Artificial precipitation enhancement ecological benefit quantification method, equipment and product

Abstract

The invention discloses an artificial precipitation enhancement ecological benefit quantification method, device and product, and relates to the field of ecological meteorology, and the method comprises the steps: determining an artificial precipitation enhancement potential influence region based on the flight path of an artificial precipitation enhancement airplane; all meteorological stations in the potential influence area of artificial precipitation enhancement are identified; performing spatial interpolation on the artificial precipitation amount observed by the meteorological station to form raster data of the artificial precipitation amount, and determining an actual influence area of the artificial precipitation amount; quantifying the change rate of the NDVI on the grid scale based on a time sequence NDVI measured by multiple times of remote sensing after artificial precipitation; the change significance of the time sequence NDVI corresponding to each grid point is detected; coupling an NDVI change rate and change significance on a grid scale, and quantifying an artificial precipitation enhancement ecological benefit significant region; and according to the artificial precipitation enhancement ecological benefit significant region, quantifying the artificial precipitation enhancement ecological benefit. The method can accurately quantify the artificial precipitation enhancement ecological benefit.

Description

Technical Field

[0001] This application relates to the field of ecological meteorology, as well as disciplines such as remote sensing and geographic information systems, and technical fields such as weather modification, artificial intelligence and ecological benefit evaluation. In particular, it relates to a method, equipment and product for quantifying the ecological benefits of artificial rain enhancement. Background Technology

[0002] Artificial rain enhancement, a typical weather modification technology, primarily utilizes methods such as aircraft seeding, ground-based rocket / artillery launches, and ground-based generator releases to scientifically catalyze the precipitation potential of clouds, causing water vapor to condense and fall. Artificial rain enhancement offers numerous ecological benefits, including replenishing water resources, improving soil moisture, alleviating drought, accelerating vegetation recovery, slowing desertification, and suppressing dust storms; improving ecological quality, enhancing ecosystem carbon sequestration capacity, and improving ecosystem function. With the widespread application of artificial rain enhancement in drought relief and ecological restoration, the demand for ecological benefit assessments is increasing.

[0003] However, the ecological benefits of artificial rain enhancement are often relatively weak and easily affected by subsequent natural precipitation. These benefits are also difficult to identify and quantify. Accurate quantification of ecological benefits is crucial for ecosystem restoration and climate adaptation, and provides technical support. Currently, relevant research cases are relatively scarce, and a complete and practical technical methodology for evaluating the ecological benefits of artificial rain enhancement has not yet been established. How to scientifically and accurately quantify the ecological benefits of artificial rain enhancement, especially at a finer grid scale, remains a critical technical bottleneck that urgently needs to be overcome. Summary of the Invention

[0004] The purpose of this application is to provide a method, equipment, and product for quantifying the ecological benefits of artificial rain enhancement, which can accurately quantify the ecological benefits of artificial rain enhancement.

[0005] To achieve the above objectives, this application provides the following solution.

[0006] Firstly, this application provides a method for quantifying the ecological benefits of artificial rain enhancement, which includes the following steps.

[0007] Based on the flight trajectory of the artificial rainmaking aircraft, the potential impact area of ​​artificial rainmaking was determined.

[0008] Identify all meteorological stations within the potential impact area of ​​the artificial rain enhancement program.

[0009] Spatial interpolation is performed on the artificial rain enhancement amounts observed at meteorological stations to form raster data of artificial rain enhancement, and the actual impact area of ​​artificial rain enhancement is determined based on the raster data.

[0010] Based on the time series NDVI measured by remote sensing multiple times after artificial rain enhancement in the actual affected area and the non-rain enhancement area, the NDVI change rate is quantified at the raster scale; the natural conditions of the non-rain enhancement area are the same as those of the actual affected area of ​​artificial rain enhancement.

[0011] The significance of changes in the time series NDVI corresponding to each grid point is detected.

