A method for extracting information of eclogite-type rutile deposits based on remote sensing images

Abstract

The present invention discloses a method for extracting information of eclogite-type rutile ore based on remote sensing images, which is characterized in that: in the area to be identified, based on the first remote sensing image, a silicon dioxide low-value abnormal sub-area and a garnet abnormal sub-area are obtained, and a titanium geochemical abnormal sub-area in the area to be identified is obtained, and the silicon dioxide low-value abnormal sub-area, the garnet abnormal sub-area, and the titanium geochemical abnormal sub-area are superimposed to obtain silicon dioxide, garnet and titanium geochemical abnormal sub-areas as the initial target area position; based on the second remote sensing image, the eclogite geological body is interpreted in the initial target area, the rutile ore body position is optimized, and the final target area is delineated. The present application is based on remote sensing image processing, gradually narrows the scope of exploration, realizes the preliminary delineation of the rutile ore area, reduces the workload of field exploration, and saves manpower, material resources and financial resources.

Description

Technical Field

[0001] The invention relates to the technical field of remote sensing geological survey, and in particular to a method for extracting information of eclogite-type rutile ore based on remote sensing images. Background Art

[0002] Rutile is a relatively pure titanium dioxide (TiO2), a tetragonal crystal system, often with a perfect tetragonal columnar or needle-shaped crystal shape, and the aggregate is granular or dense blocky. The color is dark red, brown red, yellow or orange, and the iron-rich ones are black; the streak is yellow to light brown. It has a diamond luster, and iron rutile has a semi-metallic luster. It is brittle, with a hardness of 6 to 6.5 and a density of 4.2 to 4.3 g / cm 3 , those rich in iron, niobium and tantalum have increased density, and the highest can reach more than 5.5g / cm3. It can be dissolved in hot phosphoric acid, and adding sodium peroxide after cooling and dilution can make the solution turn yellow-brown (titanium reaction). Rutile can be produced in gneiss, pegmatite, eclogite (amphibolite) rock and sand mines, and has a close symbiotic relationship with garnet alteration in the identification area. Rutile is an important mineral raw material for refining titanium, and its reserves in the earth's crust are relatively small. Titanium metal has excellent properties such as high temperature resistance, low temperature resistance, corrosion resistance, high strength, and low specific gravity. It is widely used in military aviation, aerospace, navigation, machinery, chemical industry, seawater desalination and other aspects.

[0003] At present, geological and mineral exploration work is gradually expanding to the sparsely populated high-altitude areas in the central and western regions. These areas have complex natural conditions, harsh environment and very inconvenient transportation, which seriously affects the development of exploration work.

[0004] Therefore, given the limited human, material and financial resources, how to efficiently, quickly, accurately and economically identify rutile mineral resources in a short period of time and guide and optimize rutile mine exploration is an urgent problem to be solved. Summary of the invention

[0005] The purpose of the present invention is to provide a method for extracting information of eclogite-type rutile ore based on remote sensing images. Through remote sensing images, a SiO2 low-value abnormal sub-region and a garnet high-value abnormal sub-region are distinguished in the area to be identified, and the two sub-regions are superimposed to obtain a sub-region with both SiO2 and garnet abnormalities, which is then superimposed with the titanium geochemical abnormal sub-region to obtain a preliminary ore target area, and then the eclogite geological body is interpreted in the preliminary ore target area to obtain the rutile ore area. By gradually narrowing the area, the workload of field exploration is reduced, and manpower, material resources and financial resources are saved.

[0006] The above-mentioned object of the present invention is achieved through the following technical solutions:

[0007] A method for extracting information of eclogite-type rutile ore based on remote sensing images, in the area to be identified, based on the first remote sensing image (Aster), obtains silica low-value anomaly sub-areas and garnet anomaly sub-areas, superimposes the silica low-value anomaly sub-areas with the garnet anomaly sub-areas, obtains silica and garnet simultaneous anomaly sub-areas, combines with the titanium geochemical anomaly sub-areas in the area to be identified, obtains silica, garnet and titanium simultaneous anomaly sub-areas, and obtains the location of the preliminary ore target area; based on the second remote sensing image (GF-2), the eclogite geological body is interpreted in the preliminary ore target area, the rutile ore body position is optimized, and the final ore target area is delineated.

