CN110189043B - Usable land resource analysis system based on high-score satellite remote sensing data - Google Patents
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Abstract
The invention belongs to the field of land analysis systems, and particularly relates to a usable land resource analysis system based on high-resolution satellite remote sensing data. The intelligent early warning module is respectively in bidirectional connection with the data transmission module, the data processing module and the land use classification system module and comprises an intelligent image recognition and analysis module and a threshold judgment module. The system of the invention can intelligently identify the actual land type in the remote sensing image data and judge the phenomenon that the actual land use type is covered by people, thereby avoiding the occurrence of errors.
Description
Technical Field
The invention belongs to the field of land analysis systems, and particularly relates to a usable land resource analysis system based on high-score satellite remote sensing data.
Background
The traditional investigation method adopted for investigating the land utilization condition is field on-site investigation, measurement, judgment and control which are all based on visual sense, the randomness is large, the precision and the accuracy can not be ensured, the investigation method has very large limitation, a large amount of manpower, material resources, financial resources and time are consumed, the time period for completing an investigation task is long, the precision and the situation of the final result are difficult to ensure, and the investigation method can not be successfully completed for the investigation task with large range and global property.
Due to the development of computer technology and remote sensing technology, satellite remote sensing survey is gradually replacing the above-mentioned survey method. The present and real-time characteristics of the remote sensing data have the advantages of no substitution in the dynamic monitoring of land resources, and the specific change of each category in the land utilization change process can be reflected macroscopically.
However, the inventor finds that the existing satellite remote sensing data investigation method gradually exposes the defects. For example, for the identification and detection of the type of the green land, the existing satellite remote sensing method cannot identify the artificial false production of false and false green vegetation, so that the land type identification has larger errors. An obvious example is that at the moment that land utilization monitoring is increasingly strict, in some places, in order to cover the fact that forest vegetation is damaged and the greening rate is not high, green paint is splashed on a large area of a barren slope, a rock and soil block and even a gobi desert, so that satellite remote sensing detection is cheated, and the greening rate of a local area is improved, because the land is 'obvious' to belong to the forest vegetation in the aspect of satellite remote sensing; moreover, when the satellite is to be detected and identified, a large area of green materials are uniformly paved on a large area of industrial land, so that satellite remote sensing can be cheated.
Because the data volume to be processed by satellite remote sensing is large, the actual conditions cannot be compared one by one only by adopting computer identification and analysis, and therefore, the existing remote sensing system for the phenomenon has a great defect.
Disclosure of Invention
Aiming at the problems, the invention provides a system for analyzing available land resources based on high-score satellite remote sensing data.
In order to achieve the above object, the present invention adopts a technical solution that the present invention provides a system for analyzing available land resources based on high-score satellite remote sensing data, comprising a data acquisition module, a data transmission module, a data processing module, a land use classification system module, a central processing unit and a data conversion module, the data acquisition module, the data transmission module, the data processing module, the land utilization classification system module and the data conversion module are all connected with the central processing unit, the output end of the data acquisition module is connected with the input end of the data transmission module, the output end of the data transmission module is connected with the input end of the data processing module, the output end of the data processing module is connected with the input end of the land use classification system module, and the output end of the land utilization classification system module is connected with the input end of the data conversion module.
As a first innovation point provided by the invention for solving the technical problems, the system further comprises an intelligent early warning module, wherein the intelligent early warning module comprises an intelligent image recognition and analysis module, a threshold judgment module and an image block elimination module; the intelligent early warning module is respectively in bidirectional connection with the data transmission module, the data processing module and the land utilization classification system module; the image block eliminating module is used for eliminating the image blocks of the data input by the data transmission module based on the output results of the intelligent image identification and analysis module and the threshold judgment module.
Specifically, the intelligent image recognition and analysis module performs image recognition on the data input by the data transmission module, recognizes image blocks of which the uniformity of image attribute data in the input data is greater than a predetermined threshold value within a predetermined range, inputs the image blocks into the threshold value judgment module, judges whether the predetermined range and/or the predetermined threshold value are/is greater than a preset standard threshold value, and inputs the judgment result into the image block elimination module.
In actual implementation, the data processing module (3) receives the output result of the image block eliminating module, and then performs feature extraction, remote sensing scale selection and remote sensing image classification on the remote sensing image.
And the data processing module (3) receives the output result of the image block eliminating module, and then performs feature extraction, remote sensing scale selection and remote sensing image classification on the remote sensing image.
