CN114758218A - High-turbidity underwater topography inversion method suitable for hyperspectral satellite images - Google Patents
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Abstract
A high-turbidity underwater topography inversion method suitable for hyperspectral images comprises the following steps: acquiring a hyperspectral satellite remote sensing image to be inverted, and synchronously acquiring the actually measured water depth data and the actually measured surface water sand content data of a research water area; counting the water depth of the sampling point and the corresponding spectral characteristic curve to obtain the wave trough wave band reflectivity which is less sensitive to the sand content reflection spectrum; establishing a correlation function between the water depth and the reflectivity according to the wave trough wave band reflectivity, changing the slope of the function by taking the surface sand content as a main control factor, and constructing an inversion model of the water depth and the surface sand content; the inversion model is utilized, and the hyperspectral satellite remote sensing images are combined, so that the quantitative inversion of the high-turbidity underwater topography is realized, and the distribution condition of the underwater topography is obtained. Experiments verify that the method can improve the accuracy of high-turbidity underwater topography inversion by visible light satellite remote sensing, so that the hyperspectral satellite image can be applied to the field of high-turbidity underwater topography monitoring.
Description
Technical Field
The invention belongs to the field of remote sensing technology application and underwater topography mapping, and relates to a method for quantitatively inverting a high-turbidity underwater topography by using a high-resolution optical remote sensing image.
Background
The water depth measurement is the basis for scientific research, and the water depth change has extremely important significance for coastal zone development, shipping traffic, ocean engineering, national defense safety and the like.
The traditional sea water depth measuring methods comprise a measuring rod method, a plumb line method, a multi-beam sounding method and the like, and the methods are limited by resource conditions such as ships and manpower and natural factors such as sea conditions, so that the efficiency is low, the cost is high, the measuring accuracy is influenced by factors such as sea condition weather, and the like, and the large-range long-time synchronization measurement is difficult to carry out.
Under the background that the satellite-borne satellite technology in China is becoming mature, the field spectral measurement mode is gradually applied to the field of water depth measurement. At present, on-site spectral measurement modes mainly comprise overwater spectral measurement and section spectral measurement, and because the transparency of a high-turbidity water area is not high, and overhigh radiation attenuation can be generated during underwater spectral measurement, the overwater spectral measurement is generally adopted in the high-turbidity water area. Although the above-water spectral measurement can realize the monitoring of the underwater topography distribution of a large-area water area, the above-water spectral measurement is limited by the influence of factors such as spectral resolution, water optical characteristics and the like, the underwater topography inversion accuracy of high-turbidity water bodies is generally low, and the above-water spectral measurement is mostly applied to the underwater topography measurement of water areas with low turbidity and high transparency.
With the development of remote sensing technology, the hyperspectral remote sensing greatly improves the capability of classifying and identifying ground objects due to the advantages of high resolution, few wave bands, small data magnitude, low signal-to-noise ratio and the like. However, the algorithm of the hyperspectral remote sensing terrain inversion is greatly influenced by the region, and the model has poor transportability and low precision. Therefore, a universal and high-precision quantitative inversion method for high-turbidity underwater topography is needed.
Disclosure of Invention
The invention aims to provide a high-turbidity underwater topography inversion method suitable for a hyperspectral satellite image, which improves the inversion precision of visible light satellite remote sensing on the high-turbidity underwater topography and enables the hyperspectral satellite image to be applied to the field of high-turbidity underwater topography monitoring.
The invention can be realized by the following technical scheme:
a high-turbidity underwater topography inversion method suitable for a hyperspectral satellite image comprises the following steps:
the method comprises the following steps: acquiring a hyperspectral satellite remote sensing image to be inverted, and synchronously acquiring actually measured water depth data and actually measured surface water sand content data of a research water area;
step two: counting the depth of water of the sampling point and a corresponding spectral characteristic curve to obtain the wave trough wave band reflectivity insensitive to the sand content reflection spectrum;
step three: according to the wave trough wave band reflectivity in the second step, a correlation function between the water depth and the reflectivity is established, the surface sand content is used as a control factor to change the slope of the function, and an inversion model of the water depth and the surface sand content is established;
step four: by utilizing the inversion model and combining with a hyperspectral satellite remote sensing image, quantitative inversion of high-turbidity underwater topography is realized, and the distribution condition of the underwater topography is obtained.
