CN114648491A - Remote sensing monitoring system and method for cultivated land road - Google Patents
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Abstract
The application discloses a remote sensing monitoring system and method for cultivated land roads, and mainly relates to the technical field of remote sensing monitoring. The method is used for solving the technical problems that the data collected by the existing monitoring technology are overlapped more, the processing process mainly depends on human resources and the like. The method comprises the following steps: the remote sensing acquisition module is used for acquiring a plurality of ground acquisition images corresponding to a preset cultivated land area by using a remote sensing technology; the image processing module is used for carrying out common-reference reduction processing on the plurality of ground collected images based on the hypergraph theory so as to obtain farmland road information and further establish a ground road network model corresponding to a preset farmland area; and the point distribution determining module is used for determining the farmland roads corresponding to the ground information acquisition points based on the road network model, the farmland road information, the preset depth-first algorithm and the preset greedy algorithm. The method realizes the common-finger reduction of the coincident images and the automatic selection of the farmland roads.
Description
Technical Field
The application relates to the field of remote sensing monitoring, in particular to a remote sensing monitoring system and method for cultivated land roads.
Background
During the development, utilization and remediation of arable land, the plot is often altered. When the regulation project supervision, quality evaluation, property right adjustment, land parcel replacement and circulation management are carried out on a large cultivated land, the data of a road corresponding to the cultivated land needs to be collected through remote sensing monitoring equipment.
In order to maximize the collected information of cultivated land roads corresponding to the distribution points of the remote sensing monitoring equipment. At the present stage, data of the cultivated land are mainly collected by using a remote sensing technology, then relevant personnel actually investigate the road to obtain actual investigation data, and finally the actual investigation data and the collected data are summarized to determine the corresponding optimal distribution point of the remote sensing monitoring equipment on the cultivated land road.
However, the data collected by the remote sensing technology has many same coverage areas, which is not beneficial to the utilization of related personnel. And the method for determining the corresponding distribution points of the remote sensing monitoring equipment by means of professionals depends on human resources too much, whether the determined distribution points can correspond to the optimal positions or not mainly depends on personal experience, and is not beneficial to the utilization and popularization of the remote sensing monitoring equipment on cultivated land roads.
Disclosure of Invention
In view of the above-mentioned deficiencies of the prior art, the present invention provides a remote sensing monitoring system and method for cultivated land road to solve the above-mentioned technical problems.
In a first aspect, an embodiment of the present application provides a remote sensing monitoring system for an arable land road, and the system includes: the remote sensing acquisition module is used for acquiring a plurality of ground acquisition images corresponding to a preset cultivated land area by using a remote sensing technology; the image processing module is used for carrying out common-reference reduction processing on the plurality of ground collected images based on the hypergraph theory so as to obtain farmland road information and further establish a ground road network model corresponding to a preset farmland area; and the point distribution determining module is used for determining the farmland roads corresponding to the ground information acquisition points based on the road network model, the farmland road information, the preset depth-first algorithm and the preset greedy algorithm.
Further, the remote sensing acquisition module comprises: the system comprises an original image acquisition unit, an image preprocessing unit and a module determination unit; the original image acquisition unit is used for acquiring a plurality of original acquisition images corresponding to a preset cultivated land area by using a remote sensing technology; the image preprocessing unit is used for determining a signal domain corresponding to an originally acquired image by utilizing a Fourier transform algorithm; determining the detection number of the signal values in the signal domain which are larger than a preset signal threshold; when the detection number is smaller than or equal to a preset number threshold, determining the signals and the corresponding original collected images as ground collected images; and the module determining unit is used for determining the processing quantity of the ground collected images to be processed corresponding to the plurality of image processing modules so as to send the newly determined ground collected images to the image processing module with the minimum processing quantity.
