Method and device for evaluating water area shoreline condition of river, lake and reservoir based on remote sensing interpretation

Abstract

This application relates to the field of ecological and environmental protection technology, and in particular to a method and apparatus for evaluating the health of river, lake, and reservoir shoreline conditions based on remote sensing interpretation. The method involves detecting remote sensing images that identify the local shoreline environment of rivers, lakes, and reservoirs; performing species detection on the remote sensing images to identify aquatic species information contained within them; performing clustering processing on the aquatic species information to obtain at least one type of species information; and searching for disaster early warning schemes associated with the river, lake, and reservoir based on the at least one type of species information to determine disaster early warning scheme information that matches the local shoreline environment. This invention reduces the workload of investigations, improves the safety of personnel operations, and enhances the accuracy of data collection. Overall, it improves the efficiency of the river chief system work—river, lake, and reservoir health assessment—river, lake, and reservoir shoreline stability index survey, and has significant social and technical benefits.

Description

Technical Field

[0001] This application relates to the field of ecological and environmental protection technology, and in particular to a method and apparatus for evaluating the health of river, lake and reservoir shoreline conditions based on remote sensing interpretation. Background Technology

[0002] Currently, the investigation of river and lake bank stability indicators in the river chief system's health assessment of rivers, lakes, and reservoirs requires on-site determination of factors such as bank slope height, slope angle, bank / shore vegetation coverage, substrate (type), river / lake / reservoir bank erosion status, degree of illegal development and utilization of water areas and shorelines, and the condition of structures. This process currently suffers from drawbacks, including a large workload for on-site investigation and measurement, long processing time, unsuitable terrain for manual labor, and significant deviations in values ​​obtained through manual estimation. Summary of the Invention

[0003] To achieve the above objectives, this application provides the following technical solution: According to a first aspect of the present invention, the present invention claims protection for a method for evaluating the health of river, lake, and reservoir shoreline conditions based on remote sensing interpretation, comprising: Remote sensing images that identify the local waterfront environment of rivers, lakes, and reservoirs; wherein, the remote sensing images contain information on aquatic species in the biological scenes associated with the local waterfront environment; Species detection is performed on the remote sensing image to detect the aquatic species information contained in the remote sensing image; The aquatic species information is clustered to obtain at least two types of species information; Based on the information of at least two species, a search is conducted among the disaster early warning schemes associated with the rivers, lakes, and reservoirs to determine the disaster early warning scheme information that matches the local waterfront environment.

[0004] Furthermore, the step of searching through the disaster early warning schemes associated with the rivers, lakes, and reservoirs based on the information of the at least two types of species to determine the disaster early warning scheme information that matches the local aquatic environment includes: Determine the abundance value for each species category; Based on the abundance value of each species information, the disaster early warning schemes associated with the rivers, lakes and reservoirs are searched to determine the disaster early warning scheme information that matches the local waterfront environment.

[0005] Further, wherein the abundance value based on the information of each species is searched in the disaster early warning schemes associated with the rivers, lakes, and reservoirs to determine the disaster early warning scheme information that matches the local aquatic environment, including: When the abundance value of the first type of species information is before that of the second type of species information, the first type of species information is searched in the disaster early warning scheme associated with the river, lake and reservoir to determine the first disaster early warning scheme information containing the first type of species information, and the first disaster early warning scheme information contains the nearest neighbor of the first type of species information. Search for the second type of species information in the first disaster early warning scheme information, determine the second disaster early warning scheme information containing the second type of species information, and the second disaster early warning scheme information contains the nearest neighbor of the second type of species information. Use a similar method to search until the information of each type of species has been searched. The disaster early warning scheme information containing information on the last type of species will be used as the disaster early warning scheme information that is matched with the local waterfront environment.

[0006] Further, the step of searching for the second type of species information in the first disaster early warning scheme information includes: Determine the first habitat of the first type of species information in the biological scene and the second habitat of the second type of species information in the biological scene; When the first habitat is before the second habitat, search for the second species information downstream of the first species information in the first disaster early warning scheme information; or, when the first habitat is after the second habitat, search for the second species information upstream of the first species information in the first disaster early warning scheme information.

