Method, device and electronic equipment for extracting rare earth minerals

Abstract

The application provides a rare earth mineral extraction method, device and electronic equipment, and relates to the field of rare earth mineral extraction. The rare earth mineral extraction method comprises the following steps: calculating an absorption characteristic position of reflectivity data in a rare earth mineral absorption wave band interval, wherein the rare earth mineral absorption characteristic position comprises an absorption characteristic position of a 568-597 nm wave band interval, an absorption characteristic position of a 719-769 nm wave band interval, an absorption characteristic position of a 783-826 nm wave band interval and an absorption characteristic position of a 862-876 nm wave band interval. The rare earth mineral extraction method provided in the application can efficiently and accurately obtain the distribution of rare earth minerals in a wide range.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of rare earth mineral extraction, and in particular, to a rare earth mineral extraction method, device and electronic equipment. BACKGROUND

[0002] As a key mineral resource in China, rare earth elements have extremely high strategic significance. Rare earth minerals are widely used in high-tech industries, national defense industries and new energy fields, and are known as "industrial vitamins". The detection and mining of rare earth minerals are of great importance to China's economic development and national security.

[0003] In the search for rare earth minerals, traditional remote sensing technology mainly relies on indirect prospecting methods, which infer the existence of rare earth minerals by identifying associated minerals or geological features of rare earth minerals. In recent years, some scholars have used single-band absorption characteristics to identify rare earth minerals, ignoring other key bands, and the extraction results are easily affected by the same spectrum different object phenomenon, reducing the identification accuracy. SUMMARY

[0004] The purpose of the embodiments of the present application is to provide a rare earth mineral extraction method, device and electronic equipment, which uses the method of combining feature absorption and weighting, and comprehensively uses four characteristic absorption peaks of rare earth minerals. The rare earth mineral extraction method provided by the embodiments of the present application can efficiently and accurately obtain the distribution of rare earth minerals in a large range.

[0005] In a first aspect, the embodiments of the present application provide a rare earth mineral extraction method, which comprises:

[0006] Obtaining reflectance data based on aerial hyperspectral data of a target area;

[0007] Calculating the matching degree of a standard spectrum of a rare earth mineral and the reflectance data in the wavelength range of 500nm-950nm, and determining whether the matching degree meets a first preset condition;

[0008] Calculating the absorption characteristic positions of the reflectance data in the absorption band interval of the rare earth mineral, wherein the absorption characteristic positions of the rare earth mineral include the absorption characteristic positions in the band interval of 568-597nm, the absorption characteristic positions in the band interval of 719-769nm, the absorption characteristic positions in the band interval of 783-826nm and the absorption characteristic positions in the band interval of 862-876nm;

[0009] Calculating the reflectance ratio of each absorption characteristic position and the adjacent shoulder position of the absorption characteristic position, and sequentially obtaining a first reflectance ratio, a second reflectance ratio, a third reflectance ratio and a fourth reflectance ratio;

[0010] weightedly summing the first reflectivity ratio, the second reflectivity ratio, the third reflectivity ratio, and the fourth reflectivity ratio based on a weighting coefficient to obtain a weighted sum value, and determining whether the weighted sum value meets a second preset condition;

[0011] The rare earth mineral distribution range of the target area is determined based on the intersection of the first rare earth mineral distribution information and the second rare earth mineral distribution information, wherein the first rare earth mineral distribution information is determined based on the weighted sum value that meets the second preset condition, and the second rare earth mineral distribution information is determined based on the reflectivity data within the wavelength range of 500nm-950nm.

[0012] In the above implementation process, the rare earth mineral extraction method provided by the embodiment of the present application can comprehensively consider the unique absorption characteristics of rare earth minerals in the four bands of 568-597nm, 719-769nm, 783-826nm, and 862-876nm in a weighted manner, thereby avoiding misjudgment and recognition errors caused by single band identification, and can efficiently and accurately extract the distribution information of rare earth minerals from aerial hyperspectral data. Compared with traditional methods, the systematic mineral extraction method provided by the embodiment of the present application not only improves the accuracy and reliability of rare earth mineral detection, but also can quickly identify the distribution of rare earth minerals in a large range by combining the first rare earth mineral distribution information and the second rare earth mineral distribution information. In addition, when calculating the final reflectivity of the absorption feature position, the reflectivity ratio can be obtained by combining the reflectivity of the adjacent positions of the absorption feature position, thereby improving the calculation accuracy of the final reflectivity of the absorption feature position.

[0013] Optionally, the numerical range of the absorption characteristic position in the 568-597nm band range is 576-584nm, the numerical range of the absorption characteristic position in the 719-769nm band range is 740-744nm, the numerical range of the absorption characteristic position in the 783-826nm band range is 797-800nm, and the numerical range of the absorption characteristic position in the 862-876nm band range is 866-869nm.

[0014] Optionally, in an embodiment of the present application, calculating the absorption characteristic position of the reflectivity data in the absorption band of the rare earth mineral includes:

[0015] Calculate the minimum reflectivity value of the 568nm-597nm band, the minimum reflectivity value of the 719-769nm band, the minimum reflectivity value of the 783-826nm band, and the minimum reflectivity value of the 862-876nm band based on the reflectivity data;

[0016] determining a spectral segment position corresponding to the minimum reflectance value of the 568-597 nm waveband interval as an absorption characteristic position of the 568-597 nm waveband interval;

[0017] determining a spectral segment position corresponding to the minimum reflectance value of the 719-769 nm waveband interval as an absorption characteristic position of the 719-769 nm waveband interval;

[0018] determining a spectral segment position corresponding to the minimum reflectance value of the 783-826 nm waveband interval as an absorption characteristic position of the 783-826 nm waveband interval;

[0019] determining a spectral segment position corresponding to the minimum reflectance value of the 862-876 nm waveband interval as an absorption characteristic position of the 862-876 nm waveband interval.

