Soil heavy metal detection method based on near infrared spectrum

Abstract

The invention relates to the field of soil heavy metal analysis, in particular to a near infrared spectrum-based soil heavy metal detection method, which comprises the following steps of: shooting a near infrared dynamic image of soil in a target area, and acquiring a near infrared reflection spectrum of a plurality of near infrared image sets subordinate to the near infrared dynamic image; determining heavy metal distribution information of the soil in the target area in the detection time interval, and generating a soil heavy metal distribution map; based on the rainfall data of the target area, determining the rainwater permeation characteristic information of the soil of the target area, and combining the soil heavy metal distribution map to obtain the migration characteristic information of the heavy metal in the soil of the target area, thereby predicting the enrichment trend information of the heavy metal in the soil of the target area, and locating the heavy metal pollution range of the target area. The heavy metal in the soil can be dynamically detected globally and continuously in a natural state, the dynamic enrichment trend of the heavy metal in the soil is accurately predicted, the heavy metal pollution range in the soil is positioned, and the heavy metal detection accuracy is improved.

Description

[Technical field]

[0001] The present invention relates to the field of soil heavy metal analysis, and in particular to a soil heavy metal detection method based on near infrared spectroscopy. [Background technology]

[0002] The impact of human industrial activities on the environment has received increasing attention. Some factories will randomly discharge untreated sewage during the production process. These sewage usually contain a large amount of heavy metal compounds, which will cause heavy metal pollution in the soil after being discharged and entering the soil. The heavy metal compounds in the soil will be transmitted through the food chain with groundwater and crops and enriched in the human body, endangering human health.

[0003] In order to obtain the heavy metal pollution of soil, the prior art usually uses the means of fixed-point sampling and analysis of soil to detect the types and concentrations of heavy metals enriched in the soil. However, the above method requires a lot of manpower and material resources to sample the soil at a fixed point, and the selection of sampling points and the sampling process directly affect the credibility of the sample. In order to improve the detection accuracy, it is necessary to increase the number of sampling points and implement strict sampling operations. In addition, the soil samples collected are analyzed in the laboratory, so that the analysis results can only reflect the heavy metal pollution at several discrete positions in the soil during the sampling period, and it is impossible to dynamically identify the transfer and aggregation of heavy metal compounds in the soil. In addition, environmental factors such as precipitation will also affect the transfer and aggregation of heavy metal compounds in the soil, and the existing laboratory detection method cannot realize the dynamic tracking and detection of heavy metal compounds in the soil when the soil is in a natural state. It can be seen that how to perform global and continuous dynamic detection of heavy metals in the soil in a natural state is of great significance to determining the pollution diffusion of heavy metals in the soil. [Summary of the invention]

[0004] In order to perform global and continuous dynamic detection of heavy metals in soil under natural conditions, comprehensively determine the distribution of heavy metals in soil and the migration of heavy metals in soil under the influence of environmental factors such as precipitation, accurately predict the dynamic enrichment trend of heavy metals in soil, and accurately locate the scope of heavy metal pollution in soil, and improve the reliability of heavy metal pollution prevention and control in soil, the present invention provides a soil heavy metal detection method based on near infrared spectroscopy, the method comprising the following steps:

[0005] The soil in the target area is photographed to obtain a near-infrared dynamic image; the near-infrared dynamic image is divided to obtain a number of near-infrared image sets corresponding to a number of detection time intervals, and a near-infrared reflectance spectrum of each near-infrared image set is obtained;

[0006] Based on the near-infrared reflectance spectra of all near-infrared image sets, determine the heavy metal distribution information of the soil in the target area corresponding to all detection time intervals; based on the heavy metal distribution information, generate a soil heavy metal distribution map of the target area;

[0007] Obtain precipitation data corresponding to all detection time intervals in the target area, analyze the precipitation data, and determine rainwater infiltration characteristic information of the soil in the target area; based on the rainwater infiltration characteristic information and the soil heavy metal distribution map, perform heavy metal migration analysis on the soil in the target area to obtain migration characteristic information of heavy metals in the soil in the target area;

[0008] Based on the migration characteristic information, the enrichment trend information of heavy metals in the soil of the target area is predicted; based on the enrichment trend information, the heavy metal pollution range corresponding to the target area is located.

[0009] Preferably, the soil in the target area is photographed to obtain a near-infrared dynamic image, specifically:

[0010] Controlling the UAV flying over the target area to collect wireless signals emitted by a number of signal transmitters pre-set on the boundary of the target area, performing strength analysis on the wireless signals, and determining the relative distance change information between the UAV and the boundary of the target area during the flight;

[0011] Based on the relative distance change information, the flight path of the UAV over the target area is adjusted, so that the UAV can scan and photograph the soil in the target area during the flight over the target area, and obtain a near-infrared dynamic image of the soil in the target area during a preset time period.

[0012] Preferably, the near-infrared dynamic image is divided to obtain a plurality of near-infrared image sets corresponding to a plurality of detection time intervals, and a near-infrared reflectance spectrum of each near-infrared image set is obtained, specifically:

[0013] Based on the start and end times of all the detection time intervals during the preset time period and the time axis of the drone's scanning and shooting, the near-infrared dynamic image is framed to obtain a number of near-infrared image sets corresponding to all the detection time intervals; wherein each near-infrared image set includes a number of near-infrared images captured and generated within the corresponding detection time interval;

[0014] Near infrared spectral reflectance data analysis is performed on all near infrared images contained in each near infrared image set to obtain near infrared reflectance spectra of all near infrared images contained in each near infrared image set.

