CN104036507A - Light satellite based urban change area and evolution type rapid extraction method - Google Patents
Light satellite based urban change area and evolution type rapid extraction method Download PDFInfo
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- CN104036507A CN104036507A CN201410262168.XA CN201410262168A CN104036507A CN 104036507 A CN104036507 A CN 104036507A CN 201410262168 A CN201410262168 A CN 201410262168A CN 104036507 A CN104036507 A CN 104036507A
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Abstract
The invention provides a light satellite based urban change area and evolution type rapid extraction method. Different years of light satellite images are obtained and data preprocessing is performed, the three years of images are selected, different urban evolution types of colors are set, rapid extraction of different urban evolution areas is implemented according to color discrimination, pseudo spectrum curves are built and urban evolution type spectrum libraries are established in the different evolution type areas, rapid extraction of urban change areas and evolution types is implemented, and an urban evolution type graph is drawn. According to the light satellite based urban change area and evolution type rapid extraction method, the rapid extraction of the urban change areas within a large range and the discrimination of the individual urban evolution types are implemented, the rapid and efficient effect is achieved, the scientific basis can be provided for governmental urbanization macroscopic planning, the market layout of consulting companies and transnational corporations and the like, and the market prospect is good.
Description
Technical field
The present invention relates to a kind of city region of variation based on light satellite and develop type rapid extracting method, belonging to remote sensing image processing and area of pattern recognition.
Background technology
Substantially be the conventional road resource satellite of application to city region of variation and the analytical approach that develops type at present, first extract city, the Complicated Flow that rear variation detects.City research based on light satellite image is also confined to the simple analysis of urban sprawl, or change by some the method detecting and extract city region of variation, algorithm complexity, efficiency is low, does not study the discriminatory analysis of rapid extraction and the individual city evolvement type of city region of variation.
Summary of the invention
In order to solve the deficiencies in the prior art, the invention provides a kind of city region of variation based on light satellite and develop type rapid extracting method, synthesize, extract the pseudo-curve of spectrum, build the means such as city evolvement type library of spectra by false colour, in having realized on a large scale, the rapid extraction of city region of variation and the differentiation of individual city evolvement type, have advantages of rapidly and efficiently.
The present invention for the technical scheme that its technical matters of solution adopts is: a kind of city region of variation based on light satellite be provided and developed type rapid extracting method, specifically having comprised the following steps:
(1) obtain the light satellite image of different year in same detection region; The described time at least comprises Y
1time, Y
2time and Y
3time;
(2) light satellite image is carried out to data pre-service:
(201) radiation calibration: urban lighting satellite image is carried out to relative radiant correction;
(202) go negative value: the image after step (201) radiation calibration goes negative value processing, and the value that is less than 0 is given up;
(203) Image registration: will go negative value light satellite image after treatment according to geographic coordinate through step (202), to year piece of data carry out registration;
(204) wave band is synthetic: be considered as a wave band for the image of each different year, according to time order and function order, image carried out to wave band and synthesize, obtain a scape multiband image;
(3) arrange and develop the color of type, represent different types of evolution with different colours;
(4) false colored synthetic: from choose Y through step (204) urban lighting satellite image after treatment
1time, Y
2time and Y
3the image in time, wherein, Y
1<Y
2<Y
3; The image in 3 times is carried out to false colored compound display, wherein, Y
1time image is set to red channel, Y
2time image is set to green channel, Y
2time image is set to blue channel;
(5) discrimination standard of setting up according to step (3), develops type to the False color comp osite image of step (4) by visual interpretation preliminary judgement, surveyed area is divided into not development zone, stable region, development zone and blighted area;
(6) build the pseudo-curve of spectrum: choose respectively in surveyed area each pixel that develops type area, extract this pixel DN value over the years, taking the time as transverse axis, DN value is that the longitudinal axis is constructed DN value change curve, obtains the pseudo-curve of spectrum of each differentiation type;
(7) set up and develop type library of spectra: the color of the different types of evolution arranging according to step (3), choose respectively the single pixel of each differentiation type area and/or more than 2 pixel, average for each differentiation type area respectively, and construct the pseudo-curve of spectrum of each differentiation type, set up the differentiation type library of spectra being formed by the pseudo-curve of spectrum;
(8) rapid extraction of city region of variation: the differentiation type library of spectra of setting up according to step (7), adopt Spectral matching algorithm, identify fast developing type, for different types of evolution is given corresponding color, generate and develop type map, thereby city region of variation and differentiation type are shown in the drawings.
Further, in step (201), utilize following formula to carry out relative radiant correction:
y＝c
0+c
1x+c
2x
2……(1)
Wherein, c
0, c
1and c
2be relative radiant correction parameter, provided by remote sensor production unit or Subscriber Unit, x represents DN value, and y represents the DN value after relative radiant correction.