[0012] The rate of change of NDVI and the significance of the change are coupled at the raster scale to quantify the area of ​​significant ecological benefits of artificial rain enhancement; the area of ​​significant ecological benefits of artificial rain enhancement is a raster with significant changes in NDVI over time series.

[0013] The ecological benefits of artificial rain enhancement are quantified based on the areas with significant ecological benefits.

[0014] Secondly, this application provides a computer device, including: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the above-described method for quantifying the ecological benefits of artificial rain enhancement.

[0015] Thirdly, this application provides a computer program product, including a computer program that, when executed by a processor, implements the above-described method for quantifying the ecological benefits of artificial rain enhancement.

[0016] According to the specific embodiments provided in this application, this application has the following technical effects: Based on the flight trajectory of artificial rainmaking aircraft, this application determines the potential impact area of ​​artificial rainmaking, thereby obtaining all meteorological stations and forming raster data of artificial rainmaking to obtain the actual impact area of ​​artificial rainmaking. Based on the identified actual impact area of ​​artificial rainmaking, this application further narrows the detection range and improves the detection accuracy. At the same time, based on the time series Normalized Differential Vegetation Index (NDVI) measured by remote sensing multiple times after artificial rainmaking in the actual impact area of ​​artificial rainmaking and non-rainmaking areas with the same natural conditions, the NDVI change rate is quantified at the raster scale, and the significance of the change of the time series NDVI corresponding to each raster point is detected. The area with significant ecological benefits of artificial rainmaking is quantified to accurately quantify the ecological benefits of artificial rainmaking, providing technical support for ecosystem restoration and climate adaptation. Attached Figure Description

[0017] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0018] Figure 1 This application provides a flowchart illustrating a method for quantifying the ecological benefits of artificial rain enhancement in one embodiment.

[0019] Figure 2 This is a schematic diagram of the Mann-Kendall significance test provided in an embodiment of this application. Detailed Implementation

[0020] 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 some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0021] To make the objectives, features and advantages of this application more apparent and understandable, the application will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0022] like Figure 1 As shown in the figure, this application provides a method for quantifying the ecological benefits of artificial rain enhancement, including the following steps.

[0023] S1: Based on the flight trajectory of the artificial rainmaking aircraft, determine the potential impact area of ​​artificial rainmaking.

[0024] S2: Identify all meteorological stations within the potential impact area of ​​the artificial rain enhancement.

[0025] S3: Spatial interpolation is performed on the artificial rain enhancement amounts observed at meteorological stations to form raster data of artificial rain enhancement, and the actual impact area of ​​artificial rain enhancement is determined based on the raster data.

[0026] S4: Based on the time series NDVI measured by remote sensing multiple times after artificial rain enhancement in the actual affected area and the non-rain enhancement area, the NDVI change rate is quantified at the grid scale; the natural conditions of the non-rain enhancement area are the same as those of the actual affected area of ​​artificial rain enhancement.

[0027] S5: Detect the significance of changes in the time series NDVI corresponding to each grid point.

[0028] S6: Couple the NDVI change rate and the significance of the change at the raster scale to quantify the area of ​​significant ecological benefits of artificial rain enhancement; the area of ​​significant ecological benefits of artificial rain enhancement is a raster with significant changes in NDVI over time series.

[0029] S7: Quantify the ecological benefits of artificial rain enhancement based on the areas with significant ecological benefits.

[0030] In an exemplary embodiment, S1 specifically includes: generating a flight trajectory based on the coordinates of the artificial rainmaking aircraft's flight path.

[0031] The potential impact area of ​​artificial rain enhancement is determined by extending a set distance outward from the flight trajectory.

[0032] In an exemplary embodiment, spatial interpolation is performed on the artificial rainfall amount observed at meteorological stations to form raster data of artificial rainfall, and the actual impact area of ​​artificial rainfall is determined based on the raster data. Specifically, this includes: using the Kriging interpolation method to spatially interpolate the artificial rainfall amount observed at meteorological stations to form raster data of artificial rainfall.