[0015] Preferably, the heavy metal distribution information of the soil in the target area corresponding to all detection time intervals is determined based on the near infrared reflectance spectra of all near infrared image sets, specifically:

[0016] Perform spectral feature analysis on the near-infrared reflectance spectra of all near-infrared image sets to obtain the relationship between the reflectivity and near-infrared wavelength of all near-infrared images contained in each near-infrared image set;

[0017] Based on the relationship between the reflectivity and the wavelength change of near-infrared light, the heavy metal distribution information of the target area soil at the detection time point corresponding to each of the near-infrared images contained in each near-infrared image set is determined; wherein the heavy metal distribution information includes the types and contents of heavy metals corresponding to a number of discrete locations in the target area soil and its adjacent areas at each detection time point.

[0018] Preferably, the generating of a soil heavy metal distribution map of a target area based on the heavy metal distribution information is specifically as follows:

[0019] Based on the coordinate information of all discrete locations in the soil of the target area, the types and contents of heavy metals distributed in all discrete locations corresponding to each detection time point and their adjacent areas are spatially integrated to obtain a static distribution map of heavy metals in the soil of the target area at each detection time point;

[0020] Based on the relative time sequence relationship of all detection time points, the heavy metal static distribution maps corresponding to all detection time points are integrated in the time domain to generate a soil heavy metal distribution map of the target area; wherein, the soil heavy metal distribution map includes a spatial representation map of the types of heavy metals distributed in the soil of the target area and the changes in their contents over time.

[0021] Preferably, the step of acquiring precipitation data corresponding to all detection time intervals in the target area, analyzing the precipitation data, and determining rainwater infiltration characteristic information of the soil in the target area is specifically as follows:

[0022] Obtaining precipitation data corresponding to all detection time intervals of the target area, wherein the precipitation data includes the precipitation coverage and precipitation amount data of the target area in each detection time interval;

[0023] The precipitation data is analyzed in the spatial domain and the temporal domain to obtain the precipitation change data of the global surface of the soil in the target area in all the detection time intervals; based on the surface void data of the soil in the target area and the precipitation change data of the global surface of the soil in the target area in all the detection time intervals, the rainwater infiltration characteristic information of the soil in the target area is determined; wherein the rainwater infiltration characteristic information includes the rainwater infiltration amount per unit time of each grid sub-area on the soil surface of the target area.

[0024] Preferably, based on the rainwater infiltration characteristic information and the soil heavy metal distribution map, heavy metal migration analysis is performed on the soil in the target area to obtain the migration characteristic information of heavy metals in the soil in the target area, specifically:

[0025] Based on the rainwater infiltration characteristic information and the component distribution information of the target area soil, the rainwater flow and diffusion characteristic information inside the target area soil is estimated; wherein the component distribution information of the target area soil includes the distribution position and distribution content information of different types of soil components in the target area soil; the rainwater flow and diffusion characteristic information includes the flow and diffusion path information and flow and diffusion flow rate information of rainwater in the target area soil;

[0026] Based on the rainwater flow and diffusion characteristic information and the soil heavy metal distribution map, a heavy metal migration analysis is performed on the soil in the target area to obtain the migration characteristic information of heavy metals in the soil in the target area.

[0027] Preferably, based on the rainwater flow and diffusion characteristic information and the soil heavy metal distribution map, heavy metal migration analysis is performed on the soil in the target area to obtain the migration characteristic information of heavy metals in the soil in the target area, specifically:

[0028] Based on the flow diffusion flow rate information of the rainwater in the soil of the target area and the soil heavy metal distribution map, the dissolution amount information of heavy metals existing in the flow-through position during the flow and diffusion of the rainwater in the soil of the target area is determined; then based on the flow diffusion path information of the rainwater in the soil of the target area and the dissolution amount information, the migration characteristic information of the heavy metals in the soil of the target area is determined; wherein the migration characteristic information includes the migration path information and migration flow rate information of the heavy metals in the soil of the target area.

[0029] Preferably, the prediction of the enrichment trend information of heavy metals in the soil of the target area based on the migration characteristic information is specifically:

[0030] Based on the migration path information and migration flow rate information of heavy metals in the soil of the target area, the accumulation area of ​​heavy metals in the soil of the target area and the rate of increase of their accumulation are predicted, which is used as the enrichment trend information of heavy metals.

[0031] Preferably, the heavy metal pollution range corresponding to the target area is located based on the enrichment trend information, specifically:

[0032] Comparing the locations of the heavy metal accumulation area with the groundwater existence area corresponding to the target area, and determining whether the accumulation area overlaps with the groundwater existence area;

[0033] When the accumulation area overlaps with the groundwater, the heavy metal diffusion trend information in the groundwater corresponding to the target area is predicted based on the increase rate of heavy metal accumulation, so as to locate the scope of groundwater contaminated by heavy metals as the heavy metal pollution scope.