[0008] The present invention is further configured to include the following steps:

[0009] S1, obtaining a first remote sensing image and a second remote sensing image of the area to be identified;

[0010] S2, performing a first preprocessing on the first remote sensing image data to obtain ground object emissivity data;

[0011] S3, performing a second preprocessing on the second remote sensing image data to obtain high-resolution orthophoto remote sensing image data;

[0012] S4. Using the ground object emissivity data, perform silica abundance inversion and extract the silica low value abnormal sub-region as the first sub-region;

[0013] S5. Using the ground object emissivity data and the diagnostic spectrum characteristics of almandine, an almandine extraction model based on band logic operation and matched filtering is constructed to extract the garnet abnormal sub-region as the second sub-region;

[0014] S6, obtaining a titanium geochemical exploration anomaly sub-region of the area to be identified as the third sub-region;

[0015] S7, superimposing the first sub-region, the second sub-region, and the third sub-region to obtain a preliminary mineral target region;

[0016] S8. Based on the high-resolution orthophoto remote sensing image data, interpret the eclogite geological body in the preliminary target area and determine the rutile ore body area.

[0017] The present invention is further configured as follows: the first remote sensing image adopts Aster-TIR remote sensing image, the second remote sensing image adopts GF-2 remote sensing image, based on Aster-TIR remote sensing image, the emissivity data of ground objects in the area to be identified is obtained, based on GF-2 remote sensing image, the high-resolution orthophoto remote sensing image of the area to be identified is obtained.

[0018] The present invention is further configured as follows: the first preprocessing includes performing radiation calibration, atmospheric correction, and temperature and emissivity separation on the first remote sensing image data.

[0019] The present invention is further configured as follows: the first pre-processing comprises the following steps:

[0020] A1. Using remote sensing image processing software to read the first remote sensing image data, perform radiation calibration, and determine the radiation value unit after calibration;

[0021] A2. Using the radiation transfer model, the actual atmospheric parameters, including atmospheric transmittance, atmospheric upward radiation and atmospheric downward radiation, are calculated according to the acquisition phase, geographical range and empirical atmospheric parameters of the first remote sensing image data;

[0022] A3. Perform atmospheric correction on the first remote sensing image data according to actual atmospheric parameters, use an algorithm to separate temperature and emissivity, and obtain ground object emissivity data.

[0023] The present invention is further configured as follows: the second preprocessing includes orthorectification, GS fusion and geometric precision correction of the second remote sensing image data.

[0024] The present invention is further configured to: calculate the band ratio of the ground object emissivity data as the silica index, calculate the silica abundance according to the statistical relationship between the silica index and the silica content, and extract the silica low-value abnormal sub-region.

[0025] The present invention is further configured as follows: remote sensing image processing software is applied, and a logic operation is used to create an almandine extraction mask; matched filtering is performed on the ground object emissivity data according to the almandine spectrum in the ground object spectrum library to obtain a matched filtering result, and the matched filtering result is cropped using the almandine extraction mask to extract a high-value abnormal area to obtain a garnet high-value abnormal sub-area.

[0026] The present invention is further configured as follows: the logical operation formula is as follows:

[0027] (float(b12) / float(b13))>1) and (float(b14) / float(b13)>1) and(float(b12) / float(b14)>1) and (float(b12) / float(b11)>1) and (float(b13) / float(b11)<1) and (float(b14) / float(b11)<1) and (float(b14) / float(b10)<1);

[0028] Wherein, float(bn) represents the nth band data of floating-point thermal infrared remote sensing data, and and represents logical AND.