In step (202), utilize following formula to go negative value:
y
DN>0＝(x
radiation>0)×x
radiation……(2)
Wherein, y
dN>0represent the image after the negative value of place to go, x
radiationrepresent the image after relative radiant correction.
Further, the described city evolvement type decision of step (3) standard is: represent to develop Class1 with black; Represent to develop type 2 by white; Represent to develop type 3 by blue, cyan and green; Represent to develop type 4 by yellow, redness and pink colour.
Further, in step (8), utilize following steps to identify fast developing type:
(801) obtain the light satellite resultant image that will develop type identification;
(802) obtain the size of image, columns and the line number of establishing its pixel are respectively nSample and nLine, and wave band number is nBand, the independent variable i=0 that definition ranks change, j=0;
(803) line number judgement, line number, in the time being less than nLine, enters step 804, otherwise enters step 810;
(804) columns judgement, columns, in the time being less than nSample, enters step 805, otherwise enters step 806;
(805) columns zero clearing j=0, line number i increases by 1, returns to step 803;
(806) obtain the pseudo-curve of spectrum that image (i, j) is located;
(807) pseudo-curve of spectrum step 806 being obtained, utilizes Spectral matching algorithm to realize and the mating of pseudo-spectrum in differentiation type library of spectra;
(808) step 807 Spectral matching result is differentiated, obtained the differentiation type of step 806 (i, j) position, and give corresponding color by the type;
(809) columns cumulative 1;
(810) traveled through all row and columns, finished quick identification and differentiate differentiation type map with the Spectral matching generating based on developing type library of spectra.
The present invention is based on the beneficial effect that its technical scheme has is:
(1) the present invention has avoided the Complicated Flow of " first extract, rear variation detects ", can save the plenty of time, meets the efficient requirement of data processing;
(2) the present invention is synthesized, extracts the pseudo-curve of spectrum, built the means of city evolvement type library of spectra by false colour, realized on a large scale in the rapid extraction of city region of variation and the differentiation of individual city evolvement type, have advantages of rapidly and efficiently;
(3) the present invention can provide scientific basis for government's urbanization macro-plan, consulting firm, transregional company carry out market presence etc., has good market outlook.
Brief description of the drawings
Fig. 1 is the city region of variation and differentiation type rapid extracting method process flow diagram based on light satellite.
Fig. 2 is data pretreatment process figure.
Fig. 3 is the city evolvement type schematic diagram that utilizes three primary colors definition, and wherein, A, B, C, D, E, F and G represent respectively white stable region, blue development zone, cyan development zone, Green Development district, yellow blighted area, red blighted area and pink colour blighted area.
Fig. 4 is the pseudo-spectral curve in city evolvement type library of spectra.
Fig. 5 is that city evolvement type is carried out quick identification process figure.
Fig. 6 is city evolvement type map.
Embodiment
Below in conjunction with drawings and Examples, the invention will be further described.
The invention provides a kind of city region of variation based on light satellite and develop type rapid extracting method, with reference to Fig. 1, specifically comprising the following steps:
(1) obtain the light satellite image of different year in same detection region; The described time at least comprises Y
1time, Y
2time and Y
3time;
(2), with reference to Fig. 2, by following steps, light satellite image is carried out to data pre-service:
(201) utilize following formula to carry out relative radiant correction to urban lighting satellite image:
y＝c
0+c
1x+c
2x
2……(1)
Wherein, c
0, c
1and c
2be relative radiant correction parameter, provided by remote sensor production unit or Subscriber Unit, x represents DN value, and y represents the DN value after relative radiant correction;
(202) utilize following formula to go negative value processing to the image after step (201) radiation calibration:
y
DN>0＝(x
radiation>0)×x
radiation……(2)
Wherein, y
dN>0represent the image after the negative value of place to go, x
radiationrepresent the image after relative radiant correction;
(203) Image registration: will go negative value light satellite image after treatment according to geographic coordinate through step (202), to year piece of data carry out registration;
(204) wave band is synthetic: be considered as a wave band for the image of each different year, according to time order and function order, image carried out to wave band and synthesize, obtain a scape multiband image;
(3) with reference to Fig. 3, the color that develops type is set, utilize three primary colors to represent different types of evolution, wherein:
Develop Class1 for development zone not, be set to black, expression light satellite DN value approaches 0, and the urban area of any variation does not occur for many years;
Developing type 2 is stable region, is set to white, represents that early stage, mid-term, later stage light satellite DN value all approach 60, there is no to occur the region of larger variation, represents Y here
1, Y
2and Y
3the urban area that year all exists;
Developing type 3 is development zone, with following three kinds of color settings:
Blue expression do not change early stage within this time period in mid-term, arrives the DN value in post city region mid-term in continuous increase, is expressed as Y here
1to Y
2year does not change substantially, at Y
2to Y
3the region that year expansion is city;
Cyan represent early stage to mid-term in state of development, in steady state (SS), be expressed as Y to the later stage here mid-term
1to Y
2the urban area of year expansion, but at Y
2to Y
3year keeps stable urban area;
Green expression, is expressed as Y here at expansion and the urban area in the decline of mid-term to later stage from early stage to mid-term
1to Y
2the urban area of year expansion, Y
3the city of failing gradually after year.
