CN111274918B - River dryout and cutoff monitoring method and device based on multi-source remote sensing image - Google Patents
River dryout and cutoff monitoring method and device based on multi-source remote sensing image Download PDFInfo
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Abstract
The invention discloses a river dryout and flow break monitoring method and device based on a multi-source remote sensing image, belonging to the field of river monitoring and comprising the following steps: acquiring a multi-source satellite remote sensing image of a monitoring area, wherein the multi-source satellite remote sensing image comprises a meter-level remote sensing image and a sub-meter-level remote sensing image; preprocessing a multi-source satellite remote sensing image; calculating a normalized water body index by using the meter-level remote sensing image, and extracting the water body information of the main river; reversely cutting a trunk river water body based on the regional river channel buffer vector data to obtain a first-stage suspected dry river channel; analyzing a primary suspected dry river channel by using an object-oriented method based on a sub-meter-level remote sensing image to obtain water body information of the small river; and reversely cutting the primary suspected dry river channel by utilizing the information of the small river water body to obtain a secondary suspected dry river channel. The invention can realize comprehensive, objective, high-efficiency and dynamic supervision on the situation of dry and flow break of the river and provides technical support for evaluation, management, guarantee and restoration of the water environment of rivers and lakes.
Description
Technical Field
The invention relates to the field of river monitoring, in particular to a river dry-up and flow-break monitoring method and device based on a multi-source remote sensing image, a computer readable storage medium and equipment.
Background
The water quantity of a river and lake water system is the basis of the existence of the water system and plays an important role in the health of the water ecological environment, however, along with the global climate change and the rapid development of social economy, the unbalanced distribution and the unreasonable utilization of water resources cause the reduction of a large amount of water quantity of river sections in partial areas of China, even the dry and cutoff conditions occur, so that a plurality of hazards such as the reduction of underground water level, the aggravation of water resource crisis, the shrinkage of water environment capacity and the like are caused, and the water ecological environment of a drainage basin is seriously damaged. In order to master the water resource condition of rivers and lakes and find out the dry and cutoff nodes of the water system, the dry and cutoff areas of the rivers need to be quickly and accurately positioned, first-hand data and data are provided for the environment management department, and timely support is provided for the environment management department.
For a long time, the supervision of China on river water resources mainly depends on the traditional hydrological monitoring station, the traditional hydrological monitoring station mainly realizes the water quantity monitoring of rivers by setting monitoring sections in different river sections, and the supervision of a standing station is usually taken as a main part, and the patrol and automatic monitoring are taken as auxiliary parts.
The traditional hydrological monitoring station is limited in distribution points, so that the spatial distribution condition of river dryness and flow interruption in China is difficult to reflect comprehensively. In addition, some engineering construction of illegal wading development is hidden, a large amount of manpower, material resources and financial resources are consumed by simply relying on manual field investigation, and comprehensive investigation is difficult.
In recent years, remote sensing technology also gradually starts to play a role, and the application of the remote sensing technology in water resource monitoring mainly focuses on water area extraction, water level inversion and the like. However, the river water surface area extraction can only qualitatively judge the river water flowing condition, and can not quantitatively determine the flow cutoff degree indexes such as the dry cutoff flow cutoff length, the dry cutoff ratio and the like.
At present, the remote sensing technology based on visual interpretation can solve some disadvantages of the existing remote sensing technology, but visual interpretation needs to rely on human eyes to extract surface feature information from a sub-meter level fusion image, and has the advantages of large workload, low efficiency, large image storage space requirement, difficulty in meeting the requirement of processing large-area mass data in real time and difficulty in improving the intelligent level of environment monitoring.
Disclosure of Invention
In order to solve the technical problems, the invention provides a river dryness and flow break monitoring method and device based on a multi-source remote sensing image.