[0007] Furthermore, the search based on the at least two types of species information within the disaster early warning scheme associated with the river, lake, and reservoir includes: Based on the metadata in the at least two types of species information, disaster early warning schemes associated with the rivers, lakes, and reservoirs are found in the biological application of disaster early warning schemes; The search is performed in the disaster early warning scheme based on the information of at least two types of species.

[0008] Furthermore, the remote sensing images of the local waterfront environment of the detected and identified rivers, lakes, and reservoirs include: Based on the activation operation of the controls in the biological list of the disaster early warning scheme, the binocular camera is turned on; Based on the shooting operation of the binocular camera, remote sensing images of the local waterfront environment of rivers, lakes and reservoirs are detected.

[0009] Furthermore, the remote sensing images of the local waterfront environment of the detected and identified rivers, lakes, and reservoirs include: Detect the user's activated and followed habitats during the shooting process; The species information associated with the habitat of interest is identified as the local riparian environment of the river, lake, and reservoir.

[0010] Furthermore, the at least two types of species information include information on species within the same class, information on species from different classes, and any two of a predetermined number of families and genera.

[0011] According to a second aspect of the present invention, the present invention claims protection for a device for assessing the health of river, lake, and reservoir shoreline conditions based on remote sensing interpretation, comprising: One or more processors; A memory having stored one or more programs, which, when executed by the one or more processors, cause the one or more processors to perform the following operations: Remote sensing images that identify the local waterfront environment of rivers, lakes, and reservoirs; wherein, the remote sensing images contain information on aquatic species in the biological scenes associated with the local waterfront environment; Species detection is performed on the remote sensing image to detect the aquatic species information contained in the remote sensing image; The aquatic species information is clustered to obtain at least two types of species information; Based on the information of at least two species, a search is conducted in the disaster early warning schemes associated with the rivers, lakes and reservoirs to determine the disaster early warning scheme information that matches the local waterfront environment; The aforementioned device for evaluating the health of river, lake, and reservoir water area and shoreline based on remote sensing interpretation is used to execute the aforementioned method for evaluating the health of river, lake, and reservoir water area and shoreline based on remote sensing interpretation.

[0012] This application relates to the field of ecological and environmental protection technology, and in particular to a method and apparatus for evaluating the health of river, lake, and reservoir shorelines based on remote sensing interpretation. The method involves detecting remote sensing images that identify the local shoreline environment of rivers, lakes, and reservoirs; performing species detection on the remote sensing images to identify aquatic species information contained within them; performing clustering processing on the aquatic species information to obtain at least two types of species information; and searching for disaster early warning schemes associated with the rivers, lakes, and reservoirs based on the at least two types of species information to determine disaster early warning scheme information that matches the local shoreline environment. This invention reduces the workload of investigations, improves the safety of personnel during operations, and enhances the accuracy of data collection. Overall, it improves the efficiency of the river chief system work—river, lake, and reservoir health assessment—and the investigation of river, lake, and reservoir shoreline stability indicators, demonstrating significant social and technical benefits. Attached Figure Description

[0013] Figure 1 A flowchart illustrating a method for evaluating the health of river, lake, and reservoir shoreline conditions based on remote sensing interpretation, as claimed in this application. Figure 2A schematic diagram of the second process of a method for evaluating the health of water area shoreline based on remote sensing interpretation, as claimed in an embodiment of this application; Figure 3 A schematic diagram of the third process of a method for evaluating the health of water area shoreline based on remote sensing interpretation of a river, lake and reservoir, as claimed in an embodiment of this application; Figure 4 This is a schematic diagram of the fourth process of a method for evaluating the health of river, lake and reservoir shoreline based on remote sensing interpretation, as claimed in the embodiments of this application. Figure 5 This is a structural diagram of a device for evaluating the health of river, lake, and reservoir shoreline conditions based on remote sensing interpretation, as claimed in an embodiment of this application. Detailed Implementation

[0014] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only one embodiment of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of this application.

[0015] The terms "first," "second," and "third" in this application are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Therefore, a feature defined as "first," "second," or "third" may explicitly or implicitly include at least one of that feature. In the description of this application, "multiple" means at least two, such as two, three, etc., unless otherwise explicitly specified. All directional indications (such as up, down, left, right, front, back, etc.) in the embodiments of this application are only used to explain the relative habitat relationships, movement, etc., between components in a specific posture (as shown in the figures). If the specific posture changes, the directional indication will change accordingly. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion. For example, a process, method, system, product, or device that includes a series of steps or units is not limited to the listed steps or units, but may optionally include steps or units not listed, or may optionally include other steps or units inherent to these processes, methods, products, or devices.

