Environment monitoring method and device based on multispectral image processing

Abstract

The invention discloses an environment monitoring method and device based on multispectral image processing, and relates to the technical field of environment monitoring. The method comprises the following steps: acquiring a multispectral image of target soil; acquiring environment state data corresponding to the multispectral image through an environment monitoring sensor; performing fusion calibration on the environment state data and the preprocessed multispectral image to obtain soil spectral data; based on a preset soil pollutant index set and the soil spectrum data, extracting soil pollutant characteristics, and performing spectrum matching on the soil pollutant characteristics and a pollutant spectrum database to obtain a pollutant spectrum; based on the pollutant pedigree, combined with the soil temperature, the soil humidity and the soil PH value, generating a soil health index through multi-dimensional weighted calculation; and performing soil environment monitoring according to the soil health index to obtain an environment monitoring result. The technical problem that it is difficult to accurately evaluate the soil health state in the prior art is solved, and the technical effect of improving the soil health state evaluation accuracy is achieved.

Description

Technical Field

[0001] The present invention relates to the technical field of environmental monitoring, and in particular to an environmental monitoring method and device based on multispectral image processing. Background Art

[0002] Existing environmental monitoring methods usually rely on a single data source or limited sensing equipment, making it difficult to comprehensively and accurately assess the soil health status and pollutant distribution in complex environments. For example, traditional soil sampling and analysis methods often have the defects of small geographical coverage and poor timeliness, and cannot provide information on the spatial distribution and dynamic changes of soil pollutants. At the same time, relying solely on a single parameter, such as soil temperature or humidity, is difficult to fully reflect the actual health status of the soil. Summary of the invention

[0003] The present application provides an environmental monitoring method and device based on multispectral image processing, which solves the technical problem in the prior art that it is difficult to accurately assess the health status of soil.

[0004] In view of the above problems, the present application provides an environmental monitoring method and device based on multispectral image processing.

[0005] In a first aspect of the present application, a method for environmental monitoring based on multispectral image processing is provided, the method comprising:

[0006] A multispectral camera is arranged on the target soil to collect a multispectral image of the target soil; environmental status data corresponding to the multispectral image is acquired through an environmental monitoring sensor, wherein the environmental status data includes light intensity, soil temperature, soil moisture, and soil pH value; the environmental status data is fused and calibrated with the pre-processed multispectral image to obtain soil spectral data; soil pollutant characteristics are extracted based on a preset soil pollutant index set and the soil spectral data, and the soil pollutant characteristics are spectrally matched with a pollutant spectral database to obtain a pollutant spectrum, wherein the pollutant spectrum includes a pollutant concentration distribution map; based on the pollutant spectrum, in combination with the soil temperature, the soil moisture and the soil pH value, a soil health index is generated through multidimensional weighted calculation; soil environmental monitoring is performed according to the soil health index to obtain environmental monitoring results, wherein the environmental monitoring results include health signals and risk signals.

[0007] A second aspect of the present application provides an environmental monitoring device based on multispectral image processing, the device comprising:

[0008] An image acquisition module, the image acquisition module is used to deploy a multispectral camera on the target soil to collect the multispectral image of the target soil; an environmental status data acquisition module, the environmental status data acquisition module is used to acquire environmental status data corresponding to the multispectral image through an environmental monitoring sensor, wherein the environmental status data includes light intensity, soil temperature, soil moisture, and soil pH value; a fusion calibration module, the fusion calibration module is used to fuse and calibrate the environmental status data with the pre-processed multispectral image to obtain soil spectral data; a matching module, the matching module is used to extract soil pollutant characteristics based on a preset soil pollutant index set and the soil spectral data, and spectrally match the soil pollutant characteristics with a pollutant spectral database to obtain a pollutant spectrum, wherein the pollutant spectrum includes a pollutant concentration distribution map; a calculation module, the calculation module is used to generate a soil health index based on the pollutant spectrum, combined with the soil temperature, the soil moisture and the soil pH value, through multidimensional weighted calculation; a monitoring module, the monitoring module is used to perform soil environmental monitoring according to the soil health index to obtain environmental monitoring results, wherein the environmental monitoring results include health signals and risk signals.

