CN109059796A - The multispectral satellite remote sensing inversion method of shallow water depth without depth of water control point region - Google Patents
The multispectral satellite remote sensing inversion method of shallow water depth without depth of water control point region Download PDFInfo
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Abstract
The multispectral satellite remote sensing inversion method of shallow water depth without depth of water control point region, belongs to satellite ocean remote sensing applied technical field.The linear shallow water depth inverse model of two waveband based on derivation, by the pixel point of different depth difference seabed type to data set, solve optimal wave band rotational units vector, and the typical sediment types pixel based on flood boundaries line position uses, bottom parameters in appraising model, it is calculated simultaneously by the pel data of identical sediment types different depth and obtains bluish-green wave band diffusion attenuation coefficient ratio, and the profundal zone data based on closest neritic area, it is analyzed using half and diffusion attenuation coefficient algorithm calculates green wave band attenuation coefficient.It is calculated by the above parameter, to realize the shallow water depth remote-sensing inversion without depth of water control point region.
Description
Technical field
The invention belongs to satellite ocean remote sensing applied technical fields, more particularly, to the shallow sea water in no depth of water control point region
Deep multispectral satellite remote sensing inversion method.
Background technique
Shallow water depth navigates by water the important parameter of guarantee and the offshore ecosystem and optical research as warship safety, is always
The important content of marine charting and optical remote sensing.Conventional shallow water depth measurement be mainly boat-carrying it is more/simple beam acoustic measurement, closely
The airborne laser sounding technology of development in several years is also gradually used widely.But for some danger or there is dispute sea area, this
A little technological means are time-consuming and laborious, or even cannot achieve.Although investigation depth and precision cannot still substitute conventional Ocean Surveying,
Satellite remote sensing technology is the method for obtaining these region shallow water depth data unique feasibles.Therefore, it is distant to carry out shallow water depth satellite
Sense inversion technique research is of great significance and application prospect.
The inversion method of shallow water depth satellite remote sensing at present can totally be summarized as two major classes: the EO-1 hyperion based on semi-analytic algorithm
Remote sensing and multispectral remote sensing based on empirical model, from the point of view of document report, the current Depth extraction precision of the two is substantially suitable.
Although there is physical basis to define and without surveying the advantages such as depth of water point for high-spectrum remote-sensing, there are spaces for current high spectrum image
Resolution ratio is lower, the few deficiency of availability data.In contrast, multispectral image spatial resolution can reach 2m, and can
It is more with number of satellite, it is more suitable for carrying out shallow water depth remote sensing.But multispectral shallow water depth inverse model needs a certain number of
The depth of water point data of actual measurement or reliable sea chart carries out model coefficient resolving as input.Due to water body property and seabed type
Variation, multispectral Depth extraction model have apparent regional.For some remote, dangerous or controversial, actual measurement water
Deep point is few, and Depth extraction result is unreliable, and sometimes even without available depth of water control point, it is anti-can not to carry out shallow water depth remote sensing
It drills.Therefore, the multispectral satellite remote sensing inversion method of shallow water depth for developing a kind of no depth of water control point region, which just seems, very must
It wants.
Summary of the invention
It is an object of the invention to need problem existing for depth of water control point for multispectral shallow water depth remote-sensing inversion, lead to
Analytical Expression two waveband linear model is crossed, in conjunction with multispectral image sampled point, parameter needed for calculating shallow water depth model is provided
The multispectral satellite remote sensing inversion method of shallow water depth without depth of water control point region.
The present invention the following steps are included:
1) according to the vector multiplications formal grammar shallow water depth inversion formula (1) of two waveband linear model:
Xi=ln [rw(λi)-rdp(λi)] i=1,2
In formula, z is the shallow water depth to inverting；α1,α2For bluish-green wave band weight feature vector；g1,g2For bluish-green band of light
It composes water body round trip and diffuses attenuation coefficient；rw(λi) it is Remote Sensing Reflectance under the water surface of the i-th wave band (bluish-green)；rb(λi) it is the i-th wave
The seabed Remote Sensing Reflectance of section (bluish-green)；rdp(λi) it is Remote Sensing Reflectance under the water surface of the i-th wave band (bluish-green) optics profundal zone；I.e.