[0034] Compared with the prior art, the present invention has the following beneficial effects:

[0035] The soil in the target area is photographed to obtain a near-infrared dynamic image; the near-infrared dynamic image is divided to obtain a number of near-infrared image sets corresponding to a number of detection time intervals, and the near-infrared reflection spectrum of each near-infrared image set is obtained. Heavy metals in the soil exist in the form of ions, among which common heavy metal ions in the soil include but are not limited to copper, lead and cadmium ions. Different types of heavy metal ions have different absorption peaks for near-infrared light and other electromagnetic waves, which makes the near-infrared reflection spectra of different types of heavy metal ions present different reflectivity difference characteristics. In this way, the type of heavy metal in the sample and its content concentration can be determined by performing near-infrared reflection spectrum analysis on the sample. It is precisely by utilizing the above-mentioned near-infrared reflection spectrum characteristics of heavy metal ions that heavy metal detection can be directly performed when the soil is in its natural original state. Specifically, the soil in the target area is dynamically photographed by near-infrared spectroscopy to obtain a near-infrared dynamic image of the soil, wherein the near-infrared dynamic image can reflect the changes in the near-infrared reflective spectrum of the soil during a preset time period, thereby comprehensively and accurately recording the changes in the distribution of heavy metals in the soil in the target area during the preset time period, and realizing real-time dynamic detection of the distribution of heavy metals in the soil in the target area; the near-infrared dynamic image is also divided into several near-infrared image sets correspondingly based on several detection time intervals that are sequentially adjacent in the time domain during the preset time period, so that the several near-infrared images contained in each near-infrared image set correspond to the detection time points in the detection time interval. By analyzing all the near-infrared images contained in each near-infrared image set, the near-infrared reflective spectrum corresponding to each near-infrared image is obtained, so that each near-infrared reflective spectrum accurately reflects the distribution of heavy metals in the soil in the target area at the corresponding detection time point, and realizes the continuous time-fixed point heavy metal detection of the soil in the target area.

[0036] Based on the near-infrared reflection spectra of all near-infrared image sets, the heavy metal distribution information of the soil in the target area corresponding to all detection time intervals is determined; based on the heavy metal distribution information, a soil heavy metal distribution map of the target area is generated. From the above, it can be seen that each near-infrared image set includes a number of near-infrared images corresponding to all detection time points in the detection time interval, and each near-infrared image corresponds to a near-infrared reflection spectrum, so that the near-infrared reflection spectrum of each near-infrared image set includes a number of near-infrared reflection spectra corresponding to a number of detection time points. It can be understood that the near-infrared reflection spectrum of each near-infrared image set dynamically and continuously reflects the changes in the near-infrared reflection spectrum of the soil in the dependent detection time interval. Based on the near-infrared reflection spectra of all near-infrared image sets, the heavy metal distribution information of the soil in the target area corresponding to all detection time intervals is determined, so that the heavy metal distribution information corresponding to each detection time interval accurately reflects the changes in the heavy metal distribution of the soil in the detection time interval. The heavy metal distribution information corresponding to all detection time intervals is then integrated in the time domain and spatial domain to generate a soil heavy metal distribution map of the target area, so that the soil heavy metal distribution map can truly reflect the changes in the distribution of heavy metals in the soil of the target area during the entire preset time period, thereby calibrating the heavy metal distribution state of the soil in its natural original state, and providing a reliable and comprehensive data basis for the subsequent determination of heavy metal migration in combination with precipitation data in the target area.

[0037] Obtain precipitation data corresponding to all detection time intervals in the target area, analyze the precipitation data, and determine the rainwater infiltration characteristic information of the soil in the target area; based on the rainwater infiltration characteristic information and the soil heavy metal distribution map, perform heavy metal migration analysis on the soil in the target area to obtain the migration characteristic information of heavy metals in the soil in the target area. The heavy metals in the soil of the target area exist in ionic state. When precipitation occurs in the target area, rainwater penetrates into the soil. The ionic heavy metals in the soil will dissolve in the rainwater and diffuse and flow in the soil with the flow of rainwater. In areas where the more heavy metals are distributed in the soil and the greater the amount of rainwater infiltration, the easier it is for the heavy metals to migrate and the greater the amount of migration. At the same time, after rainwater penetrates into the soil, the composition of the soil itself will affect the diffusion flow path and speed of rainwater in the soil. Generally speaking, when the content of hydrophobic substances such as sand in the soil is greater, the easier it is for rainwater to diffuse and flow around the soil; when the content of dense substances such as clay in the soil is greater, it is more difficult for rainwater to diffuse and flow in the soil. Based on the rainwater infiltration characteristic information and the soil heavy metal distribution map, the heavy metal migration analysis is carried out on the soil of the target area to obtain the migration characteristic information of heavy metals in the soil of the target area. This can accurately determine the migration path and migration flow rate of heavy metals in the soil as they diffuse and flow with rainwater, providing a reliable basis for subsequent judgment of the enrichment trend of heavy metals in the soil and the size of the pollution range.