Therefore, the intelligent early warning module is adopted, so that the artificial manufactured 'false green belt' data in the background technology can be identified through the combined action of the intelligent image identification and analysis module, the threshold judgment module and the image block elimination module, and the correct land remote measurement result is obtained.
As another innovative point of the present invention, the intelligent early warning module is divided into a three-layer module structure, an intelligent image recognition and analysis module, a threshold determination module and an image block elimination module, and the output result of each layer of module result can be bidirectionally connected with the corresponding data transmission module, the data processing module and the land use classification system module, and can select data feedback at the same time, successively or at different data processing stages.
Preferably, the data acquisition module is used for acquiring raster data of the remote sensing image and basic data of land space configuration.
Preferably, the data processing module is used for performing feature extraction, selection of a remote sensing scale and remote sensing image classification on a remote sensing image, the remote sensing image feature extraction is used for extracting spectral, texture and shape features, the selection of the remote sensing scale comprises a local variance method and a variation function method, and the remote sensing image classification method comprises a statistical analysis-based method and a multi-source data fusion-based method.
Preferably, the spectral feature extraction method comprises an algebraic operation method, a derivative method and a transformation method; the texture feature extraction is to visually interpret the image; the shape feature extraction method includes using edge information and using block information; the statistical analysis method mainly comprises a supervised classification method and an unsupervised classification method.
Preferably, the land utilization classification system module comprises a cultivated land module, a forest land module, a grassland module, a water area module and an urban and rural construction land module.
Preferably, the arable land module comprises woodland, paddy field and dry land, the woodland module comprises woodland, shrub woodland, solvons and other woodland, the grassland module comprises high-coverage grassland, medium-coverage grassland and ground-coverage grassland, and the water area module comprises rivers, reservoirs and pools.
Preferably, the data module is used for overlapping the obtained basic data of the land space configuration with the raster data of the satellite remote sensing image to obtain land utilization type information of each pixel in the raster data of the satellite remote sensing image and transmitting the land utilization type information to the data processing module.
Preferably, the data conversion module is used for converting the current land use type into the land use type to which the current land use type actually belongs and establishing a spatial data model.
Compared with the prior art, the invention has the advantages and positive effects that,
1. the intelligent early warning module is adopted, and the artificial manufacturing 'false green belt' data in the background technology can be identified through the combined action of the intelligent image identification and analysis module, the threshold judgment module and the image block elimination module, so that the correct land remote measurement result is obtained.
2. The multi-spectral, remote sensing satellite can obtain and sub-band provide from visible light to near-infrared, short wave infrared and even longer ground spectral reflection information of wavelength, is abundant than aerial photograph piece far away, and different spectral segments have different reflection characteristic to different ground objects, can strengthen the recognition ability to the ground object.
3. The satellite image products are stored in digital form, and can directly perform various digital processing, compared with aerial photographs, aerial photographs need to be digitally scanned, and a special scanner with high precision and high scanning resolution is used, so that certain information loss is caused in the scanning process.
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In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings needed to be used in the description of the embodiments are briefly introduced below, and it is obvious that the drawings in the following description are some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without inventive labor.
FIG. 1 is a schematic block diagram of a land resource utilization analysis system based on high-score satellite remote sensing data provided in example 1;
FIG. 2 is a schematic view of a land use classification system module provided in example 1;
FIG. 3 is a simplified diagram of the land resources available according to example 1;
in the above figures, 1, a data acquisition module; 2. a data transmission module; 3. a data processing module; 4. a land use classification system module; 5. a central processing unit; 6. a data conversion module; 7. a ploughing module; 8. a forest land module; 9. a grass module; 10. a water area module; 11. land module is used in urban and rural construction.
Detailed Description
In order that the above objects, features and advantages of the present invention can be more clearly understood, the present invention will be further described with reference to the accompanying drawings and examples. It should be noted that the embodiments and features of the embodiments of the present application may be combined with each other without conflict.
In the following description, numerous specific details are set forth in order to provide a thorough understanding of the present invention, however, the present invention may be practiced in other ways than those specifically described herein, and thus the present invention is not limited to the specific embodiments of the present disclosure.