[0020] In the implementation process, the absorption characteristic position of the 568-597 nm waveband interval, the absorption characteristic position of the 719-769 nm waveband interval, the absorption characteristic position of the 783-826 nm waveband interval, and the absorption characteristic position of the 862-876 nm waveband interval are determined in sequence according to the absorption characteristic position of the 568-597 nm waveband interval, the minimum reflectance of the 719-769 nm waveband interval, the minimum reflectance of the 783-826 nm waveband interval, and the minimum reflectance of the 862-876 nm waveband interval.

[0021] Optionally, in the embodiment of the present application, the reflectance of the adjacent shoulder position of each absorption characteristic position is determined based on the reflectance data.

[0022] Optionally, in the embodiment of the present application, the calculation of the reflectance ratio of each absorption characteristic position to the reflectance of the adjacent shoulder position of the absorption characteristic position comprises:

[0023] calculating the reflectance of each absorption characteristic position;

[0024] calculating the reflectance of the adjacent shoulder position of each absorption characteristic position;

[0025] calculating the reflectance ratio of each absorption characteristic position to the reflectance of the adjacent shoulder position of the absorption characteristic position based on the reflectance of each absorption characteristic position and the reflectance of the adjacent shoulder position of the absorption characteristic position.

[0026] Optionally, in the embodiment of the present application, the calculation of the reflectance ratio of each absorption characteristic position to the reflectance of the adjacent shoulder position of the absorption characteristic position based on the reflectance of each absorption characteristic position and the reflectance of the adjacent shoulder position of the absorption characteristic position corresponds to a calculation formula:

[0027]

[0028] wherein Y represents a reflectivity ratio of the absorption feature position to a shoulder position adjacent to the absorption feature position, p m is reflectivity of the absorption feature position, and p1 and p2 are reflectivity of the shoulder position adjacent to the absorption feature position.

[0029] Optionally, in the embodiments of the present application, the reflectivity data is obtained based on the aerial hyperspectral data of the target region, and the reflectivity data comprises:

[0030] The aerial hyperspectral data of the target region is preprocessed to obtain the reflectivity data.

[0031] Optionally, in the embodiments of the present application, envelope removal is performed on the reflectivity data in the wavelength range of 500 nm-950 nm, and normalization processing is performed. In the above implementation process, the envelope removal and the spectral normalization processing performed after the absorption feature spectrum is intercepted make the absorption feature of the rare earth mineral more obvious, and optimize the subsequent recognition and classification process based on the multi-band absorption feature, thereby laying a foundation for high-precision rare earth mineral distribution detection.

[0032] In a second aspect, the embodiments of the present application provide a rare earth mineral extraction device, and the device comprises:

[0033] The acquisition module is configured to obtain reflectivity data based on aerial hyperspectral data of a target region.

[0034] The second calculation module is configured to calculate a matching degree of a rare earth mineral standard spectrum and the reflectivity data in a wavelength range of 500 nm-950 nm, and determine whether the matching degree satisfies a first preset condition.

[0035] The second calculation module is configured to calculate absorption feature positions of the reflectivity data in a rare earth mineral absorption band interval, wherein the rare earth mineral absorption feature positions comprise an absorption feature position in a 568-597 nm band interval, an absorption feature position in a 719-769 nm band interval, an absorption feature position in a 783-826 nm band interval, and an absorption feature position in a 862-876 nm band interval.

[0036] The third calculation module is configured to calculate a reflectivity ratio of each of the absorption feature positions to a shoulder position adjacent to the absorption feature position, and sequentially obtain a first reflectivity ratio, a second reflectivity ratio, a third reflectivity ratio, and a fourth reflectivity ratio.

[0037] The fourth calculation module is configured to weight and sum the first reflectivity ratio, the second reflectivity ratio, the third reflectivity ratio and the fourth reflectivity ratio based on the weighting coefficient to obtain a weighted sum value, and determine whether the weighted sum value satisfies a second preset condition;

[0038] The determination module is configured to determine a rare earth mineral distribution range of the target region based on an intersection of first rare earth mineral distribution information and second rare earth mineral distribution information, wherein the first rare earth mineral distribution information is determined based on the weighted sum value satisfying the second preset condition, and the second rare earth mineral distribution information is determined based on the reflectivity data in the wavelength range of 500 nm-950 nm.

[0039] In a third aspect, an embodiment of the present application provides an electronic device, which includes a memory and a processor, the memory stores program instructions, and the processor reads and runs the program instructions to perform the steps in any of the implementation manners described above.

[0040] In a fourth aspect, an embodiment of the present application further provides a computer readable storage medium, which stores computer program instructions, and the computer program instructions are read and run by a processor to perform the steps in any of the implementation manners described above. BRIEF DESCRIPTION OF DRAWINGS

[0041] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the following will briefly introduce the drawings needed to be used in the embodiments of the present application. It should be understood that the following drawings only show some embodiments of the present application, and therefore should not be regarded as a limitation on the scope, and for those skilled in the art, other related drawings can also be obtained without creative labor on the basis of these drawings.

