CN106503662B - A kind of appraisal procedure of intertidal zone sargassum thunbergii algae bed stock number - Google Patents
A kind of appraisal procedure of intertidal zone sargassum thunbergii algae bed stock number Download PDFInfo
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Abstract
The invention belongs to marine ecology scientific domains, are related to a kind of appraisal procedure of intertidal zone sargassum thunbergii algae bed stock number, in particular to 10 km of one kind2The Scientific evaluation method of intertidal zone sargassum thunbergii resource within area.There are larger systematic error and the technical deficiency fully assessed is difficult to during sargassum thunbergii stock assessment in the prior art in order to overcome, the present invention uses unmanned aerial vehicle remote sensing technology, remote sensing monitoring is carried out to intertidal zone sargassum thunbergii algae bed in the withered damp phase, Inversion Calculation sargassum thunbergii kelp bed stock number can be completed in a short time the sargassum thunbergii kelp bed stock number assessment of large scale.The method of the present invention is efficient, convenient, accuracy is high, is suitble to the assessment of Intertidal Algae stock number.
Description
Technical field
The invention belongs to marine ecology scientific domains, are related to a kind of appraisal procedure of intertidal zone sargassum thunbergii algae bed stock number,
In particular to a kind of 10km2The Scientific evaluation method of intertidal zone sargassum thunbergii resource within area.
Background technique
To the assessment mode of marine algae resource amount, there are mainly two types of modes at present:
(1) traditional approach: several biological observation sample points are laid according to certain way to survey region, pass through statistical analysis
The quantity of each sample point sample acquisition, the stock number in evaluation studies region.But sargassum thunbergii kelp bed is mostly non-company in intertidal zone
Continuous, non-uniform Distribution, thus it is larger using systematic error when conventional method estimation marine algae resource amount.
(2) satellite remote sensing mode: the assessment of ecological resources amount, but remote sensing mode can be carried out to large scale range vegetation resources
It is influenced in marine ecology research by sea, part below sea can not provide remote sensing data.Sargassum thunbergii is a kind of intertidal belt submarine
Algae is generally exposed the surface in the withered damp phase, and the time of satellite remote sensing has uncontrollability, and by inside even from weather (cloud layer, mist
Haze etc.), therefore satellite remote sensing has certain technical limitation for the estimation of Intertidal Algae stock number.
Based on this, the present invention provides a kind of appraisal procedure of intertidal zone sargassum thunbergii algae bed stock number.
Summary of the invention
In order to overcome the above-mentioned deficiencies of the prior art, the present invention uses unmanned aerial vehicle remote sensing technology, in the withered damp phase to intertidal zone
Sargassum thunbergii algae bed carries out remote sensing monitoring, and Inversion Calculation sargassum thunbergii kelp bed stock number can be completed in a short time large scale (10
km2Within) sargassum thunbergii kelp bed stock number assessment.The method of the present invention is efficient, convenient, accuracy is high, is suitble to Intertidal Algae
The assessment of stock number.
The present invention is achieved through the following technical solutions above-mentioned technical purpose:
A kind of appraisal procedure of intertidal zone sargassum thunbergii algae bed stock number comprising following steps:
1) remote sensing images acquire: presetting multiple biological photo control points, control biological 1 × 1 m of photo control point sample area2, biology
Photo control point chooses the representative sample prescription of different abundance, each abundance photo control point >=3, and completes biological photo control point GPS letter
Breath and the acquisition of sargassum thunbergii quantity information；Intertidal zone sargassum thunbergii kelp bed is monitored using unmanned aerial vehicle remote sensing, obtains remote sensing figure
Picture；
2) remote sensing images are inputted into 10.0 software of ArcGIS, shapefile formatted file, coordinate is created in Catalog
System uses WGS 1984, utm projection, and image display scale is set as 1:100, draws sargassum thunbergii distribution situation according to remote sensing images,
It is saved after the completion of editor and obtains remote sensing images file；Shapefile format is successively established in Catalog according to photo control point number
File is drawn according to photo control point number and sargassum thunbergii quantity information successively editing files according to the biological photo control point GPS information of record
Remote sensing images are inputted ENVI4.7 software by sargassum thunbergii biology photo control point file processed, and biology is loaded in ENVI4.7 software as control
Then dot file exports the ROI the file information of ASCII fromat, in the ASCII fromat extracted in remote sensing images file
Corresponding color value information and image element information item number are found in ROI file；The color value information includes R value, G value, B value；
Using color value as independent variable, sargassum thunbergii quantity is dependent variable, is believed the color of image value and photo control point sargassum thunbergii quantity extracted
Breath carries out linear multiple regression statistical analysis, obtains regression analysis equation:
Y=(aR+bG+cB+d) × n
Wherein Y makes a living object photo control point sargassum thunbergii quantity；R, G, B are respectively R value, the G value, B in ROI image colouring information
Value；A, b, c, d are respectively regression calculation computational constant coefficient；N value is that ROI image extracts image element information item number；Work as regression analysis
The regression coefficient r of equation2When >=0.8, Inversion Calculation model is more accurate, if r2< 0.8 then needs to add photo control point or change
It gains and returns statistical model.