[0009] One or more technical solutions provided in this application have at least the following technical effects or advantages:

[0010] First, a multispectral camera is arranged in the target soil to collect a multispectral image of the target soil; the environmental status data corresponding to the multispectral image is obtained through the environmental monitoring sensor, wherein the environmental status data includes light intensity, soil temperature, soil moisture, and soil pH value. Next, the environmental status data is fused and calibrated with the preprocessed multispectral image to obtain soil spectral data. Then, based on the preset soil pollutant index set and soil spectral data, the soil pollutant characteristics are extracted, and the soil pollutant characteristics are spectrally matched with the pollutant spectrum database to obtain the pollutant spectrum, wherein the pollutant spectrum includes a pollutant concentration distribution map. Further, based on the pollutant spectrum, combined with soil temperature, soil moisture and soil pH value, a soil health index is generated through multidimensional weighted calculation. Finally, soil environmental monitoring is performed according to the soil health index to obtain environmental monitoring results, wherein the environmental monitoring results include health signals and risk signals. The technical problem that it is difficult to accurately evaluate the soil health status in the prior art is solved, and the technical effect of improving the accuracy of soil health status evaluation is achieved. BRIEF DESCRIPTION OF THE DRAWINGS

[0011] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0012] Figure 1 A schematic diagram of a process flow of an environmental monitoring method based on multispectral image processing provided in an embodiment of the present application;

[0013] Figure 2 A schematic diagram of the structure of an environmental monitoring device based on multispectral image processing provided in an embodiment of the present application.

[0014] Explanation of the reference numerals: image acquisition module 11 , environment status data acquisition module 12 , fusion calibration module 13 , matching module 14 , calculation module 15 , monitoring module 16 . DETAILED DESCRIPTION

[0015] The present application solves the technical problem in the prior art that it is difficult to accurately assess the health status of soil by providing an environmental monitoring method and device based on multispectral image processing.

[0016] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, rather than all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of this application.

[0017] It should be noted that the terms "including" and "having" are intended to cover non-exclusive inclusions. For example, a process, method, system, product or server that includes a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or modules that are not explicitly listed or are inherent to these processes, methods, products or devices.

[0018] Embodiment 1, as Figure 1 As shown, the present application provides an environmental monitoring method based on multispectral image processing, wherein the method comprises:

[0019] A multispectral camera is deployed on the target soil to collect a multispectral image of the target soil.

[0020] In the target soil area, multiple multispectral cameras are deployed to cover the entire monitoring area according to soil distribution and environmental conditions, so as to collect multispectral images of the target soil, thereby providing basic data for subsequent soil property analysis and environmental monitoring.

[0021] Environmental status data corresponding to the multispectral image is acquired through an environmental monitoring sensor, wherein the environmental status data includes light intensity, soil temperature, soil moisture, and soil pH value.

[0022] While collecting multispectral images, environmental status data corresponding to these images are obtained through environmental monitoring sensors deployed in the target soil area. Environmental monitoring sensors can measure key environmental parameters such as light intensity, soil temperature, soil moisture, and soil pH value in the target area in real time. By obtaining these environmental status data synchronized with multispectral images, it can provide accurate references for subsequent data fusion and calibration processes, thereby improving the accuracy of soil pollutant feature extraction.

[0023] The environmental status data is fused and calibrated with the preprocessed multispectral image to obtain soil spectral data.

[0024] The collected multispectral images are preprocessed to eliminate interference factors such as noise and distortion, and to standardize the spectral information in the image. The preprocessed multispectral images can better reflect the spectral characteristics of the target soil. The environmental status data (light intensity, soil temperature, humidity, pH value, etc.) are fused and calibrated with the preprocessed multispectral images; by establishing a linear relationship between the environmental status data and the spectral reflectance characteristics in the image, the image deviation caused by changes in environmental conditions can be corrected. For example, changes in light intensity may lead to differences in spectral reflectance in different bands, and the brightness and contrast of the multispectral image can be calibrated by light intensity data. Through fusion calibration, high-precision soil spectral data is finally obtained. The soil spectral data comprehensively considers the details of the multispectral image and the influence of the environmental status, and can more accurately reflect the spectral characteristics of the target soil.