[0042] Figure 1 is a flowchart of the rare earth mineral extraction method provided by the embodiments of the present application;

[0043] Figure 2 is a schematic diagram of quantification of spectral absorption characteristics disclosed by the embodiments of the present application;

[0044] Figure 3 is a structural schematic diagram of a rare earth mineral extraction device disclosed by the embodiments of the present application;

[0045] Figure 4 is a structural schematic diagram of an electronic device provided by the embodiments of the present application. DETAILED DESCRIPTION

[0046] The technical solutions in the embodiments of the present application will be described below with reference to the drawings in the embodiments of the present application. For example, the flowcharts and block diagrams in the drawings show the possible implementation architecture, functions and operations of the systems, methods and computer program products according to the embodiments of the present application. In this regard, each block in the flowcharts or block diagrams can represent a module, a program segment or a part of code, which includes one or more executable instructions for implementing the specified logical functions. It should also be noted that in some alternative implementations, the functions noted in the blocks can occur in different orders from those noted in the drawings. For example, two consecutive blocks can actually be executed substantially in parallel, and sometimes they can be executed in reverse order, depending on the functions involved. It should also be noted that each block in the block diagrams and / or flowcharts, and the combination of blocks in the block diagrams and / or flowcharts, can be implemented by a special hardware-based system that performs the specified functions or actions, or can be implemented by a combination of special hardware and computer instructions. In addition, the functional modules in the various embodiments of the present application can be integrated together to form a separate part, or each module can exist independently, or two or more modules can be integrated to form a separate part.

[0047] As a key mineral resource in China, rare earth elements have extremely high strategic significance. Rare earth minerals are widely used in high-tech industries, defense industries, and new energy fields, and are known as "industrial vitamins". The exploration and mining of rare earth minerals are crucial to China's economic development and national security.

[0048] Traditional remote sensing technology mainly relies on indirect prospecting methods to infer the existence of rare earth minerals by identifying other minerals or geological features associated with rare earth minerals. In recent years, some scholars have used the absorption characteristics of the 740nm band in the Sentinel-2 satellite data to extract apatite from rare earth minerals, thereby indirectly locating rare earth minerals. However, this method often has certain limitations, as indirect prospecting cannot directly locate rare earth minerals and is prone to identification errors.

[0049] On the other hand, rare earth minerals have unique spectral absorption characteristics due to electronic transition effects in the visible and short-wave infrared bands. The spectral absorption characteristics of rare earth minerals usually occur in multiple bands, and relying on the absorption characteristics of a single band to identify rare earth minerals ignores other key absorption characteristics, which can lead to incomplete identification results. In addition, different substances may exhibit similar spectral characteristics in a certain band (i.e., the same spectrum different substances phenomenon), and relying on a single band can easily lead to misidentification and fail to accurately locate the distribution of rare earth minerals.

[0050] Finally, the unmanned aerial vehicle is limited by the endurance time and flight speed when acquiring hyperspectral data, and cannot acquire large-area hyperspectral data, which is difficult to meet the needs of large-scale high-precision rare earth mineral exploration.

[0051] Based on this, the present application provides a rare earth mineral extraction method, device and electronic equipment. The rare earth mineral extraction method comprehensively considers four rare earth mineral characteristic absorption peaks by using the method of characteristic absorption and weighting combination. The rare earth mineral extraction method provided by the embodiments of the present application can realize efficient, large-scale and high-precision acquisition of the distribution of rare earth minerals.

[0052] Please refer to Figure 1 , Figure 1 The flowchart of the rare earth mineral extraction method provided by the embodiments of the present application; the present application provides a rare earth mineral extraction method, which can be executed by the electronic equipment Figure 4 The rare earth mineral extraction method includes the following steps:

[0053] 101, acquiring reflectance data based on aerial hyperspectral data of a target area;

[0054] 102, calculating the matching degree of the reflectance data and the standard spectrum of the rare earth mineral in the wavelength range of 500nm-950nm, and determining whether the matching degree meets the first preset condition;

[0055] 103, calculating the absorption characteristic position of the reflectance data in the rare earth mineral absorption band interval, wherein the rare earth mineral absorption characteristic position includes the absorption characteristic position of the 568-597nm band interval, the absorption characteristic position of the 719-769nm band interval, the absorption characteristic position of the 783-826nm band interval and the absorption characteristic position of the 862-876nm band interval;

[0056] 104, calculating the reflectance ratio of each absorption characteristic position and the adjacent shoulder position of the absorption characteristic position, and sequentially obtaining the first reflectance ratio, the second reflectance ratio, the third reflectance ratio and the fourth reflectance ratio;

[0057] 105, weighting and summing the first reflectance ratio, the second reflectance ratio, the third reflectance ratio and the fourth reflectance ratio based on the weighting coefficient to obtain a weighted sum value, and determining whether the weighted sum value meets the second preset condition;

[0058] 106, determining the distribution range of the rare earth mineral in the target area based on the intersection of the first rare earth mineral distribution information and the second rare earth mineral distribution information, wherein the first rare earth mineral distribution information is determined based on the weighted sum value meeting the second preset condition, and the second rare earth mineral distribution information is determined based on the reflectance data in the wavelength range of 500nm-950nm.

[0059] In the implementation process described above, by using the rare earth mineral extraction method provided in the embodiments of the present application, the unique absorption characteristics of the rare earth mineral in the four wave bands of 568-597 nm, 719-769 nm, 783-826 nm, and 862-876 nm can be comprehensively considered by using a weighting method, avoiding misjudgment and recognition errors caused by single-band recognition, and the distribution information of the rare earth mineral can be efficiently and accurately extracted from the aerial hyperspectral data. Compared with the traditional method, the system mineral extraction method provided in the embodiments of the present application not only improves the accuracy and reliability of rare earth mineral detection, but also quickly identifies the distribution of rare earth minerals in a large range by combining the first rare earth mineral distribution information and the second rare earth mineral distribution information. In addition, when calculating the final reflectivity of the absorption characteristic position, the reflectivity ratio can be obtained by combining the reflectivity of the adjacent position of the absorption characteristic position, thereby improving the calculation accuracy of the final reflectivity of the absorption characteristic position.

[0060] As an example, it is assumed that the target area includes an A ground surface position, a B ground surface position, a C ground surface position, and a D ground surface position. Correspondingly, the aerial hyperspectral data of the target area obtained includes the aerial hyperspectral data of the A ground surface position, the B ground surface position, the C ground surface position, and the D ground surface position, and the initial reflectivity data includes the reflectivity data of the A ground surface position, the B ground surface position, the C ground surface position, and the D ground surface position. It should be noted that at this time, the reflectivity data of the A ground surface position, the B ground surface position, the C ground surface position, and the D ground surface position refers to the reflectivity data of the A ground surface position, the B ground surface position, the C ground surface position, and the D ground surface position in the full wave band range. Further, the rare earth mineral standard spectrum is matched with the initial reflectivity data, specifically, the reflectivity data of the A ground surface position in the 500 nm-950 nm wavelength range is matched with the rare earth mineral standard spectrum, the reflectivity data of the B ground surface position in the 500 nm-950 nm wavelength range is matched with the rare earth mineral standard spectrum, the reflectivity data of the C ground surface position in the 500 nm-950 nm wavelength range is matched with the rare earth mineral standard spectrum, and the reflectivity data of the D ground surface position in the 500 nm-950 nm wavelength range is matched with the rare earth mineral standard spectrum, and then the matching degree corresponding to the A ground surface position, the matching degree corresponding to the B ground surface position, the matching degree corresponding to the C ground surface position, and the matching degree corresponding to the D ground surface position are obtained. At this time, if the matching degree corresponding to the A ground surface position does not satisfy the first preset condition, and the matching degree corresponding to the B ground surface position, the matching degree corresponding to the C ground surface position, and the matching degree corresponding to the D ground surface position all satisfy the first preset condition, the second rare earth mineral distribution information is determined, and the second rare earth mineral distribution information indicates that the B ground surface position, the C ground surface position, and the D ground surface position are likely to be distributed with rare earth minerals, so that the ground surface positions that are likely to have rare earth minerals are first identified in a large range based on the matching method of the rare earth mineral standard spectrum.

[0061] However, the second rare earth mineral distribution information only identifies surface locations where rare earth minerals may be found, and does not accurately determine whether rare earth minerals are actually found at the corresponding surface locations. Therefore, steps 104-106 search for troughs in the initial reflectivity data. If rare earth minerals are found at a surface location, the reflectivity data at that location will reflect a trough. Therefore, the location of a trough in the initial reflectivity data indicates that the surface location corresponding to that trough may be home to rare earth minerals. It should be noted that since troughs can also be caused by other factors, the location of a trough in the initial reflectivity data only indicates that rare earth minerals may be found at the corresponding surface location, and is not a 100% certainty. On the other hand, according to the characteristics of rare earth minerals, they only absorb light in specific bands. Therefore, only the troughs that appear in specific bands can indicate that rare earth minerals may be distributed at the surface location corresponding to the trough position. Therefore, looking for troughs in the initial reflectivity data is specifically: looking for troughs in specific bands in the initial reflectivity data. The specific bands refer to the 568-597nm band range, the 719-769nm band range, the 783-826nm band range and the 862-876nm band range. It should be noted that since the troughs in the 568-597nm band range, the 719-769nm band range, the 783-826nm band range, and the 862-876nm band range indicate that rare earth minerals may be distributed at the surface positions corresponding to the trough positions, the troughs in the 568-597nm band range, the 719-769nm band range, the 783-826nm band range, and the 862-876nm band range are also called the absorption characteristic positions of the 568-597nm band range, the absorption characteristic positions of the 719-769nm band range, the absorption characteristic positions of the 783-826nm band range, and the absorption characteristic positions of the 862-876nm band range.

[0062] Further, since the initial reflectivity data includes the full-band reflectivity data of the B surface position, the full-band reflectivity data of the C surface position, and the full-band reflectivity data of the D surface position, the absorption feature positions calculated based on the initial reflectivity data include the absorption feature positions of the B surface position in the 568-597 nm band interval, the 719-769 nm band interval, the 783-826 nm band interval, and the 862-876 nm band interval, the absorption feature positions of the C surface position in the 568-597 nm band interval, the 719-769 nm band interval, the 783-826 nm band interval, and the 862-876 nm band interval, and the absorption feature positions of the D surface position in the 568-597 nm band interval, the 719-769 nm band interval, the 783-826 nm band interval, and the 862-876 nm band interval.

[0063] Further, the rare earth mineral recognition accuracy can be improved according to the multiple troughs. Specifically, for any one of the B surface position, the C surface position, and the D surface position, since the troughs can also be caused by other factors, it is not accurate to determine whether the surface position is distributed with the rare earth mineral depending on the trough of a single specific fluctuation. Taking the B surface position as an example, if the B surface position is distributed with a substance S that is the same spectrum as the rare earth mineral, the substance S can cause a trough in the 568-597 nm band interval, but not in the 783-826 nm band interval. Therefore, when recognizing, the B surface position can be avoided from being misjudged as being distributed with the rare earth mineral due to the trough in the 568-597 nm band interval. That is, only when the troughs appear in the 783-826 nm band interval and the 568-597 nm band interval at the same time, it can be determined that the B surface position is distributed with the rare earth mineral. Based on this, the embodiments of the present application comprehensively recognize whether the rare earth mineral exists based on the absorption feature positions in the 568-597 nm band interval, the 719-769 nm band interval, the 783-826 nm band interval, and the 862-876 nm band interval, which has higher accuracy than determining whether the surface position is distributed with the rare earth mineral depending on the trough of a single specific fluctuation.

[0064] Further, the numerical range of the absorption feature position in the 568-597 nm band interval is 576-584 nm, the numerical range of the absorption feature position in the 719-769 nm band interval is 740-744 nm, the numerical range of the absorption feature position in the 783-826 nm band interval is 797-800 nm, and the numerical range of the absorption feature position in the 862-876 nm band interval is 866-869 nm. That is, the absorption feature position in the 568-597 nm band interval is always in the numerical range of 576-584 nm, the absorption feature position in the 719-769 nm band interval is in the numerical range of 740-744 nm, the absorption feature position in the 783-826 nm band interval is in the numerical range of 797-800 nm, and the absorption feature position in the 862-876 nm band interval is in the numerical range of 866-869 nm. Among them, the numerical range of the above absorption feature position covers the corresponding absorption feature position value under various conditions.

[0065] Further, the absorption feature position appears as a trough, but not all troughs are caused by rare earth minerals, for example, due to measurement factors, the reflectance data of the ground surface position B appears a slight trough in the 579-568 nm fluctuation interval, which actually cannot be used to identify whether there are rare earth minerals distributed. Based on this, it is necessary to use the reflectance ratio of the trough to determine whether the trough is caused by rare earth minerals.

[0066] In summary, the presence of rare earth minerals in the surface location can be determined by the troughs in the reflectance data of the specific wavelength range and the degree of each trough. In step 102, the reflectance data in the wavelength range of 500-950 nm is extracted based on the matching degree, and the second rare earth mineral distribution information is determined based on the reflectance data in the wavelength range of 500-950 nm, so that the surface location with a data waveform similar to the rare earth mineral in the wavelength range of 500-950 nm is first screened out from the target area. For example, when the reflectance data in the wavelength range of 500-950 nm includes the reflectance data of the B surface location in the wavelength range of 500-950 nm, the reflectance data of the C surface location in the wavelength range of 500-950 nm, and the reflectance data of the D surface location in the wavelength range of 500-950 nm, the B surface location, the C surface location, and the D surface location can be first screened out from the target area, i.e., the second rare earth mineral distribution information includes the B surface location, the C surface location, and the D surface location. On the other hand, based on steps 103, 104, and 105, the C surface location and the D surface location with the four troughs satisfying the second preset condition are determined, i.e., the first rare earth mineral distribution information includes the C surface location and the D surface location. Finally, the intersection of the first rare earth mineral distribution information and the second rare earth mineral distribution information is the C surface location and the D surface location, and the C surface location and the D surface location constitute the rare earth mineral distribution range of the target area.

[0067] In step 101, the target area includes a plurality of surface locations, such as the A surface location and the B surface location. Correspondingly, the airborne hyperspectral data contains the spectral data of the surface material at different wavelengths of different surface locations, such as the spectral data of the A surface material in the wavelength range of 568-597 nm, the spectral data of the A surface material in the wavelength range of 719-769 nm, the spectral data of the B surface material in the wavelength range of 568-597 nm, and the spectral data of the B surface material in the wavelength range of 719-769 nm.

[0068] In step 101, the hyperspectral data of the target area can be obtained based on a CASI airborne hyperspectral imager. The CASI airborne hyperspectral imager is mounted on a fixed-wing aircraft. Compared with the prior art of using a drone to obtain hyperspectral data, the battery endurance and flight speed of the drone limit the area that can be covered. The use of a drone to obtain hyperspectral data in complex terrain or large area is greatly limited, and it is difficult to realize extensive regional exploration. Due to the limitation of endurance and flight speed, the process of obtaining data by the drone is usually time-consuming and has a small coverage range. Therefore, the rare earth mineral extraction method provided in the embodiments uses a fixed-wing aircraft to mount a CASI airborne hyperspectral imager. Compared with a drone, a fixed-wing aircraft has longer endurance and faster flight speed, can cover a wide area in a short time, and is suitable for large-scale hyperspectral data acquisition.

[0069] In step 101, one specific embodiment of obtaining reflectance data based on the hyperspectral data of the target area is as follows:

[0070] The hyperspectral data of the target area is preprocessed to obtain the reflectance data.

[0071] The data preprocessing of the hyperspectral data of the target area can include radiation correction, geometric correction, and atmospheric correction.

[0072] In step 102, the matching degree of the rare earth mineral standard spectrum and the reflectance data in the wavelength range of 500 nm-950 nm refers to matching the reflectance data of all ground positions in the wavelength range of 500 nm-950 nm between the rare earth mineral standard spectrum and the reflectance data, for example, matching the reflectance data of ground position A in the wavelength range of 500 nm-950 nm between the rare earth mineral standard spectrum and the reflectance data, and matching the reflectance data of ground position B in the wavelength range of 500 nm-950 nm between the rare earth mineral standard spectrum and the reflectance data. The purpose is to preliminarily screen out ground positions where rare earth minerals may be distributed from the target area. If the matching degree meets the first preset condition, it means that the ground position may have rare earth minerals distributed therein, so the reflectance data of the ground position in the wavelength range of 500 nm-950 nm needs to be cut out, and the second rare earth mineral sub-information is determined.

[0073] In step 102, the matching degree meeting the first preset condition can mean that the matching degree is greater than or equal to a first preset threshold, wherein the first preset threshold is the matching degree when the ground position does not contain rare earth minerals.

[0074] In step 102, the matching degree of the rare earth mineral standard spectrum and the reflectance data in the wavelength range of 500nm-950nm can be calculated by the ENVI software, wherein the ENVI software can calculate the matching degree of the rare earth mineral standard spectrum and the reflectance data in the wavelength range of 500nm-950nm by the spectral angle matching method.

[0075] It should be noted that the rare earth mineral standard spectrum is obtained by laboratory or field measurement.

[0076] In the embodiments of the present application, the spectral angle matching method refers to using the spectral angle mapping method (SAM, Spectral Angle Mapper) to calculate the included angle between the target spectrum (airborne hyperspectral data) and the reference spectrum (rare earth mineral standard spectrum) vector to measure the similarity of the two. The smaller the included angle, the higher the matching degree; otherwise, the larger the included angle, the lower the matching degree.

[0077] In step 105, the weighted sum of the first reflectance ratio, the second reflectance ratio, the third reflectance ratio and the fourth reflectance ratio is obtained based on the weighting coefficient, and the calculation formula corresponding to the weighted sum value is:

[0078] Z=Y1*0.07+Y2*0.40+Y3*0.30+Y4*0.23;

[0079] Wherein Y1, Y2, Y3, Y4 are the first reflectance ratio, the second reflectance ratio, the third reflectance ratio and the fourth reflectance ratio respectively, and 0.07, 0.40, 0.30, 0.23 are the weight of the first reflectance ratio, the weight of the second reflectance ratio, the weight of the third reflectance ratio and the weight of the fourth reflectance ratio respectively.

[0080] Optionally, in the embodiments of the present application, the absorption characteristic position of the reflectance data in the rare earth mineral absorption band interval comprises the following steps:

[0081] Calculating the minimum reflectance value of the 568nm-597nm band interval, the minimum reflectance value of the 719-769nm band interval, the minimum reflectance value of the 783-826nm band interval and the minimum reflectance value of the 862-876nm band interval based on the reflectance data;

[0082] Determining the spectral segment position corresponding to the minimum reflectance value of the 568nm-597nm band interval as the absorption characteristic position of the 568nm-597nm band interval;

[0083] Determining the spectral segment position corresponding to the minimum reflectance value of the 719-769nm band interval as the absorption characteristic position of the 719-769nm band interval;

[0084] The spectral segment position corresponding to the minimum reflectivity value of the 783-826 nm waveband interval is determined as the absorption characteristic position of the 783-826 nm waveband interval.

[0085] The spectral segment position corresponding to the minimum reflectivity value of the 862-876 nm waveband interval is determined as the absorption characteristic position of the 862-876 nm waveband interval.

[0086] In the implementation process described above, the absorption characteristic position of the 568-597 nm waveband interval, the absorption characteristic position of the 719-769 nm waveband interval, the absorption characteristic position of the 783-826 nm waveband interval, and the absorption characteristic position of the 862-876 nm waveband interval can be determined in sequence according to the absorption characteristic position of the 568-597 nm waveband interval, the minimum reflectivity of the 719-769 nm waveband interval, the minimum reflectivity of the 783-826 nm waveband interval, and the minimum reflectivity of the 862-876 nm waveband interval.

[0087] Optionally, in the embodiment of the present application, the reflectivity of the adjacent shoulder position of each absorption characteristic position is determined based on the reflectivity data.

[0088] Optionally, in the embodiment of the present application, the reflectivity ratio of each absorption characteristic position to the reflectivity of the adjacent shoulder position of the absorption characteristic position is calculated, comprising:

[0089] The reflectivity of each absorption characteristic position is calculated.

[0090] The reflectivity of the adjacent shoulder position of each absorption characteristic position is calculated.

[0091] The reflectivity ratio of each absorption characteristic position to the reflectivity of the adjacent shoulder position of the absorption characteristic position is calculated based on the reflectivity of each absorption characteristic position and the reflectivity of the adjacent shoulder position of the absorption characteristic position.

[0092] In the embodiment of the present application, please refer to Figure 2 , Figure 2 is a schematic diagram of the spectral absorption characteristic quantification disclosed in the embodiment of the present application, as Figure 2 shown, the calculation formula of the reflectivity ratio of each absorption characteristic position to the reflectivity of the adjacent shoulder position of the absorption characteristic position is:

[0093]

[0094] wherein Y represents the reflectivity ratio of the absorption characteristic position to the reflectivity of the adjacent shoulder position of the absorption characteristic position, ρ m is the reflectivity of the absorption characteristic position, ρ1 and ρ2 are the reflectivity of the adjacent shoulder position of the absorption characteristic position, that isFigure 2 The reflectivity of S1 and S2.

[0095] Optionally, in an embodiment of the present application, obtaining reflectance data based on aerial hyperspectral data of a target area includes:

[0096] The aerial hyperspectral data of the target area are preprocessed to obtain reflectance data.

[0097] Optionally, in an embodiment of the present application, obtaining reflectance data based on aerial hyperspectral data of a target area includes:

[0098] The aerial hyperspectral data of the target area are preprocessed to obtain reflectance data.

[0099] Optionally, in an embodiment of the present application, the reflectivity data within the wavelength range of 500nm-950nm is subjected to envelope removal and normalization. In the above implementation process, after intercepting the absorption characteristic spectrum, the rare earth mineral extraction method provided in the embodiment of the present application performs envelope removal and spectral normalization, making the absorption characteristics of the rare earth mineral more distinct, optimizing the subsequent identification and classification process based on multi-band absorption characteristics, and laying the foundation for high-precision rare earth mineral distribution detection.

[0100] Example 2

[0101] See also Figure 3 , Figure 3 This is a schematic diagram of the structure of a rare earth mineral extraction device disclosed in the embodiment of the present application. Figure 3 As shown, the device of the embodiment of the present application includes the following functional modules:

[0102] An acquisition module 201 is used to acquire reflectance data based on the aerial hyperspectral data of the target area;

[0103] The second calculation module 202 is used to calculate the matching degree between the rare earth mineral standard spectrum and the reflectance data in the wavelength range of 500nm-950nm, and determine whether the matching degree meets the first preset condition;

[0104] The second calculation module 203 is used to calculate the absorption characteristic position of the reflectivity data in the rare earth mineral absorption band range, wherein the rare earth mineral absorption characteristic position includes the absorption characteristic position of the 568-597nm band range, the absorption characteristic position of the 719-769nm band range, the absorption characteristic position of the 783-826nm band range, and the absorption characteristic position of the 862-876nm band range;

[0105] The third calculation module 204 is configured to calculate a reflectivity ratio of each absorption feature position to a neighboring shoulder position of the absorption feature position, and sequentially obtain a first reflectivity ratio, a second reflectivity ratio, a third reflectivity ratio and a fourth reflectivity ratio.

[0106] The fourth calculation module 205 is configured to weight and sum the first reflectivity ratio, the second reflectivity ratio, the third reflectivity ratio and the fourth reflectivity ratio based on a weighting coefficient to obtain a weighted sum value, and determine whether the weighted sum value meets a second preset condition.

[0107] The determination module 206 is configured to determine a rare earth mineral distribution range of the target region based on an intersection of first rare earth mineral subdivision information and second rare earth mineral subdivision information, wherein the first rare earth mineral subdivision information is determined based on the weighted sum value meeting the second preset condition, and the second rare earth mineral subdivision information is determined based on reflectivity data in a wavelength range of 500 nm-950 nm.

[0108] Embodiment three

[0109] See Figure 4 , Figure 4 is a structural schematic diagram of an electronic device provided by an embodiment of the present application. The electronic device provided by an embodiment of the present application comprises a processor 301 and a memory 302, the memory 302 stores machine readable instructions executable by the processor 301, and the machine readable instructions are executed by the processor 301 to perform the method as above.

[0110] Based on the same inventive concept, an embodiment of the present application further provides a computer readable storage medium, the computer readable storage medium stores computer program instructions, and the computer program instructions are read and run by a processor to perform the steps in any implementation manner of the rare earth mineral extraction method.

[0111] The computer readable storage medium can be a random access memory (RAM), a read only memory (ROM), a programmable read only memory (PROM), an erasable programmable read only memory (EPROM), an electric erasable programmable read only memory (EEPROM) and various media that can store program codes.

[0112] In this document, relational terms such as first and second and the like can be used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Moreover, the terms "comprises", "comprising", or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but can include other elements not expressly listed or inherent to such process, method, article, or apparatus. An element proceeded by "comprises... a" does not, without more constraints, exclude the existence of additional identical elements in the process, method, article, or apparatus that comprises the element.

[0113] The embodiments of the present application only illustrate the technical solutions of the present application and do not limit the protection scope of the present application. Any modification, equivalent replacement, improvement, and the like made within the spirit and principle of the present application shall be included in the protection scope of the present application.

Claims

1. A method for extracting rare earth minerals, characterized in that: The method comprises: Obtain reflectance data based on aerial hyperspectral data of the target area; Calculating a matching degree between the rare earth mineral standard spectrum and the reflectivity data in a wavelength range of 500 nm to 950 nm, and determining whether the matching degree satisfies a first preset condition; Calculating the absorption characteristic position of the reflectivity data in the rare earth mineral absorption band range, wherein the rare earth mineral absorption characteristic position includes the absorption characteristic position in the 568-597 nm band range, the absorption characteristic position in the 719-769 nm band range, the absorption characteristic position in the 783-826 nm band range, and the absorption characteristic position in the 862-876 nm band range; Calculating the reflectivity ratio of each of the absorption characteristic positions to the shoulder position adjacent to the absorption characteristic position, and sequentially obtaining a first reflectivity ratio, a second reflectivity ratio, a third reflectivity ratio, and a fourth reflectivity ratio; weightedly summing the first reflectivity ratio, the second reflectivity ratio, the third reflectivity ratio, and the fourth reflectivity ratio based on a weighting coefficient to obtain a weighted sum value, and determining whether the weighted sum value meets a second preset condition; determining a rare earth mineral distribution range of the target area based on an intersection of first rare earth mineral distribution information and second rare earth mineral distribution information, wherein the first rare earth mineral distribution information is determined based on a weighted sum value that satisfies the second preset condition, and the second rare earth mineral distribution information is determined based on reflectivity data within the wavelength range of 500 nm to 950 nm; Furthermore, calculating the reflectivity ratio between each absorption characteristic position and the shoulder position adjacent to the absorption characteristic position comprises: Calculating the reflectivity of each absorption feature position; Calculating the reflectivity of the shoulder position adjacent to each of the absorption feature positions; Calculating a reflectivity ratio of each absorption characteristic position to a shoulder position adjacent to the absorption characteristic position based on the reflectivity of each absorption characteristic position and the reflectivity of a shoulder position adjacent to the absorption characteristic position; Furthermore, based on the reflectivity of each absorption characteristic position and the reflectivity of the shoulder position adjacent to the absorption characteristic position, the calculation formula corresponding to the reflectivity ratio of each absorption characteristic position to the shoulder position adjacent to the absorption characteristic position is: Wherein, Y represents the reflectivity ratio of the absorption characteristic position to the adjacent shoulder position of the absorption characteristic position, ρ m is the reflectivity of the absorption characteristic position, ρ1 and ρ2 are the reflectivity of the adjacent shoulder positions of the absorption characteristic position.