[0029] The present invention is further configured to interpret the eclogite geological body. The eclogite is dark black in the GF-2 431 band composite image, and is in the shape of strips, lenses and irregular shapes, which forms a sharp contrast with the eclogite felsic surrounding rock, and the rutile ore body area is distinguished and determined.

[0030] Compared with the prior art, the beneficial technical effects of this application are:

[0031] 1. This application is based on remote sensing image processing, gradually narrowing the scope of exploration, achieving the preliminary delineation of the rutile mine area, reducing the workload of field exploration, and saving manpower, material and financial resources;

[0032] 2. Furthermore, the present application obtains a preliminary mine target area by processing two different remote sensing images separately and then superimposing them, thereby achieving preliminary positioning of the mine target;

[0033] 3. Furthermore, the present application combines the eclogite geological body within the target area of ​​the mine to accurately locate the ore body, reduce the scope of field exploration, and achieve efficient, rapid, accurate and economical identification of rutile mineral resources in a short period of time. BRIEF DESCRIPTION OF THE DRAWINGS

[0034] Figure 1 It is a schematic diagram of the extraction method flow of a specific embodiment of the present application. DETAILED DESCRIPTION

[0035] The present invention is further described in detail below in conjunction with the accompanying drawings. Specific embodiment 1

[0037] The present application discloses a method for extracting information of eclogite-type rutile ore based on remote sensing images, comprising: obtaining ground object emissivity data of a to-be-identified area through a first remote sensing image, performing silica abundance inversion according to the ground object emissivity data, and obtaining a sub-area with low silica value anomaly as a first sub-area; then, according to the ground object emissivity data and in combination with the diagnostic spectrum characteristics of almandine, constructing an almandine garnet extraction model based on band logic operation and matched filtering, extracting a sub-area with high garnet value anomaly as a second sub-area; obtaining a sub-area with titanium geochemical anomaly in the to-be-identified area as a third sub-area, overlapping the first sub-area, the second sub-area, and the third sub-area, obtaining a sub-area with low silica value anomaly, high garnet value anomaly, and titanium geochemical anomaly coexisting as a preliminary ore target area, and then, based on the first remote sensing image, interpreting the eclogite geological body in the preliminary ore target area, optimizing the position of the rutile ore body, and delineating the final ore target area.

[0038] In a specific embodiment of the present application, the first remote sensing image adopts Aster remote sensing image, and the second remote sensing image adopts GF-2 remote sensing image.

[0039] Specifically, the steps include:

[0040] S1, obtain Aster remote sensing images and GF-2 remote sensing images of the area to be identified;

[0041] S2, performing a first preprocessing on the Aster remote sensing image data to obtain ground object emissivity data;

[0042] S3, performing a second preprocessing on the GF-2 remote sensing image data to obtain high-resolution orthophoto remote sensing image data;

[0043] S4. Using the ground object emissivity data, perform silica abundance inversion and extract the sub-region with low silica value anomaly as the first sub-region;

[0044] S5. Using the ground object emissivity data and the diagnostic spectrum characteristics of almandine, an almandine extraction model based on band logic operation and matched filtering is constructed to extract the garnet abnormal sub-region as the second sub-region;

[0045] S6, obtaining a titanium geochemical exploration anomaly sub-region of the area to be identified as the third sub-region;

[0046] S7, superimposing the first sub-region, the second sub-region, and the third sub-region to obtain a preliminary mineral target region;

[0047] S8. Based on the high-resolution orthophoto remote sensing image data, interpret the eclogite geological body in the preliminary target area and determine the rutile ore body area.

[0048] In a specific embodiment of the present application, the superposition of the first sub-region, the second sub-region, and the third sub-region is performed in two steps. First, two of the sub-regions are superimposed, and then the last sub-region is superimposed.