[0025] Based on a preset soil pollutant index set and the soil spectral data, soil pollutant characteristics are extracted, and the soil pollutant characteristics are spectrally matched with a pollutant spectral database to obtain a pollutant spectrum, wherein the pollutant spectrum includes a pollutant concentration distribution map.

[0026] The acquired soil spectral data is analyzed based on the pre-set soil pollutant index set. The soil pollutant index set is a parameter set consisting of common pollutant types and related standards, which is used to guide the identification and classification of soil pollutants. Pollutants may include heavy metals (such as lead, cadmium, mercury, etc.), organic pollutants (such as polycyclic aromatic hydrocarbons, pesticide residues, etc.) and other harmful compounds. By analyzing the soil spectral data, the spectral characteristics related to these pollutants in specific bands can be extracted. The spectral performance of each pollutant at different wavelengths is unique, which is called its spectral characteristics. After extracting the soil pollutant characteristics, the soil pollutant characteristics are spectrally matched with the pollutant spectral database to generate a pollutant spectrum. The pollutant spectrum contains the types of pollutants and their pollutant concentration distribution maps in the soil.

[0027] Furthermore, based on a preset soil pollutant index set and the soil spectral data, soil pollutant characteristics are extracted, and the soil pollutant characteristics are spectrally matched with a pollutant spectral database to obtain a pollutant spectrum. The method includes:

[0028] The soil spectral data is converted into a spectral reflectance characteristic curve; according to the preset soil pollutant index set, the spectral characteristic bands of multiple pollutants are screened, and the soil pollutant characteristics are obtained in combination with the spectral reflectance characteristic curve; the soil pollutant characteristics are spectrally matched with the pollutant spectral database, and a pollutant spectrum is generated according to the spectral matching results.

[0029] Specifically, the acquired soil spectral data is converted into a spectral reflectance characteristic curve through a data processing algorithm. The spectral reflectance characteristic curve represents the light reflection intensity of the soil in different bands, reflecting the spectral characteristics of various substances in the soil. The different band information of the spectral reflectance characteristic curve is helpful to identify the types of pollutants in the soil; according to the preset soil pollutant indicator set, the spectral characteristic bands related to various pollutants are screened out. Each pollutant has its own specific spectral characteristic band, which represents the reflectivity change of the pollutant in this band; the screened spectral characteristic bands are combined with the converted spectral reflectance characteristic curve to further analyze and extract the spectral characteristics of the corresponding pollutants; the extracted soil pollutant spectral characteristics are spectrally matched with the pollutant spectral database to obtain the pollutant spectrum.

[0030] Furthermore, the soil pollutant characteristics are spectrally matched with a pollutant spectrum database, and a pollutant spectrum is generated according to the spectral matching result. The method includes:

[0031] The pollutant spectral database includes a standard pollutant spectral reflectance curve; a spectral matching result is obtained by calculating the similarity between the standard pollutant spectral reflectance curve and the spectral reflectance characteristic curve; based on the spectral matching result and combined with the amplitude change of the spectral reflectance characteristic curve, a concentration analysis is performed to generate a pollutant spectrum.

[0032] Specifically, the pollutant spectral database pre-stores standard spectral reflectance curves of various common pollutants. These curves reflect the spectral characteristics of different pollutants within a specific wavelength range. The standard spectral curve of each pollutant has been experimentally measured and calibrated as benchmark data for subsequent spectral matching. The degree of matching between the spectral reflectance characteristic curve extracted from the target soil and the standard spectral reflectance curve in the pollutant spectral database is determined by calculating the similarity between the two. The similarity calculation can use cosine similarity. The higher the similarity, the closer the pollutant characteristics in the soil are to the spectral characteristics of a certain pollutant in the database, and the higher the matching accuracy. If the similarity is greater than the preset similarity threshold, the pollutant type is determined. After matching the pollutant type, the concentration analysis is further performed in combination with the amplitude change of the spectral reflectance characteristic curve. The amplitude of the spectral reflectance characteristic curve reflects the reflection intensity of different pollutants in the spectral band. By analyzing the amplitude change, the concentration of the pollutant in the soil can be estimated. Based on the results of spectral matching and concentration analysis, a pollutant spectrum is generated.