[0016] In this document, the term "embodiment" means that a particular feature, structure, or characteristic described in connection with an embodiment may be included in at least one embodiment of this application. The appearance of this phrase in various places throughout the specification does not necessarily refer to the same embodiment, nor is it a separate or alternative embodiment that is mutually exclusive with other embodiments. It will be explicitly and implicitly understood by those skilled in the art that the embodiments described herein can be combined with other embodiments.

[0017] Example 1 Figure 1 This document illustrates a flowchart of a method for evaluating the health of river, lake, and reservoir shorelines based on remote sensing interpretation, as provided in Embodiment 1 of the present invention. The method is executed by a remote sensing interpretation-based shoreline evaluation device, which can be implemented in software or hardware and can be integrated into a terminal device or server. The terminal device can be, for example, a mobile phone terminal, a computer terminal, a bioreactor, and / or a smart wearable device, while the server can be a bioapplication server for disaster early warning schemes.

[0018] like Figure 1 As shown, the method includes: Step S110: Detect remote sensing images that identify the local waterfront environment of rivers, lakes, and reservoirs; wherein, the remote sensing images contain information on aquatic species in the biological scenes associated with the local waterfront environment.

[0019] Specifically, users often carry disaster warning plans rather than river, lake, and reservoir records when traveling. However, because the biological experience of disaster warning plans is not as good as that of rivers, lakes, and reservoirs, rivers, lakes, and reservoirs remain the primary source of biological information at home. When using river, lake, and reservoir records in conjunction with disaster warning plans, it is necessary to synchronize the waterfront environment of both rivers, lakes, reservoirs, and disaster warning plans. For example, a control can be provided in the electronic biological list to which the disaster early warning scheme belongs. By activating this control, the water area shoreline status evaluation device based on remote sensing interpretation of the river, lake and reservoir health provided in this embodiment of the invention will turn on the binocular camera and display the shooting interface according to the activation operation of the control in the biological list of the disaster early warning scheme. The user moves the binocular camera of the water area shoreline status evaluation device based on remote sensing interpretation of the river, lake and reservoir health to the local water area shoreline environment associated biological scene of the river, lake and reservoir, and shoots the aquatic species information that identifies the local water area shoreline environment in the biological scene (e.g., a corner of the biological scene, a paragraph of the biological scene, or a line of the biological scene). For example, by activating the shooting detection control, the water area shoreline status evaluation device based on remote sensing interpretation of the river, lake and reservoir health provided in this embodiment of the invention will detect the remote sensing image that identifies the local water area shoreline environment of the river, lake and reservoir according to the shooting operation of the binocular camera.

[0020] If a shot is unsuccessful, a list will appear containing a reshoot control. By activating the reshoot control, the remote sensing interpretation-based water area shoreline condition evaluation device for rivers, lakes, and reservoirs provided in this embodiment of the invention will re-detect the remote sensing image identifying the local waterfront environment of the river, lake, and reservoir based on the shooting operation of the binocular camera.

[0021] Step S120: Species detection is performed on the remote sensing image to detect aquatic species information contained in the remote sensing image.

[0022] Specifically, species detection algorithms, such as OCR technology, can be used to detect aquatic species information contained in remote sensing images. This aquatic species information can be from a specific corner of a river, lake, or reservoir scene; it doesn't need to be the species information for the entire page of the scene. Furthermore, the species information can be continuous (each row complete) or discontinuous (the information in each row doesn't connect).

[0023] Step S130: Cluster the aquatic species information to obtain at least two types of species information.

[0024] The clustering method can be to group species information of the same class into one group, species information of different classes into another group, or to extract a preset number of metadata from species information of the same class or several rows as one group. The associated species information includes species information of the same class, species information of different classes, or a preset number of families and genera, etc. There are no specific limitations here.

[0025] Step S140: Based on information on at least two types of species, search for disaster early warning schemes associated with rivers, lakes, and reservoirs to determine disaster early warning scheme information that matches the local waterfront environment.

