CN109211798A - A kind of annual sea ice distributed intelligence extracting method based on remote sensing image spectral signature - Google Patents
A kind of annual sea ice distributed intelligence extracting method based on remote sensing image spectral signature Download PDFInfo
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- CN109211798A CN109211798A CN201811364317.8A CN201811364317A CN109211798A CN 109211798 A CN109211798 A CN 109211798A CN 201811364317 A CN201811364317 A CN 201811364317A CN 109211798 A CN109211798 A CN 109211798A
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- G—PHYSICS
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- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
- G01N21/17—Systems in which incident light is modified in accordance with the properties of the material investigated
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
- G01N21/17—Systems in which incident light is modified in accordance with the properties of the material investigated
- G01N2021/1793—Remote sensing
Abstract
The annual sea ice distributed intelligence extracting method based on remote sensing image spectral signature that the present invention relates to a kind of, using the sea Sentinel-3 OLCI(land chromascope) image data is data source, a new sea ice index Remote Sensing Model with the 20th wave band of OLCI and the 21st wave band atmosphere top layer reflectivity (respectively b20 and b21) for parameter is constructed, can be directly used for the extraction of Bohai Sea ice-control distributed intelligence.The sea ice information extraction effect of the method for the present invention is good, without carrying out the film that salts down of cloud layer and land, realize sea ice information it is quick, it is convenient, accurately extract, provide new technical method for the monitoring of Bohai Sea in Winter Sea Ice Remote Sensing.
Description
Technical field
The present invention relates to remote sensing fields, especially a kind of annual sea ice distributed intelligence based on remote sensing image spectral signature
Extracting method.
Background technique
The Bohai Sea is the freezed in winter sea area of Northern Hemisphere southernmost end, and different degrees of sea ice phenomenon can all occur in annual winter.
Bohai Rim is the important economic development region of China, and regular Bohai Sea ice damage can cause very big shadow to the regional economy
It rings, constitutes a serious threat to aquaculture, harbour shipping, offshore platform operation etc..The distributed intelligence of Bohai Sea ice-control is the reflection winter
The important parameter of Ji Bohai ice condition and Regional climate change has a major impact the offshore activities in sea ice periglacial area.It is suitable
Ocean development and ocean mitigation requirements of one's work are answered, the macroscopic view observation of satellite remote sensing, in real time dynamic, the advantage of fast imaging are utilized
It is most important to carry out Bohai Sea ice-control monitoring, sparse, limited, the at high cost deficiency of field observation can be made up well.
As the optical remote sensing imaging device of a new generation, the OLCI sensor of Sentinel-3A Seeds of First Post-flight is able to carry out
For a long time, persistently, high-frequency offshore monitoring water environment.OLCI has the time resolution less than 3d with full resolution mode operation
Rate, spatial resolution 300m, sweep bandwidth 1270km have in 400~1020nm wave-length coverage of visible light to near-infrared
21 wave bands, spectral resolution with higher.Bohai Sea water environment is complicated, and water body sediment content is high, how to utilize OLCI mostly light
Spectrum remote sensing data is eliminated the interference of other types of ground objects (especially turbid water body), is accurately extracted from numerous types of ground objects
Sea ice distributed intelligence out better describes the change in time and space of sea ice distribution, can be provided with for the remote sensing monitoring of Bohai Sea in Winter sea ice
The technical support of power.
Summary of the invention
In view of this, the purpose of the present invention is to propose to a kind of, the annual sea ice based on remote sensing image spectral signature is distributed letter
Extracting method is ceased, can be realized the quick and precisely extraction of Bohai Sea ice-control.
The present invention is realized using following scheme: a kind of annual sea ice distributed intelligence based on remote sensing image spectral signature mentions
Method is taken, specifically includes the following steps:
Step S1: the remote sensing image data of OLCI (extra large land chromascope) in icing sea area is obtained, and image data is carried out
Pretreatment；Choose image in be located near infrared band two channels, central wavelength be respectively 940 ± 10nm, 1020 ±
20nm；
Step S2: band math is carried out to the image data that step S1 is obtained according to new sea ice index Remote Sensing Model, is obtained
To sea ice index image；
Step S3: using the method for Threshold segmentation, sea ice pixel is extracted according to discriminate, obtains Sea ice load distribution map；
Wherein, the discriminate are as follows:
NDSIIOLCI> R0；
In formula, R0For segmentation threshold.
Further, in step S1, the OLCI comes from Sentinel-3 satellite, and the remote sensing image is the 20 of OLCI
With the image data of the 21st wave band.
Further, in step S1, the pretreatment includes: to carry out spoke brightness to reflectivity conversion to image data, is incited somebody to action
Atmosphere top layer spoke brightness data is converted into atmosphere top layer reflectivity data；Re-projection；The cutting of target area.