[0038] Based on the migration characteristic information, the enrichment trend information of heavy metals in the soil of the target area is predicted; based on the enrichment trend information, the corresponding heavy metal pollution range of the target area is located. Heavy metals in the soil will be enriched and gathered at the corresponding positions in the soil as they diffuse and flow with rainwater, and the soil is in direct contact with groundwater. The enrichment and gathering positions of heavy metals will overlap with the groundwater area, causing heavy metals to directly enter the groundwater area and pollute the groundwater. Based on the migration characteristic information of heavy metals in the soil, the enrichment trend information of heavy metals in the soil of the target area is predicted, so as to locate the corresponding heavy metal pollution range of the target area, thereby accurately determining the contaminated range of groundwater during the transfer and enrichment process of heavy metals, and providing an important reference for the subsequent prevention and control of heavy metal pollution in the soil.

Brief Description of the Drawings

[0039] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for describing 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. Among them:

[0040] Figure 1 The present invention provides a flow chart of a method for detecting heavy metals in soil based on near infrared spectroscopy. [Specific implementation method]

[0041] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are described in detail below in conjunction with the accompanying drawings. It is understood that the specific embodiments described herein are only used to explain the present invention, rather than to limit the present invention. It should also be noted that, for ease of description, only the parts related to the present invention rather than all structures are shown in the accompanying drawings. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0042] The terms "including" and "having" and any variations thereof in the present invention are intended to cover non-exclusive inclusions. For example, a process, method, method, product or device comprising a series of steps or units is not limited to the listed steps or units, but may optionally include steps or units not listed, or may optionally include other steps or units inherent to these processes, methods, products or devices.

[0043] Reference to "embodiments" herein means that a particular feature, structure, or characteristic described in conjunction with the embodiments may be included in at least one embodiment of the present invention. The appearance of the phrase in various places in the specification does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment that is mutually exclusive with other embodiments. It is explicitly and implicitly understood by those skilled in the art that the embodiments described herein may be combined with other embodiments.

[0044] See also Figure 1 As shown, the present invention provides a soil heavy metal detection method based on near infrared spectroscopy, the method comprising the following steps:

[0045] S100, photographing the soil in the target area to obtain a near-infrared dynamic image; dividing the near-infrared dynamic image to obtain a number of near-infrared image sets corresponding to a number of detection time intervals, and obtaining a near-infrared reflectance spectrum of each near-infrared image set.

[0046] Furthermore, the soil in the target area is photographed to obtain near-infrared dynamic images, specifically:

[0047] Control the drone flying over the target area to collect wireless signals sent by several signal transmitters pre-set on the boundary of the target area, analyze the strength of the wireless signals, and determine the relative distance change between the drone and the boundary of the target area during flight;

[0048] Based on the relative distance change information, the flight path of the UAV over the target area is adjusted so that the UAV can scan and photograph the soil in the target area while flying over the target area, thereby obtaining a near-infrared dynamic image of the soil in the target area during a preset time period.

[0049] Furthermore, the near-infrared dynamic image is divided to obtain a number of near-infrared image sets corresponding to a number of detection time intervals, and the near-infrared reflectance spectrum of each near-infrared image set is obtained, specifically:

[0050] Based on the start and end times of all detection time intervals within the preset time period and the time axis of the drone's scanning and shooting, the near-infrared dynamic image is framed to obtain a number of near-infrared image sets corresponding to all detection time intervals; wherein each near-infrared image set includes a number of near-infrared images captured and generated within the corresponding detection time interval;

[0051] Near infrared spectral reflectance data analysis is performed on all near infrared images contained in each near infrared image set to obtain near infrared reflectance spectra of all near infrared images contained in each near infrared image set.

[0052] Generally speaking, the target area such as industrial production area covers a large area, and the area of ​​soil that may be contaminated by heavy metals in the target area is also relatively large. If the conventional manual shooting method is used to shoot the soil in the target area by near-infrared spectrum, only local soil can be shot at the same time, and the soil in the target area cannot be shot globally. This not only requires a lot of preparation work such as manual shooting positioning in the early stage, but also requires a lot of processing work such as spectral image splicing and combination in the later stage, which seriously reduces the shooting efficiency and reliability of the soil in the target area. In view of the above problems, drones are used here to shoot the soil in the target area globally and synchronously. In order to accurately define the flight range of drones and avoid drones from shooting across the boundary, several signal transmitters are set at equal intervals on the boundary of the target area in advance, and each signal transmitter can independently send wireless signals of a specific band. When the drone flies over the target area, the drone will receive the wireless signal sent by the signal transmitter and detect the strength of the received wireless signal. When the drone is closer to the signal transmitter during flight, the stronger the wireless signal strength detected by the drone is, the relative distance between the drone and the boundary of the target area can be accurately determined by analyzing the change in the strength of the wireless signal received by the drone, thereby obtaining the relative distance change information between the drone and the boundary of the target area during flight. Generally speaking, the stronger the wireless signal strength received by the drone is, the closer the drone is to the boundary of the target area, that is, the smaller the relative distance between the drone and the boundary of the target area is. Based on the relative distance change information between the drone and the boundary of the target area during flight, the flight path of the drone over the target area is adjusted so that the drone adjusts its own flight direction when it reaches the boundary of the target area to avoid the drone flying out of the target area. At the same time, the drone is instructed to scan and shoot the soil of the target area during flight over the target area, so as to obtain a full range of near-infrared dynamic images of the soil in the target area during a preset time period; wherein, the preset time period may be, but is not limited to, the duration of the drone's flight over the target area, and the time start and end points and time duration during the preset time period may be changed according to actual detection needs, and it may have different time start and end points and different time durations in different detection occasions. Furthermore, the preset time period may include a number of detection time intervals that are sequentially adjacent in the time domain, and each detection time interval has the same time length, so as to facilitate subsequent time domain differentiation processing of the near-infrared dynamic image based on the detection time interval.

