Remote sensing detection method, device, equipment and storage medium for wetland ecological environment

Abstract

The present invention relates to the field of data analysis, and in particular to a remote sensing detection method for a wetland ecological environment, comprising: obtaining first wetland type data of a wetland area based on a long-time series wetland remote sensing classification data set, obtaining an exponential factor according to the first wetland type data and an algorithm of an exponential factor corresponding to the first wetland type data, normalizing the exponential factor, and obtaining a wetland comprehensive index corresponding to the exponential factor; obtaining a display instruction, wherein the display instruction includes a long-time series wetland remote sensing classification data set of an area to be detected, obtaining electronic map data of the area to be detected, obtaining a corresponding wetland comprehensive index according to the long-time series wetland remote sensing classification data set of the area to be detected, obtaining a wetland comprehensive index according to the wetland comprehensive index and a preset index interval and a wetland identifier corresponding to the index interval, and displaying and marking the wetland identifier on the electronic map data.

Description

Technical Field

[0001] The present invention relates to the field of data analysis, and in particular to a remote sensing detection method, device, equipment and storage medium for wetland ecological environment. Background Art

[0002] As the kidneys of the earth, wetlands have ecological environmental and social service functions such as replenishing water, equalizing floods, regulating climate, degrading pollutants, providing habitats for animals and plants, and providing resources and leisure and tourist attractions. They are the common wealth of mankind and are known as the three major ecosystems on the earth together with forests and oceans.

[0003] In the current wetland ecological environment analysis methods, due to the poor accessibility of wetlands and other problems, manual surveys are difficult, it is difficult to analyze the dynamic changes of wetlands over the past few decades, and it is impossible to accurately analyze the ecological environment of wetlands, which is inefficient. Summary of the invention

[0004] Based on this, the purpose of the present invention is to provide a remote sensing detection method, device, equipment and storage medium for wetland ecological environment, which can analyze the area, development and distribution pattern of various types of wetlands in the wetland area, realize multi-faceted analysis of the ecological environment of the wetland, and improve the accuracy and efficiency of the analysis.

[0005] In a first aspect, an embodiment of the present application provides a remote sensing detection method for a wetland ecological environment, comprising the following steps:

[0006] Based on the long-term wetland remote sensing classification data set, first wetland type data of the wetland area is obtained, wherein the first wetland type data includes area characteristic data and shape characteristic data of each wetland type;

[0007] According to the first wetland type data and an algorithm of the index factor corresponding to the first wetland type data, an index factor is obtained, wherein the index factor at least includes: one or more of an area index, a development index and a pattern index;

[0008] Normalizing the index factor to obtain a wetland comprehensive index corresponding to the index factor;

[0009] Obtain display instructions, wherein the display instructions include a long-term wetland remote sensing classification data set of a to-be-detected area, obtain electronic map data of the to-be-detected area, obtain a corresponding wetland comprehensive index based on the long-term wetland remote sensing classification data set of the to-be-detected area, obtain wetland identifiers of various areas of the electronic map data based on the wetland comprehensive index and a preset index interval and a wetland identifier corresponding to the index interval, and display and mark the wetland identifiers on the electronic map data.

[0010] In a second aspect, an embodiment of the present application provides a wetland ecological environment detection device, including:

[0011] An acquisition module, used for acquiring first wetland type data of a wetland area based on a long-time series wetland remote sensing classification data set, wherein the first wetland type data includes area characteristic data and shape characteristic data of each wetland type;

[0012] An index factor calculation module, used to obtain an index factor according to the first wetland type data and an algorithm of the index factor corresponding to the first wetland type data, wherein the index factor includes at least one or more of an area index, a development index and a pattern index;

[0013] A wetland comprehensive index calculation module is used to normalize the index factor to obtain a wetland comprehensive index corresponding to the index factor;

[0014] A display module is provided for obtaining display instructions, wherein the display instructions include a long-time series wetland remote sensing classification data set of a to-be-detected area, obtaining electronic map data of the to-be-detected area, obtaining a corresponding wetland comprehensive index based on the long-time series wetland remote sensing classification data set of the to-be-detected area, obtaining wetland identifiers of various areas of the electronic map data based on the wetland comprehensive index and a preset index interval and a wetland identifier corresponding to the index interval, and displaying and marking the wetland identifiers on the electronic map data.