Optionally, step two includes: carrying out preprocessing operations such as geometric correction, radiometric calibration, atmospheric correction and the like according to the hyperspectral remote sensing image to obtain hyperspectral satellite remote sensing image reflectivity data of a surface sand content sampling point;
according to the actually measured surface water sand content data of the research water area, drawing a satellite-ground synchronous spectrum characteristic curve related to the wavelength and the reflectivity under different sand contents;
acquiring the reflectivity of the wave bands where the main peak and the secondary peak of the curve are located in the visible light wavelength range, namely the reflectivity of the sand content sensitive wave band, according to the change characteristics of the satellite-ground synchronous spectrum characteristic curve; and acquiring the reflectivity of a wave band where the curve wave trough is located in the visible light wavelength range, namely the reflectivity of a sand content insensitive wave band.
Optionally, the surface sand content in step three is obtained by constructing an algorithm between the surface sand content SSC and the reflectivity of the sensitive band through an exponential model.
Drawing a scatter diagram according to the water depth data of the research water area and the corresponding water body spectral characteristics in the third step, and drawing a scatter diagram according to a formula
y＝a1e-42r+a3With a1As a function variable, a2、a3Establishing an inversion model between the water depth and the sand content of the surface layer of the water body as a constant; wherein y is the depth of the water area to be studied; r is the water depth inversion waveband reflectivity; a is1Carrying out linear fitting by using a least square method with the actually measured surface water sand content to obtain a formula a1＝b1SSC+b2Thereby establishing the relationship between the surface water body inversion sand content and the water depth, wherein b1、b2Is a constant; SSC is the inversion sand content of the surface water body.
Wherein, the constant a2、a3The numerical value of (A) is obtained by fitting a power exponential function and actually measured data, and the correlation coefficient is high enough; the higher the correlation coefficient, the higher the accuracy. For a constant b1、b2The same is true.
Optionally, in order to eliminate the influence of sand content on the water depth inversion model as much as possible, a single measurement section is selected as a research object.
Optionally, comprehensive analysis is performed on sections with different sand contents.
Optionally, the number of sections is not less than 3.
According to the hyperspectral satellite remote sensing image of the research water area random date, the water depth data can be obtained through the steps.
Because the sand content of the high-turbidity area is very large, the topography of the water area to be measured only has the modes of field multi-beam measurement and the like, but the method is time-consuming and labor-consuming and can only be used for measuring the area. According to the method, aiming at the underwater topography measurement requirement of a high-turbidity water area, by means of the characteristics of high penetrability, high resolution and the like of a hyperspectral satellite, inversion modeling is carried out based on a hyperspectral satellite image, the surface sand content is taken as a main influence factor and substituted into an underwater topography inversion model, and the high-turbidity underwater topography can be obtained, so that the defect of high-turbidity underwater topography in inversion accuracy by hyperspectral satellite remote sensing is overcome.
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FIG. 1 is a flow chart of the method of the present invention.
Fig. 2 is a cross-sectional view of a sample taken from a long estuary in 3/27/2019 (left: high-resolution five-size satellite image; right: schematic view of observation points) according to an embodiment of the invention.
Fig. 3 is a satellite image spectral characteristic curve of a satellite-ground synchronous observation point.
FIG. 4 is a fitting of the relation between the depth of the sampled cross section and the reflectivity.
FIG. 5 is a1Fitting to SSC relationships.
FIG. 6 shows the sand content inversion model calibration results.
FIG. 7 is a comparison of the underwater topography inversion results of the 27-day long estuary in 3 months and 3 months in 2019 in the embodiment shown in FIG. 2 (section 1, section 2 and section 3 are compared).
Detailed Description
The invention provides a high-turbidity underwater topography inversion method suitable for a hyperspectral satellite image, which improves the inversion precision of visible light satellite remote sensing on high-turbidity underwater topography by utilizing the characteristics of hyperspectral resolution and wide spectrum band of the hyperspectral satellite image, so that the hyperspectral satellite image can be applied to the field of high-turbidity underwater topography monitoring.
The spectral characteristic curve is recorded in the remote sensing image, and the spectral characteristic curve of the target point can be extracted through post-processing (methods such as ENVI and MATLAB). According to the invention, a plurality of sampling points in different areas are selected, and the sand contents of different sampling points have differences, so that a sand content gradient is formed, and preparation is made for selecting a wave band insensitive to the sand content.
The water body silt reflection spectrum has twoA reflection peak of less than 0.16kg/m3The water body can form a first reflection peak at 560 nm-590 nm, which is more than 0.16kg/m3The water body forms a second reflection peak at 690 nm-720 nm, the two wave bands are mostly adopted as sensitive wave bands of sand content in the sand content inversion process, and a statistical model method is adopted for fitting in a single wave band or a double wave band.
The invention is further described with reference to the following figures and examples.