The technical scheme provided by the invention is as follows:
in a first aspect, the invention provides a river dryout and flow break monitoring method based on a multi-source remote sensing image, which comprises the following steps:
step 10: acquiring a multi-source satellite remote sensing image of a monitoring area, wherein the multi-source satellite remote sensing image comprises a meter-level remote sensing image and a sub-meter-level remote sensing image;
step 20: preprocessing the multi-source satellite remote sensing image;
step 30: calculating a normalized water body index by utilizing the preprocessed multispectral data of the meter-level remote sensing image, and extracting water body information of the main river;
step 40: reversely cutting a trunk river water body based on the regional river channel buffer vector data to obtain a first-stage suspected dry river channel;
step 50: analyzing the primary suspected dry river channel by using an object-oriented method based on the preprocessed sub-meter-level remote sensing image to obtain water body information of the small river;
step 60: and reversely cutting the primary suspected dry river channel by utilizing the information of the small river water body to obtain a secondary suspected dry river channel.
Further, after the step 40, the step 50 includes:
step 41: and removing river-crossing roads and bridges from the primary suspected dry river channel by using a set length threshold.
Further, the step 20 includes:
step 21: carrying out radiation correction, atmospheric correction and geometric correction on the meter-level remote sensing image and the sub-meter-level remote sensing image;
step 22: and performing remote sensing image fusion on the sub-meter remote sensing image.
Further, the normalized water body index is obtained by the following formula:
wherein NDWI is normalized water body index, rhoGreen、ρNIRThe remote sensing reflectivity of the green wave band and the near infrared wave band respectively.
In a second aspect, the present invention provides a river dryness and flow break monitoring device based on a multi-source remote sensing image, the device comprising:
the acquisition module is used for acquiring multi-source satellite remote sensing images of a monitoring area, wherein the multi-source satellite remote sensing images comprise meter-level remote sensing images and sub-meter-level remote sensing images;
the preprocessing module is used for preprocessing the multi-source satellite remote sensing image;
the main river water body information extraction module is used for calculating a normalized water body index by utilizing the multi-spectral data of the preprocessed meter-level remote sensing image and extracting main river water body information;
the primary suspected dry river acquisition module is used for reversely cutting a main river water body based on the regional river buffer vector data to obtain a primary suspected dry river;
the fine river water body information extraction module is used for analyzing the primary suspected dry river channel by utilizing an object-oriented method based on the preprocessed sub-meter-level remote sensing image to obtain fine river water body information;
and the secondary suspected dry river channel acquisition module is used for reversely cutting the primary suspected dry river channel by utilizing the information of the small river water body to obtain a secondary suspected dry river channel.
Further, the apparatus further comprises:
and the removing module is used for removing river-crossing roads and bridges from the primary suspected dry river channel by using the set length threshold.
Further, the preprocessing module comprises:
the correction unit is used for carrying out radiation correction, atmospheric correction and geometric correction on the meter-level remote sensing image and the sub-meter-level remote sensing image;
and the fusion unit is used for carrying out remote sensing image fusion on the sub-meter-level remote sensing image.
Further, the normalized water body index is obtained by the following formula:
wherein NDWI is normalized water body index, rhoGreen、ρNIRThe remote sensing reflectivity of the green wave band and the near infrared wave band respectively.
In a third aspect, the present invention provides a computer readable storage medium for river dry out cutout monitoring, comprising a memory for storing processor executable instructions, which when executed by the processor, implement the steps of the river dry out cutout monitoring method based on multi-source remote sensing images according to the first aspect.
In a fourth aspect, the present invention provides a device for river dryness flow break monitoring, which is characterized by comprising at least one processor and a memory storing computer executable instructions, wherein the processor executes the instructions to implement the steps of the river dryness flow break monitoring method based on the multi-source remote sensing image in the first aspect.
The invention has the following beneficial effects:
the river dryout and cutoff monitoring method based on the multi-source remote sensing images is based on meter-level and sub-meter-level remote sensing images and river channel vector data, water body information is repeatedly extracted and eliminated, and a suspected dryout and cutoff river channel is obtained. The invention overcomes the defects of incomplete monitoring, time and labor waste of the traditional hydrological monitoring station, and can realize water resource supervision in a large-range and comprehensive dynamic manner; the defect that the existing remote sensing monitoring can only qualitatively judge the water flowing condition of the river is overcome, the water flowing condition of the river can be qualitatively judged, the cutoff degree indexes such as the dry cutoff length, the dry ratio and the like can be quantitatively determined, and the intelligent level of the river dry cutoff monitoring is improved; the workload of visual interpretation is effectively reduced, the requirement on image storage space is reduced, the monitoring cost is reduced, and the monitoring efficiency is improved. Therefore, the invention can realize comprehensive, objective, efficient and dynamic supervision on the condition of dry and flow break of the river and provides technical support for evaluation, management, guarantee and restoration of the water environment of the river and lake.