[0015] In a third aspect, an embodiment of the present application provides a device comprising: a processor, a memory, and a computer program stored in the memory and executable on the processor; when the computer program is executed by the processor, the steps of the remote sensing detection method of the wetland ecological environment as described in the first aspect are implemented.

[0016] In a fourth aspect, an embodiment of the present application provides a storage medium, wherein the storage medium stores a computer program, and when the computer program is executed by a processor, the steps of the remote sensing detection method of the wetland ecological environment as described in the first aspect are implemented.

[0017] In an embodiment of the present application, a remote sensing detection method, device, equipment and storage medium for a wetland ecological environment are provided, which can analyze the area, development and distribution pattern of various types of wetlands in a wetland area, realize a multi-faceted analysis of the ecological environment of the wetland, and improve the accuracy and efficiency of the analysis.

[0018] For better understanding and implementation, the present invention is described in detail below with reference to the accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] Figure 1A schematic flow chart of a remote sensing detection method for a wetland ecological environment provided in the first embodiment of the present application;

[0020] Figure 2 A partial flow diagram of S2 in the process of the remote sensing detection method for wetland ecological environment provided in the first embodiment of the present application;

[0021] Figure 3 A partial flow diagram of S2 in the flow of the remote sensing detection method for wetland ecological environment provided in the second embodiment of the present application;

[0022] Figure 4 A partial flow diagram of S2 in the process of the remote sensing detection method for wetland ecological environment provided in the third embodiment of the present application;

[0023] Figure 5 A schematic diagram of the process of S204 in the process of the remote sensing detection method of the wetland ecological environment provided in the third embodiment of the present application;

[0024] Figure 6 A schematic diagram of the process of S3 in the process of the remote sensing detection method of the wetland ecological environment provided in the first embodiment of the present application;

[0025] Figure 7 A schematic diagram of the structure of a wetland ecological environment detection device provided in the fourth embodiment of the present application;

[0026] Figure 8 A schematic diagram of the structure of the device provided in the fifth embodiment of the present application. DETAILED DESCRIPTION

[0027] Exemplary embodiments will be described in detail herein, examples of which are shown in the accompanying drawings. When the following description refers to the drawings, the same numbers in different drawings represent the same or similar elements unless otherwise indicated. The implementations described in the following exemplary embodiments do not represent all implementations consistent with the present application. Instead, they are merely examples of devices and methods consistent with some aspects of the present application as detailed in the appended claims.

[0028] The terms used in this application are for the purpose of describing specific embodiments only and are not intended to limit this application. The singular forms of "a", "said" and "the" used in this application and the appended claims are also intended to include plural forms unless the context clearly indicates other meanings. It should also be understood that the term "and / or" used herein refers to and includes any or all possible combinations of one or more associated listed items.

[0029] It should be understood that, although the terms first, second, third, etc. may be used in the present application to describe various information, these information should not be limited to these terms. These terms are only used to distinguish the same type of information from each other. For example, without departing from the scope of the present application, the first information may also be referred to as the second information, and similarly, the second information may also be referred to as the first information. Depending on the context, the words "if" / "if" as used herein may be interpreted as "at the time of" or "when" or "in response to determination".

[0030] See also Figure 1 , Figure 1 A schematic flow chart of a remote sensing detection method for a wetland ecological environment provided in the first embodiment of the present application, the method comprising the following steps:

[0031] S1: Based on the long-term wetland remote sensing classification data set, first wetland type data of the wetland area is obtained, wherein the first wetland type data includes area characteristic data and shape characteristic data of each wetland type.