[0026] The at least two types of species information may contain metadata, which can be used to find disaster early warning schemes associated with rivers, lakes, and reservoirs in the biological application of disaster early warning schemes. Specifically, this metadata can be detected in the following ways: First, perform correlation calculations on the species information in the remote sensing image, and use the attribute group that appears most frequently as the family and genus. Second, pre-establish an attribute database associated with or possessing obvious characteristics of associated disaster early warning schemes for rivers, lakes, and reservoirs, match the attribute groups after correlation calculation with the attribute groups in the database, and use the successfully matched attribute groups as metadata. If the at least two types of species information do not contain metadata that can be used to find associated disaster early warning schemes in the biological application of disaster early warning schemes, then the associated disaster early warning schemes for the rivers, lakes, and reservoirs can be found through manual operation.

[0027] Specifically, after identifying disaster early warning schemes associated with rivers, lakes, and reservoirs, information on various species can be searched within these schemes to obtain information on disaster early warning schemes associated with each species. The intersection of these schemes then determines the disaster early warning scheme that best matches the local riparian environment. Alternatively, disaster early warning schemes containing information on related species can be searched sequentially within the river, lake, and reservoir-associated disaster early warning schemes according to a preset order. By gradually narrowing down the scope of disaster early warning scheme information, the scheme that best matches the local riparian environment can be determined. This preset order can be based on abundance values ​​or habitat order within the river, lake, or reservoir, as described in Examples 2 and 3 below.

[0028] Therefore, this embodiment does not have high requirements for the acquisition of remote sensing images. The remote sensing images can contain information on aquatic species, and based on this information, the progress of river, lake, reservoir and disaster early warning schemes can still be synchronized.

[0029] Example 2 Figure 2 This document illustrates a flowchart of a method for evaluating the health of river, lake, and reservoir shoreline conditions based on remote sensing interpretation, as provided in Embodiment 2 of the present invention. The method described in this embodiment is a further optimization of the method in Embodiment 1.

[0030] like Figure 2 As shown, the method includes: Step S210: Detect remote sensing images that identify the local waterfront environment of rivers, lakes, and reservoirs; wherein, the remote sensing images contain information on aquatic species in the biological scenes associated with the local waterfront environment.

[0031] Step S220: Species detection is performed on the remote sensing image to detect aquatic species information contained in the remote sensing image.

[0032] Step S230: Cluster the aquatic species information to obtain at least two types of species information.

[0033] Step S240: Determine the abundance value of each species information.

[0034] Specifically, abundance values ​​can be determined based on the habitat order of species information in rivers, lakes, and reservoirs. For example, the abundance value of a species information that appears earlier in the habitat is higher than that of a species that appears later in the habitat. Alternatively, abundance values ​​can be determined based on the importance of species information.

[0035] Optionally, the abundance value of each type of information species can be determined based on the salience, or rarity, of the species information. Specifically, the higher the rarity of the species information, the higher its abundance value will appear. Since higher rarity indicates that the species information is more special and its generality is lower, these species information will be searched first, thus narrowing the search results and enabling faster matching and synchronization.

[0036] Step S250: Based on the abundance value of each species information, search in the disaster early warning schemes associated with rivers, lakes and reservoirs to determine the disaster early warning scheme information that matches the local water and shore environment.

[0037] Specifically, after determining the abundance value of each species type, a search can be performed on disaster early warning schemes associated with rivers, lakes, and reservoirs based on this abundance value. For example, one possible search method is as follows: when the abundance value of the first species type is higher than that of the second species type, the first species type is searched in the disaster early warning schemes associated with rivers, lakes, and reservoirs to determine the first disaster early warning scheme containing the first species type, and the first disaster early warning scheme containing the nearest neighbor of the first species type; the second species type is searched in the first disaster early warning scheme to determine the second disaster early warning scheme containing the second species type, and the second disaster early warning scheme containing the nearest neighbor of the second species type, and so on, until each species type has been searched; the disaster early warning scheme containing the last species type is taken as the disaster early warning scheme matching the local waterfront environment. By gradually narrowing down the disaster early warning scheme information in this way, the disaster early warning scheme matching the local waterfront environment can be found more quickly and efficiently.

[0038] To further improve the search rate, one possible implementation of searching for the second type of species information in the first disaster early warning scheme information is as follows: determine the first type of species information in the first habitat of the biological scene and the second type of species information in the second habitat of the biological scene; when the first habitat is before the second habitat, search for the second type of species information downstream of the first type of species information in the first disaster early warning scheme information; or, when the first habitat is after the second habitat, search for the second type of species information upstream of the first type of species information in the first disaster early warning scheme information.