Drawings
FIG. 1 is a flow chart of a river dryout and cutoff monitoring method based on a multi-source remote sensing image;
fig. 2 is a schematic diagram of the river dry-up and flow-break monitoring device based on the multi-source remote sensing image.
Detailed Description
In order to make the technical problems, technical solutions and advantages of the present invention more apparent, the following detailed description is given with reference to the accompanying drawings and specific embodiments.
Example 1:
the embodiment of the invention provides a river dryout and cutoff monitoring method based on a multi-source remote sensing image, which comprises the following steps of:
step 10: and acquiring a multi-source satellite remote sensing image of the monitoring area, wherein the multi-source satellite remote sensing image comprises a meter-level remote sensing image and a sub-meter-level remote sensing image.
The obtained multiple remote sensing image data of the same area are the multi-source remote sensing images, and the multiple remote sensing images can be multi-platform, multi-temporal, multi-spectrum, multi-sensor and multi-resolution remote sensing images.
The information provided by the multi-source remote sensing image data has redundancy, complementarity and cooperativity. Redundancy means that their representation, description or interpretation of the environment or object is the same; complementarity refers to information from different degrees of freedom and independent of each other; collaboration information is the fact that different sensors have dependencies on other information when observing and processing information.
In this step, a multi-source remote sensing image is obtained from a satellite, the multi-source satellite remote sensing image comprises a meter-level remote sensing image and a sub-meter-level remote sensing image, the meter-level remote sensing image refers to an image with a spatial resolution of more than 1 meter, and for example, the meter-level remote sensing image is obtained by a plurality of high-resolution serial satellites (not including high-resolution second satellites) in China. The sub-meter remote sensing image is an image with a spatial resolution of less than 1 meter, for example, the sub-meter remote sensing image is obtained by a high-grade second satellite and a Beijing second satellite in China, and the resolution is 0.8 meter.
Step 20: and preprocessing the multisource satellite remote sensing image, wherein the preprocessing can eliminate distortion, errors and the like of the remote sensing image.
Step 30: and calculating a normalized water body index by utilizing the preprocessed multispectral data of the meter-level remote sensing image, and extracting the water body information of the main river.
The NDWI (Normalized Difference Water Index) is a grayscale image representing Water information, and Normalized Difference processing is performed using a specific band of the remote sensing image to highlight the Water information in the image. The method uses the normalized water body index to extract the water body information in the image, judges the water body of the main river and has better effect.
After the NDWI is calculated, the NDWI of each pixel of the meter-level remote sensing image is compared with a preset threshold range, pixels meeting conditions (for example, falling within the preset threshold range) are water parts, and all pixels meeting the conditions form the water parts of the river, namely the water information of the main river.
Step 40: and reversely cutting the trunk river water body based on the regional river channel buffer vector data to obtain a first-stage suspected dry river channel.
The regional river channel buffer vector data are river channel vector data, namely a preset river range, and basic river channel vector data can be obtained from a national basic geographic information system terrain database; correcting the basic river channel vector data by using the control image to ensure that the river channel vector is positioned on the center line of the river channel; and setting a buffer range for the corrected river channel vector data, and obtaining regional river channel buffer vector data to obtain the range of the river.
In order to obtain the dry river channel area of the river, the main river water body information (the water body part of the river) is obtained in the step 30, and the main river water body is reversely cut by utilizing the regional river channel buffer vector data (the river range), so that the non-water body part in the river, namely the dry river channel of the river, can be obtained and is used as the first-level suspected dry river channel.
Step 50: and analyzing the primary suspected dry river channel by using an object-oriented method based on the preprocessed sub-meter-level remote sensing image to obtain the water body information of the small river.
The spatial resolution of the sub-meter-level remote sensing image is below 1 meter, the precision is higher, the invention obtains the water body information of the tiny river by using the sub-meter-level remote sensing image, and the adopted method is an object-oriented method.