[0033] Further, after generating the pollutant spectrum, the method includes:

[0034] Acquire the spatial location data of the target soil; associate the spatial location data with the pollutant spectrum to generate a pollutant spatial distribution map; compare the pollutant spatial distribution map with a preset pollutant concentration threshold to generate a pollutant concentration exceeding standard area map; perform pollutant diffusion trend analysis based on the pollutant concentration exceeding standard area map to obtain potential pollution risk areas, wherein the potential pollution risk areas include key monitoring area identification.

[0035] Preferably, the spatial location data of the target soil is obtained through a geographic information system (GIS). These data can accurately locate the location of the soil monitoring area and provide a geographic coordinate basis for subsequent spatial distribution analysis of pollutants; the spatial location data of the soil is associated with the generated pollutant spectrum, and a pollutant spatial distribution map is generated in combination with the types of different pollutants in the soil and their concentration information. The pollutant spatial distribution map can show the concentration changes of various pollutants at different spatial locations, providing a visual reference for the regional distribution of pollutants; by comparing the spatial distribution map of pollutants with a preset pollutant concentration threshold, it is determined which areas have pollutant concentrations exceeding the safety threshold, and based on the comparison results, a pollutant concentration exceeding standard area map is generated to intuitively display the distribution of pollutants exceeding the standard in the target soil area; based on the pollutant concentration exceeding standard area map, a pollutant diffusion trend analysis is performed, and by analyzing the diffusion pattern of pollutants in time and space, the direction and range of possible pollutant diffusion are predicted, potential pollution risk areas are generated, and potential pollution risk areas are identified as key monitoring areas.

[0036] Based on the pollutant spectrum, combined with the soil temperature, the soil moisture and the soil pH value, a soil health index is generated through multi-dimensional weighted calculation.

[0037] The pollutant spectrum includes the types and concentration distribution of various pollutants in the soil. As the basic data for soil health assessment, the types and concentrations of pollutants have an important weight in assessing the health of the soil. The higher the concentration of pollutants, the greater the negative impact on soil health. Through weighted calculation, data from multiple dimensions such as pollutant concentration, soil temperature, humidity and pH value are comprehensively considered to generate a soil health index. The higher the value of the soil health index, the better the health of the soil, while a lower value indicates that the soil may be threatened by pollution or environmental deterioration.

[0038] Furthermore, based on the pollutant spectrum, combined with the soil temperature, the soil moisture and the soil pH value, a soil health index is generated through multi-dimensional weighted calculation, and the method includes:

[0039] Soil health index calculation formula: Among them, SHI represents the soil health index, ω T Characterizes the soil temperature weight, ω H Characterizes the soil moisture weight, ω P Characterize soil pH weight, represents the weight of the concentration of the i-th pollutant, T represents the standardized soil temperature, H represents the standardized soil moisture, P represents the standardized soil pH value, C i Characterize the concentration of the i-th pollutant; perform multi-dimensional weighted calculation according to the soil health index calculation formula to generate the soil health index.

[0040] Specifically, the soil health index is calculated using the formula Perform multi-dimensional weighted calculation to generate the soil health index, where SHI represents the soil health index, ω T Characterizes the soil temperature weight, ω H Characterizes the soil moisture weight, ω P Characterize soil pH weight, represents the weight of the concentration of the i-th pollutant, T represents the standardized soil temperature, H represents the standardized soil moisture, P represents the standardized soil pH value, C i Characterizes the concentration of the i-th pollutant.

[0041] Soil environment monitoring is performed according to the soil health index to obtain environmental monitoring results, wherein the environmental monitoring results include health signals and risk signals.

[0042] The soil health index obtained through multi-dimensional weighted calculation is used as the core indicator to reflect the overall health status of the target soil. The soil health index covers the comprehensive influence of key factors such as soil pollutant concentration, temperature, humidity and pH value. Soil environmental monitoring is carried out according to the soil health index, that is, the soil status is divided into healthy status and risk status, and corresponding health signals and risk signals are generated.