Embodiment 1, as shown in fig. 1 to 3, the present invention provides a system for analyzing available land resources based on high-score satellite remote sensing data, which comprises a data acquisition module 1, a data transmission module 2, a data processing module 3, a land use classification system module 4, a central processing unit 5 and a data conversion module 6, the data acquisition module 1, the data transmission module 2, the data processing module 3, the land use classification system module 4 and the data conversion module 6 are all connected with the central processing unit 5, and the output end of the data acquisition module 1 is connected with the input end of the data transmission module 2, the output end of the data transmission module 2 is connected with the input end of the data processing module 3, the output end of the data processing module 3 is connected with the input end of the land use classification system module 4, the output end of the land utilization classification system module 4 is connected with the input end of the data conversion module 6; the data acquisition module 1 can be used for collecting remote sensing image data and geographic information data, so that reliable resources and data can be provided for land resource analysis, the data transmission module 2 is used for carrying out superposition processing on the acquired remote sensing image data and the spatial configuration data of land and transmitting the data and processing the data through the data processing module 3, so that the precision and the feasibility of the data are improved, and the land utilization classification system module 4 is used for dividing the types of the land, so that the usable land resources can be calculated and analyzed conveniently; compared with the traditional aerial remote sensing, the satellite remote sensing has the characteristics that a computer-readable digital image can be directly obtained, extracted land information is sent into a geographic information system, the space and attribute relation of each land can be known by utilizing the powerful spatial analysis and mapping functions of the satellite remote sensing, the interconversion information of different land types in different time periods can be extracted, various land utilization current situation graphs and statistical reports can be output, an effective tool for collecting and classifying spatial data and an effective tool for analyzing the spatial data are combined, the remote sensing technology is brought into play to rapidly provide various data for the geographic information system, the analysis function of the spatial data of the geographic information system is brought into play, and the spatial analysis capability and the analysis precision of the remote sensing are improved.
As an important innovation of the embodiment, the system further comprises an intelligent early warning module, and the intelligent early warning module comprises three layers of modules shown in fig. 1: the device comprises an intelligent image identification and analysis module, a threshold judgment module and an image block elimination module; the intelligent early warning module is respectively in bidirectional connection with the data transmission module, the data processing module and the land utilization classification system module; the image block eliminating module is used for eliminating the image blocks of the data input by the data transmission module based on the output results of the intelligent image identification and analysis module and the threshold judgment module.
Specifically, the intelligent image recognition and analysis module performs image recognition on the data input by the data transmission module, recognizes image blocks of which the uniformity of image attribute data in the input data is greater than a predetermined threshold value within a predetermined range, inputs the image blocks into the threshold value judgment module, judges whether the predetermined range and/or the predetermined threshold value are/is greater than a preset standard threshold value, and inputs the judgment result into the image block elimination module.
Due to the adoption of the intelligent early warning module, the artificial green belt data manufactured in the background technology can be identified through the combined action of the intelligent image identification and analysis module, the threshold judgment module and the image block elimination module, so that the correct land remote measurement result is obtained.
Specifically, the inventor finds that image data generated by artificially manufactured 'false green belts' has obvious difference in data attribute from actual data, and the difference can be reflected on the uniformity of the image attribute data in a predetermined area through repeated comparison and screening of the inventor; in the experimental result, the attribute data of the embodiment selects the reflectivity, the pixel value, the infrared absorption rate, the radar wavelength absorption rate and the like to test, and the result shows that the reflectivity has the best effect, and the pixel value, the infrared absorption rate and the radar wavelength absorption rate have the next effect respectively, but can both play an obvious distinguishing effect.
Taking the reflectivity as an example, the artificially manufactured 'false green belt' has higher uniformity in a preset range, in other words, the reflectivity is not changed greatly; the actual forest vegetation has large differences in reflection degrees from different angles due to the well-arranged, different heights and diversified vegetation types;
in this way, the intelligent image recognition and analysis module performs image recognition on the data input by the data transmission module, recognizes image blocks in which image attribute data such as the degree of reflection of light in the input data is greater than a predetermined threshold in a predetermined range in uniformity, and inputs the image blocks into the threshold judgment module, where the threshold judgment module judges whether the predetermined range and/or the predetermined threshold is greater than a preset standard threshold, where the standard threshold may be set in combination with the predetermined range and the predetermined threshold, for example, the larger the predetermined range, the higher the predetermined threshold is, and the lower the standard threshold may be;
here, there are two threshold value determination processes, "a process of identifying an image block in which image attribute data such as a degree of homogeneity of a degree of reflection of light in an input data is greater than a predetermined threshold value within a predetermined range", and "the threshold value determination module determines whether or not the predetermined range and/or the predetermined threshold value is higher than a predetermined standard threshold value", which is one of improvements of the present invention, so that two-step threshold value setting can better avoid occurrence of erroneous determination;
and the threshold judging module inputs the judging result into the image block eliminating module, so that the data input by the data transmission module is subjected to image block elimination.