[0053] In addition, the near-infrared dynamic image is divided into several near-infrared image sets correspondingly based on several detection time intervals that are sequentially adjacent in the time domain during the preset time period, so that the several near-infrared images contained in each near-infrared image set correspond to the detection time points in the detection time interval, so that the near-infrared image analysis of the soil in the target area based on the time point can be carried out in each detection time interval. Then all the near-infrared images contained in each near-infrared image set are analyzed to obtain the near-infrared reflection spectrum corresponding to each near-infrared image, so that each near-infrared reflection spectrum accurately reflects the distribution of heavy metals in the soil in the target area at the corresponding detection time point, and realizes the continuous time-fixed point heavy metal detection of the soil in the target area.

[0054] S200, based on the near infrared reflectance spectra of all near infrared image sets, determining the heavy metal distribution information of the soil in the target area corresponding to all detection time intervals; based on the heavy metal distribution information, generating a soil heavy metal distribution map of the target area.

[0055] Furthermore, based on the near-infrared reflectance spectra of all near-infrared image sets, the heavy metal distribution information of the soil in the target area corresponding to all detection time intervals is determined, specifically:

[0056] Perform spectral feature analysis on the near-infrared reflectance spectra of all near-infrared image sets to obtain the relationship between the reflectivity and near-infrared wavelength of all near-infrared images contained in each near-infrared image set;

[0057] Based on the relationship between reflectivity and near-infrared light wavelength changes, the heavy metal distribution information of the target area soil at the detection time points corresponding to all near-infrared images contained in each near-infrared image set is determined; wherein the heavy metal distribution information includes the types and contents of heavy metals distributed corresponding to several discrete locations in the target area soil and its adjacent areas at each detection time point.

[0058] Furthermore, based on the heavy metal distribution information, a soil heavy metal distribution map of the target area is generated, specifically:

[0059] Based on the coordinate information of all discrete locations in the soil of the target area, the types and contents of heavy metals distributed in all discrete locations corresponding to each detection time point and their adjacent areas are spatially integrated to obtain a static distribution map of heavy metals in the soil of the target area at each detection time point;

[0060] Based on the relative time sequence relationship of all detection time points, the heavy metal static distribution maps corresponding to all detection time points are integrated in the time domain to generate a soil heavy metal distribution map of the target area; among which, the soil heavy metal distribution map includes a spatial representation map of the types of heavy metals distributed in the soil of the target area and the changes in their content over time.

[0061] Heavy metals in the soil exist in the form of ions, among which common heavy metal ions in the soil include but are not limited to copper, lead and cadmium ions. Different types of heavy metal ions have different absorption peaks for near-infrared light and other electromagnetic waves, so that the near-infrared reflection spectra of different types of heavy metal ions show different reflectivity difference characteristics. In this way, the types of heavy metals in the sample and their content concentrations can be determined by performing near-infrared reflection spectrum analysis on the sample. Each near-infrared image set includes a number of near-infrared images corresponding to all detection time points within the detection time interval, and each near-infrared image corresponds to a near-infrared reflection spectrum, so that the near-infrared reflection spectrum of each near-infrared image set includes a number of near-infrared reflection spectra corresponding to a number of detection time points. It can be understood that the near-infrared reflection spectrum of each near-infrared image set dynamically and continuously reflects the changes in the near-infrared reflection spectrum of the soil within the dependent detection time interval. Based on the near-infrared reflectance spectra of all near-infrared image sets, the heavy metal distribution information of the soil in the target area corresponding to all detection time intervals is determined, so that the heavy metal distribution information corresponding to each detection time interval accurately reflects the changes in the heavy metal distribution of the soil within the detection time interval, thereby quantitatively determining the type of heavy metals distributed in the soil at each detection time point within the detection time interval and their content (concentration).

[0062] In addition, based on the coordinate information of all discrete position points in the soil of the target area, the types and contents of heavy metals distributed in all discrete position points and their neighboring areas corresponding to each detection time point are spatially integrated to obtain a static distribution map of heavy metals corresponding to the soil of the target area at each detection time point. Such a static distribution map of heavy metals characterizes the distribution of heavy metal types and contents in the target area at the corresponding detection time point. Based on the relative time sequence relationship of all detection time points, the static distribution maps of heavy metals corresponding to all detection time points are integrated in the time domain to generate a soil heavy metal distribution map of the target area; wherein the soil heavy metal distribution map includes a spatial characterization map of the changes in the types of heavy metals and their contents distributed in the soil of the target area over time. By integrating the heavy metal distribution information corresponding to all detection time intervals in the time domain and the air domain, a soil heavy metal distribution map of the target area is generated, so that the soil heavy metal distribution map can truly reflect the changes in the distribution of heavy metals in the soil of the target area during the entire preset time period, thereby calibrating the heavy metal distribution state of the soil in its natural original state, and providing a reliable and comprehensive data basis for the subsequent determination of heavy metal migration in combination with precipitation data in the target area.