[0043] Furthermore, soil environmental monitoring is performed according to the soil health index to obtain environmental monitoring results, and the method includes:

[0044] The soil health index is compared with a preset soil health threshold; if the soil health index is greater than or equal to the preset soil health threshold, a health signal is generated; if the soil health index is less than the preset soil health threshold, a risk signal is generated.

[0045] Specifically, the calculated soil health index is compared with the preset soil health threshold. The preset soil health threshold is a value that reflects the soil health standard, which is usually determined by experimental data or industry standards. If the calculated soil health index is greater than or equal to the preset health threshold, it means that the soil is in good condition and meets the health standard, and a health signal is generated, indicating that the soil is in a safe state, the pollutant concentration is low or within a safe range, and the environmental conditions are suitable, and no additional measures are required. For example, if the health threshold is 60 and the current soil health index is 75, a health signal is generated. If the soil health index is less than the preset health threshold, it means that the soil health has deteriorated and may be contaminated or the environmental conditions are poor, then a risk signal is generated, indicating that the soil may have pollution risks or other environmental problems and further monitoring and control measures are required. For example, if the health threshold is 60 and the current soil health index is 45, a risk signal is generated.

[0046] Furthermore, after performing soil environmental monitoring according to the soil health index and obtaining environmental monitoring results, the method further includes:

[0047] Acquire historical soil monitoring data and historical meteorological data; use the historical soil monitoring data and the historical meteorological data as training data to train a machine learning model to obtain a risk trend prediction model; input real-time meteorological data and the soil health index into the risk trend prediction model to perform trend prediction and obtain a risk prediction result; and adjust the environmental monitoring result according to the risk prediction result.

[0048] Preferably, historical soil monitoring data of the target area is collected, including soil health index, pollutant concentration, soil temperature, humidity, pH value, etc.; at the same time, historical meteorological data related to soil is obtained, including meteorological parameters such as temperature, humidity, rainfall, wind speed, etc.; the acquired historical soil monitoring data and historical meteorological data are used as training data and input into the machine learning model. Through model training, the change pattern of soil environment can be identified from historical data, and a risk trend prediction model for predicting future risk trends can be generated. The risk trend prediction model can identify which meteorological conditions or soil indicators will cause significant changes in the soil health index or increase in risk; the current meteorological data and the latest soil health index are collected in real time, and these data are input into the trained risk trend prediction model. The risk trend prediction model will analyze based on real-time data to predict future trends in soil health; according to the risk prediction results, the existing environmental monitoring strategy is adjusted.

[0049] Furthermore, according to the risk prediction result, the environmental monitoring result is adjusted, and the method includes:

[0050] The risk prediction results include an increase in the soil health index and a decrease in the soil health index; if the soil health index increases, the soil health threshold is adjusted to generate a soil improvement signal; if the soil health index decreases, an early warning signal is generated.

[0051] Specifically, the risk prediction results include an increase in the soil health index and a decrease in the soil health index. An increase in the soil health index indicates that the soil condition has improved, the pollutant concentration has decreased, or the environmental conditions have become more suitable. A decrease in the soil health index indicates that the soil condition has deteriorated, and there may be increased pollution or poor environmental conditions. When the prediction results show that the soil health index has increased, it means that the soil health status is gradually improving. In this case, the soil health threshold can be appropriately adjusted. Adjusting the soil health threshold means improving or optimizing the health standard based on the current soil improvement trend to ensure that future monitoring can more accurately reflect soil changes. For example, if the current threshold is 60 and the health status continues to improve , the threshold can be raised to 65 or higher; with the adjustment of the threshold, a soil improvement signal is generated, indicating that the soil has returned to normal or the environment has been significantly improved. This signal can guide decision makers to reduce the monitoring frequency or adjust the key monitoring areas, indicating that the restoration measures are effective; when the prediction results show that the soil health index has declined, it means that the soil condition has a deteriorating trend. At this time, there is no need to adjust the health threshold, but an early warning signal needs to be generated immediately. The early warning signal can be divided into different warning levels according to the degree of decline in the health index, such as mild, moderate or severe warnings. The generated early warning signal is intended to remind relevant personnel that the soil environment is facing potential risks and that corresponding intervention measures or further environmental monitoring are required.