[0049] The first preprocessing includes radiation calibration, atmospheric correction and separation of temperature and emissivity. The specific steps are as follows:

[0050] A1. Use the remote sensing image processing software ENVI to read the Aster remote sensing image data and perform radiation calibration. The radiation value after calibration is determined to be in W / m 2 / sr / um;

[0051] A2. Using the radiation transfer model in the software Modtran, the actual atmospheric parameters are calculated according to the acquisition phase, geographical range, empirical atmospheric parameters and other parameters of the Aster remote sensing image data, including atmospheric transmittance τ, atmospheric upward radiation Lup (unit: W / m 2 / sr / um) and atmospheric downward radiation Ldown, where the units of atmospheric upward radiation and atmospheric downward radiation are W / m 2 / sr / um;

[0052] A3. Based on the actual atmospheric parameters, the Aster remote sensing image data is atmospherically corrected, and the temperature and emissivity are separated using the Aster-TES algorithm to obtain the emissivity data of the ground objects.

[0053] Based on the ground object emissivity data, the SiO2 abundance inversion is performed, including:

[0054] B1. Using the band ratio of the ground object emissivity data, calculate the ratio of the twelfth band to the thirteenth band of the Aster remote sensing image data, i.e., ε12 / ε13, and obtain the index representing the SiO2 content, i.e., the SiO2 index;

[0055] B2. Calculate SiO2 abundance based on the statistical relationship between SiO2 index and SiO2 content, i.e., y = -70.41x + 126.5; where y represents SiO2 content and x represents SiO2 index.

[0056] Logical operations are used to create an almandine extraction mask, and then remote sensing image processing software is used to perform matched filtering. Combined with the almandine spectrum in the surface feature spectrum library, matched filtering is performed on the surface feature emissivity data to obtain the matched filtering results. The almandine extraction mask is used to crop the matched filtering results, extract high-value anomaly areas, and obtain garnet high-value anomaly sub-areas.

[0057] The logical operation formula is as follows:

[0058] (float(b12) / float(b13))>1) and (float(b14) / float(b13)>1) and(float(b12) / float(b14)>1) and (float(b12) / float(b11)>1) and (float(b13) / float(b11)<1) and (float(b14) / float(b11)<1) and (float(b14) / float(b10)<1);

[0059] Wherein, float(bn) represents the nth band data of floating-point thermal infrared remote sensing data, and and represents logical AND.

[0060] The ground feature spectral library adopts the ground feature spectral library of JHU (Johns Hopkins University) in the United States.

[0061] Titanium (Ti) geochemical anomalies in the area to be identified are collected, and superimposed with the garnet high-value anomaly sub-areas and SiO2 low-value anomaly sub-areas on the ArcGIS platform for analysis to delineate preliminary mineral target areas.

[0062] The second preprocessing includes orthorectification, GS fusion and geometric correction.

[0063] Using high-resolution orthophoto remote sensing image data, the eclogite geological body was interpreted in the preliminary target area: in the interpretation of the eclogite geological body, the eclogite appears dark black on the 431 band composite image of the GF-2 remote sensing image data, and is strip-shaped, lens-shaped and irregular, forming a sharp contrast with the eclogite felsic surrounding rock, thereby optimizing the location of the rutile ore body and delineating the final target area. Specific embodiment 2

[0065] The present application discloses a eclogite-type rutile mine information extraction terminal based on remote sensing images. An embodiment of the present invention provides an eclogite-type rutile mine information extraction terminal device based on remote sensing images. The terminal device of this embodiment includes: a processor, a memory, and a computer program stored in the memory and executable on the processor, such as a remote sensing image extraction computer program. When the processor executes the computer program, the method in Example 1 is implemented.

[0066] Exemplarily, the computer program can be divided into one or more modules / units, which are stored in the memory and executed by the processor to complete the present invention. The one or more modules / units can be a series of computer program instruction segments that can complete specific functions, and the instruction segments are used to describe the execution process of the computer program in the eclogite-type rutile mine information extraction terminal device based on remote sensing images. For example, the computer program can be divided into multiple modules, and the specific functions of each module are as follows:

[0067] 1. Remote sensing image extraction module, used to extract remote sensing images;

[0068] 2. Image processing module, used for preprocessing images;

[0069] 3. Image overlay module, used to overlay the preprocessed images.