The object-oriented method is also called object-oriented classification method. The multispectral remote sensing image extraction water body with object-oriented classification comprehensively considers information such as spectral characteristics, textures and structures. The method mainly comprises the steps of combining adjacent pixels with similar characteristics in an image into a homogeneous object by selecting a proper image segmentation method and a proper segmentation scale, constructing a water body characteristic knowledge base by integrating statistical characteristics of a target water body, and extracting the water body according to a corresponding image classification method.
Step 60: and reversely cutting the primary suspected dry river channel by utilizing the information of the small river water body to obtain a secondary suspected dry river channel.
The primary suspected dry river channel is obtained based on the meter-level remote sensing image and represents the dry condition of the main river with a wider water surface, so that the dry condition of the fine river cannot be well reflected.
After the secondary suspected dry river channel is obtained, the secondary suspected dry river channel can be directly used as the final situation of dry and cutoff of the river, and the secondary suspected dry river channel is analyzed and calculated, so that the water flowing situation of the river can be qualitatively judged, and cutoff degree indexes such as dry and cutoff length, dry and cutoff ratio and the like can be quantitatively determined.
The invention can also not directly use the secondary suspected dry river channel as the final situation of the dry and cut-off of the river, but further use artificial visual interpretation to check the secondary suspected dry river channel and determine the situation of the dry and cut-off of the river channel (cut-off degree indexes such as dry and cut-off length, dry and dry ratio and the like). Please note that the artificial visual interpretation is not the content protected by the present invention, and the present invention only provides data for the artificial visual interpretation, so that the artificial visual interpretation is not directly based on the original remote sensing image data, but based on the extracted secondary suspected dry river data, thereby effectively reducing the workload of the visual interpretation, reducing the image storage space requirement, reducing the monitoring cost, and improving the monitoring efficiency.
In conclusion, the river dryout and flow break monitoring method based on the multi-source remote sensing images repeatedly extracts and eliminates water body information based on meter-level and sub-meter-level remote sensing images and river channel vector data to obtain the suspected dryout and flow break river channel. The invention overcomes the defects of incomplete monitoring, time and labor waste of the traditional hydrological monitoring station, and can realize water resource supervision in a large-range and comprehensive dynamic manner; the defect that the existing remote sensing monitoring can only qualitatively judge the water flowing condition of the river is overcome, the water flowing condition of the river can be qualitatively judged, the cutoff degree indexes such as the dry cutoff length, the dry ratio and the like can be quantitatively determined, and the intelligent level of the river dry cutoff monitoring is improved; the workload of visual interpretation is effectively reduced, the requirement on image storage space is reduced, the monitoring cost is reduced, and the monitoring efficiency is improved. Therefore, the invention can realize comprehensive, objective, efficient and dynamic supervision on the condition of dry and flow break of the river and provides technical support for evaluation, management, guarantee and restoration of the water environment of the river and lake.
As a modification of the present invention, after step 40, step 50 includes:
step 41: and removing river-crossing roads and bridges from the primary suspected dry river channel by using a set length threshold.
Because the primary suspected dry riverway is obtained by reversely cutting the river area and the main river water body area, if river-crossing roads and bridges exist on the river, the roads and bridges can be mistakenly judged as dry riverways, namely the primary suspected dry riverway comprises the river-crossing roads and bridges, and the primary suspected dry riverway needs to be eliminated.
The river-crossing road and the bridge have the following characteristics: the length of the bridge is long (the length of a general river-crossing road and a bridge is larger than the width of a river), and the bridge is straight. By utilizing the characteristics of the river-crossing road and the bridge, if a certain area is straight and the length of the certain area exceeds a set length threshold value, the certain area is regarded as the river-crossing road and the bridge and is removed.
The multi-source satellite remote sensing image preprocessing method can be used for preprocessing the multi-source satellite remote sensing image through various methods, and exemplarily, the step 20 comprises the following steps:
step 21: and carrying out radiation correction, atmospheric correction and geometric correction on the meter-level remote sensing image and the sub-meter-level remote sensing image.