[0032] The executor of the remote sensing detection method of the wetland ecological environment is the detection equipment of the remote sensing detection method of the wetland ecological environment (hereinafter referred to as the detection equipment). In an optional embodiment, the detection equipment can be a computer device, a server, or a server cluster composed of multiple computer devices.

[0033] The detection device obtains a long-time series wetland remote sensing classification data set input by a user, and may also obtain a long-time series wetland remote sensing classification data set from a database. The detection device obtains first wetland type data of the wetland area based on the long-time series wetland remote sensing classification data set, wherein the first wetland type data includes area characteristic data and shape characteristic data of each wetland type in the wetland area for several years.

[0034] The long-term wetland remote sensing classification dataset refers to a dataset composed of wetland remote sensing classification data at different times in a preset time period. For example, a dataset composed of wetland remote sensing classification data of each year from 1990 to 2020 is a long-term wetland remote sensing classification dataset.

[0035] The area characteristic data include area data of each wetland type and wetland patch area data, wherein the wetland patch refers to wetland areas that are spatially clustered and interconnected.

[0036] The shape feature data includes shape data of each wetland type and boundary length data of each wetland type.

[0037] S2: Obtain an index factor according to the first wetland type data and an algorithm of the index factor corresponding to the first wetland type data, wherein the index factor includes at least one or more of an area index, a development index and a pattern index.

[0038] In this embodiment, the detection device obtains the exponential factor according to the first wetland type data and an algorithm of the exponential factor corresponding to the first wetland type data.

[0039] See also Figure 2 , Figure 2 The schematic diagram of a partial process of S2 in the process of the remote sensing detection method of the wetland ecological environment provided in the first embodiment of the present application includes step S201:

[0040] S201: Analyze the area of ​​each wetland type in the first wetland type data according to the area characteristic data and the area index calculation algorithm to obtain the area index.

[0041] The area index calculation algorithm is:

[0042]

[0043] In the formula, A represents the area index, N represents the total number of wetland types, and a i represents the area of ​​a certain wetland type, M represents the total area of ​​wetland patches of a certain wetland type, and the wetland patches are wetland areas that are spatially clustered and interconnected.

[0044] In this embodiment, the detection device obtains the area characteristic data in the first wetland type data, analyzes the area of ​​each wetland type in the first wetland type data according to the area of ​​each wetland type in the area characteristic data, the total area of ​​wetland patches of a certain wetland type and the area index calculation algorithm, and obtains the area index.

[0045] See also Figure 3 , Figure 3 The schematic diagram of a partial process of S2 in the process of the remote sensing detection method of the wetland ecological environment provided in the second embodiment of the present application includes steps S202 to S203:

[0046] S202: Classify the first wetland type data to obtain second wetland type data, wherein the second wetland type data includes area percentage data of each wetland classification.

[0047] In an optional embodiment, the detection device divides the wetland types in the first wetland type data into 8 levels, wherein the wetland types of level 1 include rivers, shallow sea waters, mangroves, and tidal flats; the wetland types of level 2 include aquaculture and lakes; the wetland types of level 3 include terrestrial vegetation; the wetland types of level 4 include bare land; the wetland types of level 7 include cultivated land; and the wetland types of level 8 include building land;

[0048] The detection device classifies the first wetland type data, obtains the second wetland type data, and analyzes the area of ​​the classified first wetland type data to obtain the area percentage data of each wetland classification.

[0049] S203: Obtaining the development index according to the area ratio data of each wetland classification, a preset wetland classification index and a development index calculation algorithm.

[0050] The development index calculation algorithm is:

[0051]

[0052] Where, represents the development index, L i represents the i-th level wetland classification index, C i It represents the percentage of area of ​​the i-th wetland classification, and n represents the number of wetland classifications.