Further, in step S2, the calculating of the sea ice index uses following formula:
NDSIIOLCI=(b20-b21)/(b20+b21)；
In formula, NDSIIOLCIFor the new sea ice index based on OLCI；B20, b21 respectively represent the 20th wave of OLCI sensor
The atmosphere top layer reflectivity of section and the 21st wave band.
Further, in step S3, the segmentation threshold R0Value be 0.
Compared with prior art, the invention has the following beneficial effects: the sea ice information extraction effect of the method for the present invention is good, nothing
The film that salts down that need to carry out cloud layer and land, realize sea ice information it is quick, it is convenient, accurately extract, be Bohai Sea in Winter Sea Ice Remote Sensing
Monitoring provides new technical method.
Detailed description of the invention
Fig. 1 is the method flow schematic diagram of the embodiment of the present invention.
Fig. 2 is the specific implementation flow block diagram of the embodiment of the present invention.
Fig. 3 is the 6th wave band gray level image of Bohai Sea region Sentinel-3OLCI of the embodiment of the present invention, and the imaging date is north
When the 2018 capital time morning 10 on the 24th in January.
Fig. 4 is the Bohai Sea region sea ice index image in the 24 days January in 2018 of the embodiment of the present invention.
Fig. 5 is the Bohai Sea region sea ice distributed intelligence figure in the 24 days January in 2018 of the embodiment of the present invention.
Specific embodiment
The present invention will be further described with reference to the accompanying drawings and embodiments.
It is noted that described further below be all exemplary, it is intended to provide further instruction to the application.Unless another
It indicates, all technical and scientific terms used herein has usual with the application person of an ordinary skill in the technical field
The identical meanings of understanding.
It should be noted that term used herein above is merely to describe specific embodiment, and be not intended to restricted root
According to the illustrative embodiments of the application.As used herein, unless the context clearly indicates otherwise, otherwise singular
Also it is intended to include plural form, additionally, it should be understood that, when in the present specification using term "comprising" and/or " packet
Include " when, indicate existing characteristics, step, operation, device, component and/or their combination.
As shown in Figure 1 and Figure 2, a kind of annual sea ice based on remote sensing image spectral signature point is present embodiments provided
Cloth information extracting method, specifically includes the following steps:
Step S1: the remote sensing image data of OLCI (extra large land chromascope) in icing sea area is obtained, and image data is carried out
Pretreatment；Choose image in be located near infrared band two channels, central wavelength be respectively 940 ± 10nm, 1020 ±
20nm；
Step S2: band math is carried out to the image data that step S1 is obtained according to new sea ice index Remote Sensing Model, is obtained
To sea ice index image；
Step S3: using the method for Threshold segmentation, sea ice pixel is extracted according to discriminate, obtains Sea ice load distribution map；
Wherein, the discriminate are as follows:
NDSIIOLCI> R0；
In formula, R0For segmentation threshold.
In the present embodiment, in step S1, the OLCI comes from Sentinel-3 satellite, and the remote sensing image is OLCI's
The image data of 20th and the 21st wave band.
In the present embodiment, in step S1, the pretreatment includes: to carry out spoke brightness to image data to turn to reflectivity
It changes, converts atmosphere top layer reflectivity data for atmosphere top layer spoke brightness data；Re-projection；The cutting of target area.
In the present embodiment, in step S2, the calculating of the sea ice index uses following formula:
NDSIIOLCI=(b20-b21)/(b20+b21)；
In formula, NDSIIOLCIFor the new sea ice index based on OLCI；B20, b21 respectively represent the 20th wave of OLCI sensor
The atmosphere top layer reflectivity of section and the 21st wave band.If NDSIIOLCIGreater than preset threshold R0, then judge the pixel for sea ice；Otherwise
For other atural objects.
In the present embodiment, in step S3, the segmentation threshold R0Value be 0.
Specifically, the present embodiment is comparing several main image cover types that research area occurs (including sea ice, sea
Water, cloud layer, land and accumulated snow) it finds after Reflectivity in OLCI atmosphere top layer reflectivity data after the pre-treatment, sea
Ice has apparent characteristic difference in the reflectivity of the 20th (930-950nm) and 21 (1000-1040nm) wave bands and other atural objects.
Sea ice is greater than it in the reflectivity of 21 wave bands in the reflection of the 20th wave band, and other atural objects are in contrast.It is significant according to this
Feature, the present embodiment construct new sea ice index (Normalized Difference Sea using the form of normalization difference
Ice Index,NDSIIOLCI), NDSIIOLCIBe expressed as follows:
NDSIIOLCI=(b20-b21)/(b20+b21)；
In formula, NDSIIOLCIFor the new sea ice index based on OLCI sensor；B20, b21 respectively represent OLCI sensor
The atmosphere top layer reflectivity of 20th wave band and the 21st wave band.