Further, the image processing module includes: the system comprises a road processing unit, a common-finger reduction unit and a road modeling unit; the road processing unit is used for acquiring a plurality of farmland road information corresponding to the ground collected image through image recognition; the farmland road information comprises road routes, road route directions, road route weights and road intersection name sets; wherein the set of road junction names comprises: the name of a front intersection of a road, the names of a plurality of middle intersections of the road and the names of rear intersections of the road; the common-finger reducing unit is used for detecting whether the road intersection name set corresponding to the current road route is intersected with the road intersection name set corresponding to any other road route; when the sets intersect and are the same; determining that the current road route and any other road route are the same route; deleting arable land road information corresponding to any other road route; when the sets are intersected and one set completely comprises the other set, deleting arable land road information corresponding to the small set; when the sets are intersected and are partially intersected, carrying out information fusion on the cultivated land road information corresponding to the current road route and the cultivated land road information corresponding to any other road route on the basis of the intersected parts, deleting the cultivated land road information corresponding to the original current road route and the cultivated land road information corresponding to any other road route, and acquiring the cultivated land road information after common finger reduction; and the road modeling unit is used for establishing a ground road network model based on farmland road information after the common-finger-based reduction processing.
Further, the stationing determination module includes: a route traversing unit and a point arrangement determining unit; the route traversing unit is used for acquiring an initial point and an end point; traversing a cultivated land road network in the ground road network model by utilizing a preset depth-first algorithm based on the initial point and the end point; acquiring a plurality of cultivated land roads with the traversal times exceeding the preset traversal times; and the point distribution determining unit is used for leading the plurality of cultivated land roads into a preset greedy algorithm so as to determine the cultivated land roads corresponding to the ground information acquisition points from the plurality of cultivated land roads.
In a second aspect, an embodiment of the present application provides a remote sensing monitoring method for a cultivated land road, the method including: the server obtains a plurality of ground acquisition images corresponding to a preset cultivated land area by using a remote sensing technology; determining edge calculation nodes corresponding to the ground collected images; the method comprises the steps that an edge computing node obtains ground collected images, common-finger reduction processing is conducted on a plurality of ground collected images based on a hypergraph theory to obtain farmland road information, and then a ground road network model corresponding to a preset farmland area is established; the server determines the farmland road corresponding to the ground information acquisition point based on the road network model, the farmland road information, the preset depth-first algorithm and the preset greedy algorithm.
Further, the server obtains a plurality of ground acquisition images corresponding to the preset cultivated land area by using a remote sensing technology, and the method specifically comprises the following steps: acquiring a plurality of original collected images corresponding to a preset cultivated land area by using a remote sensing technology;
determining a signal domain corresponding to an original collected image by utilizing a Fourier transform algorithm; determining the detection number of the signal values in the signal domain which are larger than a preset signal threshold; and when the detection number is less than or equal to the preset number threshold, determining that the signals and the corresponding original collected images are ground collected images.
Further, acquiring a ground collected image, and performing common-finger reduction processing on a plurality of ground collected images based on a hypergraph theory to acquire cultivated land road information, specifically comprising: acquiring a plurality of farmland road information corresponding to the ground acquisition image through image identification; the farmland road information comprises road routes, road route directions, road route weights and road intersection name sets; wherein the set of road junction names comprises: the name of a front intersection of a road, the names of a plurality of middle intersections of the road and the names of rear intersections of the road; detecting whether a road intersection name set corresponding to the current road route is intersected with a road intersection name set corresponding to any other road route; when the sets intersect and are the same; determining that the current road route is the same as any one of other road routes; deleting arable land road information corresponding to any other road route; when the sets are intersected and one set completely comprises the other set, deleting arable land road information corresponding to the small set; and when the sets are intersected and are partially intersected, carrying out information fusion on the farmland road information corresponding to the current road route and the farmland road information corresponding to any other road route based on the intersected parts, deleting the farmland road information corresponding to the original current road route and the farmland road information corresponding to any other road route, and acquiring the farmland road information after the common finger reduction.
Further, determining the arable land road corresponding to the ground information acquisition point based on the road network model, the arable land road information, the preset depth-first algorithm and the preset greedy algorithm, and specifically comprising: acquiring an initial point and an end point; traversing a cultivated land road network in the ground road network model by utilizing a preset depth-first algorithm based on the initial point and the end point; acquiring a plurality of cultivated land roads with the traversal times exceeding the preset traversal times; and importing the plurality of cultivated land roads into a preset greedy algorithm so as to determine the cultivated land roads corresponding to the ground information acquisition points from the plurality of cultivated land roads.