Therefore, the 'artificial' data in the remote sensing data can be accurately removed, and the satellite remote sensing data is processed into real remote sensing data, so that objective and correct classification results can be obtained;
of course, the removed image block data should be classified, and therefore, the image block data should be connected to the land use classification system module.
In embodiment 2, the data acquisition module 1 is configured to acquire raster data of remote sensing images and basic data of land space configuration.
In embodiment 3, the data processing module 3 is configured to perform feature extraction, selection of a remote sensing scale, and remote sensing image classification on a remote sensing image, the remote sensing image feature extraction is configured to extract spectral, texture, and shape features, the selection of the remote sensing scale includes a local variance method and a variation function method, and the remote sensing image classification method includes a statistical analysis-based method and a multi-source data fusion-based method.
Embodiment 4, the spectral feature extraction method includes an algebraic operation method, a derivative method, and a transformation method; the texture feature extraction is to visually interpret the image; the shape feature extraction method includes using edge information and using block information; the statistical analysis method mainly comprises a supervised classification method and an unsupervised classification method.
Example 6, the arable land module 7 includes woodland, paddy field, and dry land, the woodland module 8 includes woodland, shrub land, solvons, and other woodland, the grass module 9 includes high-coverage grassland, medium-coverage grassland, and ground-coverage grassland, and the water area module 10 includes rivers, reservoirs, and ponds.
In embodiment 7, the data module is configured to superimpose the obtained basic data of the land space configuration with the raster data of the satellite remote sensing image to obtain land use type information of each pixel in the raster data of the satellite remote sensing image, and transmit the land use type information to the data processing module 3.
For the convenience of understanding the technical solutions of the present invention, the following detailed description will be made on the working principle or the operation mode of the present invention in the practical process.
In practical application, remote sensing data and GIS technology are used for sorting, processing and updating interpretation of data, the resolution adopted by the same remote sensing model is different, and the final conclusion obtained is also different, so that the research on remote sensing images by finding a proper scale is vital that each ground feature has a proper scale, only classification is carried out under the proper scale, the classification precision of the corresponding ground feature is higher, the original remote sensing image has serious geometric deformation, so that the position of each pixel on the image has a certain difference with the coordinate of a target ground feature in a map coordinate, the image needs to be geometrically corrected, the geometric correction is generally carried out by using ground control points and correction models, various algorithms and models are used for ratio transformation, histogram equalization, linear stretching and other treatments, atmospheric scattering is eliminated through radiation correction, The method comprises the steps of absorbing influence on a remote sensing image, selecting a wave band according to sensitivity of a ground object to a certain wave band according to research, using the wave band as an image for basic analysis, carrying out multi-wave band image synthesis, extracting land resource information by adopting a visual interpretation and automatic computer identification and classification method, wherein the automatic computer identification and classification is that different spectral characteristics are presented on the remote sensing image according to different land types on the ground, and different land utilization types are automatically classified by adopting a proper method through a computer; and the area of available land resources is { suitable land for construction } - { land for existing construction } - { basic farmland };
the land resource available to all people is { the area where the land resource can be used }/{ the population in the town };
the construction method comprises the following steps of (1) construction land, available terrain, forest land, water area, marsh and desert, land with an appropriate elevation, land with an appropriate gradient, and the like, wherein the suitable construction land is the available terrain; forest land area ═ forest land area + meadow area }. 0.85; the method comprises the following steps of (1) obtaining a used construction land, namely { the construction land of the existing town village } + { the existing transportation land } + { the existing industrial and mining land } + { the existing special land } + { the existing rural residential site } + { the existing water conservancy facility land };
wherein, the town and country construction land of the village is { the town and country construction land of each county }/{ county general population }; a transportation place is 6 m; the basic farmland area is 0.9 { the actual farmland area at the end of the year }.
It is noted that the data identified by the computer automatically and distinguishably is the data which is automatically analyzed, identified and eliminated by the intelligent image identification and analysis module, which is obviously different from the prior art which does not perform any identification or needs manual identification.