[0063] S300, obtaining precipitation data corresponding to all detection time intervals in the target area, analyzing the precipitation data, and determining rainwater infiltration characteristic information of the soil in the target area; based on the rainwater infiltration characteristic information and the soil heavy metal distribution map, performing heavy metal migration analysis on the soil in the target area, and obtaining the migration characteristic information of heavy metals in the soil in the target area.

[0064] Furthermore, the precipitation data of the target area corresponding to all detection time intervals is obtained, and the precipitation data is analyzed to determine the rainwater infiltration characteristic information of the soil in the target area, specifically:

[0065] Obtain precipitation data for each of the target area corresponding to all detection time intervals, wherein the precipitation data includes the precipitation coverage and precipitation amount data of the target area in each detection time interval;

[0066] The precipitation data is analyzed in the spatial and temporal domains to obtain the precipitation change data on the global surface of the soil in the target area in all detection time intervals; based on the surface void data of the soil in the target area and the precipitation change data on the global surface of the soil in the target area in all detection time intervals, the rainwater infiltration characteristic information of the soil in the target area is determined; wherein the rainwater infiltration characteristic information includes the rainwater infiltration amount per unit time in each grid sub-area of ​​the soil surface in the target area.

[0067] Furthermore, based on the rainwater infiltration characteristic information and the soil heavy metal distribution map, the heavy metal migration analysis is performed on the soil in the target area to obtain the migration characteristic information of heavy metals in the soil in the target area, specifically:

[0068] Based on the rainwater infiltration characteristic information and the component distribution information of the target area soil, the rainwater flow and diffusion characteristic information inside the target area soil is estimated; wherein the component distribution information of the target area soil includes the distribution position and distribution content information of different types of soil components in the target area soil; the rainwater flow and diffusion characteristic information includes the flow and diffusion path information and flow and diffusion flow rate information of rainwater in the target area soil;

[0069] Based on the rainwater flow and diffusion characteristic information and the soil heavy metal distribution map, the heavy metal migration analysis of the soil in the target area is carried out to obtain the migration characteristic information of heavy metals in the soil in the target area.

[0070] Furthermore, based on the rainwater flow and diffusion characteristics and the soil heavy metal distribution map, the heavy metal migration analysis of the target area soil was carried out to obtain the migration characteristics of heavy metals in the target area soil, specifically:

[0071] Based on the flow and diffusion rate information of rainwater in the soil of the target area and the soil heavy metal distribution map, the dissolution amount information of heavy metals existing in the flow-through position during the flow and diffusion of rainwater in the soil of the target area is determined; then, based on the flow and diffusion path information and dissolution amount information of rainwater in the soil of the target area, the migration characteristic information of heavy metals in the soil of the target area is determined; wherein, the migration characteristic information includes the migration path information and migration flow rate information of heavy metals in the soil of the target area.

[0072] Heavy metals exist in the soil of the target area in an ionic state. When precipitation occurs in the target area, rainwater penetrates into the soil. The heavy metals in the ionic state in the soil will dissolve in the rainwater and diffuse and flow in the soil with the flow of rainwater. In areas where the more heavy metals are distributed in the soil and the greater the amount of rainwater penetration, the easier it is for the heavy metals to migrate and the greater the amount of migration. In order to accurately determine the amount of rainwater infiltration in the soil when precipitation occurs in the target area, the precipitation coverage range and precipitation data of each detection time interval corresponding to the target area are obtained, and the precipitation coverage range and precipitation data are analyzed in the air and time domains to obtain the precipitation change data of the global surface of the soil in the target area in all detection time intervals (i.e., the precipitation volume change data of the global surface of the soil in the target area in all detection time intervals). In addition, the surface void data such as the average size of the surface voids and the surface void distribution density of the soil in the target area affect the ratio of rainwater infiltration from the soil surface to the soil interior. Generally speaking, the larger the average size of the surface voids and the higher the surface void distribution density, the greater the ratio of rainwater infiltration from the soil surface to the soil interior. To this end, based on the surface void data of the target area soil and the precipitation change data of the global surface of the target area soil in all detection time intervals, the rainwater infiltration amount per unit time (i.e., the rainwater infiltration volume) of each grid sub-area on the target area soil surface is determined; wherein the grid sub-area on the target area soil surface is divided into grid sub-areas at equal intervals based on the plane where the target area soil is located.

[0073] After rainwater infiltrates into the soil, the composition of the soil itself will affect the diffusion path and speed of rainwater in the soil. Generally speaking, the greater the content of hydrophobic substances such as sand in the soil, the easier it is for rainwater to diffuse and flow around the soil; the greater the content of dense substances such as clay in the soil, the more difficult it is for rainwater to diffuse and flow in the soil. In order to determine the diffusion and flow of rainwater in the soil, based on the rainwater infiltration characteristic information and the component distribution information of the soil in the target area, the rainwater flow and diffusion characteristic information in the soil of the target area is estimated. The rainwater infiltration characteristic information and the distribution position and distribution content information of different types of soil components such as sand and clay in the soil of the target area are combined to accurately quantify the rainwater flow and diffusion path and flow diffusion flow rate in the soil.