Radiometric correction refers to a process of correcting systematic and random radiation distortion or distortion due to external factors, data acquisition and transmission systems, and eliminating or reducing image distortion caused by radiation errors.
Atmospheric correction (atmospheric correction) is used for eliminating errors caused by atmospheric scattering, absorption and reflection.
And (3) geometric correction: in the remote sensing imaging process, due to the influences of factors such as the attitude, the height, the speed and the earth rotation of an aircraft, geometric distortion occurs to an image relative to a ground target, the distortion is expressed by extrusion, distortion, stretching, offset and the like of an actual position of a pixel relative to the ground target, and the error correction performed on the geometric distortion is called geometric correction.
Step 22: and performing remote sensing image fusion on the sub-meter remote sensing image.
Remote sensing imaging is the provision of data in different spectral bands of the electromagnetic spectrum at different spatial, temporal, spectral, and radiation resolutions. Due to different imaging principles and the limitation of technical conditions, the remote sensing data acquired by any single remote sensor (such as a satellite) cannot comprehensively reflect the characteristics of a target object, and each remote sensor has a certain application range and limitation.
If remote sensing data (multi-source remote sensing images) with various different characteristics are combined and mutually make up for deficiencies, respective advantages can be exerted, respective defects can be made up, ground targets can be more comprehensively reflected, and stronger information interpretation capability and more reliable analysis results are provided. The remote sensing image fusion is to perform operation processing on spatial or temporal redundant or complementary multi-source data according to a certain rule or algorithm to obtain more accurate and richer information than any single data, and generate a synthetic image with new spatial, spectral and temporal characteristics. The remote sensing image fusion not only expands the application range of each data, but also improves the analysis precision, the application effect and the practical value.
The normalized water body index is obtained by the following formula:
wherein NDWI is normalized water body index, rhoGreen、ρNIRThe remote sensing reflectivity of the green wave band and the near infrared wave band respectively.
Example 2:
the embodiment of the invention provides a river dryout and flow break monitoring device based on a multi-source remote sensing image, and as shown in fig. 2, the device comprises:
the acquisition module 1 is used for acquiring multisource satellite remote sensing images of a monitoring area, wherein the multisource satellite remote sensing images comprise meter-level remote sensing images and sub-meter-level remote sensing images.
And the preprocessing module 2 is used for preprocessing the multi-source satellite remote sensing image.
And the main river water body information extraction module 3 is used for calculating a normalized water body index by utilizing the preprocessed multispectral data of the meter-level remote sensing image and extracting the main river water body information.
And the primary suspected dry river channel acquisition module 4 is used for reversely cutting the main river water body based on the regional river channel buffer vector data to acquire a primary suspected dry river channel.
And the fine river water body information extraction module 5 is used for analyzing the primary suspected dry river channel by using an object-oriented method based on the preprocessed sub-meter-level remote sensing image to obtain fine river water body information.
And the secondary suspected dry river channel acquisition module 6 is used for reversely cutting the primary suspected dry river channel by utilizing the information of the small river water body to obtain a secondary suspected dry river channel.
The river dryout and cutoff monitoring device based on the multi-source remote sensing images repeatedly extracts and rejects water body information based on meter-level and sub-meter-level remote sensing images and river channel vector data to obtain a suspected dryout and cutoff river channel. The invention overcomes the defects of incomplete monitoring, time and labor waste of the traditional hydrological monitoring station, and can realize water resource supervision in a large-range and comprehensive dynamic manner; the defect that the existing remote sensing monitoring can only qualitatively judge the water flowing condition of the river is overcome, the water flowing condition of the river can be qualitatively judged, the cutoff degree indexes such as the dry cutoff length, the dry ratio and the like can be quantitatively determined, and the intelligent level of the river dry cutoff monitoring is improved; the workload of visual interpretation is effectively reduced, the requirement on image storage space is reduced, the monitoring cost is reduced, and the monitoring efficiency is improved. Therefore, the invention can realize comprehensive, objective, efficient and dynamic supervision on the condition of dry and flow break of the river and provides technical support for evaluation, management, guarantee and restoration of the water environment of the river and lake.