It can get the RS Fathoming inversion result without depth of water point region；
2) choose image on different depth difference substrate adjacent picture elements pair, by the Xi data set to adjacent picture elements pair into
Row, which minimizes, to be solved, and one group of optimal wave band rotational units vector [α is obtained1,α2]:
In formula, i indicates certain adjacent picture elements pair, Δ sziIt is i-th of pixel to the difference being worth after rotation, A, B are indicated should
Pixel point is to corresponding different sediment types, and n is pixel point to quantity, and f is to minimize function；
3) a variety of typical sediment pixel collection are selected at image flowage line, in conjunction with the wave band rotational units that acquisition is optimal
Vector [α1,α2], by average statistics, obtain bottom parameters α1ln rb1+α2ln rb2Value；
4) identical sediment type on image, X in different depth position are utilized1~X2Data set calculates bluish-green band dual
Journey diffuses attenuation coefficient ratio g1/g2；
5) it assuming that under the premise of water body uniform properties, analyzes and diffusion attenuation coefficient algorithm, calculates closest using half
Green wave band in neritic province domain optics profundal zone diffuses attenuation coefficient g2；
6) above-mentioned steps are calculated to the coefficient obtained, including [α1、α2], bottom parameters α1ln rb1+α2ln rb2、g1/g2With
g2Shallow water depth inversion formula is substituted into, and is applied to entire image, realizes that the shallow water depth without depth of water control point region is multispectral
Satellite remote sensing inverting.
Compared with prior art, the present invention has the advantage that
1) the present invention is based on the linear shallow water depth inverse models of the two waveband of derivation, pass through different depth difference seabed type
Pixel point optimal wave band rotational units vector is solved to data set, and the typical substrate class based on flood boundaries line position
Type pixel uses, the bottom parameters in appraising model, while being obtained by the calculating of the pel data of identical sediment types different depth
It obtains bluish-green wave band and diffuses attenuation coefficient ratio, and the profundal zone data based on closest neritic area, utilize half to analyze and diffuse
Attenuation coefficient algorithm calculates green wave band attenuation coefficient.It is calculated by the above parameter, to realize without the shallow of depth of water control point region
Seawater depth remote-sensing inversion.
2) compared with inversion method that is existing, needing depth of water control point to participate in, the present invention can be to a certain extent
Eliminating sediment type difference influences Depth extraction, while not needing depth of water control point and no depth of water control point area can be realized
The shallow water depth remote-sensing inversion in domain.
Detailed description of the invention
Fig. 1 is minute Butut such as image picture elements sampled point and depth of water precision test point in the embodiment of the present invention；
Fig. 2 is blue, green wave band sandy bottom sampled point X in the embodiment of the present invention1~X2Scatter plot and its linear fit；
Fig. 3 is RS Fathoming inversion result figure in the embodiment of the present invention；
Fig. 4 is new method inverting depth of water precision test result in the embodiment of the present invention.
Specific embodiment
The present invention obtains Depth extraction institute by image itself for the multispectral satellite remote sensing of the depth of water in no depth of water point region
The relevant parameter needed, to realize the shallow water depth remote-sensing inversion without depth of water point region.
With reference to the accompanying drawings and examples, the specific implementation process of the present invention is described in detail technical solution:
Step 1: obtaining research area's high-resolution multi-spectral satellite image, carries out atmospheric correction and obtains albedo image, and
Reflectivity data is converted into underwater Remote Sensing Reflectance data rw.It need to carry out first when satellite image position error is lower than 6m
Geometric correction processing；When image is interfered there are apparent solar flare, also need to carry out solar flare correction process；
Step 2: the profundal zone pixel (Fig. 1) of closest neritic province domain is chosen in interpretation by visual observation, counts its blue, green wave
Section rdpValue, and according to formula Xi=ln [rw(λi)-rdp(λi)], calculate the X for obtaining blue, green wave bandiImage data；
Step 3: selection-difference sediment types adjacent picture elements point pair that in water front different distance (represents different depth)
Data set (Fig. 1), and calculated using optimal algorithm (formula 2), obtain optimal wave band rotational units vector [α1,α2]；
Step 4: referring to near-infrared image, takes the pixel collection (figure of typical sediment types in the flood boundaries line selection of image
1) X, is calculatediData, and combine the optimal wave band rotational units vector [α obtained1,α2], calculate bottom parameters α1ln rb1+α2ln
rb2；
Step 5: the X of sandy bottom, different depth position is chosen on the image1~X2Data set (Fig. 1) utilizes minimum two
Multiplication establishes the linear regression formula (such as Fig. 2) of the two, and the water body round trip for obtaining blue, green wave band diffuses attenuation coefficient ratio g1/
g2；
Step 6: attenuation coefficient algorithm is analyzed and is diffused according to half, calculates the profundal zone pixel of closest neritic province domain
Green wave band diffuses downwards attenuation coefficient summation g upwards2；
Step 7: [the α without depth of water point region obtained will be calculated1、α2]、α1ln rb1+α2ln rb2、g1/g2And g2Deng ginseng
Number substitutes into formula 1, and is applied to entire image, obtains the RS Fathoming inversion result (such as Fig. 3) without depth of water point region；
Step 8: it randomly selects actual measurement depth of water point data collection (Fig. 1 is shown in distribution) and precision is carried out to RS Fathoming inversion result
Verifying, draws the inverting depth of water and the actual measurement depth of water compares scatter plot, and calculates root-mean-square error RMSE (such as Fig. 4).In the present embodiment,
The RMSE error of Depth extraction is 1.18m.