[0074] Based on the rainwater infiltration characteristic information and the soil heavy metal distribution map, the information on the dissolution amount of heavy metals in the flow and diffusion process of rainwater in the target area soil is determined. The greater the dissolution amount of heavy metals in the soil in rainwater, the more heavy metals will diffuse and flow in the soil with rainwater. Based on the flow and diffusion path information of rainwater in the target area soil and the dissolution amount information, the migration path information and migration flow rate information of heavy metals in the target area soil are determined, providing a reliable basis for the subsequent judgment of the enrichment trend of heavy metals in the soil and the size of the pollution range.

[0075] S400, predicting the enrichment trend information of heavy metals in the soil of the target area based on the migration characteristic information; and locating the heavy metal pollution range corresponding to the target area based on the enrichment trend information.

[0076] Furthermore, based on the migration characteristic information, the enrichment trend information of heavy metals in the soil of the target area is predicted, specifically:

[0077] Based on the migration path information and migration flow rate information of heavy metals in the soil of the target area, the accumulation area of ​​heavy metals in the soil of the target area and the rate of increase of their accumulation are predicted, which is used as the enrichment trend information of heavy metals.

[0078] Furthermore, based on the enrichment trend information, the heavy metal pollution range corresponding to the target area is located, specifically:

[0079] Compare the locations of heavy metal accumulation areas with the groundwater areas corresponding to the target areas to determine whether the accumulation areas overlap with the groundwater areas;

[0080] When the accumulation area overlaps with the groundwater, the heavy metal diffusion trend information in the groundwater corresponding to the target area is predicted based on the increase rate of heavy metal accumulation, so as to locate the scope of groundwater contaminated by heavy metals and use it as the scope of heavy metal pollution.

[0081] Heavy metals in the soil will be enriched and gathered at the corresponding positions in the soil as they diffuse and flow with rainwater, and the soil is in direct contact with groundwater. The enrichment and gathering positions of heavy metals will overlap with the groundwater area, so that heavy metals directly enter the groundwater area and pollute the groundwater. Based on the migration path information and migration flow rate information of heavy metals in the soil of the target area, the accumulation area of ​​heavy metals in the soil of the target area and the rate of increase of their accumulation are predicted, which is used as the enrichment trend information of heavy metals. Then, the position of the accumulation area of ​​heavy metals is compared with the groundwater area corresponding to the target area to determine whether the accumulation area overlaps with the groundwater area; when the accumulation area overlaps with the groundwater area, based on the rate of increase of heavy metal accumulation, the diffusion trend information of heavy metals in the groundwater corresponding to the target area is predicted, so as to locate the scope of groundwater contaminated by heavy metals, provide an important reference basis for the subsequent prevention and control of heavy metal pollution in the soil, and realize the global and continuous dynamic detection of heavy metals in the soil under natural conditions.

[0082] Through the description of the above implementation methods, technicians in this field can clearly understand that each implementation method can be implemented by adding a necessary general hardware platform, and of course can also be implemented by combining hardware and software. Based on this understanding, the above technical solution is essentially or the part that contributes to the prior art can be embodied in the form of a computer product, and the present invention can be in the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program codes.

[0083] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it, and other embodiments may also be used. Although the present invention has been described in detail with reference to the aforementioned embodiments, ordinary technicians in this field should understand that they can still modify the technical solutions recorded in the aforementioned embodiments, or replace some of the technical features therein with equivalents. However, these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A soil heavy metal detection method based on near infrared spectroscopy, characterized in that: The method comprises the following steps: The soil in the target area is photographed to obtain a near-infrared dynamic image; the near-infrared dynamic image is divided to obtain a number of near-infrared image sets corresponding to a number of detection time intervals, and a near-infrared reflectance spectrum of each near-infrared image set is obtained; Based on the near-infrared reflectance spectra of all near-infrared image sets, determine the heavy metal distribution information of the soil in the target area corresponding to all detection time intervals; based on the heavy metal distribution information, generate a soil heavy metal distribution map of the target area; Obtain precipitation data corresponding to all detection time intervals in the target area, analyze the precipitation data, and determine rainwater infiltration characteristic information of the soil in the target area; based on the rainwater infiltration characteristic information and the soil heavy metal distribution map, perform heavy metal migration analysis on the soil in the target area to obtain migration characteristic information of heavy metals in the soil in the target area; Based on the migration characteristic information, the enrichment trend information of heavy metals in the soil of the target area is predicted; based on the enrichment trend information, the heavy metal pollution range corresponding to the target area is located.

2. The method according to claim 1, characterized in that The soil in the target area is photographed to obtain a near-infrared dynamic image, specifically: Controlling the UAV flying over the target area to collect wireless signals emitted by a number of signal transmitters pre-set on the boundary of the target area, performing strength analysis on the wireless signals, and determining the relative distance change information between the UAV and the boundary of the target area during the flight; Based on the relative distance change information, the flight path of the UAV over the target area is adjusted, so that the UAV can scan and photograph the soil in the target area during the flight over the target area, and obtain a near-infrared dynamic image of the soil in the target area during a preset time period.