[0039] Therefore, this embodiment can further improve the search speed and efficiency by determining the abundance value of each species information, achieve paper-to-electronic synchronization faster and more efficiently, and has low requirements for remote sensing image acquisition. The remote sensing images can contain aquatic species information, and the progress of river, lake, reservoir and disaster early warning schemes can still be synchronized based on this aquatic species information.

[0040] Example 3 Figure 3 This document illustrates a flowchart of a method for evaluating the health of river, lake, and reservoir shoreline conditions based on remote sensing interpretation, according to Embodiment 3 of the present invention. The method described in this embodiment is a further optimization of the method in Embodiment 1.

[0041] like Figure 3 As shown, the method includes: Step S310: Detect remote sensing images that identify the local waterfront environment of rivers, lakes, and reservoirs; wherein, the remote sensing images contain information on aquatic species in the biological scene associated with the local waterfront environment.

[0042] Step S320: Species detection is performed on the remote sensing image to detect aquatic species information contained in the remote sensing image.

[0043] Step S330: Cluster the aquatic species information to obtain at least two types of species information.

[0044] Step S340: Determine the habitat of each species in the biological scene associated with the local waterfront environment of rivers, lakes and reservoirs.

[0045] Step S350: Based on the habitat information of each species, search for disaster early warning schemes associated with rivers, lakes and reservoirs to determine disaster early warning scheme information that matches the local waterfront environment.

[0046] Specifically, when the habitat of the first type of species information is located before the second type of species information, the first type of species information is searched in the disaster early warning schemes associated with rivers, lakes, and reservoirs to determine the first disaster early warning scheme information containing the first type of species information, and the first disaster early warning scheme information contains the neighbors of the first type of species information; downstream of the first type of species information in the first disaster early warning scheme information, the second type of species information is searched to determine the second disaster early warning scheme information containing the second type of species information, and the second disaster early warning scheme information contains the neighbors of the second type of species information. Further, when the habitat of the second type of species information is located before the third type of species information, the third type of species information is searched downstream of the second type of species information in the second disaster early warning scheme information to determine the second disaster early warning scheme information containing the third type of species information, and the third disaster early warning scheme information contains the neighbors of the third type of species information. A similar search method is used until each type of species information has been searched; the disaster early warning scheme information containing the last type of species information is taken as the disaster early warning scheme information that matches the local waterfront environment. By gradually narrowing down the disaster early warning scheme information in this way, the disaster early warning scheme information that matches the local waterfront environment can be matched more quickly and efficiently.

[0047] Therefore, this embodiment can further improve the search speed and efficiency by searching and determining the disaster early warning scheme associated with rivers, lakes and reservoirs based on the habitat order of each species information, and achieve paper-to-electronic synchronization more quickly and efficiently. Moreover, it does not have high requirements for the acquisition of remote sensing images, and the remote sensing images can contain aquatic species information. Based on this aquatic species information, the progress synchronization of rivers, lakes and reservoirs and disaster early warning schemes can still be achieved.

[0048] Example 4 Figure 4 This document illustrates a flowchart of a method for evaluating the health of river, lake, and reservoir shoreline conditions based on remote sensing interpretation, as provided in Embodiment 4 of the present invention. The method described in this embodiment is a further optimization of the method in Embodiment 1.

[0049] like Figure 4 As shown, the method includes: Step S410: Based on the activation operation of the control in the biological list of the disaster early warning scheme, turn on the binocular camera and make the binocular camera focus on the species information related to the local waterfront environment.

[0050] Step S420: Based on the shooting operation of the binocular camera, detect the habitats of interest activated by the user during the shooting process, and determine the species information associated with the habitats of interest as local waterfront environments of rivers, lakes and reservoirs.

[0051] Step S430: Species detection is performed on the aquatic species information of the habitat of interest in the remote sensing image.

[0052] Step S440: Cluster the aquatic species information to obtain at least two types of species information.

[0053] Step S450: Determine the habitat of each species in the biological scene associated with the local riparian environment of rivers, lakes and reservoirs.