[0052] In summary, the embodiments of the present application have at least the following technical effects:

[0053] First, a multispectral camera is arranged in the target soil to collect a multispectral image of the target soil; the environmental status data corresponding to the multispectral image is obtained through the environmental monitoring sensor, wherein the environmental status data includes light intensity, soil temperature, soil moisture, and soil pH value. Next, the environmental status data is fused and calibrated with the preprocessed multispectral image to obtain soil spectral data. Then, based on the preset soil pollutant index set and soil spectral data, the soil pollutant characteristics are extracted, and the soil pollutant characteristics are spectrally matched with the pollutant spectrum database to obtain the pollutant spectrum, wherein the pollutant spectrum includes a pollutant concentration distribution map. Further, based on the pollutant spectrum, combined with soil temperature, soil moisture and soil pH value, a soil health index is generated through multidimensional weighted calculation. Finally, soil environmental monitoring is performed according to the soil health index to obtain environmental monitoring results, wherein the environmental monitoring results include health signals and risk signals. The technical problem that it is difficult to accurately evaluate the soil health status in the prior art is solved, and the technical effect of improving the accuracy of soil health status evaluation is achieved.

[0054] Embodiment 2 is based on the same inventive concept as the environmental monitoring method based on multispectral image processing in the above embodiment. Figure 2 As shown, the present application provides an environmental monitoring device based on multispectral image processing, wherein the device includes:

[0055] An image acquisition module 11 is used to deploy a multispectral camera in the target soil to collect the multispectral image of the target soil; an environmental status data acquisition module 12 is used to acquire environmental status data corresponding to the multispectral image through an environmental monitoring sensor, wherein the environmental status data includes light intensity, soil temperature, soil moisture, and soil pH value; a fusion calibration module 13 is used to fuse and calibrate the environmental status data with the pre-processed multispectral image to obtain soil spectral data; a matching module 14 is used to match the environmental status data based on a preset soil The soil pollutant index set and the soil spectral data are used to extract soil pollutant characteristics, and the soil pollutant characteristics are spectrally matched with the pollutant spectral database to obtain a pollutant spectrum, wherein the pollutant spectrum includes a pollutant concentration distribution map; a calculation module 15, wherein the calculation module 15 is used to generate a soil health index based on the pollutant spectrum, combined with the soil temperature, the soil moisture and the soil pH value, through multi-dimensional weighted calculation; a monitoring module 16, wherein the monitoring module 16 is used to perform soil environmental monitoring according to the soil health index to obtain environmental monitoring results, wherein the environmental monitoring results include health signals and risk signals.

[0056] Furthermore, the matching module 14 is used to perform the following method:

[0057] The soil spectral data is converted into a spectral reflectance characteristic curve; according to the preset soil pollutant index set, the spectral characteristic bands of multiple pollutants are screened, and the soil pollutant characteristics are obtained by combining the spectral reflectance characteristic curve; the pollutant characteristics are spectrally matched with the pollutant spectral database, and a pollutant spectrum is generated according to the spectral matching results.

[0058] Furthermore, the matching module 14 is used to perform the following method:

[0059] The pollutant spectral database includes a standard pollutant spectral reflectance curve; a spectral matching result is obtained by calculating the similarity between the standard pollutant spectral reflectance curve and the spectral reflectance characteristic curve; based on the spectral matching result and combined with the amplitude change of the spectral reflectance characteristic curve, a concentration analysis is performed to generate a pollutant spectrum.

[0060] Furthermore, the matching module 14 is used to perform the following method:

[0061] Acquire the spatial location data of the target soil; associate the spatial location data with the pollutant spectrum to generate a pollutant spatial distribution map; compare the pollutant spatial distribution map with a preset pollutant concentration threshold to generate a pollutant concentration exceeding standard area map; perform pollutant diffusion trend analysis based on the pollutant concentration exceeding standard area map to obtain potential pollution risk areas, wherein the potential pollution risk areas include key monitoring area identification.