[0070] The eclogite-type rutile mine information extraction terminal device based on remote sensing images can be a computing device such as a desktop computer, a notebook, a PDA, and a cloud server. The terminal device may include, but is not limited to, a processor and a memory. Those skilled in the art can understand that the above examples are only examples of eclogite-type rutile mine information extraction terminal devices based on remote sensing images, and do not constitute a limitation on the eclogite-type rutile mine information extraction terminal device based on remote sensing images. It may include more or fewer components, or a combination of certain components, or different components. For example, the eclogite-type rutile mine information extraction terminal device based on remote sensing images may also include input and output devices, network access devices, buses, etc.

[0071] The processor may be a central processing unit (CPU), or other general-purpose processors, a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA) or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components, etc. The general-purpose processor may be a microprocessor or any conventional processor, etc. The processor is the control center of the eclogite-type rutile mine information extraction terminal device based on remote sensing images, and uses various interfaces and lines to connect the various parts of the entire eclogite-type rutile mine information extraction terminal device based on remote sensing images.

[0072] The memory can be used to store the computer program and / or module, and the processor realizes various functions of the eclogite-type rutile mine information extraction terminal device based on remote sensing images by running or executing the computer program and / or module stored in the memory, and calling the data stored in the memory. The memory can mainly include a program storage area and a data storage area, wherein the program storage area can store an operating system, an application required for at least one function (such as a sound playback function, an image playback function, etc.), etc.; the data storage area can store data created according to the use of the mobile phone (such as audio data, a phone book, etc.), etc. In addition, the memory can include a high-speed random access memory, and can also include a non-volatile memory, such as a hard disk, a memory, a plug-in hard disk, a smart memory card (Smart Media Card, SMC), a secure digital (SecureDigital, SD) card, a flash card (Flash Card), at least one disk storage device, a flash memory device, or other volatile solid-state storage devices.

[0073] The embodiments of this specific implementation method are all preferred embodiments of the present invention, and are not intended to limit the protection scope of the present invention. Therefore, any equivalent changes made based on the structure, shape, and principle of the present invention should be included in the protection scope of the present invention.

Claims

1. A method for extracting information of eclogite-type rutile ore based on remote sensing images, characterized in that: In the area to be identified, based on the first remote sensing image, a silica low-value anomaly sub-area and a garnet anomaly sub-area are obtained, and a titanium geochemical anomaly sub-area in the area to be identified is obtained, and the silica low-value anomaly sub-area, the garnet high-value anomaly sub-area and the titanium geochemical anomaly sub-area are superimposed to obtain a silica low-value, garnet high-value and titanium geochemical anomaly sub-area as a preliminary mineral target area; based on the second remote sensing image, an eclogite geological body is interpreted in the preliminary mineral target area, the position of the rutile ore body is optimized, and the final mineral target area is delineated; The following steps are involved: S1, obtaining a first remote sensing image and a second remote sensing image of the area to be identified; S2, performing a first preprocessing on the first remote sensing image data to obtain ground object emissivity data; S3, performing a second preprocessing on the second remote sensing image data to obtain high-resolution orthophoto remote sensing image data; S4. Using the ground object emissivity data, perform silica abundance inversion and extract the silica low value abnormal sub-region as the first sub-region; S5. Using the ground object emissivity data and the diagnostic spectrum characteristics of almandine, an almandine extraction model based on band logic operation and matched filtering is constructed to extract the garnet abnormal sub-region as the second sub-region; S6, obtaining a titanium geochemical exploration anomaly sub-region of the area to be identified as the third sub-region; S7, superimposing the first sub-region, the second sub-region, and the third sub-region to obtain a preliminary mineral target region; S8. Based on the high-resolution orthophoto remote sensing image data, interpret the eclogite geological body in the preliminary target area to determine the rutile ore body area; The first preprocessing includes performing radiation calibration, atmospheric correction, and temperature and emissivity separation on the first remote sensing image data; The first pre-processing includes the following steps: A1. Use the remote sensing image processing software ENVI to read the Aster remote sensing image data and perform radiation calibration. The radiation value after calibration is determined to be in W / m 2 / sr / um; A2. Using the radiation transfer model in the software Modtran, according to the acquisition phase, geographical range, and empirical atmospheric parameters of Aster remote sensing image data, calculate the actual atmospheric parameters, including atmospheric transmittance τ and atmospheric upward radiation Lup in W / m 2 / sr / um and atmospheric downward radiation Ldown, where the units of atmospheric upward radiation and atmospheric downward radiation are W / m 2 / sr / um; A3. Perform atmospheric correction on Aster remote sensing image data according to actual atmospheric parameters, use Aster-TES algorithm to separate temperature and emissivity, and obtain ground object emissivity data; Based on the ground object emissivity data, the SiO2 abundance inversion is performed, including: B1. Using the band ratio of the ground object emissivity data, calculate the ratio of the twelfth band to the thirteenth band of the Aster remote sensing image data, i.e., ε12 / ε13, and obtain the index representing the SiO2 content, i.e., the SiO2 index; B2. Calculate SiO2 abundance based on the statistical relationship between SiO2 index and SiO2 content, i.e., y = -70.41x + 126.5; where y represents SiO2 content and x represents SiO2 index.