[0054] Step S460: Based on the habitat information of each species, search for disaster early warning schemes associated with rivers, lakes and reservoirs to determine disaster early warning scheme information that matches the local waterfront environment.

[0055] Therefore, this embodiment can achieve more accurate positioning when searching by focusing on species information associated with the local waterfront environment, thereby achieving faster and more efficient paper-to-electronic synchronization.

[0056] Example 5 Embodiment 5 of the present invention provides a non-volatile computer storage medium storing at least one executable instruction that can execute the remote sensing interpretation-based method for evaluating the health of river, lake, and reservoir shoreline conditions in any of the above method embodiments.

[0057] Executable instructions can specifically be used to cause the processor to perform the following operations: Remote sensing images that identify the local waterfront environment of rivers, lakes, and reservoirs; wherein, the remote sensing images contain information on aquatic species in the biological scenes associated with the local waterfront environment; Species detection is performed on the remote sensing image to detect the aquatic species information contained in the remote sensing image; The aquatic species information is clustered to obtain at least two types of species information; Based on the information of at least two species, a search is conducted among the disaster early warning schemes associated with the rivers, lakes, and reservoirs to determine the disaster early warning scheme information that matches the local waterfront environment.

[0058] In an alternative embodiment, the executable instructions cause the processor to perform the following operations: Determine the abundance value for each species category; Based on the abundance value of each species information, the disaster early warning schemes associated with the rivers, lakes and reservoirs are searched to determine the disaster early warning scheme information that matches the local waterfront environment.

[0059] In an alternative embodiment, the executable instructions cause the processor to perform the following operations: When the abundance value of the first type of species information is before that of the second type of species information, the first type of species information is searched in the disaster early warning scheme associated with the river, lake and reservoir to determine the first disaster early warning scheme information containing the first type of species information, and the first disaster early warning scheme information contains the nearest neighbor of the first type of species information. Search for the second type of species information in the first disaster early warning scheme information, determine the second disaster early warning scheme information containing the second type of species information, and the second disaster early warning scheme information contains the nearest neighbor of the second type of species information. Use a similar method to search until the information of each type of species has been searched. The disaster early warning scheme information containing information on the last type of species will be used as the disaster early warning scheme information that is matched with the local waterfront environment.

[0060] In an alternative embodiment, the executable instructions cause the processor to perform the following operations: Determine the first habitat of the first type of species information in the biological scene and the second habitat of the second type of species information in the biological scene; When the first habitat is before the second habitat, search for the second species information downstream of the first species information in the first disaster early warning scheme information; or, when the first habitat is after the second habitat, search for the second species information upstream of the first species information in the first disaster early warning scheme information.

[0061] In an alternative embodiment, the executable instructions cause the processor to perform the following operations: Based on the metadata in the at least two types of species information, disaster early warning schemes associated with the rivers, lakes, and reservoirs are found in the biological application of disaster early warning schemes; The search is performed in the disaster early warning scheme based on the information of at least two types of species.

[0062] In an alternative embodiment, the executable instructions cause the processor to perform the following operations: Based on the activation operation of the controls in the biological list of the disaster early warning scheme, the binocular camera is turned on; Based on the shooting operation of the binocular camera, remote sensing images of the local waterfront environment of rivers, lakes and reservoirs are detected.

[0063] In an alternative embodiment, the executable instructions cause the processor to perform the following operations: Detect the user's activated and followed habitats during the shooting process; The species information associated with the habitat of interest is identified as the local riparian environment of the river, lake, and reservoir.

[0064] In one optional embodiment, the at least two types of species information include information on species within the same class, information on species from different classes, and any two of a preset number of families and genera.

[0065] Therefore, this embodiment does not have high requirements for the acquisition of remote sensing images. The remote sensing images can contain information on aquatic species, and based on this information, the progress of river, lake, reservoir and disaster early warning schemes can still be synchronized.

[0066] Example 6 Figure 5 This diagram illustrates the structure of a remote sensing interpretation-based device for evaluating the health of river, lake, and reservoir shorelines, as provided in Embodiment Six of the present invention. The specific embodiments of the present invention do not limit the specific implementation of the remote sensing interpretation-based device for evaluating the health of river, lake, and reservoir shorelines.