As an improvement of the present invention, the river dry-up and flow-out monitoring device based on the multi-source remote sensing image further comprises:
and the removing module is used for removing river-crossing roads and bridges from the primary suspected dry river channel by using the set length threshold.
The preprocessing module of the present invention comprises:
and the correction unit is used for carrying out radiation correction, atmospheric correction and geometric correction on the meter-level remote sensing image and the sub-meter-level remote sensing image.
And the fusion unit is used for carrying out remote sensing image fusion on the sub-meter-level remote sensing image.
Further, the normalized water body index is obtained by the following formula:
wherein NDWI is normalized water body index, rhoGreen、ρNIRThe remote sensing reflectivity of the green wave band and the near infrared wave band respectively.
The device provided by the embodiment of the present invention has the same implementation principle and technical effect as the method embodiment, and for the sake of brief description, reference may be made to the corresponding content in the method embodiment 1 without reference to the device embodiment. It is clear to those skilled in the art that, for convenience and brevity of description, the specific working processes of the apparatus and the unit described above may refer to the corresponding processes in the foregoing method embodiments, and are not described herein again.
Example 3:
the method provided by the embodiment of the present specification can implement the service logic through a computer program and record the service logic on a storage medium, and the storage medium can be read and executed by a computer, so as to implement the effect of the solution described in embodiment 1 of the present specification. Accordingly, the present invention also provides a computer readable storage medium for river dryout cutout monitoring, comprising a memory for storing processor executable instructions which, when executed by the processor, implement the steps of the method for river dryout cutout monitoring based on multi-source remote sensing imagery, comprising embodiment 1.
The invention can realize comprehensive, objective, high-efficiency and dynamic supervision on the situation of dry and flow break of the river and provides technical support for evaluation, management, guarantee and restoration of the water environment of rivers and lakes.
The storage medium may include a physical device for storing information, and typically, the information is digitized and then stored using an electrical, magnetic, or optical media. The storage medium may include: devices that store information using electrical energy, such as various types of memory, e.g., RAM, ROM, etc.; devices that store information using magnetic energy, such as hard disks, floppy disks, tapes, core memories, bubble memories, and usb disks; devices that store information optically, such as CDs or DVDs. Of course, there are other ways of storing media that can be read, such as quantum memory, graphene memory, and so forth.
The above description of the storage medium according to the method embodiment may also include other implementations. The specific implementation manner may refer to the description of the related method embodiment 1, and is not described in detail here.
Example 4:
the invention also provides a device for river dry-out flow break monitoring, which can be a single computer, and can also comprise an actual operation device and the like using one or more methods or devices of one or more embodiments in the specification. The device for river dryout flow break monitoring may comprise at least one processor and a memory storing computer-executable instructions, wherein the processor executes the instructions to implement the steps of the river dryout flow break monitoring method based on multi-source remote sensing images according to any one or more of embodiments 1.
The invention can realize comprehensive, objective, high-efficiency and dynamic supervision on the situation of dry and flow break of the river and provides technical support for evaluation, management, guarantee and restoration of the water environment of rivers and lakes.
The above description of the device according to the method or apparatus embodiment may also include other implementation manners, and a specific implementation manner may refer to the description of related method embodiment 1, which is not described in detail herein.
It should be noted that, the above-mentioned apparatus or system in this specification may also include other implementation manners according to the description of the related method embodiment, and a specific implementation manner may refer to the description of the method embodiment, which is not described herein in detail. The embodiments in the present specification are described in a progressive manner, and the same and similar parts among the embodiments are referred to each other, and each embodiment focuses on the differences from the other embodiments. In particular, for the hardware + program class, storage medium + program embodiment, since it is basically similar to the method embodiment, the description is relatively simple, and for the relevant points, refer to the partial description of the method embodiment.
The foregoing description has been directed to specific embodiments of this disclosure. Other embodiments are within the scope of the following claims. In some cases, the actions or steps recited in the claims may be performed in a different order than in the embodiments and still achieve desirable results. In addition, the processes depicted in the accompanying figures are not necessarily required to be in the particular order shown or in sequential order to achieve desirable results. In some embodiments, multitasking and parallel processing may also be possible or may be advantageous.
