative data generation method for rapid earthquake-induced landslide susceptibility mapping | |
| Li et al. | Automatic detection of geological folds using attributed relational graphs and formal grammar | |
| Argyriou | A methodology for the rapid identification of neotectonic features using geographical information systems and remote sensing: A case study from Western Crete, Greece | |
| Karimzadeh et al. | A fast topographic characterization of seismic station locations in Iran through integrated use of digital elevation models and GIS |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |