CN111060456B - Method for identifying sandstone uranium ore structure excretion zone by using remote sensing image - Google Patents
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Abstract
The invention belongs to the technical field of multispectral remote sensing analysis, and particularly relates to a method for identifying sandstone uranium ore structure excretion zone by using remote sensing image, which comprises the following steps: the method comprises the following steps: unifying the spatial resolution of the visible light and the near-infrared image of the ASTER remote sensing data, and performing band synthesis; step two: calculating single-waveband images of the salinized belt for multiple times by adjusting floating parameters, and storing the single-waveband images of the salinized belt with better discrimination; step three: determining the range of the salinized zone by using a density segmentation method, and outputting vector elements; step four: the contrast ratio of the surface water body and the background is enhanced through wave band calculation; step five: determining the water body range by using a density segmentation method, and outputting vector elements; step six: calculating and enhancing the contrast ratio of the earth surface vegetation and the background through the wave band; and seventhly, determining the vegetation range by using a density segmentation method, and outputting vector elements.
Description
Technical Field
The invention belongs to the technical field of multispectral remote sensing analysis, and particularly relates to a method for identifying sandstone uranium ore structure excretion zone by using remote sensing image.
Background
And the drainage zone is identified and constructed, so that the method has direct significance for researching the basin hydrodynamic circulating system and further exploring the in-situ leachable sandstone uranium ore resources and underground water resources. Sandstone uranium ore resources are produced in a confined water basin, confined water moves upwards through a structural drainage zone and is supplied to an overlying aquifer and a diving aquifer to reach the ground surface. Since the ground is covered by soil or desert and the ground surface is strongly evaporated, the constructed excretory band is often somewhat concealed.
The traditional remote sensing structure is excreteed and is taken identification technology to think that the regional soil humidity of area is excreteed to the structure is great, discerns the abnormal area of humidity through the humidity index that calculates remote sensing data, and then observes the interior space spread characteristic that the area was excreteed to the structure of basin, analyzes into the hydrodynamic force environment of mining period research district, and the area is excreteed to the discernment structure.
Groundwater drainage can be divided into two main categories: one is runoff drainage, including drainage in the form of spring, drainage and the like, and is characterized in that salt is removed with water, and salt is also removed while water is drained. The other is evaporative excretion, which is characterized by water-carrying out salt retention. The combination of supply and drainage can be divided into two major types of groundwater circulation: sink-flow type and sink-evaporation type. The seepage radial flow type is the result of long-term circulation, so that rock and soil and underground water existing in the rock and soil develop towards the direction of dissolution, filtration and desalination; the infiltration evaporation type is long-term circulation, so that the rock soil and the underground water in the supply area are desalted and desalted, the underground water in the discharge area is salinized, and the soil is salinized.
The edge of the basin with low drought degree has weak evaporation effect, and the groundwater is discharged from the constructed excretion zone and is often closely related to the vegetation, so the edge of the vegetation zone generated by groundwater excretion is also an important mark of the constructed excretion zone. Therefore, through analysis of the groundwater excretion theory and combined with research on remote sensing images of the known sandstone-type deposit structure excretion zone, the remote sensing images of the structure excretion zone are considered to reflect saline zones caused by strong evaporation and transpiration besides soil humidity abnormal zones, and vegetation zones generated by groundwater excretion from the structure excretion zone.
Linear salinized zones, water body humidity zones and vegetation margin zones which are consistent with the main fracture structure trend in the basin are identified through a remote sensing method, and the linear salinized zones, the water body humidity zones and the vegetation margin zones are possible marks left on the ground surface by cutting the structure drainage zones through the stratum and flowing out of underground submergence. Wherein, the arid area in the basin mainly shows a salinized area due to the evaporation effect, and the wetter area mainly shows a water body humidity area and a vegetation margin area. Because the drainage structures are always consistent with the grids of the main structure in the trend and are linear, the interference of the rivers in the runoff area or the evaporation to the identification of the drainage structures caused by saline-alkali soil can be eliminated. The salinized zone is mainly represented as a high-brightness value area on the image, the high-soil-humidity zone is represented as a linearly distributed spring, marsh and river, and the information can be calculated through the ASTER image and is identified by image high-end segmentation.
The traditional structural excretion zone recognition considers that the structural excretion zone is only related to the moisture zone exposed on the surface, and only the remote sensing recognition and analysis of the moisture zone are concerned, so that the recognition zone extraction accuracy is low.
Therefore, a method for identifying the drainage zone of the sandstone uranium ore structure by using the ASTER remote sensing image is needed to be designed, so that the accuracy of identifying the drainage zone is improved.
Disclosure of Invention
The invention aims to provide a method for identifying an excretion zone of a sandstone uranium deposit structure by using a remote sensing image, aiming at overcoming the defects in the prior art, and solving the technical problem that the extraction accuracy of the identification zone is low because the excretion zone identification only focuses on remote sensing identification and analysis of a humidity zone in the prior art.
The technical scheme of the invention is as follows:
a method for identifying an excretion zone of a sandstone uranium deposit structure by using a remote sensing image comprises the following steps:
the method comprises the following steps: unifying the spatial resolution of the visible light and the near-infrared image of the ASTER remote sensing data, and performing band synthesis;
step two: calculating single-waveband images of the salinized belt for multiple times by adjusting floating parameters, and storing the single-waveband images of the salinized belt with better discrimination;
step three: determining the range of the salinized zone by using a density segmentation method, and outputting vector elements;
step four: the contrast ratio of the surface water body and the background is enhanced through wave band calculation;
step five: determining the water body range by using a density segmentation method, and outputting vector elements;
step six: calculating and enhancing the contrast ratio of the earth surface vegetation and the background through the wave band;
and seventhly, determining the vegetation range by using a density segmentation method, and outputting vector elements.
The first step further comprises:
step 1.1: the original ASTER remote sensing image is divided into a visible light band image and a short wave infrared band image which are respectively recorded as: ASTER _ VSR and ASTER _ SWIR, wherein the number of bands of the ASTER _ VSR and the ASTER _ SWIR is 3 and 6 respectively; converting the spatial resolution of the ASTER _ SWIR, converting the spatial resolution into 15 meters, and recording the short wave infrared image after the spatial resolution is converted into the ASTER _ SWIR _ 15;
step 1.2: and performing band synthesis on the visible light band image ASTER _ VSR and the short wave infrared image ASTER _ SWIR _15 after the spatial resolution is converted, wherein the image after the band synthesis is marked as ASTER _ STACK, and the number of the bands is 9.
The second step further comprises: the set band is calculated to be A _ yz for the enhanced saline band enhanced image, and the 2 nd band of the intermediate band synthesized image ASTER _ STACK in the step one is recorded as A _ S 2 The 5 th band of ASTER _ STACK is denoted as A _ S 5 (ii) a The 6 th band of ASTER _ STACK is denoted as A _ S 6 G is a floating parameter, g belongs to (0.25,1), and the g value is adjusted according to the enhancement effect of the salted streaks, then
A_yz＝(A_S 2 -(A_S 5 +A_S 6 )×g)/(A_S 2 +(A_S 5 +A_S 6 )×g)
And (4) according to the enhancement effect of the salinized belt, continuously adjusting the g value, calculating and storing a plurality of single-waveband images of the salinized belt.
The third step further comprises: adjusting and setting a threshold value of a pixel value of the saline band enhanced image A _ yz after wave band enhancement: calculating an A _ yz pixel value of the reinforced salinized band image after being reinforced by the wave band, and recording the A _ yz pixel value as A _ yz (i, j), wherein i is a longitude value and j is a dimension value; and setting the threshold as n, and obtaining a satisfactory extraction effect of the saline band when A _ yz (i, j) > n through experiments, and outputting a vector file of the range of the saline band, which is recorded as yzd.
The fourth step further comprises: setting the wave band to calculate the enhanced water body image as A _ st, and recording the 1 st wave band of the intermediate wave band synthetic image ASTER _ STACK as A _ S 1 The 4 th band of ASTER _ STACK is denoted as A _ S 4 The 6 th band of ASTER _ STACK is denoted as A _ S 6 Then, then
A_st＝(A_S 1 -(A_S 4 +A_S 6 )×0.5)/(A_S 1 +(A_S 4 +A_S 6 )×0.5)。
The fifth step further comprises: adjusting and setting a threshold value of a pixel value of the water body image A _ st after the wave band calculation enhancement, and recording the pixel value of the water body image A _ st after the wave band calculation enhancement as A _ st (i, j), wherein i is a longitude value and j is a dimension value; and setting the threshold value as m, obtaining a satisfactory water body extraction effect through experiments when A _ st (i, j) < m, and outputting a vector file of a water body range, which is recorded as st.shp.
The seventh step further comprises: setting the band to calculate the enhanced vegetation image as A _ zb, and recording the 2 nd band of the intermediate band synthetic image ASTER _ STACK as A _ S 2 The 8 th band of ASTER _ STACK is denoted as A _ S 8 Then, then
A_zb＝(A_S 2 -A_S 8 )/(A_S 2 +A_S 8 ))。
The seventh step further comprises: adjusting and setting a threshold value of a pixel value of the band-calculated enhanced vegetation image A _ zb, and recording the pixel value of the band-calculated enhanced vegetation image A _ zb as A _ zb (i, j), wherein i is a longitude value and j is a dimension value; and setting the threshold value as p, and through experiments, when A _ zb (i, j) > p, a satisfactory vegetation extraction effect can be obtained, and a vector file of a vegetation range is output and is recorded as zb.
The invention has the beneficial effects that:
according to the remote sensing characteristics possibly shown by sandstone uranium ore structure excretion zones on the earth surface, the salt water zone, the humidity zone and the vegetation zone are identified by using the Aster data, and visual analysis is combined, so that the structure excretion zones in the basin are identified, and the ore finding prediction zone is reduced. Compared with the traditional structure identification band extraction method, the method is more accurate. In addition, the invention discloses a linearly-spread salinized zone in a basin in northern China, which has evidence for identifying a structural excretion zone, and provides a method for extracting the salinized zone, a humidity zone and a vegetation zone by using an ASTER remote sensing image, and the method is used for identifying the structural excretion zone according to the salinized zone, the humidity zone and the vegetation zone, and the method is more accurate than the traditional structural identification zone.
The invention provides a salinized belt extraction method based on floating parameter wave band calculation, which adjusts the extraction effect according to dynamic parameters, so that the salinized belt extraction is more accurate.
Drawings
Fig. 1 is a flow chart of a method for identifying a sandstone uranium deposit structure drainage zone by using a remote sensing image according to the invention;
Detailed Description
The method for identifying the excretion zone of the sandstone uranium ore structure by using the remote sensing image according to the invention is described in detail below with reference to the accompanying drawings and embodiments.
A method for identifying a sandstone uranium deposit structure drainage zone by using a remote sensing image comprises the following steps:
the method comprises the following steps: unifying the spatial resolution of the visible light and the near-infrared image of the ASTER remote sensing data, and performing band synthesis;
step two: calculating the single-waveband images of the salinized belt for multiple times by adjusting the floating parameters, and storing the single-waveband images of the salinized belt with better discrimination;
step three: determining the range of the salinized zone by using a density segmentation method, and outputting vector elements;
step four: the contrast ratio of the surface water body and the background is enhanced through wave band calculation;
step five: determining the water body range by using a density segmentation method, and outputting vector elements;
step six: calculating and enhancing the contrast ratio of the earth surface vegetation and the background through the wave band;
and seventhly, determining the vegetation range by using a density segmentation method, and outputting vector elements.
The first step further comprises the following steps:
step 1.1: the original ASTER remote sensing image is divided into a visible light band image and a short wave infrared band image which are respectively recorded as: ASTER _ VSR and ASTER _ SWIR, wherein the number of bands of the ASTER _ VSR and the ASTER _ SWIR is 3 and 6 respectively; converting the spatial resolution of the ASTER _ SWIR, converting the spatial resolution into 15 meters, and recording the short wave infrared image after the spatial resolution is converted into the ASTER _ SWIR _ 15;
step 1.2: and (3) performing band synthesis on the visible light band image ASTER _ VSR and the short wave infrared image ASTER _ SWIR _15 after the spatial resolution is converted, wherein the image after the band synthesis is marked as ASTER _ STACK, and the number of the bands is 9.
The second step further comprises: set band computation enhancementThe saline band enhanced image is then A _ yz, and the 2 nd band of the intermediate band synthesized image ASTER _ STACK in step one is denoted as A _ S 2 The 5 th band of ASTER _ STACK is denoted as A _ S 5 (ii) a The 6 th band of ASTER _ STACK is marked as A _ S 6 G is a floating parameter, g belongs to (0.25,1), and the g value is adjusted according to the enhancement effect of the salted streaks, then
A_yz＝(A_S 2 -(A_S 5 +A_S 6 )×g)/(A_S 2 +(A_S 5 +A_S 6 )×g)
And (4) according to the enhancement effect of the salinized belt, continuously adjusting the g value, calculating and storing a plurality of single-waveband images of the salinized belt.
The third step further comprises: adjusting and setting a threshold value of a pixel value of the saline band enhanced image A _ yz after wave band enhancement: calculating an A _ yz pixel value of the reinforced salinized band image after being reinforced by the wave band, and recording the A _ yz pixel value as A _ yz (i, j), wherein i is a longitude value and j is a dimension value; and setting the threshold value as n, and obtaining a satisfactory extraction effect of the saline zone when A _ yz (i, j) > n through experiments, and outputting a vector file of the range of the saline zone, wherein the vector file is recorded as yzd.
The fourth step further comprises: setting the wave band to calculate the enhanced water body image as A _ st, and recording the 1 st wave band of the intermediate wave band synthetic image ASTER _ STACK as A _ S 1 The 4 th band of ASTER _ STACK is denoted as A _ S 4 The 6 th band of ASTER _ STACK is denoted as A _ S 6 Then, then
A_st＝(A_S 1 -(A_S 4 +A_S 6 )×0.5)/(A_S 1 +(A_S 4 +A_S 6 )×0.5)。
The fifth step further comprises: adjusting and setting a threshold value of a pixel value of the water body image A _ st after the wave band calculation enhancement, and recording the pixel value of the water body image A _ st after the wave band calculation enhancement as A _ st (i, j), wherein i is a longitude value and j is a dimension value; and setting the threshold value as m, obtaining a satisfactory water body extraction effect through experiments when A _ st (i, j) < m, and outputting a vector file of a water body range, which is recorded as st.shp.
The seventh step further comprises: setting the band to calculate the enhanced vegetation image as A _ zb, and recording the 2 nd band of the intermediate band synthetic image ASTER _ STACK as A _ S 2 The 8 th band of ASTER _ STACK is denoted as A _ S 8 Then, then
A_zb＝(A_S 2 -A_S 8 )/(A_S 2 +A_S 8 ))。
The seventh step further comprises: adjusting and setting a threshold value of a pixel value of the vegetation image A _ zb after the band calculation enhancement, and recording the pixel value of the vegetation image A _ zb after the band calculation enhancement as A _ zb (i, j), wherein i is a longitude value and j is a dimension value; and setting the threshold value as p, and obtaining a satisfactory vegetation extraction effect through experiments when A _ zb (i, j) > p, and outputting a vector file of a vegetation range, which is recorded as zb.
Claims (1)
1. A method for identifying an excretion zone of a sandstone uranium deposit structure by using a remote sensing image is characterized by comprising the following steps:
the method comprises the following steps: unifying the spatial resolution of the visible light and the near-infrared image of the ASTER remote sensing data, and performing band synthesis;
step 1.1: the original ASTER remote sensing image is divided into a visible light band image and a short wave infrared band image which are respectively recorded as: ASTER _ VSR and ASTER _ SWIR, wherein the number of bands of the ASTER _ VSR and the ASTER _ SWIR is 3 and 6 respectively; converting the spatial resolution of the ASTER _ SWIR, converting the spatial resolution into 15 meters, and recording the short wave infrared image after the spatial resolution is converted into the ASTER _ SWIR _ 15;
step 1.2: carrying out wave band synthesis on a visible light wave band image ASTER _ VSR and a short wave infrared image ASTER _ SWIR _15 after the spatial resolution is converted, wherein an image after the wave band synthesis is marked as ASTER _ STACK, and the number of the wave bands is 9;
step two: calculating the single-waveband images of the salinized belt for multiple times by adjusting the floating parameters, and storing the single-waveband images of the salinized belt with better discrimination; the set band is calculated to be A _ yz for the enhanced saline band enhanced image, and the 2 nd band of the intermediate band synthesized image ASTER _ STACK in the step one is recorded as A _ S 2 The 5 th band of ASTER _ STACK is denoted as A _ S 5 (ii) a The 6 th band of ASTER _ STACK is denoted as A _ S 6 G is a floating parameter, g belongs to (0.25,1), and the g value is adjusted according to the enhancement effect of the salted streaks, then
A_yz＝(A_S 2 -(A_S 5 +A_S 6 )×g)/(A_S 2 +(A_S 5 +A_S 6 )×g)
According to the enhancement effect of the salinized belt, continuously adjusting the g value, calculating and storing a plurality of single-waveband images of the salinized belt;
step three: determining the range of the salinized zone by using a density segmentation method, and outputting vector elements; adjusting and setting a threshold value of a pixel value of the saline band enhanced image A _ yz after wave band enhancement: calculating an enhanced A _ yz pixel value of the saline zone enhanced image after the wave band is enhanced, and recording the pixel value as A _ yz (i, j), wherein i is a longitude value, and j is a dimension value; setting a threshold value as n, obtaining a satisfactory extraction effect of the saline band when A _ yz (i, j) > n through experiments, and outputting a vector file of the range of the saline band, which is recorded as yzd.shp;
step four: the contrast ratio of the surface water body and the background is enhanced through wave band calculation; setting the wave band to calculate the enhanced water body image as A _ st, and recording the 1 st wave band of the intermediate wave band synthetic image ASTER _ STACK as A _ S 1 The 4 th band of ASTER _ STACK is denoted as A _ S 4 The 6 th band of ASTER _ STACK is denoted as A _ S 6 Then, then
A_st＝(A_S 1 -(A_S 4 +A_S 6 )×0.5)/(A_S 1 +(A_S 4 +A_S 6 )×0.5)；
Step five: determining the water body range by using a density segmentation method, and outputting vector elements; adjusting and setting a threshold value of a pixel value of the water body image A _ st after the wave band calculation enhancement, and recording the pixel value of the water body image A _ st after the wave band calculation enhancement as A _ st (i, j), wherein i is a longitude value and j is a dimension value; setting a threshold value as m, obtaining a satisfactory water body extraction effect when A _ st (i, j) < m through experiments, and outputting a vector file of a water body range to be recorded as st.shp;
step six: calculating and enhancing the contrast ratio of the earth surface vegetation and the background through the wave band; setting the band to calculate the enhanced vegetation image as A _ zb, and recording the 2 nd band of the intermediate band synthetic image ASTER _ STACK as A _ S 2 The 8 th band of ASTER _ STACK is denoted as A _ S 8 Then, then
A_zb＝(A_S 2 -A_S 8 )/(A_S 2 +A_S 8 ))；
Determining a vegetation range by using a density segmentation method, and outputting vector elements; adjusting and setting a threshold value of a pixel value of the vegetation image A _ zb after the band calculation enhancement, and recording the pixel value of the vegetation image A _ zb after the band calculation enhancement as A _ zb (i, j), wherein i is a longitude value and j is a dimension value; and setting the threshold value as p, and obtaining a satisfactory vegetation extraction effect through experiments when A _ zb (i, j) > p, and outputting a vector file of a vegetation range, which is recorded as zb.
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