[0033] Based on the grid data, the grid areas where the artificial rain enhancement rainfall exceeds the set rainfall threshold are identified as the actual impact area of ​​artificial rain enhancement.

[0034] In practical applications, the "buffer zone" method is used to identify potential impact areas for artificial rain enhancement. Specifically, this involves generating a flight path (or rocket launcher coordinates) based on the coordinates of the aircraft's flight path, and then extending a certain distance outward from the flight path (or rocket launcher coordinates) as the center to define the "potential impact area for artificial rain enhancement." Based on experience, the impact radius of artificial rain enhancement generally does not exceed 50km; therefore, extending the center point of the flight path outward by at least 50km is considered the possible range of the potential impact area for artificial rain enhancement.

[0035] For the center point (x0, y0), the extended distance radius r is defined as ≥ 50km.

[0036] In practical applications, the "spatial matching method" is used to identify the actual impact area of ​​artificial rain enhancement, specifically including: Based on the potential impact area of ​​artificial rain enhancement, identify all meteorological stations within that spatial area.

[0037]

[0038] in, Search results for weather stations. For the i-th weather station, S To define the search range, R To find the radius, PointInRegion is the spatial containment determination function.

[0039] Based on actual cases of artificial rain enhancement, the duration of precipitation after a single rain enhancement operation generally does not exceed 6 hours. Therefore, the precipitation observed within 6 hours after the start of an artificial rain enhancement operation is defined as the amount of artificial rain enhancement.

[0040] ,

[0041] in, P The amount of artificially increased rainfall (mm) is used. denoted as hourly precipitation, and D as the duration of precipitation.

[0042] Ordinary Kriging interpolation was used to spatially interpolate the artificial rainfall amounts observed at various meteorological stations, obtaining raster data. Based on this raster data, the artificial rainfall amounts were... The grid area was determined to be the actual impact area of ​​artificial rain enhancement.

[0043] In one exemplary embodiment, the ecological benefits of artificial rain enhancement are quantified using the rate of change at the grid scale, specifically including: Following the principles of scientific rigor and operability, the Normalized Difference Vegetation Index (NDVI), a highly precipitation-sensitive and easily obtainable indicator through remote sensing, was selected as the quantitative indicator for the ecological benefits of artificial rain enhancement. Based on time-series NDVI values ​​measured multiple times after artificial rain enhancement in the actual impact area and a nearby non-rain enhancement area with similar natural conditions, the NDVI change rate was quantified using a univariate regression equation trend method at the raster scale. The ecological benefits of artificial rain enhancement were identified by comparing the time-series NDVI change rates of the actual impact area and the non-rain enhancement area.

[0044] The rate of change of NDVI for: 。

[0045] in, n This represents the total number of days with rainfall. For the first i The daily NDVI variable value.

[0046] In an exemplary embodiment, S5 specifically includes: calculating the NDVI order column of the sequential time series and the NDVI order column of the reverse time series based on the time series NDVI corresponding to each grid point.

[0047] Calculate the order statistics and reverse statistics based on the NDVI order column of the sequential time series and the NDVI order column of the reverse time series.

[0048] The significance of the change in NDVI of the time series corresponding to each grid point is determined based on the sequence curve formed by the ordered statistics, the sequence curve formed by the reverse statistics, and the two critical lines.

[0049] In practical applications, "rate of change" and "significance of change" are coupled at the grid scale to quantify areas with significant ecological benefits from artificial rain enhancement. Specifically, this includes: calculating the rate of change of NDVI for each grid point based on time-series NDVI values ​​measured by remote sensing multiple times after artificial rain enhancement; and simultaneously using the Mann-Kendall test to detect the significance of the time-series NDVI change for each grid point.

[0050] Mann-Kendall is a nonparametric statistical test method suitable for detecting the significance of changes in a sequence. Its advantage is that it does not require the samples to follow a certain distribution and is not affected by a few outliers.