2. The method for extracting information of eclogite-type rutile ore based on remote sensing images according to claim 1, characterized in that: The first remote sensing image uses Aster-TIR remote sensing image, and the second remote sensing image uses GF-2 remote sensing image. Based on Aster-TIR remote sensing image, the emissivity data of the object in the area to be identified is obtained, and based on GF-2 remote sensing image, the high-resolution orthophoto remote sensing image of the area to be identified is obtained.

3. The method for extracting information of eclogite-type rutile ore based on remote sensing images according to claim 1, characterized in that: The second preprocessing includes orthorectification, GS fusion and geometric precision correction of the second remote sensing image data.

4. The method for extracting information of eclogite-type rutile ore based on remote sensing images according to claim 1, characterized in that: The band ratio of the ground object emissivity data is calculated as the silica index. Based on the statistical relationship between the silica index and the silica content, the silica abundance is calculated and the sub-areas with low silica value anomalies are extracted.

5. The method for extracting information of eclogite-type rutile ore based on remote sensing images according to claim 1, characterized in that: Remote sensing image processing software is used to create an almandine extraction mask using logical operations; matched filtering is performed on the ground object emissivity data according to the almandine spectrum in the ground object spectrum library to obtain a matched filtering result, and the matched filtering result is cropped using the almandine extraction mask to extract high-value abnormal areas and obtain garnet high-value abnormal sub-areas.

6. The method for extracting information of eclogite-type rutile ore based on remote sensing images according to claim 5, characterized in that: The logical operation formula is as follows: (float(b12) / float(b13))>1) and (float(b14) / float(b13)>1) and(float(b12) / float(b14)>1) and (float(b12) / float(b11)>1) and (float(b13) / float(b11)<1) and(float(b14) / float(b11)<1) and (float(b14) / float(b10)<1); Wherein, float(bn) represents the nth band data of floating-point thermal infrared remote sensing data, and and represents logical AND.

7. The method for extracting information of eclogite-type rutile ore based on remote sensing images according to claim 1, characterized in that: The interpretation of the eclogite geological body shows that the eclogite is dark black in the GF-2 431 band composite image, and is in the shape of strips, lenses and irregular shapes, which forms a sharp contrast with the eclogite felsic surrounding rock, distinguishing and determining the rutile ore body area.

8. A terminal for extracting information of eclogite-type rutile ore based on remote sensing images, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, the method according to any one of claims 1 to 7 is implemented.

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