[0053] In this embodiment, the detection equipment pre-sets a wetland classification index corresponding to the wetland classification. After obtaining the second wetland type data, the area of ​​each wetland classification in the second wetland type data is analyzed according to the area proportion data of each wetland classification, the preset wetland classification index and the development index calculation algorithm to obtain the development index.

[0054] See also Figure 4 , Figure 4 The schematic diagram of a partial process of S2 in the process of the remote sensing detection method of the wetland ecological environment provided in the third embodiment of the present application includes step S204:

[0055] S204: Analyze the area, shape and boundary length of each wetland type in the first wetland type data to obtain the pattern index.

[0056] The pattern index includes a first pattern index and a second pattern index. The first pattern index is used to reflect the pattern characteristics of the shape and length of each wetland type in the first wetland type data, and the second pattern index is used to reflect the distribution pattern characteristics of each wetland type in the first wetland type data.

[0057] See also Figure 5, Figure 5 The schematic diagram of the process of S204 in the process of the remote sensing detection method of the wetland ecological environment provided in the third embodiment of the present application includes steps S2041 to S2042:

[0058] S2041: Analyze the shape and length of each wetland type in the first wetland type data according to the area characteristic data, shape characteristic data and the first pattern index calculation algorithm to obtain the first pattern index.

[0059] The first pattern index calculation algorithm is:

[0060]

[0061] In the formula, S represents the first pattern index, P represents the total length of all wetland patch boundaries, and A p represents the total area of ​​all wetland patches;

[0062] In this embodiment, the detection equipment obtains the area characteristic data and shape characteristic data in the first wetland type data, analyzes the wetland patches of all wetland types, obtains the total length and total area of ​​all wetland patch boundaries, and analyzes the shape and length of each wetland type in the first wetland type data based on the total length and total area of ​​the wetland patch boundaries and the first pattern calculation algorithm to obtain the first pattern index.

[0063] S2042: Analyze the distribution of each wetland type in the first wetland type data according to the area characteristic data and the second pattern index calculation algorithm to obtain the second pattern index.

[0064] The second pattern index calculation algorithm is:

[0065]

[0066] Where F represents the second pattern index, N represents the total number of wetland types, and Q represents the average area of ​​all wetland types.

[0067] In this embodiment, the detection device obtains the total number of wetland types in the first wetland type data, analyzes the area characteristic data, obtains the average area of ​​all wetland types, and analyzes the distribution of each wetland type in the first wetland type data based on the total number of wetland types, the average area of ​​all wetland types and the second pattern calculation algorithm to obtain the second pattern index.

[0068] S3: Normalize the index factor to obtain a wetland comprehensive index corresponding to the index factor.

[0069] In this embodiment, the detection device normalizes the index factor to obtain a wetland comprehensive index corresponding to the index factor.

[0070] See also Figure 6 , Figure 6 The schematic diagram of the process of S3 in the process of the remote sensing detection method of the wetland ecological environment provided in the first embodiment of the present application includes steps S301 to S303:

[0071] S301: Obtain a processed exponential factor according to the exponential factor and a normalization algorithm.

[0072] The normalization algorithm includes f1 to f3, which are as follows:

[0073]

[0074]

[0075]

[0076] Where n y represents the time series length of the first wetland type data, represents the exponential factor of the i-th year before the treatment, μ represents the average value of the exponential factor before the treatment in the time series, σ represents the standard deviation of the exponential factor before the treatment, and I represents the exponential factor after the treatment. represents the exponential factor before treatment;

[0077] In this embodiment, the detection device obtains the time series length of the first wetland type data, and according to the exponential factor before processing and the functions f1 and f2 in the normalization algorithm, obtain the average value μ of the exponential factor before processing in the time series and the standard deviation σ of the exponential factor before processing, and calculate the average value μ, σ, and the standard deviation σ of the exponential factor before processing according to the average value μ, σ, and the standard deviation σ of the exponential factor before processing. And the function f3 in the normalization algorithm obtains the processed exponential factor.