According to the invention, the experiment is carried out by the high-turbidity underwater topography inversion method suitable for the hyperspectral satellite image, and the specific implementation mode comprises the following steps:
the method comprises the steps of obtaining a hyperspectral satellite remote sensing image of a high turbidity research water area, carrying out preprocessing operations such as geometric correction, radiometric calibration and atmospheric correction on the image, and analyzing to obtain remote sensing reflectivity data of the hyperspectral satellite remote sensing image. Synchronously acquiring the water depth data of the research water area covered by the satellite image and the sand content data of the surface layer of the water body.
And extracting reflectivity data with different sand contents through remote sensing image post-processing modes such as ENVI, MATLAB and the like, and drawing a satellite-ground synchronous spectral characteristic curve.
Taking a high-resolution five-size hyperspectral image of a estuary watershed of 27 Yangtze river in 3 months in 2019 as an example, in order to eliminate the influence of sand content on a water depth inversion model as much as possible, selecting a single measurement section as a research object, and selecting the following 3 sections from the water depth measurement sections of the image in 27 months in 3 months in 2019 according to an inversion result of the sand content model for analysis, wherein the water depth of the upper section of a north groove has a large gradient in the transverse direction, and 2 sections are arranged, which are respectively shown as section 1 and section 2 in fig. 2; the south trough is arranged with 1 section, such as section 3 in fig. 2. The sand content amplitude of the measured section is 0.040kg/m3～2.630kg/m3And belongs to a high-turbidity water area.
It should be noted that, in general, the selection of the cross section is related to the size of the sand content. The water depth inversion of the model firstly needs to find out the wave band insensitive to the sand content, so that only a plurality of sections with different sand contents need to be provided in the process of selecting the sections, for example, 3 or more.
And (3) obtaining spectral characteristic curves of water satellite images with different sand contents according to satellite-ground synchronous monitoring (as shown in figure 3). Under the strong absorption action of water, 690nm-750nm wave band shows a rapid descending trend and has a reflection valley, so 720nm wave band in the reflection valley range is selected, namely the sand content insensitive wave band; meanwhile, the reflectivity of a sensitive waveband of a sand content reflection spectrum is required to be adopted during inversion of the sand content of the surface layer, two peak values exist in a water spectrum characteristic curve in a visible light spectrum range, a main peak is located near 587nm, and a secondary peak is located near 801 nm.
According to the scattered point distribution diagram of the water depth and the remote sensing reflectivity of the cross section of the graph shown in fig. 4, 3 curves can be drawn according to the correlation between the water depth and the reflectivity, function fitting is respectively carried out on the 3 curves, and according to the form of the correlation curves, the fitting function form adopts the negative exponential form of e. The formula is as follows:
y＝a1e-a2r+a3 [0029]
wherein y is the water depth; r is the reflectance of 720nm band. Since all 3 sections were in shallow water, 3 curves were grouped together, keeping a in the fitting function2And a3Unchanged, here a2Take 300, a3Take-0.8. By changing a1The slope of the function is changed to fit the correlation of the 3 curves.
A through existing 3 curves1And linear fitting is carried out on the relationship between the SSC (surface sand content) value and the SSC value by using a least square method. The result of the fitted curve is shown in fig. 5, so that the water depth inversion model can be corrected by taking the sand content of the surface layer as a main influence factor. Fitting result a1The relationship to SSC is shown in the following formula:
a1＝576690 SSC-40740 [0032]
in the formula, SSC is the surface sand content obtained by inversion of a single-waveband model, and the inversion formula is that a logarithmic model is established, and the measured data is fitted with a calibration curve of waveband combination. The fitting results are shown in fig. 6, and the inversion formula of the surface sand content is as follows:
SSC＝0.020e70r’ [0035]
wherein r' is the reflectivity of the secondary peak 801nm wave band in the previous step.
Substituting a formula [0035] into a formula [0032], and substituting the formula [0032] into a formula [0029] to obtain the water depth inversion model taking the surface sand content as a main influence factor. The formula is as follows:
By using the underwater topography inversion model established above, fig. 7 shows the comparison result between the inversion water depth of the section and the measured data. Because the sampling section is influenced by peripheral engineering and the water body disturbance is enhanced by ships to and from, the sand content is increased, and therefore errors (as shown in a black box in fig. 6) appear in partial areas, and the fitting result is good on the whole. And (5) obtaining the high-turbidity underwater topography within 8m of water depth through inspection.
The foregoing description and description of the embodiments are provided to facilitate understanding and application of the invention by those skilled in the art. It will be readily apparent to those skilled in the art that various modifications can be made to these teachings and the generic principles described herein may be applied to other embodiments without the use of the inventive faculty. Therefore, the present invention is not limited to the above description and the description of the embodiments, and those skilled in the art should make improvements and modifications within the scope of the present invention based on the disclosure of the present invention.