As can be appreciated by those skilled in the art, the present invention has at least the following beneficial effects:
the acquisition of a plurality of ground acquisition images is realized through a remote sensing acquisition module; through the image processing module, the common-finger reduction of the overlapped parts in the ground collected images is realized, and the same coverage area of a plurality of ground collected images is removed. Traversing a road network in a road network model by a preset depth-first algorithm, acquiring cultivated land roads with the most traversal times, and acquiring a plurality of cultivated land roads with strong connectivity with other roads; through a preset greedy algorithm, the cultivated land road with the best connectivity with other roads is determined, and the cultivated land road corresponding to the automatic ground information acquisition point is further realized.
Drawings
Some embodiments of the disclosure are described below with reference to the accompanying drawings, in which:
FIG. 1 is a schematic diagram of an internal structure of a remote sensing monitoring system for an arable land road provided by an embodiment of the application.
FIG. 2 is a flow chart of a remote sensing monitoring method for cultivated land roads provided by the embodiment of the application.
Detailed Description
It should be understood by those skilled in the art that the embodiments described below are only preferred embodiments of the present disclosure, and do not mean that the present disclosure can be implemented only by the preferred embodiments, which are merely for explaining the technical principles of the present disclosure and are not intended to limit the scope of the present disclosure. All other embodiments that can be derived by one of ordinary skill in the art from the preferred embodiments provided by the disclosure without undue experimentation will still fall within the scope of the disclosure.
It should also be noted that 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 the process, method, article, or apparatus that comprises the element.
The technical solutions proposed in the embodiments of the present application are described in detail below with reference to the accompanying drawings.
FIG. 1 is a remote sensing monitoring system for arable land road provided by the embodiment of this application. As shown in FIG. 1, the remote sensing monitoring system method for cultivated land roads provided by the embodiment of the application mainly comprises the following steps: the system comprises a remote sensing acquisition module 110, an image processing module 120 and a stationing determination module 130.
The remote sensing acquisition module 110 is configured to acquire a plurality of ground collected images corresponding to a preset cultivated land area by using a remote sensing technology.
Illustratively, the remote sensing acquisition module 110 includes: an original image acquisition unit 111, an image preprocessing unit 112, and a module determination unit 113. Specifically, the original image obtaining unit 111 is configured to obtain, by using a remote sensing technology, a plurality of original collected images corresponding to a preset cultivated land area; the image preprocessing unit 112 is configured to determine a signal domain corresponding to an originally acquired image by using a fourier transform algorithm; determining the detection number of the signal values in the signal domain which are larger than a preset signal threshold; when the detection number is smaller than or equal to a preset number threshold, determining the signals and the corresponding original collected images as ground collected images; the module determining unit 113 is configured to determine the processing number of the ground captured images waiting to be processed corresponding to the plurality of image processing modules 120, so as to send the newly determined ground captured images to the image processing module 120 with the smallest processing number.
It should be noted that, the signal domain corresponding to the original captured image with the image defect has more signal protrusions, that is, whether the image defect exists in the original captured image can be determined by verifying the detection number of the signals in the signal domain corresponding to the original captured image exceeding the preset signal threshold, so that the original captured image without the image defect can be screened from a plurality of images. The specific number corresponding to the preset signal threshold and the detection number can be obtained by a person skilled in the art through multiple tests.
In addition, the specific implementation process of converting the image information into the signal domain by using the fourier transform algorithm may be implemented by an existing method or device, which is not limited in this embodiment.
The image processing module 120 is configured to perform common-reference subtraction processing on the plurality of ground collected images based on a hypergraph theory to obtain farmland road information, and then establish a ground road network model corresponding to a preset farmland area.
It should be noted that, the common reduction means to delete the common parts of the plurality of ground captured images where the images overlap. The ground road network model is a road network model comprising the whole acquisition area.