2. The method according to claim 1, wherein The numerical range of the absorption characteristic position in the 568-597nm band is 576-584nm, the numerical range of the absorption characteristic position in the 719-769nm band is 740-744nm, the numerical range of the absorption characteristic position in the 783-826nm band is 797-800nm, and the numerical range of the absorption characteristic position in the 862-876nm band is 866-869nm.

3. The method according to claim 1, wherein Calculating the absorption characteristic position of the reflectivity data in the absorption band of rare earth minerals includes: Calculate the minimum reflectivity value of the 568nm-597nm band, the minimum reflectivity value of the 719-769nm band, the minimum reflectivity value of the 783-826nm band, and the minimum reflectivity value of the 862-876nm band based on the reflectivity data; Determine the spectral band position corresponding to the minimum reflectivity value in the 568nm-597nm band as the absorption characteristic position in the 568nm-597nm band; Determine the spectral band position corresponding to the minimum reflectivity value in the 719-769nm band as the absorption characteristic position in the 719-769nm band; Determine the spectral band position corresponding to the minimum reflectivity value in the 783-826 nm band as the absorption characteristic position in the 783-826 nm band; The spectral band position corresponding to the minimum reflectivity value in the 862-876 nm band is determined as the absorption characteristic position in the 862-876 nm band.

4. The method according to claim 1, wherein The method further comprises: The reflectivity of a shoulder position adjacent to each of the absorption feature positions is determined based on the reflectivity data.

5. The method according to claim 1, wherein The method of obtaining reflectance data based on the aerial hyperspectral data of the target area includes: Data preprocessing is performed on the aerial hyperspectral data of the target area to obtain the reflectance data.

6. The method according to claim 1, wherein The method further comprises: The reflectivity data within the wavelength range of 500 nm to 950 nm is subjected to envelope removal and normalization.

7. A rare earth mineral extraction device, characterized in that: The device comprises: An acquisition module, used to acquire reflectance data based on aerial hyperspectral data of the target area; a second calculation module, configured to calculate a matching degree between a standard spectrum of a rare earth mineral and the reflectivity data within a wavelength range of 500 nm to 950 nm, and to determine whether the matching degree satisfies a first preset condition; A second calculation module is used to calculate the absorption characteristic position of the reflectivity data in the rare earth mineral absorption band interval, wherein the rare earth mineral absorption characteristic position includes the absorption characteristic position of the 568-597nm band interval, the absorption characteristic position of the 719-769nm band interval, the absorption characteristic position of the 783-826nm band interval, and the absorption characteristic position of the 862-876nm band interval; a third calculation module, configured to calculate a reflectivity ratio between each of the absorption characteristic positions and a shoulder position adjacent to the absorption characteristic position, and sequentially obtain a first reflectivity ratio, a second reflectivity ratio, a third reflectivity ratio, and a fourth reflectivity ratio; a fourth calculation module, configured to weightedly sum the first reflectivity ratio, the second reflectivity ratio, the third reflectivity ratio, and the fourth reflectivity ratio based on a weighting coefficient to obtain a weighted sum value, and determine whether the weighted sum value meets a second preset condition; a determination module, configured to determine a rare earth mineral distribution range of the target area based on an intersection of first rare earth mineral distribution information and second rare earth mineral distribution information, wherein the first rare earth mineral distribution information is determined based on a weighted sum value that satisfies the second preset condition, and the second rare earth mineral distribution information is determined based on reflectivity data within the wavelength range of 500 nm to 950 nm; Furthermore, calculating the reflectivity ratio between each absorption characteristic position and the shoulder position adjacent to the absorption characteristic position comprises: Calculating the reflectivity of each absorption feature position; Calculating the reflectivity of the shoulder position adjacent to each of the absorption feature positions; Calculating a reflectivity ratio of each absorption characteristic position to a shoulder position adjacent to the absorption characteristic position based on the reflectivity of each absorption characteristic position and the reflectivity of a shoulder position adjacent to the absorption characteristic position; Furthermore, based on the reflectivity of each absorption characteristic position and the reflectivity of the shoulder position adjacent to the absorption characteristic position, the calculation formula corresponding to the reflectivity ratio of each absorption characteristic position to the shoulder position adjacent to the absorption characteristic position is: Wherein, Y represents the reflectivity ratio of the absorption characteristic position to the adjacent shoulder position of the absorption characteristic position, ρ m is the reflectivity of the absorption characteristic position, ρ1 and ρ2 are the reflectivity of the adjacent shoulder positions of the absorption characteristic position.

8. An electronic device, characterized in that: The electronic device includes a memory and a processor, wherein program instructions are stored in the memory, and when the processor runs the program instructions, the steps in the method according to any one of claims 1 to 6 are executed.

9. A computer-readable storage medium, characterized in that The computer-readable storage medium stores computer program instructions, and when the computer program instructions are executed by a processor, the steps of the method according to any one of claims 1 to 6 are executed.

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