The above description is only a preferred embodiment of the present invention, and not intended to limit the present invention in other forms, and any person skilled in the art may apply the above modifications or changes to the equivalent embodiments with equivalent changes, without departing from the technical spirit of the present invention, and any simple modification, equivalent change and change made to the above embodiments according to the technical spirit of the present invention still belong to the protection scope of the technical spirit of the present invention.
Claims (1)
1. A usable land resource analysis system based on high-resolution satellite remote sensing data comprises a data acquisition module (1), a data transmission module (2), a data processing module (3), a land use classification system module (4), a central processing unit (5) and a data conversion module (6), wherein the data acquisition module (1), the data transmission module (2), the data processing module (3), the land use classification system module (4) and the data conversion module (6) are all connected with the central processing unit (5);
the method is characterized in that: the system also comprises an intelligent early warning module, wherein the intelligent early warning module comprises an intelligent image recognition and analysis module, a threshold judgment module and an image block elimination module; the intelligent early warning module is respectively in bidirectional connection with the data transmission module, the data processing module and the land utilization classification system module; the image block eliminating module is used for eliminating the image blocks of the data input by the data transmission module based on the output results of the intelligent image identification and analysis module and the threshold judgment module;
the intelligent image identification and analysis module carries out image identification on the data input by the data transmission module, identifies image blocks of which the uniformity of image attribute data in the input data is greater than a preset threshold value within a preset range, inputs the image blocks into the threshold value judgment module, judges whether the preset range and/or the preset threshold value are/is greater than a preset standard threshold value or not by the threshold value judgment module, and inputs the judgment result into the image block elimination module;
the artificial green belt data is identified through the combined action of an intelligent image identification and analysis module, a threshold judgment module and an image block elimination module;
selecting wave bands according to the sensitivity degree of a researched ground object to a certain wave band, using the wave bands as images for basic analysis, carrying out multi-wave band image synthesis, extracting land resource information by adopting a visual interpretation and a computer automatic identification and classification method, wherein the computer automatic identification and classification is that different spectral characteristics are presented on a remote sensing image according to different land types on the ground, and different land utilization types are automatically distinguished by adopting a proper method through a computer;
the data acquisition module (1) is used for acquiring raster data of a remote sensing image and basic data of land space configuration;
the data processing module (3) receives the output result of the image block eliminating module, and then performs feature extraction, remote sensing scale selection and remote sensing image classification on the remote sensing image;
the land utilization classification system module receives the output result of the image block eliminating module and then carries out land utilization classification;
the land utilization classification system module (4) comprises a ploughing module (7), a woodland module (8), a grassland module (9), a water area module (10) and an urban and rural construction land module (1);
the data transmission module (2) is used for overlapping the obtained basic data of land space configuration and the satellite remote sensing image raster data to obtain land utilization type information of each pixel in the satellite remote sensing image raster data and transmitting the land utilization type information to the data processing module;
the data conversion module (6) is used for converting the current land utilization type into the land utilization type to which the current land utilization type actually belongs and establishing a spatial data model;
there are two threshold determination processes: the process of the image block with the uniformity of the light reflection degree larger than the preset threshold value in the preset range, and the process of judging whether the preset range and/or the preset threshold value are/is higher than the preset standard threshold value by the threshold value judging module;
the data processing module is used for carrying out feature extraction, remote sensing scale selection and remote sensing image classification on remote sensing images, the remote sensing image feature extraction is used for extracting spectral, texture and shape features, the remote sensing scale selection comprises a local variance method and a variation function method, and the remote sensing image classification method comprises a statistical analysis-based method and a multi-source data fusion-based method.
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| CN112381288B (en) * | 2020-11-13 | 2022-07-05 | 西北民族大学 | Ecological management system for grassland in alpine regions |
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| CN114639027B (en) * | 2022-05-20 | 2023-02-03 | 山东省地质科学研究院 | System and method for identifying low-efficiency town land use according to land use classification data |
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| CN102521624A (en) * | 2011-12-20 | 2012-06-27 | 中国科学院地理科学与资源研究所 | Classification method for land use types and system |
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| CN105740759A (en) * | 2016-01-15 | 2016-07-06 | 武汉珈和科技有限公司 | Middle-season rice information decision tree classification method based on multi-temporal data feature extraction |
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