[0078] S302: Obtain the average change rate according to the processed exponential factor and the average change rate algorithm.

[0079] The average rate of change algorithm is:

[0080]

[0081] Where ΔWCI represents the average rate of change, I iy represents the i-th exponential factor of the y-th year, and m represents the number of the exponential factors;

[0082] In this embodiment, the detection device obtains the number of the processed exponential factors, and obtains the average change rate according to the processed exponential factors and the average change rate algorithm.

[0083] S303: Obtaining the wetland comprehensive index corresponding to the index factor according to the average change rate and the wetland comprehensive index calculation algorithm.

[0084] The wetland comprehensive index calculation algorithm is:

[0085] WCI y =WCI y-1 ×ΔWCI

[0086] Where, WCI y WCI1 represents the comprehensive wetland index in the yth year, WCI1 represents the comprehensive wetland index in the first year, and WCI1=1.

[0087] In this embodiment, the detection device pre-sets the wetland comprehensive index WCI1 of the first year, and obtains the wetland comprehensive index corresponding to the index factor according to the average change rate and the wetland comprehensive index calculation algorithm.

[0088] S4: Obtain display instructions, wherein the display instructions include a long-term wetland remote sensing classification data set of the area to be detected, obtain electronic map data of the area to be detected, obtain a corresponding wetland comprehensive index based on the long-term wetland remote sensing classification data set of the area to be detected, obtain wetland identifiers of various areas of the electronic map data based on the wetland comprehensive index and a preset index interval and a wetland identifier corresponding to the index interval, and display and mark the wetland identifiers on the electronic map data.

[0089] The display instruction is sent by the user equipment and received by the detection equipment.

[0090] In this embodiment, the detection device obtains the display instruction sent by the user, and responds to obtain the electronic map data of the area to be detected.

[0091] The detection device obtains the long-term wetland remote sensing classification data set to be detected according to the display instruction, obtains the corresponding wetland comprehensive index, obtains the wetland identification of each area of ​​the electronic map data according to the wetland comprehensive index and the preset index interval and the wetland identification corresponding to the index interval, and returns it to the display interface of the detection device, and displays and marks the wetland identification on the electronic map data.

[0092] Please refer to Figure 7 , Figure 7This is a schematic diagram of the structure of a wetland ecological environment detection device provided in the fourth embodiment of the present application. The device can implement all or part of the wetland ecological environment detection device through software, hardware, or a combination of both. The device 7 includes:

[0093] An acquisition module 71 is used to acquire remote sensing images of a wetland area for several years, and acquire first wetland type data of the wetland area according to the remote sensing images, wherein the first wetland type data includes area characteristic data and shape characteristic data of each wetland type;

[0094] An index factor calculation module 72 is used to obtain an index factor according to the first wetland type data and an algorithm of the index factor corresponding to the first wetland type data, wherein the index factor at least includes: one or more of an area index, a development index and a pattern index;

[0095] A wetland comprehensive index calculation module 73 is used to perform normalization processing on the index factor to obtain a wetland comprehensive index corresponding to the index factor;

[0096] The detection module 74 is used to obtain a detection instruction from a user, wherein the detection instruction includes first wetland type data associated with the detected area, and obtain a wetland comprehensive index of the detected area based on the first wetland type data associated with the detected area.