[0051] First, calculate the NDVI order column of the sequential time series. S k And calculate the order statistics according to the equation. UF k .

[0052] For a time series X with m NDVI samples, construct an ordered sequence.

[0053]

[0054]

[0055] Among them, the order column The value at time i. Value greater than time j The cumulative count of the number of elements; k is the sample size; Let be the NDVI value of the i-th sample. Under the assumption of random independence in the time series, an order statistic is defined.

[0056]

[0057] in, UF 1=0, , They are The mean and variance of.

[0058] In the time series sequence x1, x2, ..., x m When the elements are independent and have the same continuous distribution, the value can be calculated using the following formula, where x... m Let be the NDVI value of the m-th sample.

[0059]

[0060] It follows a standard normal distribution, which is based on the time series order x1, x2, ..., x... mThe calculated statistic sequence. Given a significance level α, look up the normal distribution table; if | |> U α This indicates that there is a clear trend change in the sequence.

[0061] Then, calculate the order column of the reverse time series. S k 'Calculate according to the above method' UB k That is, in reverse order of the time series x. m ,x m-1 ..., x1, then repeat the above process to make... UB k =– UF k k= , -1,…,1), UB 1 = 0.

[0062] Finally, given the significance level α (For example α =0.05, critical value U 0.05 = 1.96). UF k and UB k The resulting sequence curve and ( 1.96) Both critical lines are plotted on the same graph, such as Figure 2 As shown, when the intersection of the two curves exceeds the critical line, that is, when it is outside the two lines, it indicates that the upward or downward trend of the NDVI of the time series is significant.

[0063] Then, by using the open-source tool Raster Calculator or the Python library Rasterio to couple "rate of change" and "significance of change", regions of significant NDVI change can be identified.

[0064] The method for coupling "rate of change" and "significance of change" is as follows.

[0065] Using open-source tools like Raster Calculator or the Python library Rasterio, mathematical and logical operations can be combined to achieve... This couples "rate of change" and "significance of change".

[0066] In one exemplary embodiment, the area with significant ecological benefits from artificial rain enhancement... as follows.

[0067]

[0068] in, The preset threshold; At the significance level, Used to characterize the significance of changes.

[0069] In an exemplary embodiment, a computer device is provided, including a memory and a processor. The memory stores a computer program, and the processor executes the computer program to implement the steps in the above-described method embodiments. The computer device can be a server or a terminal. The computer device includes a processor, a memory, an input / output interface (I / O), and a communication interface. The processor, memory, and I / O are connected via a system bus, and the communication interface is connected to the system bus via the I / O interface. The processor of the computer device provides computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and internal memory. The non-volatile storage medium stores an operating system, a computer program, and a database. The internal memory provides an environment for the operation of the operating system and computer program in the non-volatile storage medium. The database of the computer device stores data to be processed. The I / O interface of the computer device is used for exchanging information between the processor and external devices. The communication interface of the computer device is used for communicating with external terminals via a network connection. When the computer program is executed by the processor, it implements a method for quantifying the ecological benefits of artificial rain enhancement.

[0070] In one exemplary embodiment, a computer device is provided, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the steps in the above-described method embodiments.

[0071] In one exemplary embodiment, a computer program product is provided, including a computer program that, when executed by a processor, implements the steps in the above-described method embodiments.

[0072] Those skilled in the art will understand that all or part of the processes in the above embodiments can be implemented by hardware related to computer program instructions. The computer program can be stored in a non-volatile computer-readable storage medium, and when executed, it can include the processes of the embodiments described above. Any references to memory, databases, or other media used in the embodiments provided in this application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM).

[0073] The databases involved in the embodiments provided in this application may include at least one type of relational database and non-relational database. Non-relational databases may include, but are not limited to, blockchain-based distributed databases. The processors involved in the embodiments provided in this application may be general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic devices, quantum computing-based data processing logic devices, etc., and are not limited to these.