Claims (7)
1. A high-turbidity underwater topography inversion method suitable for a hyperspectral satellite image is characterized by comprising the following steps:
the method comprises the following steps: acquiring a hyperspectral satellite remote sensing image to be inverted, and synchronously acquiring actually measured water depth data and actually measured surface water sand content data of a research water area;
step two: counting the water depth of the sampling point and a corresponding spectrum characteristic curve to obtain the wave trough wave band reflectivity insensitive to the sand content reflection spectrum;
step three: according to the wave trough wave band reflectivity in the second step, a correlation function between the water depth and the reflectivity is established, the surface sand content is used as a control factor to change the slope of the function, and an inversion model of the water depth and the surface sand content is established;
step four: by utilizing the inversion model and combining with a hyperspectral satellite remote sensing image, quantitative inversion of high-turbidity underwater topography is realized, and the distribution condition of the underwater topography is obtained.
2. The method for inverting a high turbidity underwater topography suitable for hyperspectral satellite images according to claim 1,
the second step comprises: carrying out preprocessing operations such as geometric correction, radiometric calibration, atmospheric correction and the like according to the hyperspectral remote sensing image to obtain hyperspectral satellite remote sensing image reflectivity data of a surface sand content sampling point;
according to the actually measured surface water sand content data of the research water area, drawing a satellite-ground synchronous spectrum characteristic curve related to the wavelength and the reflectivity under different sand contents;
acquiring the reflectivity of the wave bands where the main peak and the secondary peak of the curve are located in the visible light wavelength range, namely the reflectivity of the sand content sensitive wave band, according to the change characteristics of the satellite-ground synchronous spectrum characteristic curve; and acquiring the reflectivity of a wave band where the curve wave trough is located in the visible light wavelength range, namely the reflectivity of a sand content insensitive wave band.
3. The high-turbidity underwater topography inversion method suitable for the hyperspectral satellite image as claimed in claim 1, wherein: the surface sand content in step three is obtained by constructing an algorithm between the surface sand content SSC and the reflectivity of the sensitive waveband through an exponential model.
4. The high-turbidity underwater topography inversion method suitable for the hyperspectral satellite image as claimed in claim 1, wherein: drawing a scatter diagram according to the water depth data of the research water area and the corresponding water body spectral characteristics in the third step, and drawing a scatter diagram according to a formula
With a1As a function variable, a2、a3Establishing an inversion model between the water depth and the sand content of the surface layer of the water body as a constant; wherein y is the depth of the water area to be studied; r is the water depth inversion waveband reflectivity; a is a1Carrying out linear fitting by using a least square method with the actually measured surface water sand content to obtain a formula a1＝b1SSC+b2Thereby establishing the relationship between the surface water body inversion sand content and the water depth, wherein b1、b2Is a constant; SSC is the inversion sand content of the surface water body.
5. The high-turbidity underwater topography inversion method suitable for the hyperspectral satellite image as claimed in claim 1, wherein: in order to eliminate the influence of sand content on the water depth inversion model as much as possible, a single measurement section is selected as a research object.
6. The high-turbidity underwater topography inversion method suitable for the hyperspectral satellite image as claimed in claim 5, wherein: and selecting sections with different sand contents for comprehensive analysis.
7. The high turbidity underwater topography inversion method suitable for the hyperspectral satellite image as claimed in claim 6, wherein: the number of the sections is not less than 3.
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Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115524294A (en) * | 2022-09-19 | 2022-12-27 | 南京中科深瞳科技研究院有限公司 | Water leaving type real-time intelligent remote sensing water quality monitoring method |
| CN117372891A (en) * | 2023-12-07 | 2024-01-09 | 中铁水利水电规划设计集团有限公司 | Method for carrying out water depth inversion by using satellite remote sensing image |
| CN117434034A (en) * | 2023-10-24 | 2024-01-23 | 上海普适导航科技股份有限公司 | Quick inversion method for water quality multisource remote sensing data based on spectrum library |
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Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115524294A (en) * | 2022-09-19 | 2022-12-27 | 南京中科深瞳科技研究院有限公司 | Water leaving type real-time intelligent remote sensing water quality monitoring method |
| CN117434034A (en) * | 2023-10-24 | 2024-01-23 | 上海普适导航科技股份有限公司 | Quick inversion method for water quality multisource remote sensing data based on spectrum library |
| CN117372891A (en) * | 2023-12-07 | 2024-01-09 | 中铁水利水电规划设计集团有限公司 | Method for carrying out water depth inversion by using satellite remote sensing image |
| CN117372891B (en) * | 2023-12-07 | 2024-02-13 | 中铁水利水电规划设计集团有限公司 | Method for carrying out water depth inversion by using satellite remote sensing image |
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