[0097] In this embodiment, the remote sensing images of the wetland area for several years are obtained through the acquisition module, and the first wetland type data of the wetland area is obtained according to the remote sensing images, wherein the first wetland type data includes the area characteristic data and shape characteristic data of each wetland type; the index factor is obtained according to the algorithm of the index factor corresponding to the first wetland type data and the first wetland type data through the index factor calculation module, wherein the index factor includes at least one or more of the area index, development index and pattern index; the index factor is normalized through the wetland comprehensive index calculation module to obtain the wetland comprehensive index corresponding to the index factor; the user's detection instruction is obtained through the detection module, wherein the detection instruction includes the first wetland type data associated with the detected area, and the wetland comprehensive index of the detected area is obtained according to the first wetland type data associated with the detected area. The area, development and distribution pattern of each type of wetland in the wetland area can be analyzed, and the multi-faceted analysis of the ecological environment of the wetland is realized, and the accuracy and efficiency of the analysis are improved.

[0098] Please refer to Figure 8 , Figure 8The structural diagram of the device provided for the fifth embodiment of the present application, the device 8 includes: a processor 81, a memory 82, and a computer program 83 stored in the memory 82 and executable on the processor 81; the computer device can store multiple instructions, and the instructions are suitable for the processor 81 to load and execute the method steps of the above-mentioned embodiments one to three. The specific execution process can refer to the specific description of embodiments one to three, which will not be repeated here.

[0099] Among them, the processor 81 may include one or more processing cores. The processor 81 uses various interfaces and lines to connect various parts in the server, and executes various functions and processes data of the wetland ecological environment detection device 7 by running or executing instructions, programs, code sets or instruction sets stored in the memory 82, and calling the data in the memory 82. Optionally, the processor 81 can be implemented in at least one hardware form of digital signal processing (Digital Signal Processing, DSP), field programmable gate array (Field-Programmable Gate Array, FPGA), and programmable logic array (Programble Logic Array, PLA). The processor 81 can integrate one or more combinations of a central processing unit 81 (Central Processing Unit, CPU), an image processor 81 (Graphics Processing Unit, GPU) and a modem. Among them, the CPU mainly processes the operating system, user interface and application programs; the GPU is responsible for rendering and drawing the content to be displayed on the touch display; the modem is used to process wireless communications. It can be understood that the above-mentioned modem may not be integrated into the processor 81, and it can be implemented by a single chip.

[0100] Among them, the memory 82 may include a random access memory 82 (Random Access Memory, RAM), and may also include a read-only memory 82 (Read-Only Memory). Optionally, the memory 82 includes a non-transitory computer-readable storage medium. The memory 82 can be used to store instructions, programs, codes, code sets or instruction sets. The memory 82 may include a program storage area and a data storage area, wherein the program storage area may store instructions for implementing an operating system, instructions for at least one function (such as touch instructions, etc.), instructions for implementing the above-mentioned various method embodiments, etc.; the data storage area may store data involved in the above-mentioned various method embodiments, etc. The memory 82 may also be optionally at least one storage device located away from the aforementioned processor 81.

[0101] An embodiment of the present application also provides a storage medium, which can store multiple instructions. The instructions are suitable for being loaded by a processor and executing the method steps of the above-mentioned embodiments one to three. The specific execution process can be found in the specific descriptions of embodiments one to three, which will not be repeated here.

[0102] The technicians in the relevant field can clearly understand that for the convenience and simplicity of description, only the division of the above-mentioned functional units and modules is used as an example for illustration. In practical applications, the above-mentioned function allocation can be completed by different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above. The functional units and modules in the embodiment can be integrated in a processing unit, or each unit can exist physically separately, or two or more units can be integrated in one unit. The above-mentioned integrated unit can be implemented in the form of hardware or in the form of software functional units. In addition, the specific names of the functional units and modules are only for the convenience of distinguishing each other, and are not used to limit the scope of protection of this application. The specific working process of the units and modules in the above-mentioned system can refer to the corresponding process in the aforementioned method embodiment, which will not be repeated here.

[0103] In the above embodiments, the description of each embodiment has its own emphasis. For parts that are not described or recorded in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0104] Those skilled in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraint algorithm of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of the present invention.