[0067] like Figure 5 As shown, the remote sensing interpretation-based device for assessing the health of river, lake, and reservoir shorelines may include: One or more processors; A memory having stored one or more programs, which, when executed by the one or more processors, cause the one or more processors to perform the following operations: Remote sensing images that identify the local waterfront environment of rivers, lakes, and reservoirs; wherein, the remote sensing images contain information on aquatic species in the biological scenes associated with the local waterfront environment; Species detection is performed on the remote sensing image to detect the aquatic species information contained in the remote sensing image; The aquatic species information is clustered to obtain at least two types of species information; Based on the information of at least two species, a search is conducted among the disaster early warning schemes associated with the rivers, lakes, and reservoirs to determine the disaster early warning scheme information that matches the local waterfront environment.

[0068] In an alternative embodiment, the program may specifically be used to cause the processor 502 to perform the following operations: Determine the abundance value for each species category; Based on the abundance value of each species information, the disaster early warning schemes associated with the rivers, lakes and reservoirs are searched to determine the disaster early warning scheme information that matches the local waterfront environment.

[0069] In one alternative embodiment, the program may specifically be used to cause the processor to perform the following operations: When the abundance value of the first type of species information is before that of the second type of species information, the first type of species information is searched in the disaster early warning scheme associated with the river, lake and reservoir to determine the first disaster early warning scheme information containing the first type of species information, and the first disaster early warning scheme information contains the nearest neighbor of the first type of species information. Search for the second type of species information in the first disaster early warning scheme information, determine the second disaster early warning scheme information containing the second type of species information, and the second disaster early warning scheme information contains the nearest neighbor of the second type of species information. Use a similar method to search until the information of each type of species has been searched. The disaster early warning scheme information containing information on the last type of species will be used as the disaster early warning scheme information that is matched with the local waterfront environment.

[0070] In one alternative embodiment, the program may specifically be used to cause the processor to perform the following operations: Determine the first habitat of the first type of species information in the biological scene and the second habitat of the second type of species information in the biological scene; When the first habitat is before the second habitat, search for the second species information downstream of the first species information in the first disaster early warning scheme information; or, when the first habitat is after the second habitat, search for the second species information upstream of the first species information in the first disaster early warning scheme information.

[0071] In one alternative embodiment, the program may specifically be used to cause the processor to perform the following operations: Based on the metadata in the at least two types of species information, disaster early warning schemes associated with the rivers, lakes, and reservoirs are found in the biological application of disaster early warning schemes; The search is performed in the disaster early warning scheme based on the information of at least two types of species.

[0072] In one alternative embodiment, the program may specifically be used to cause the processor to perform the following operations: Based on the activation operation of the controls in the biological list of the disaster early warning scheme, the binocular camera is turned on; Based on the shooting operation of the binocular camera, remote sensing images of the local waterfront environment of rivers, lakes and reservoirs are detected.

[0073] In one alternative embodiment, the program may specifically be used to cause the processor to perform the following operations: Detect the user's activated and followed habitats during the shooting process; The species information associated with the habitat of interest is identified as the local riparian environment of the river, lake, and reservoir.

[0074] In one optional embodiment, the at least two types of species information include information on species within the same class, information on species from different classes, and any two of a preset number of families and genera.

[0075] Therefore, this embodiment does not have high requirements for the acquisition of remote sensing images. The remote sensing images can contain information on aquatic species, and based on this information, the progress of river, lake, reservoir and disaster early warning schemes can still be synchronized.

[0076] In the several embodiments provided in this application, it should be understood that the disclosed systems, apparatuses, and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces, or indirect coupling or communication connection between apparatuses or units, and may be electrical, mechanical, or other forms.

[0077] Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated units described above can be implemented in hardware or as software functional units. The above are merely embodiments of this application and do not limit the patent scope of this application. Any equivalent structural or procedural transformations made using the information in the specification and drawings of this application, or direct or indirect applications in other related technical fields, are similarly included within the patent protection scope of this application.

[0078] The specific embodiments of the invention have been described in detail above, but they are only examples, and this application is not limited to the specific embodiments described above. For those skilled in the art, any equivalent modifications or substitutions to the invention are also within the scope of this application. Therefore, all equivalent changes, modifications, and improvements made without departing from the spirit and principles of this application should be covered within the scope of this application.