[0062] Furthermore, the calculation module 15 is used to execute the following method:

[0063] Soil health index calculation formula: Among them, SHI represents the soil health index, ω T Characterizes the soil temperature weight, ω H Characterizes the soil moisture weight, ω P Characterize soil pH weight, represents the weight of the concentration of the i-th pollutant, T represents the standardized soil temperature, H represents the standardized soil moisture, P represents the standardized soil pH value, C i Characterize the concentration of the i-th pollutant; perform multi-dimensional weighted calculation according to the soil health index calculation formula to generate the soil health index.

[0064] Furthermore, the monitoring module 16 is used to perform the following method:

[0065] The soil health index is compared with a preset soil health threshold; if the soil health index is greater than or equal to the preset soil health threshold, a health signal is generated; if the soil health index is less than the preset soil health threshold, a risk signal is generated.

[0066] Furthermore, the monitoring module 16 is used to perform the following method:

[0067] Acquire historical soil monitoring data and historical meteorological data; use the historical soil monitoring data and the historical meteorological data as training data to train a machine learning model to obtain a risk trend prediction model; input real-time meteorological data and the soil health index into the risk trend prediction model to perform trend prediction and obtain a risk prediction result; and adjust the environmental monitoring result according to the risk prediction result.

[0068] Furthermore, the monitoring module 16 is used to perform the following method:

[0069] The risk prediction results include an increase in the soil health index and a decrease in the soil health index; if the soil health index increases, the soil health threshold is adjusted to generate a soil improvement signal; if the soil health index decreases, an early warning signal is generated.

[0070] It should be noted that the above-mentioned sequence of the embodiments of the present application is only for description and does not represent the advantages and disadvantages of the embodiments. And the above-mentioned specific embodiments of this specification are described. The processes depicted in the accompanying drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0071] The above description is only a preferred embodiment of the present application and is not intended to limit the present application. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present application shall be included in the protection scope of the present application.

[0072] This specification and the drawings are merely exemplary illustrations of the present application and are deemed to cover any and all modifications, variations, combinations or equivalents within the scope of the present application. Obviously, those skilled in the art may make various modifications and variations to the present application without departing from the scope of the present application. Thus, if these modifications and variations of the present application fall within the scope of the present application and its equivalents, the present application intends to include these modifications and variations.

Claims

1. Environmental monitoring method based on multispectral image processing, It is characterized in that The method comprises: A multispectral camera is deployed on the target soil to collect a multispectral image of the target soil; Acquire environmental status data corresponding to the multispectral image through an environmental monitoring sensor, wherein the environmental status data includes light intensity, soil temperature, soil moisture, and soil pH value; fusing and calibrating the environmental status data with the preprocessed multispectral image to obtain soil spectral data; Extracting soil pollutant characteristics based on a preset soil pollutant index set and the soil spectral data, and performing spectral matching between the soil pollutant characteristics and a pollutant spectral database to obtain a pollutant spectrum, wherein the pollutant spectrum includes a pollutant concentration distribution map; Based on the pollutant spectrum, combined with the soil temperature, the soil moisture and the soil pH value, a soil health index is generated through multi-dimensional weighted calculation; Soil environment monitoring is performed according to the soil health index to obtain environmental monitoring results, wherein the environmental monitoring results include health signals and risk signals.

2. The environmental monitoring method based on multispectral image processing as claimed in claim 1, It is characterized in that Based on a preset soil pollutant index set and the soil spectral data, soil pollutant characteristics are extracted, and the soil pollutant characteristics are spectrally matched with a pollutant spectral database to obtain a pollutant spectrum, the method comprising: Converting the soil spectrum data into a spectral reflectance characteristic curve; According to the preset soil pollutant index set, spectral characteristic bands of multiple pollutants are screened, and soil pollutant characteristics are obtained by combining the spectral reflectance characteristic curve; The soil pollutant characteristics are spectrally matched with the pollutant spectrum database, and a pollutant spectrum is generated based on the spectral matching results.

3. The environmental monitoring method based on multispectral image processing as claimed in claim 2, It is characterized in that The soil pollutant characteristics are spectrally matched with a pollutant spectrum database, and a pollutant spectrum is generated according to the spectral matching result. The method includes: The pollutant spectrum database includes standard pollutant spectrum reflectance curves; Obtaining a spectral matching result by calculating the similarity between the spectral reflectance curve of the standard pollutant and the spectral reflectance characteristic curve; According to the spectral matching result, combined with the amplitude change of the spectral reflectance characteristic curve, concentration analysis is performed to generate a pollutant spectrum.