[0105] In the embodiments provided by the present invention, it should be understood that the disclosed devices / terminal equipment and methods can be implemented in other ways. For example, the device / terminal equipment embodiments described above are only schematic. For example, the division of the modules or units is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0106] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0107] In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0108] If the integrated module / unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the present invention implements all or part of the processes in the above-mentioned embodiment method, and can also be completed by instructing the relevant hardware through a computer program. The computer program can be stored in a computer-readable storage medium, and when the computer program is executed by a processor, the steps of the above-mentioned method embodiments can be implemented. Among them, the computer program includes computer program code, and the computer program code can be in source code form, object code form, executable file or some intermediate form, etc.

[0109] The present invention is not limited to the above-mentioned embodiments. If various changes or modifications to the present invention do not depart from the spirit and scope of the present invention, and if these changes and modifications fall within the scope of the claims and equivalent technologies of the present invention, the present invention is also intended to include these changes and modifications.

Claims

1. A remote sensing detection method for wetland ecological environment, characterized in that: The following steps are involved: Based on the long-term wetland remote sensing classification data set, first wetland type data of the wetland area is obtained, wherein the first wetland type data includes area characteristic data and shape characteristic data of each wetland type; According to the first wetland type data and an algorithm of the index factor corresponding to the first wetland type data, an index factor is obtained, wherein the index factor at least includes: one or more of an area index, a development index and a pattern index; According to the exponential factor and the normalization algorithm, a processed exponential factor is obtained, wherein the normalization algorithm includes f1 to f3, which are specifically as follows: Where n y represents the time series length of the first wetland type data, represents the exponential factor of the i-th year before the treatment, μ represents the average value of the exponential factor before the treatment in the time series, σ represents the standard deviation of the exponential factor before the treatment, and I represents the exponential factor after the treatment. represents the exponential factor before treatment; The average change rate is obtained according to the processed exponential factor and the average change rate algorithm, wherein the average change rate algorithm is: Where ΔWCI represents the average rate of change, I iy represents the i-th exponential factor of the y-th year, and m represents the number of the exponential factors; According to the average change rate and the wetland comprehensive index calculation algorithm, the wetland comprehensive index corresponding to the index factor is obtained, wherein the wetland comprehensive index calculation algorithm is: WCI y =WCI y-1 ×ΔWCI Where, WCI y represents the comprehensive wetland index in the yth year, WCI1 represents the comprehensive wetland index in the first year, WCI1=1; Obtain display instructions, wherein the display instructions include a long-term wetland remote sensing classification data set of a to-be-detected area, obtain electronic map data of the to-be-detected area, obtain a corresponding wetland comprehensive index based on the long-term wetland remote sensing classification data set of the to-be-detected area, obtain wetland identifiers of various areas of the electronic map data based on the wetland comprehensive index and a preset index interval and a wetland identifier corresponding to the index interval, and display and mark the wetland identifiers on the electronic map data.

2. The remote sensing detection method of wetland ecological environment according to claim 1, characterized in that: The step of obtaining the exponential factor according to the first wetland type data and the algorithm of the exponential factor corresponding to the first wetland type data comprises the steps of: According to the area characteristic data and the area index calculation algorithm, the area of ​​each wetland type in the first wetland type data is analyzed to obtain the area index, wherein the area index calculation algorithm is: In the formula, A represents the area index, N represents the total number of wetland types, and a i represents the area of ​​a certain wetland type, M represents the total area of ​​wetland patches of a certain wetland type, and the wetland patches are wetland areas that are spatially clustered and interconnected.

3. The remote sensing detection method of wetland ecological environment according to claim 1, characterized in that: The step of obtaining the exponential factor according to the first wetland type data and the algorithm of the exponential factor corresponding to the first wetland type data comprises the steps of: Classify the first wetland type data to obtain second wetland type data, wherein the second wetland type data includes area percentage data of each wetland classification; The development index is obtained according to the area proportion data of each wetland classification, the preset wetland classification index and the development index calculation algorithm, wherein the development index calculation algorithm is: Wherein, E represents the development index, L i represents the i-th level wetland classification index, C i It represents the percentage of area of ​​the i-th wetland classification, and n represents the number of wetland classifications.