Claims (1)
1. the multispectral satellite remote sensing inversion method of shallow water depth without depth of water control point region, it is characterised in that the method packet
It includes:
1) according to the vector multiplications formal grammar shallow water depth inversion formula of two waveband linear model:
Xi=ln [rw(λi)-rdp(λi)] i=1,2
In formula, z is the shallow water depth to inverting；α1,α2For bluish-green wave band weight feature vector；g1,g2For bluish-green band spectrum water
Body round trip diffuses attenuation coefficient；rw(λi) it is Remote Sensing Reflectance under the water surface of the i-th wave band；rb(λi) be the i-th wave band seabed it is distant
Feel reflectivity；rdp(λi) it is Remote Sensing Reflectance under the i-th wave band optics profundal zone water surface；This be can be obtained without depth of water point region
RS Fathoming inversion result；
2) adjacent picture elements pair for choosing different depth difference substrate on image, are carried out most by the Xi data set to adjacent picture elements pair
Smallization solves, and obtains one group of optimal wave band rotational units vector [α1,α2]:
In formula, i indicates certain adjacent picture elements pair, Δ sziIt is i-th of pixel to the difference being worth after rotation, A, B indicate the pixel
Point is to corresponding different sediment types, and n is pixel point to quantity, and f is to minimize function；
3) a variety of typical sediment pixel collection are selected at image flowage line, in conjunction with the wave band rotational units vector that acquisition is optimal
[α1,α2], by average statistics, obtain bottom parameters α1lnrb1+α2lnrb2Value；
4) identical sediment type on image, X in different depth position are utilized1~X2It is unrestrained to calculate bluish-green wave band round trip for data set
Penetrate attenuation coefficient ratio g1/g2；
5) it assuming that under the premise of water body uniform properties, analyzes and diffusion attenuation coefficient algorithm, calculates closest in shallow using half
The green wave band of sea region optics profundal zone diffuses attenuation coefficient g2；
6) above-mentioned steps are calculated to the coefficient obtained, including [α1、α2], bottom parameters α1lnrb1+α2lnrb2、g1/g2And g2It substitutes into
Shallow water depth inversion formula, and it is applied to entire image, realize that the multispectral satellite of shallow water depth without depth of water control point region is distant
Feel inverting.
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| CN110274858A (en) * | 2019-07-15 | 2019-09-24 | 南京吉泽信息科技有限公司 | Utilize the remote sensing technique of GOCI data recurrence estimation shallow lake different depth Suspended Sedimentation Concentration |
| CN110823190A (en) * | 2019-09-30 | 2020-02-21 | 广州地理研究所 | Island reef shallow sea water depth prediction method based on random forest |
| CN111474122A (en) * | 2020-04-21 | 2020-07-31 | 自然资源部第二海洋研究所 | Remote sensing extraction method for shallow seabed material reflectivity |
| CN111561916A (en) * | 2020-01-19 | 2020-08-21 | 自然资源部第二海洋研究所 | Shallow sea water depth uncontrolled extraction method based on four-waveband multispectral remote sensing image |
| CN111651707A (en) * | 2020-05-28 | 2020-09-11 | 广西大学 | Tidal level inversion method based on optical shallow water satellite remote sensing image |
| CN113140000A (en) * | 2021-03-26 | 2021-07-20 | 中国科学院东北地理与农业生态研究所 | Water body information estimation method based on satellite spectrum |
| CN113793374A (en) * | 2021-09-01 | 2021-12-14 | 自然资源部第二海洋研究所 | Method for inverting water depth based on water quality inversion result by using improved four-waveband remote sensing image QAA algorithm |
| CN113960625A (en) * | 2021-10-22 | 2022-01-21 | 自然资源部第二海洋研究所 | Water depth inversion method based on satellite-borne single photon laser active and passive remote sensing fusion |
| CN114199827A (en) * | 2022-02-21 | 2022-03-18 | 中国石油大学(华东) | Remote sensing data-based method for inverting vertical change of PAR diffuse attenuation coefficient |
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| CN117152636A (en) * | 2023-10-29 | 2023-12-01 | 自然资源部第二海洋研究所 | Shallow sea substrate reflectivity remote sensing monitoring method based on dual-band relation |
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Address after: 361005 Fujian Province University of Siming District of Xiamen City Road No. 178 Applicant after: THIRD INSTITUTE OF OCEANOGRAPHY, MINISTRY OF NATURAL RESOURCES Address before: 361005 Fujian Province University of Siming District of Xiamen City Road No. 178 Applicant before: Third Institute of Oceanography, State Oceanic Administration |
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| GR01 | Patent grant | ||
| GR01 | Patent grant |