3. The method according to claim 2, characterized in that The near-infrared dynamic image is divided to obtain a number of near-infrared image sets corresponding to a number of detection time intervals, and a near-infrared reflectance spectrum of each near-infrared image set is obtained, specifically: Based on the start and end times of all the detection time intervals during the preset time period and the time axis of the drone's scanning and shooting, the near-infrared dynamic image is framed to obtain a number of near-infrared image sets corresponding to all the detection time intervals; wherein each near-infrared image set includes a number of near-infrared images captured and generated within the corresponding detection time interval; Near infrared spectral reflectance data analysis is performed on all near infrared images contained in each near infrared image set to obtain near infrared reflectance spectra of all near infrared images contained in each near infrared image set.

4. The method according to claim 3, characterized in that The near infrared reflectance spectra of all near infrared image sets are used to determine the heavy metal distribution information of the soil in the target area corresponding to all detection time intervals, specifically: Perform spectral feature analysis on the near-infrared reflectance spectra of all near-infrared image sets to obtain the relationship between the reflectivity and near-infrared wavelength of all near-infrared images contained in each near-infrared image set; Based on the relationship between the reflectivity and the wavelength change of near-infrared light, the heavy metal distribution information of the target area soil at the detection time point corresponding to each of the near-infrared images contained in each near-infrared image set is determined; wherein the heavy metal distribution information includes the types and contents of heavy metals corresponding to a number of discrete locations in the target area soil and its adjacent areas at each detection time point.

5. The method according to claim 4, characterized in that The generating of a soil heavy metal distribution map of a target area based on the heavy metal distribution information is specifically as follows: Based on the coordinate information of all discrete locations in the soil of the target area, the types and contents of heavy metals distributed in all discrete locations corresponding to each detection time point and their adjacent areas are spatially integrated to obtain a static distribution map of heavy metals in the soil of the target area at each detection time point; Based on the relative time sequence relationship of all detection time points, the heavy metal static distribution maps corresponding to all detection time points are integrated in the time domain to generate a soil heavy metal distribution map of the target area; wherein, the soil heavy metal distribution map includes a spatial representation map of the types of heavy metals distributed in the soil of the target area and the changes in their contents over time.

6. The method according to claim 1, characterized in that The step of obtaining precipitation data corresponding to all detection time intervals in the target area and analyzing the precipitation data to determine rainwater infiltration characteristic information of the soil in the target area is as follows: Obtaining precipitation data corresponding to all detection time intervals of the target area, wherein the precipitation data includes the precipitation coverage and precipitation amount data of the target area in each detection time interval; The precipitation data is analyzed in the spatial domain and the temporal domain to obtain the precipitation change data of the global surface of the soil in the target area in all the detection time intervals; based on the surface void data of the soil in the target area and the precipitation change data of the global surface of the soil in the target area in all the detection time intervals, the rainwater infiltration characteristic information of the soil in the target area is determined; wherein the rainwater infiltration characteristic information includes the rainwater infiltration amount per unit time of each grid sub-area on the soil surface of the target area.

7. The method according to claim 6, characterized in that Based on the rainwater infiltration characteristic information and the soil heavy metal distribution map, heavy metal migration analysis is performed on the soil in the target area to obtain migration characteristic information of heavy metals in the soil in the target area, specifically: Based on the rainwater infiltration characteristic information and the component distribution information of the target area soil, the rainwater flow and diffusion characteristic information inside the target area soil is estimated; wherein the component distribution information of the target area soil includes the distribution position and distribution content information of different types of soil components in the target area soil; the rainwater flow and diffusion characteristic information includes the flow and diffusion path information and flow and diffusion flow rate information of rainwater in the target area soil; Based on the rainwater flow and diffusion characteristic information and the soil heavy metal distribution map, a heavy metal migration analysis is performed on the soil in the target area to obtain the migration characteristic information of heavy metals in the soil in the target area.

8. The method according to claim 7, characterized in that Based on the rainwater flow and diffusion characteristic information and the soil heavy metal distribution map, the heavy metal migration analysis is performed on the soil in the target area to obtain the migration characteristic information of the heavy metals in the soil in the target area, specifically: Based on the flow diffusion flow rate information of the rainwater in the soil of the target area and the soil heavy metal distribution map, the dissolution amount information of heavy metals existing in the flow-through position during the flow and diffusion of the rainwater in the soil of the target area is determined; then based on the flow diffusion path information of the rainwater in the soil of the target area and the dissolution amount information, the migration characteristic information of the heavy metals in the soil of the target area is determined; wherein the migration characteristic information includes the migration path information and migration flow rate information of the heavy metals in the soil of the target area.

9. The method according to claim 8, characterized in that The prediction of the enrichment trend information of heavy metals in the soil of the target area based on the migration characteristic information is specifically as follows: Based on the migration path information and migration flow rate information of heavy metals in the soil of the target area, the accumulation area of ​​heavy metals in the soil of the target area and the rate of increase of their accumulation are predicted, which is used as the enrichment trend information of heavy metals.

10. The method according to claim 9, characterized in that Based on the enrichment trend information, the heavy metal pollution range corresponding to the target area is located, specifically: Comparing the locations of the heavy metal accumulation area with the groundwater existence area corresponding to the target area, and determining whether the accumulation area overlaps with the groundwater existence area; When the accumulation area overlaps with the groundwater, the heavy metal diffusion trend information in the groundwater corresponding to the target area is predicted based on the increase rate of heavy metal accumulation, so as to locate the scope of groundwater contaminated by heavy metals as the heavy metal pollution scope.

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