4. The remote sensing detection method of wetland ecological environment according to claim 1, characterized in that: The step of obtaining the exponential factor according to the first wetland type data and the algorithm of the exponential factor corresponding to the first wetland type data comprises the steps of: The area, shape and boundary length of each wetland type in the first wetland type data are analyzed to obtain the pattern index.

5. The remote sensing detection method of wetland ecological environment according to claim 4 is characterized in that: The step of analyzing the area, shape and boundary length of each wetland type in the first wetland type data to obtain the pattern index comprises the following steps: According to the area characteristic data, shape characteristic data and the first pattern index calculation algorithm, the shape and length of each wetland type in the first wetland type data are analyzed to obtain the first pattern index, wherein the first pattern index calculation algorithm is: In the formula, S represents the first pattern index, P represents the total length of all wetland patch boundaries, and A p represents the total area of ​​all wetland patches; According to the area characteristic data and the second pattern index calculation algorithm, the distribution of each wetland type in the first wetland type data is analyzed to obtain the second pattern index, wherein the second pattern index calculation algorithm is: Where F represents the second pattern index, N represents the total number of wetland types, and Q represents the average area of ​​all wetland types.

6. A wetland ecological environment detection device, characterized in that: include: An acquisition module, used for acquiring first wetland type data of a wetland area based on a long-time series wetland remote sensing classification data set, wherein the first wetland type data includes area characteristic data and shape characteristic data of each wetland type; An index factor calculation module, used to obtain an index factor according to the first wetland type data and an algorithm of the index factor corresponding to the first wetland type data, wherein the index factor includes at least one or more of an area index, a development index and a pattern index; The wetland comprehensive index calculation module is used to obtain the processed index factor according to the index factor and the normalization algorithm, wherein the normalization algorithm includes f1 to f3, which are as follows: Where n y represents the time series length of the first wetland type data, represents the exponential factor of the i-th year before the treatment, μ represents the average value of the exponential factor before the treatment in the time series, σ represents the standard deviation of the exponential factor before the treatment, and I represents the exponential factor after the treatment. represents the exponential factor before treatment; The average change rate is obtained according to the processed exponential factor and the average change rate algorithm, wherein the average change rate algorithm is: Where ΔWCI represents the average rate of change, I iy represents the i-th exponential factor of the y-th year, and m represents the number of the exponential factors; According to the average change rate and the wetland comprehensive index calculation algorithm, the wetland comprehensive index corresponding to the index factor is obtained, wherein the wetland comprehensive index calculation algorithm is: WCI y =WCI y-1 ×ΔWCI Where, WCI y represents the comprehensive wetland index in the yth year, WCI1 represents the comprehensive wetland index in the first year, WCI1=1; A display module is provided for obtaining display instructions, wherein the display instructions include a long-term wetland remote sensing classification data set of a to-be-detected area, obtaining electronic map data of the to-be-detected area, obtaining a corresponding wetland comprehensive index based on the long-term wetland remote sensing classification data set of the to-be-detected area, obtaining wetland identifiers of various areas of the electronic map data based on the wetland comprehensive index and a preset index interval and a wetland identifier corresponding to the index interval, and displaying and marking the wetland identifiers on the electronic map data.

7. A device, characterized in that: include: A processor, a memory, and a computer program stored in the memory and executable on the processor; when the computer program is executed by the processor, the steps of the remote sensing detection method for the wetland ecological environment as described in any one of claims 1 to 5 are implemented.

8. A storage medium, characterized in that: The storage medium stores a computer program, and when the computer program is executed by a processor, the steps of the remote sensing detection method of the wetland ecological environment as described in any one of claims 1 to 5 are implemented.

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