As an example, the image processing module 120 includes: a road processing unit 121, a common reduction unit 122, and a road modeling unit 123. Specifically, the road processing unit 121 is configured to acquire, through image recognition, a plurality of arable land road information corresponding to the ground collected image. The farmland road information comprises road routes, road route directions, road route weights and road intersection name sets; wherein the set of road junction names comprises: the name of a front intersection of a road, the names of a plurality of middle intersections of the road and the names of rear intersections of the road; the common-reference reduction unit 122 is configured to detect whether a road intersection name set corresponding to the current road route intersects with a road intersection name set corresponding to any other road route; when the sets intersect and are the same; determining that the current road route and any other road route are the same route; deleting arable land road information corresponding to any other road route; when the sets are intersected and one set completely comprises the other set, deleting arable land road information corresponding to the small set; when the sets are intersected and all the sets are partially intersected, carrying out information fusion on the basis of the intersected parts of the arable land road information corresponding to the current road route and the arable land road information corresponding to any other road route, deleting the arable land road information corresponding to the original current road route and the arable land road information corresponding to any other road route, and acquiring the arable land road information after common finger reduction; and the road modeling unit 123 is configured to establish a ground road network model based on arable road information after the common-finger-based reduction processing.
The stationing determining module 130 is configured to determine an arable land road corresponding to the ground information acquisition point based on the road network model, the arable land road information, the preset depth-first algorithm, and the preset greedy algorithm.
Illustratively, the stationing determination module 130 includes: a route traversing unit 131 and a stationing determination unit 132. Specifically, the route traversing unit 131 is configured to obtain an initial point and an end point; traversing a cultivated land road network in the ground road network model by utilizing a preset depth-first algorithm based on the initial point and the end point; acquiring a plurality of cultivated land roads with the traversal times exceeding the preset traversal times; and the point arrangement determining unit 132 is used for guiding the plurality of cultivated land roads into a preset greedy algorithm so as to determine cultivated land roads corresponding to the ground information acquisition points from the plurality of cultivated land roads.
It should be noted that the initial point and the end point may be determined manually, so that there are two points for the pre-set depth-first algorithm, so that the pre-set depth-first algorithm can run the traversal process. The predetermined number of passes may be obtained by one skilled in the art through a number of experiments.
In addition, the specific traversal process corresponding to the preset depth-first algorithm and the operation process of the preset greedy algorithm can be implemented by the existing method or technology, and are not limited herein.
In addition, the embodiment of the application also provides a remote sensing monitoring method for an arable land road, and as shown in fig. 2, the remote sensing monitoring system method for the arable land road provided by the embodiment of the application mainly comprises the following steps:
Illustratively, the server obtains a plurality of ground collected images corresponding to a preset cultivated land area by using a remote sensing technology, and the method specifically comprises the following steps: acquiring a plurality of original collected images corresponding to a preset cultivated land area by using a remote sensing technology; determining a signal domain corresponding to an original collected image by utilizing a Fourier transform algorithm; determining the detection number of the signal values in the signal domain which are larger than a preset signal threshold; and when the detection number is smaller than or equal to the preset number threshold value, determining that the signal and the corresponding original collected image are ground collected images.
And step 220, the edge computing node acquires the ground collected images, and performs common-finger reduction processing on the ground collected images based on the hypergraph theory to acquire cultivated land road information so as to establish a ground road network model corresponding to a preset cultivated land area.
As an example, acquiring a ground collected image, and performing a common-reference subtraction process on a plurality of ground collected images based on a hypergraph theory to acquire arable land road information specifically includes: acquiring a plurality of farmland road information corresponding to the ground acquisition image through image identification; the farmland road information comprises road routes, road route directions, road route weights and road intersection name sets; wherein the set of road junction names comprises: the name of a front intersection of a road, the names of a plurality of middle intersections of the road and the names of rear intersections of the road; detecting whether a road intersection name set corresponding to the current road route is intersected with a road intersection name set corresponding to any other road route; when the sets intersect and are the same; determining that the current road route and any other road route are the same route; deleting arable land road information corresponding to any other road route; when the sets are intersected and one set completely comprises the other set, deleting arable land road information corresponding to the small set; and when the sets are intersected and are partially intersected, carrying out information fusion on the farmland road information corresponding to the current road route and the farmland road information corresponding to any other road route based on the intersected parts, deleting the farmland road information corresponding to the original current road route and the farmland road information corresponding to any other road route, and acquiring the farmland road information after the common finger reduction.