Develop type 4 and represent blighted area, with following three kinds of color settings:
Yellow expression is from early stage to mid-term in steady state (SS), and the region of withering away gradually after mid-term, is expressed as Y here
1to Y
2year urban area is in steady state (SS), Y
2to Y
3year, this city started to wither away;
Red expression, from early stage to the later stage urban area in decline always, is expressed as Y here
1the urban area that year exists, at Y
1to Y
2after year, wither away gradually;
Pink colour represent from early stage to mid-term in decline state,, in state of development be here expressed as from Y to the later stage mid-term
1to Y
2year city starts to wither away, Y
2to Y
3year, city was again in state of development;
(4) false colored synthetic: from choose Y through step (204) urban lighting satellite image after treatment
1time, Y
2time and Y
3the image in time, wherein, Y
1<Y
2<Y
3; The image in 3 times is carried out to false colored compound display, wherein, Y
1time image is set to red channel, Y
2time image is set to green channel, Y
2time image is set to blue channel;
(5) color of the different types of evolution arranging according to step (3), the False color comp osite image of step (4) is developed to type by visual interpretation preliminary judgement, develop Class1 so that surveyed area is divided into, develop type 2, develop type 3 and develop type 4, i.e. not development zone, stable region, development zone and blighted area;
(6) build the pseudo-curve of spectrum: choose respectively in surveyed area each pixel that develops type area, extract this pixel DN value over the years, taking the time as transverse axis, DN value is that the longitudinal axis is constructed DN value change curve, obtains the pseudo-curve of spectrum of each differentiation type;
(7) set up and develop type library of spectra: the color of the different types of evolution arranging according to step (3), choose respectively the single pixel of each differentiation type area and/or more than 2 pixel, average for each differentiation type area respectively, and construct the pseudo-curve of spectrum of each differentiation type, set up the differentiation type library of spectra being formed by the pseudo-curve of spectrum; The pseudo-curve of spectrum in city evolvement type library of spectra as shown in Figure 4;
(8) rapid extraction of city region of variation: the differentiation type library of spectra of setting up according to step (7), adopt Spectral matching algorithm, identify fast developing type, for different types of evolution is given corresponding color, generate and develop type map, thereby city region of variation and differentiation type are shown in the drawings; With reference to Fig. 5, specifically adopt following steps:
(801) obtain the light satellite resultant image that will develop type identification;
(802) obtain the size of image, columns and the line number of establishing its pixel are respectively nSample and nLine, and wave band number is nBand, the independent variable i=0 that definition ranks change, j=0;
(803) line number judgement, line number, in the time being less than nLine, enters step 804, otherwise enters step 810;
(804) columns judgement, columns, in the time being less than nSample, enters step 805, otherwise enters step 806;
(805) columns zero clearing j=0, line number i increases by 1, returns to step 803;
(806) according to developing type library of spectra, utilize Spectral matching algorithm, obtain the pseudo-curve of spectrum that image (i, j) is located;
(807) pseudo-curve of spectrum step 806 being obtained, utilizes Spectral matching algorithm to realize and the mating of pseudo-spectrum in differentiation type library of spectra;
(808) step 807 Spectral matching result is differentiated, obtained the differentiation type of step 806 (i, j) position, and give corresponding color by the type;
(809) columns cumulative 1;
(810) traveled through all row and columns, finished quick identification and differentiate differentiation type map with the Spectral matching generating based on developing type library of spectra, effect as shown in Figure 6.