The systems, devices, modules or units illustrated in the above embodiments may be implemented by a computer chip or an entity, or by a product with certain functions. One typical implementation device is a computer. In particular, the computer may be, for example, a personal computer, a laptop computer, a vehicle-mounted human-computer interaction device, a cellular telephone, a camera phone, a smart phone, a personal digital assistant, a media player, a navigation device, an email device, a game console, a tablet computer, a wearable device, or a combination of any of these devices.
For convenience of description, the above devices are described as being divided into various modules by functions, and are described separately. Of course, when implementing one or more of the present description, the functions of each module may be implemented in one or more software and/or hardware, or a module implementing the same function may be implemented by a combination of multiple sub-modules or sub-units, etc. The above-described embodiments of the apparatus are merely illustrative, and for example, the division of the units is only one logical division, and other divisions may be realized in practice, for example, a plurality of units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, devices or units, and may be in an electrical, mechanical or other form.
Those skilled in the art will also appreciate that, in addition to implementing the controller as pure computer readable program code, the same functionality can be implemented by logically programming method steps such that the controller is in the form of logic gates, switches, application specific integrated circuits, programmable logic controllers, embedded microcontrollers and the like. Such a controller may therefore be considered as a hardware component, and the means included therein for performing the various functions may also be considered as a structure within the hardware component. Or even means for performing the functions may be regarded as being both a software module for performing the method and a structure within a hardware component.
The present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
In a typical configuration, a computing device includes one or more processors (CPUs), input/output interfaces, network interfaces, and memory.
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 like elements in a process, method or apparatus that comprises the element.
As will be appreciated by one skilled in the art, one or more embodiments of the present description may be provided as a method, system, or computer program product. Accordingly, one or more embodiments of the present description may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, one or more embodiments of the present description may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
One or more embodiments of the present description may be described in the general context of computer-executable instructions, such as program modules, being executed by a computer. Generally, program modules include routines, programs, objects, components, data structures, etc. that perform particular tasks or implement particular abstract data types. One or more embodiments of the specification may also be practiced in distributed computing environments where tasks are performed by remote processing devices that are linked through a communications network. In a distributed computing environment, program modules may be located in both local and remote computer storage media including memory storage devices.
The embodiments in the present specification are described in a progressive manner, and the same and similar parts among the embodiments are referred to each other, and each embodiment focuses on the differences from the other embodiments. In particular, for the system embodiment, since it is substantially similar to the method embodiment, the description is simple, and for the relevant points, reference may be made to the partial description of the method embodiment. In the description of the specification, reference to the description of the term "one embodiment," "some embodiments," "an example," "a specific example," or "some examples," etc., means that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the specification. In this specification, the schematic representations of the terms used above are not necessarily intended to refer to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples. Furthermore, various embodiments or examples and features of different embodiments or examples described in this specification can be combined and combined by one skilled in the art without contradiction.
Finally, it should be noted that: the above-mentioned embodiments are only specific embodiments of the present invention, which are used for illustrating the technical solutions of the present invention and not for limiting the same, and the protection scope of the present invention is not limited thereto, although the present invention is described in detail with reference to the foregoing embodiments, those skilled in the art should understand that: any person skilled in the art can modify or easily conceive the technical solutions described in the foregoing embodiments or equivalent substitutes for some technical features within the technical scope of the present disclosure; such modifications, changes or substitutions do not depart from the spirit and scope of the present invention in its spirit and scope. Are intended to be covered by 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 (10)
1. A river dry-up and flow-break monitoring method based on multi-source remote sensing images is characterized by comprising the following steps:
step 10: acquiring a multi-source satellite remote sensing image of a monitoring area, wherein the multi-source satellite remote sensing image comprises a meter-level remote sensing image and a sub-meter-level remote sensing image;
step 20: preprocessing the multi-source satellite remote sensing image;
step 30: calculating a normalized water body index by utilizing the preprocessed multispectral data of the meter-level remote sensing image, and extracting water body information of the main river;
step 40: reversely cutting a trunk river water body based on the regional river channel buffer vector data to obtain a first-stage suspected dry river channel;
step 50: analyzing the primary suspected dry river channel by using an object-oriented method based on the preprocessed sub-meter-level remote sensing image to obtain water body information of the small river;
step 60: and reversely cutting the primary suspected dry river channel by utilizing the information of the small river water body to obtain a secondary suspected dry river channel.