And step 230, the server determines the farmland roads corresponding to the ground information acquisition points based on the road network model, the farmland road information, the preset depth-first algorithm and the preset greedy algorithm.
Exemplarily, determining a farmland road corresponding to the ground information acquisition point based on a road network model, farmland road information, a preset depth-first algorithm and a preset greedy algorithm, specifically comprising: acquiring an initial point and an end point; traversing a cultivated land road network in the ground road network model by utilizing a preset depth-first algorithm based on the initial point and the end point; acquiring a plurality of cultivated land roads with the traversal times exceeding the preset traversal times; and importing the plurality of cultivated land roads into a preset greedy algorithm so as to determine the cultivated land roads corresponding to the ground information acquisition points from the plurality of cultivated land roads.
So far, the technical solutions of the present disclosure have been described in connection with the foregoing embodiments, but it is easily understood by those skilled in the art that the scope of the present disclosure is not limited to only these specific embodiments. The technical solutions in the above embodiments can be split and combined, and equivalent changes or substitutions can be made on related technical features by those skilled in the art without departing from the technical principles of the present disclosure, and any changes, equivalents, improvements, and the like made within the technical concept and/or technical principles of the present disclosure will fall within the protection scope of the present disclosure.
Claims (8)
1. A remote sensing monitoring system for an arable road, the system comprising:
the remote sensing acquisition module is used for acquiring a plurality of ground acquisition images corresponding to a preset cultivated land area by using a remote sensing technology;
the image processing module is used for carrying out common-finger reduction processing on a plurality of ground collected images based on a hypergraph theory so as to obtain farmland road information and further establish a ground road network model corresponding to the preset farmland area;
and the point arrangement determining module is used for determining the cultivated land road provided with the ground information acquisition point based on the road network model, the cultivated land road information, the preset depth-first algorithm and the preset greedy algorithm.
2. The remote sensing monitoring system for cultivated land road according to claim 1, characterized in that said remote sensing acquisition module comprises: the system comprises an original image acquisition unit, an image preprocessing unit and a module determining unit;
the original image acquisition unit is used for acquiring a plurality of original acquisition images corresponding to a preset cultivated land area by using a remote sensing technology;
the image preprocessing unit is used for determining a signal domain corresponding to the originally acquired image by utilizing a Fourier transform algorithm; determining the detection number of the signal values in the signal domain which are larger than a preset signal threshold; when the detection number is smaller than or equal to a preset number threshold, determining that the signal and the corresponding original collected image are ground collected images;
the module determining unit is used for determining the processing number of the ground collected images to be processed corresponding to the plurality of image processing modules so as to send the newly determined ground collected images to the image processing module with the minimum processing number.
3. The remote sensing monitoring system for an arable road as claimed in claim 1, wherein the image processing module comprises: the system comprises a road processing unit, a common-finger reduction unit and a road modeling unit;
the road processing unit is used for acquiring a plurality of farmland road information corresponding to the ground collected image through image identification; the arable land road information comprises road routes, road route directions, road route weights and road intersection name sets; and the set of road junction names comprises: the name of a front intersection of a road, the names of a plurality of middle intersections of the road and the names of rear intersections of the road;
the common-finger reducing unit is used for detecting whether the road intersection name set corresponding to the current road route is intersected with the road intersection name set corresponding to any other road route; when the sets intersect and are the same; determining that the current road route and any other road route are the same route; deleting arable land road information corresponding to any other road route; when the sets are intersected and one set completely comprises the other set, deleting arable land road information corresponding to the small set; when the sets are intersected and are partially intersected, carrying out information fusion on the cultivated land road information corresponding to the current road route and the cultivated land road information corresponding to any other road route on the basis of the intersected parts, deleting the cultivated land road information corresponding to the original current road route and the cultivated land road information corresponding to any other road route, and acquiring the cultivated land road information after common finger reduction;
and the road modeling unit is used for establishing a ground road network model based on farmland road information after the common-finger-based reduction treatment.