4. The environmental monitoring method based on multispectral image processing as claimed in claim 3, It is characterized in that After generating the contaminant spectrum, the method includes: Acquiring spatial position data of the target soil; Associating the spatial location data with the pollutant spectrum to generate a pollutant spatial distribution map; Compare the pollutant spatial distribution map with the preset pollutant concentration threshold to generate a pollutant concentration exceeding standard area map; Based on the pollutant concentration exceeding standard area map, pollutant diffusion trend analysis is performed to obtain potential pollution risk areas, and the potential pollution risk areas include key monitoring area identification.

5. The environmental monitoring method based on multispectral image processing as claimed in claim 1, It is characterized in that Based on the pollutant spectrum, combined with the soil temperature, the soil moisture and the soil pH value, a soil health index is generated through multi-dimensional weighted calculation, the method comprising: Soil health index calculation formula: Among them, SHI represents the soil health index, ω T Characterizes the soil temperature weight, ω H Characterizes the soil moisture weight, ω P Characterize soil pH weight, represents the weight of the concentration of the i-th pollutant, T represents the standardized soil temperature, H represents the standardized soil moisture, P represents the standardized soil pH value, C i Characterize the concentration of the i-th pollutant; According to the soil health index calculation formula, multi-dimensional weighted calculation is performed to generate the soil health index.

6. The environmental monitoring method based on multispectral image processing as claimed in claim 1, It is characterized in that Performing soil environmental monitoring according to the soil health index to obtain environmental monitoring results, the method comprising: comparing the soil health index to a preset soil health threshold; If the soil health index is greater than or equal to a preset soil health threshold, generating a health signal; If the soil health index is less than a preset soil health threshold, a risk signal is generated.

7. The environmental monitoring method based on multispectral image processing as claimed in claim 1, It is characterized in that After performing soil environmental monitoring according to the soil health index and obtaining environmental monitoring results, the method further comprises: Obtain historical soil monitoring data and historical meteorological data; Using the historical soil monitoring data and the historical meteorological data as training data, training a machine learning model, and obtaining a risk trend prediction model; Inputting the real-time meteorological data and the soil health index into the risk trend prediction model to perform trend prediction and obtain risk prediction results; Adjust the environmental monitoring results according to the risk prediction results.

8. The environmental monitoring method based on multispectral image processing as claimed in claim 7, It is characterized in that According to the risk prediction result, adjusting the environmental monitoring result, the method comprises: The risk prediction results include an increase in soil health index and a decrease in soil health index; If the soil health index increases, adjusting the soil health threshold to generate a soil improvement signal; If the soil health index decreases, an early warning signal is generated.

9. Environmental monitoring device based on multispectral image processing, It is characterized in that The device is used to implement the environmental monitoring method based on multispectral image processing according to any one of claims 1 to 8, comprising: An image acquisition module, wherein the image acquisition module is used to deploy a multispectral camera on the target soil to acquire a multispectral image of the target soil; An environmental status data acquisition module, the environmental status data acquisition module is used to acquire environmental status data corresponding to the multispectral image through an environmental monitoring sensor, wherein the environmental status data includes light intensity, soil temperature, soil moisture, and soil pH value; A fusion calibration module, wherein the fusion calibration module is used to fuse and calibrate the environmental status data with the pre-processed multispectral image to obtain soil spectral data; A matching module, the matching module is used to extract soil pollutant characteristics based on a preset soil pollutant index set and the soil spectral data, and spectrally match the soil pollutant characteristics with a pollutant spectrum database to obtain a pollutant spectrum, wherein the pollutant spectrum includes a pollutant concentration distribution map; A calculation module, the calculation module is used to generate a soil health index through multi-dimensional weighted calculation based on the pollutant spectrum, combined with the soil temperature, the soil moisture and the soil pH value; A monitoring module is used to perform soil environmental monitoring according to the soil health index to obtain environmental monitoring results, wherein the environmental monitoring results include health signals and risk signals.

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