2. The method for monitoring river dryness and flow interruption based on the multi-source remote sensing image according to claim 1, wherein after the step 40, the step 50 comprises the following steps:
step 41: and removing river-crossing roads and bridges from the primary suspected dry river channel by using a set length threshold.
3. The method for monitoring river dry-out flow interruption based on the multi-source remote sensing image according to claim 1, wherein the step 20 comprises:
step 21: carrying out radiation correction, atmospheric correction and geometric correction on the meter-level remote sensing image and the sub-meter-level remote sensing image;
step 22: and performing remote sensing image fusion on the sub-meter remote sensing image.
4. The method for monitoring river dry-out and flow break based on the multi-source remote sensing image according to any one of claims 1 to 3, wherein the normalized water body index is obtained by the following formula:
wherein NDWI is normalized water body index, rhoGreen、ρNIRRespectively green band and near infraredRemote sensing reflectivity of the band.
5. A river drying and flow breaking monitoring device based on multi-source remote sensing images is characterized by comprising:
the acquisition module is used for acquiring multi-source satellite remote sensing images of a monitoring area, wherein the multi-source satellite remote sensing images comprise meter-level remote sensing images and sub-meter-level remote sensing images;
the preprocessing module is used for preprocessing the multi-source satellite remote sensing image;
the main river water body information extraction module is used for calculating a normalized water body index by utilizing the multi-spectral data of the preprocessed meter-level remote sensing image and extracting main river water body information;
the primary suspected dry river acquisition module is used for reversely cutting a main river water body based on the regional river buffer vector data to obtain a primary suspected dry river;
the fine river water body information extraction module is used for analyzing the primary suspected dry river channel by utilizing an object-oriented method based on the preprocessed sub-meter-level remote sensing image to obtain fine river water body information;
and the secondary suspected dry river channel acquisition module is used for reversely cutting the primary suspected dry river channel by utilizing the information of the small river water body to obtain a secondary suspected dry river channel.
6. The device for monitoring river dry-out flow interruption based on multisource remote sensing images of claim 5, wherein the device further comprises:
and the removing module is used for removing river-crossing roads and bridges from the primary suspected dry river channel by using the set length threshold.
7. The device for monitoring river dry out flow interruption based on the multi-source remote sensing image according to claim 5, wherein the preprocessing module comprises:
the correction unit is used for carrying out radiation correction, atmospheric correction and geometric correction on the meter-level remote sensing image and the sub-meter-level remote sensing image;
and the fusion unit is used for carrying out remote sensing image fusion on the sub-meter-level remote sensing image.
8. The device for monitoring river dry-out and flow break based on the multi-source remote sensing image according to any one of claims 5 to 7, wherein the normalized water body index is obtained by the following formula:
wherein NDWI is normalized water body index, rhoGreen、ρNIRThe remote sensing reflectivity of the green wave band and the near infrared wave band respectively.
9. A computer readable storage medium for river dryout cutout monitoring, comprising a memory for storing processor executable instructions which, when executed by the processor, perform steps comprising the method for river dryout cutout monitoring based on multi-source remote sensing imagery according to any one of claims 1 to 4.
10. An apparatus for river dryout flow break monitoring, comprising at least one processor and a memory storing computer executable instructions, the processor implementing the steps of the method for river dryout flow break monitoring based on multi-source remote sensing imagery according to any one of claims 1 to 4 when executing the instructions.
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| CN112528871B (en) * | 2020-12-14 | 2022-08-02 | 中科海慧（天津）科技有限公司 | River channel sand mining identification method and device, electronic equipment and storage medium |
| CN112697232A (en) * | 2020-12-15 | 2021-04-23 | 自然资源部国土卫星遥感应用中心 | Water level measurement and change monitoring method and device based on multi-source satellite height measurement data |
| CN113033381B (en) * | 2021-03-23 | 2021-09-10 | 生态环境部卫星环境应用中心 | Remote sensing data-based automatic extraction method and device for mine and solid waste landfill |
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