Specifically, the present embodiment obtains the 20th and the 21st wave band image data of Bohai Sea region OLCI, imaging time is north
When the 2018 capital time morning 10 on the 24th in January, spoke brightness is carried out to reflectivity conversion to image respectively using SNAP6.0 software,
Atmosphere top layer spoke brightness data is converted into atmosphere top layer reflectivity data；It then, will using the re-projection function in SNAP6.0
The projected coordinate system re-projection of image is at 84 coordinate system of UTM/WGS；Finally image is cut, the image for studying area is cut out
It cuts and, reduce the data volume of processing.Fig. 3 is the grayscale image of the 6th wave band of OLCI of Bohai Sea region.
The image data of 20th and 21 wave bands is subjected to the available width sea of band math according to the formula of sea ice index
Ice index grayscale image (such as Fig. 4).Influence of the difference processing in addition to terrain differences can be eliminated is normalized, is solved in Water-Body Information
Miscellaneous hypographous problem, can also be such that the intensity value ranges of image are limited between -1 to 1, and the maximum gradation value of image will not be big
In 1, minimum value will not be less than -1.This not only eliminate it is complicated go Shadows Processing process, also help and extract threshold in step 3
The determination of value.After the processing of sea ice index, the gray value of sea ice is greater than other all cover types, shows as whole picture shadow
As most bright part.Based on this feature, the sea ice distributed intelligence that the present embodiment can be realized single threshold is extracted, and is substantially reduced
The complexity that Bohai Sea ice-control distributed intelligence is extracted, sufficiently presents new sea ice index Remote Sensing Model in Bohai Sea ice-control distributed intelligence
Conveniently advantage in extraction.
To sea ice index image carry out Threshold segmentation can it is simple, quickly and stably by image sea ice and other are several
It is distinguished in kind cover type.Scientific determination point can be compared according to the spectral reflectivity feature difference of different cover types
Cut threshold value R0.Most important difference be embodied in sea ice the 20th wave band reflectivity be greater than the 21st wave band reflectivity, and remaining
Atural object is in contrast.It is clear that there are the pixel values of sea ice to be both greater than 0 after the calculating of sea ice index, other covering classes
Type is less than 0.So the present embodiment uses 0 threshold value as segmentation, i.e. R0=0.By discriminate, the present embodiment is by gray value
1 filling of pixel greater than 0, other pixels are then 0, just can obtain the distributed intelligence (such as Fig. 5) of sea ice.
The foregoing is merely presently preferred embodiments of the present invention, all equivalent changes done according to scope of the present invention patent with
Modification, is all covered by the present invention.
Claims (5)
1. a kind of annual sea ice distributed intelligence extracting method based on remote sensing image spectral signature, it is characterised in that: including with
Lower step:
Step S1: OLCI is obtained in the remote sensing image data in icing sea area, and image data is pre-processed；It chooses in image
Positioned at two channels of near infrared band, central wavelength is respectively 940 ± 10nm, 1020 ± 20nm；
Step S2: band math is carried out to the image data that step S1 is obtained according to new sea ice index Remote Sensing Model, obtains sea
Ice index image；
Step S3: using the method for Threshold segmentation, sea ice pixel is extracted according to discriminate, obtains Sea ice load distribution map；Wherein,
The discriminate are as follows:
NDSIIOLCI> R0；
In formula, R0For segmentation threshold.
2. a kind of annual sea ice distributed intelligence extraction side based on remote sensing image spectral signature according to claim 1
Method, it is characterised in that: in step S1, the OLCI comes from Sentinel-3 satellite, and the remote sensing image is the 20th He of OLCI
The image data of 21st wave band.
3. a kind of annual sea ice distributed intelligence extraction side based on remote sensing image spectral signature according to claim 1
Method, it is characterised in that: in step S1, the pretreatment includes: to carry out spoke brightness to reflectivity conversion, by atmosphere to image data
Top layer spoke brightness data is converted into atmosphere top layer reflectivity data；Re-projection；The cutting of target area.
4. a kind of annual sea ice distributed intelligence extraction side based on remote sensing image spectral signature according to claim 2
Method, it is characterised in that: in step S2, the calculating of the sea ice index uses following formula:
NDSIIOLCI=(b20-b21)/(b20+b21)；
In formula, NDSIIOLCIFor the new sea ice index based on OLCI；B20, b21 respectively represent the 20th wave band of OLCI sensor and
The atmosphere top layer reflectivity of 21st wave band.
5. a kind of annual sea ice distributed intelligence extraction side based on remote sensing image spectral signature according to claim 1
Method, it is characterised in that: in step S3, the segmentation threshold R0Value be 0.
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