4. The remote sensing monitoring system for an arable road of claim 1, wherein the stationing determination module comprises: a route traversing unit and a point arrangement determining unit;
the route traversing unit is used for acquiring an initial point and an end point; traversing the cultivated land road network in the ground road network model by utilizing a preset depth-first algorithm based on the initial point and the end point; acquiring a plurality of cultivated land roads with the traversal times exceeding the preset traversal times;
and the point distribution determining unit is used for leading the plurality of cultivated land roads into a preset greedy algorithm so as to determine the cultivated land roads corresponding to the ground information acquisition points from the plurality of cultivated land roads.
5. A remote sensing monitoring method for cultivated land roads, characterized in that the method comprises:
the server obtains a plurality of ground acquisition images corresponding to a preset cultivated land area by using a remote sensing technology; determining an edge calculation node corresponding to the ground collected image;
the edge computing node acquires ground collected images, and performs common-finger reduction processing on a plurality of ground collected images based on a hypergraph theory to acquire cultivated land road information, so as to establish a ground road network model corresponding to the preset cultivated land area;
the server determines the cultivated land road where the ground information acquisition point is installed based on the road network model, cultivated land road information, a preset depth-first algorithm and a preset greedy algorithm.
6. The remote sensing monitoring method for cultivated land roads according to claim 5, wherein the server obtains a plurality of ground collection images corresponding to a preset cultivated land area by using a remote sensing technology, and the method specifically comprises the following steps:
acquiring a plurality of original collected images corresponding to a preset cultivated land area by using a remote sensing technology;
determining a signal domain corresponding to the original collected image by utilizing a Fourier transform algorithm; determining the detection number of the signal values in the signal domain which are larger than a preset signal threshold; and when the detection number is smaller than or equal to a preset number threshold value, determining that the signal and the corresponding original collected image are ground collected images.
7. The remote sensing monitoring method for the cultivated land road according to claim 5, characterized in that the acquired ground images are acquired to perform a common-reference subtraction processing on a plurality of the acquired ground images based on the hypergraph theory to acquire cultivated land road information, and specifically comprises:
acquiring a plurality of farmland road information corresponding to the ground acquisition image through image identification; the arable land road information comprises road routes, road route directions, road route weights and road intersection name sets; wherein the set of road junction names comprises: the name of a front intersection of a road, the names of a plurality of middle intersections of the road and the names of rear intersections of the road;
detecting whether a road intersection name set corresponding to the current road route is intersected with a road intersection name set corresponding to any other road route;
when the sets intersect and are the same; determining that the current road route and any other road route are the same route; deleting arable land road information corresponding to any other road route;
when the sets are intersected and one set completely comprises the other set, deleting arable land road information corresponding to the small set;
when the sets are intersected and all the sets are partially intersected, the arable land road information corresponding to the current road route and the arable land road information corresponding to any other road route are subjected to information fusion based on the intersected portions, the arable land road information corresponding to the original current road route and the arable land road information corresponding to any other road route are deleted, and the arable land road information after common finger reduction is obtained.
8. The remote sensing monitoring method for the cultivated land road as claimed in claim 5, wherein the cultivated land road where the ground information collection point is installed is determined based on a road network model, cultivated land road information, a preset depth-first algorithm and a preset greedy algorithm, and specifically comprises:
acquiring an initial point and an end point; traversing the cultivated land road network in the ground road network model by utilizing a preset depth-first algorithm based on the initial point and the end point; acquiring a plurality of cultivated land roads with the traversal times exceeding the preset traversal times;
and importing the plurality of cultivated land roads into a preset greedy algorithm so as to determine the cultivated land roads corresponding to the ground information acquisition points from the plurality of cultivated land roads.
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