Claims (5)
1. the city region of variation based on light satellite and differentiation type rapid extracting method, is characterized in that specifically comprising the following steps:
(1) obtain the light satellite image of different year in same detection region; The described time at least comprises Y
1time, Y
2time and Y
3time;
(2) by following steps, light satellite image is carried out to data pre-service:
(201) radiation calibration: urban lighting satellite image is carried out to relative radiant correction;
(202) go negative value: the image after step (201) radiation calibration is gone to negative value processing, the value that is less than 0 is given up;
(203) Image registration: will go negative value light satellite image after treatment according to geographic coordinate through step (202), to year piece of data carry out registration;
(204) wave band is synthetic: the image of each different year is considered as a wave band, according to time order and function order, image is carried out to wave band and synthesizes, and obtains a scape multiband image;
(3) arrange and develop the color of type, represent different types of evolution with different colours;
(4) false colored synthetic: from choose Y through step (204) urban lighting satellite image after treatment
1time, Y
2time and Y
3the image in time, wherein, Y
1<Y
2<Y
3; The image in 3 times is carried out to false colored compound display, wherein, Y
1time image is set to red channel, Y
2time image is set to green channel, Y
2time image is set to blue channel;
(5) color of the different types of evolution arranging according to step (3), develops type to the False color comp osite image of step (4) by visual interpretation preliminary judgement, surveyed area is divided into the region of different types of evolution;
(6) build the pseudo-curve of spectrum: choose respectively in surveyed area each pixel that develops type area, extract this pixel DN value over the years, taking the time as transverse axis, DN value is that the longitudinal axis is constructed DN value change curve, obtains the pseudo-curve of spectrum of each differentiation type;
(7) set up and develop type library of spectra: the color of the different types of evolution arranging according to step (3), choose respectively the single pixel of each differentiation type area and/or more than 2 pixel, average for each differentiation type area respectively, and construct the pseudo-curve of spectrum of each differentiation type, set up the differentiation type library of spectra being formed by the pseudo-curve of spectrum;
(8) rapid extraction of city region of variation: the differentiation type library of spectra of setting up according to step (7), adopt Spectral matching algorithm, identify fast developing type, for different types of evolution is given corresponding color, generate and develop type map, thereby city region of variation and differentiation type are shown in the drawings.
2. the city region of variation based on light satellite according to claim 1 and differentiation type rapid extracting method, is characterized in that: in step (201), utilize following formula to carry out relative radiant correction:
y＝c
0+c
1x+c
2x
2……(1)
Wherein, c
0, c
1and c
2be relative radiant correction parameter, provided by remote sensor production unit or Subscriber Unit, x represents DN value, and y represents the DN value after relative radiant correction.
3. the city region of variation based on light satellite according to claim 1 and differentiation type rapid extracting method, is characterized in that: in step (202), utilize following formula to go negative value:
y
DN>0＝(x
radiation>0)×x
radiation……(2)
Wherein, y
dN>0represent the image after the negative value of place to go, x
radiationrepresent the image after relative radiant correction.
4. the city region of variation based on light satellite according to claim 1 and differentiation type rapid extracting method, is characterized in that: step (3) is described represents that with different colours different types of evolution is specially:
Represent to develop Class1 with black; Represent to develop type 2 by white; Represent to develop type 3 by blue, cyan and green; Represent to develop type 4 by yellow, redness and pink colour.
5. the city region of variation based on light satellite according to claim 1 and differentiation type rapid extracting method, is characterized in that: in step (8), utilize following steps to identify fast developing type:
(801) obtain the light satellite resultant image that will develop type identification;
(802) obtain the size of image, columns and the line number of establishing its pixel are respectively nSample and nLine, and wave band number is nBand, the independent variable i=0 that definition ranks change, j=0;
(803) line number judgement, line number, in the time being less than nLine, enters step 804, otherwise enters step 810;
(804) columns judgement, columns, in the time being less than nSample, enters step 805, otherwise enters step 806;
(805) columns zero clearing j=0, line number i increases by 1, returns to step 803;
(806) obtain the pseudo-curve of spectrum that image (i, j) is located;
(807) pseudo-curve of spectrum step 806 being obtained, utilizes Spectral matching algorithm to realize and the mating of pseudo-spectrum in differentiation type library of spectra;
(808) step 807 Spectral matching result is differentiated, obtained the differentiation type of step 806 (i, j) position, and give corresponding color by the type;
(809) columns cumulative 1;
(810) traveled through all row and columns, finished quick identification and differentiate differentiation type map with the Spectral matching generating based on developing type library of spectra.
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Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20120082364A1 (en) * | 2010-09-30 | 2012-04-05 | Olympus Corporation | Image processing system |
| CN102609711A (en) * | 2012-02-21 | 2012-07-25 | 核工业北京地质研究院 | Information extraction method applicable to hyperspectral image |
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Patent Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20120082364A1 (en) * | 2010-09-30 | 2012-04-05 | Olympus Corporation | Image processing system |
| CN102609711A (en) * | 2012-02-21 | 2012-07-25 | 核工业北京地质研究院 | Information extraction method applicable to hyperspectral image |
Non-Patent Citations (3)
| Title |
|---|
| YUELIANG MA ET AL.: "Remote sensing monitoring and driving force analysis of urban expansion in Guangzhou City, China", 《HABITAT INTERNATIONAL》 * |
| 宋妍 等: "基于极大似然估计采样一致性准则的遥感影像配准参数解算方法研究", 《测绘科学》 * |
| 王勇: "基于遥感影像的城市土地利用变化检测研究", 《城市勘测》 * |
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