[0074] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0075] This document uses specific examples to illustrate the principles and implementation methods of this application. The descriptions of the above embodiments are only for the purpose of helping to understand the methods and core ideas of this application. Furthermore, those skilled in the art will recognize that, based on the ideas of this application, there will be changes in the specific implementation methods and application scope. Therefore, the content of this specification should not be construed as a limitation of this application.

Claims

1. A method for quantifying the ecological benefits of artificial rain enhancement, characterized in that, include: Based on the flight trajectory of the artificial rain enhancement aircraft, the potential impact area of ​​artificial rain enhancement was determined; Identify all meteorological stations within the potential impact area of ​​the artificial rain enhancement program; Spatial interpolation is performed on the artificial rain enhancement amounts observed at meteorological stations to form raster data of artificial rain enhancement, and the actual impact area of ​​artificial rain enhancement is determined based on the raster data; Based on the time series NDVI measured by remote sensing multiple times after artificial rain enhancement in the actual affected area and the non-rain enhancement area, the NDVI change rate is quantified at the raster scale; the natural conditions of the non-rain enhancement area are the same as those of the actual affected area of ​​artificial rain enhancement. Detect the significance of changes in the time-series NDVI corresponding to each grid point; The rate of change and significance of the NDVI change are coupled at the raster scale to quantify the area of ​​significant ecological benefits of artificial rain enhancement; the area of ​​significant ecological benefits of artificial rain enhancement is a raster with significant changes in NDVI over time. The ecological benefits of artificial rain enhancement are quantified based on the areas with significant ecological benefits.

2. The method for quantifying the ecological benefits of artificial rain enhancement according to claim 1, characterized in that, Based on the flight paths of artificial rainmaking aircraft, the potential impact areas of artificial rainmaking are determined, specifically including: The flight path is generated based on the coordinates of the artificial rainmaking aircraft. The potential impact area of ​​artificial rain enhancement is determined by extending a set distance outward from the flight trajectory.

3. The method for quantifying the ecological benefits of artificial rain enhancement according to claim 1, characterized in that, Spatial interpolation is performed on the artificial rainfall amounts observed at meteorological stations to generate raster data of artificial rainfall, and the actual impact area of ​​artificial rainfall is determined based on the raster data, specifically including: Using the Kriging interpolation method, spatial interpolation is performed on the artificial rain enhancement amounts observed at meteorological stations to form raster data of artificial rain enhancement. Based on the grid data, the grid areas where the artificial rain enhancement rainfall exceeds the set rainfall threshold are identified as the actual impact area of ​​artificial rain enhancement.

4. The method for quantifying the ecological benefits of artificial rain enhancement according to claim 1, characterized in that, The rate of change of NDVI for: ； in, n This represents the total number of days with rainfall. For the first i The variable value for the day.

5. The method for quantifying the ecological benefits of artificial rain enhancement according to claim 1, characterized in that, Detecting the significance of changes in the time-series NDVI corresponding to each grid point, specifically including: Based on the time series NDVI corresponding to each grid point, calculate the NDVI order column of the sequential time series and the NDVI order column of the reverse time series; Calculate the order statistics and reverse statistics based on the NDVI order column of the sequential time series and the NDVI order column of the reverse time series. The significance of the change in NDVI of the time series corresponding to each grid point is determined based on the sequence curve formed by the ordered statistics, the sequence curve formed by the reverse statistics, and the two critical lines.

6. The method for quantifying the ecological benefits of artificial rain enhancement according to claim 1, characterized in that, The area with significant ecological benefits from artificial rain enhancement for: ； in, The rate of change of NDVI; The preset threshold; At the significance level, Used to characterize the significance of changes.

7. A computer device, comprising: A memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that the processor executes the computer program to implement the method for quantifying the ecological benefits of artificial rain enhancement as described in any one of claims 1-6.

8. A computer program product, comprising a computer program, characterized in that, When executed by a processor, the computer program implements the method for quantifying the ecological benefits of artificial rain enhancement as described in any one of claims 1-6.

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