Claims

1. A method for evaluating the health of river, lake, and reservoir shoreline conditions based on remote sensing interpretation, characterized in that, include: Remote sensing images that identify the local waterfront environment of rivers, lakes, and reservoirs; wherein, the remote sensing images contain information on aquatic species in the biological scenes associated with the local waterfront environment; Species detection is performed on the remote sensing image to detect the aquatic species information contained in the remote sensing image; The aquatic species information is clustered to obtain at least two types of species information; Based on the information of at least two species, a search is conducted in the disaster early warning schemes associated with the rivers, lakes and reservoirs to determine the disaster early warning scheme information that matches the local waterfront environment; The process of searching through disaster early warning schemes associated with the rivers, lakes, and reservoirs based on the information of at least two species to determine disaster early warning scheme information that matches the local aquatic environment includes: Determine the abundance value for each species category; Based on the abundance value of each species information, the disaster early warning schemes associated with the rivers, lakes and reservoirs are searched to determine the disaster early warning scheme information that matches the local waterfront environment; The abundance value based on the information of each species is searched in the disaster early warning schemes associated with the rivers, lakes, and reservoirs to determine the disaster early warning scheme information that matches the local aquatic environment, including: When the abundance value of the first type of species information is before that of the second type of species information, the first type of species information is searched in the disaster early warning scheme associated with the river, lake and reservoir to determine the first disaster early warning scheme information containing the first type of species information, and the first disaster early warning scheme information contains the nearest neighbor of the first type of species information. Search for the second type of species information in the first disaster early warning scheme information, determine the second disaster early warning scheme information containing the second type of species information, and the second disaster early warning scheme information contains the nearest neighbors of the second type of species information, and search until the information of each type of species has been searched; The disaster early warning scheme information containing the last type of species information is used as the disaster early warning scheme information that matches the local waterfront environment; The step of searching for the second type of species information in the first disaster early warning scheme information includes: Determine the first habitat of the first type of species information in the biological scene and the second habitat of the second type of species information in the biological scene; When the first habitat is before the second habitat, search for the second species information downstream of the first species information in the first disaster early warning scheme information; or, when the first habitat is after the second habitat, search for the second species information upstream of the first species information in the first disaster early warning scheme information.

2. The method based on claim 1, characterized in that, The search based on the information of at least two species in the disaster early warning scheme associated with the river, lake, and reservoir includes: Based on the metadata in the at least two types of species information, disaster early warning schemes associated with the rivers, lakes, and reservoirs are found in the biological application of disaster early warning schemes; The search is performed in the disaster early warning scheme based on the information of at least two types of species.

3. The method based on any one of claims 1-2, characterized in that, The remote sensing images of the local waterfront environment of the rivers, lakes, and reservoirs that are being detected include: Based on the activation operation of the controls in the biological list of the disaster early warning scheme, the binocular camera is turned on; Based on the shooting operation of the binocular camera, remote sensing images of the local waterfront environment of rivers, lakes and reservoirs are detected.

4. The method based on claim 3, characterized in that, The remote sensing images of the local waterfront environment of the rivers, lakes, and reservoirs that are being detected include: Detect the user's activated and followed habitats during the shooting process; The species information associated with the habitat of interest is identified as the local riparian environment of the river, lake, and reservoir.

5. The method according to any one of claims 1-4, characterized in that, The at least two types of species information include information on species within the same class, information on species from different classes, and any two of the following: a predetermined number of families and genera.

6. A device for evaluating the health of river, lake, and reservoir shoreline conditions based on remote sensing interpretation, characterized in that, include: One or more processors; A memory having stored one or more programs, which, when executed by the one or more processors, cause the one or more processors to perform the following operations: Remote sensing images that identify the local waterfront environment of rivers, lakes, and reservoirs; wherein, the remote sensing images contain information on aquatic species in the biological scenes associated with the local waterfront environment; Species detection is performed on the remote sensing image to detect the aquatic species information contained in the remote sensing image; The aquatic species information is clustered to obtain at least two types of species information; Based on the information of at least two species, a search is conducted in the disaster early warning schemes associated with the rivers, lakes and reservoirs to determine the disaster early warning scheme information that matches the local waterfront environment; The device for evaluating the health of river, lake, and reservoir shoreline based on remote sensing interpretation is used to perform the method for evaluating the health of river, lake, and reservoir shoreline based on remote sensing interpretation as described in any one of claims 1-5.

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