3) remote sensing images are inputted into ENVI4.7 software, sargassum thunbergii is loaded in ENVI4.7 software and is distributed area file, then
The ROI the file information that ASCII fromat is exported in remote sensing images file, finds in the ROI file of the ASCII fromat extracted
Corresponding color value information and image element information item number, the color value information R value, G value, B value；The sargassum thunbergii of extraction is distributed
The color value information input model equation in area first calculates the corresponding seaweed quantity of single pixel, then calculates rat-tail further according to formula
Algae algae bed total resources, wherein Y is sargassum thunbergii algae bed total resources, and n is image element information item number, YiFor the seaweed number of single pixel
Amount.
The appraisal procedure of intertidal zone as described above sargassum thunbergii algae bed stock number, wherein unmanned plane configuration should be able to meet as follows
Condition: fixed-wing formula unmanned plane, speed per hour >=50 km/h, cruise duration >=1.5 h, observing and controlling radius >=10 km, wind resistance energy
Power >=4 grade, sensor valid pixel >=24,000,000, peak of flight >=2000 m.
The appraisal procedure of intertidal zone sargassum thunbergii algae bed stock number as described above, the unmanned plane is during aerial survey
Flight parameter: flying height is 150-300 m, ship's control 80%, sidelapping degree 60%；Aerial survey selection of time spring tide is withered
It carries out in damp phase 0.5-2 h, intensity of illumination >=10000 lx when flight select fine day wind-force≤4 grade.
The appraisal procedure of intertidal zone as described above sargassum thunbergii algae bed stock number, the remote sensing go out graph parameter are as follows: coordinate
System uses WGS 1984, and elevation selects transverse Mercator projection using 1985 state height reference projection modes；Image band number
3-5, image pixel depth 8bit, pixel value 0-255, it is tiff that picture, which saves format,.
The appraisal procedure of intertidal zone sargassum thunbergii algae bed stock number of the present invention, it is main compared with existing appraisal procedure
It is a technical advantage that:
1, accuracy is high: the resolution ratio of satellite remote sensing images is 0.1-0.5m；And unmanned aerial vehicle remote sensing image resolution ratio is
0.05m.Therefore unmanned aerial vehicle remote sensing has higher accuracy compared to satellite remote sensing；Remote sensing images can accurately identify intertidal zone mouse
The distributing position of tail algae algae bed and then quantity Inversion Calculation is carried out, overcomes that kelp bed distribution is discontinuous, non-uniform Distribution causes
The systematic error of statistical analysis has technical advance compared to traditional approach.
2, method is convenient:, only need to be in a small range without carrying out investigation and sampling to whole region when larger to survey region
Inversion Calculation can be carried out to whole region by establishing Inversion Calculation model.
3, method is high-efficient: conventional method needs to lay several sample points in survey region, when survey region area increases
When, the quantity of sample point also increases therewith, therefore when survey region is larger, sampling work amount is higher and analytical cycle also therewith
Extend.This research method sets 10-20 biological photo control point to the region of different abundance before only needing remote sensing monitoring, can be to remote sensing
Monitoring image carries out biomass statistics, and when studying area increase, without increasing significantly biological photo control point, sea can be realized
The inverting of algae total resources is estimated.
Detailed description of the invention
Fig. 1 kelp bed biology photo control point measures schematic diagram.
The sargassum thunbergii distribution map that Fig. 2 is drawn according to remote sensing images is wherein sargassum thunbergii actual distribution in aterrimus region
Area.
The biological photo control point file that Fig. 3 is drawn according to GPS location, object photo control point sampling area of making a living in center area.
Specific embodiment
The present invention is further described below by way of specific embodiment, but does not limit the invention patent protection in any way
Range, under the premise of not changing thinking of the present invention, the transformation or modification made are intended to be included in those skilled in the art
Within protection scope of the present invention.
The foundation of sargassum thunbergii algae in the intertidal zone of the present invention bed stock number Calculating model of embodiment 1
1.1 unmanned aerial vehicle remote sensing preparation measures:
1.1.1 unmanned plane configuration is as follows: fixed-wing formula unmanned plane, speed per hour >=50 km/h, cruise duration >=1.5 h,
Observing and controlling radius >=10 km, wind loading rating >=4 grade, sensor valid pixel >=24,000,000, peak of flight >=2000 m.
1.1.2 unmanned plane during flying parameter: the airspace for needing to obtain relevant departments before unmanned plane during flying uses license, flight
Height is 150-300 m, ship's control 80%, sidelapping degree 60%.
1.1.3 default 10-20 biological photo control point, 1 × 1 m of photo control point sample area are needed before flying2(such as Fig. 1 institute
Show), and photo control point GPS information and the acquisition of sargassum thunbergii quantity information are completed, it is representative that biological photo control point chooses different abundance
Sample prescription, each abundance photo control point >=3.
1.2 unmanned aerial vehicle remote sensing technical solutions:
1.2.1 the aerial survey time determines: determining the aerial survey time according to the tide time of survey region, aerial survey selects spring tide withered
It carries out in damp phase 0.5-2 h, intensity of illumination >=10000 lx when flight select fine day wind-force≤4 grade.
1.2.2 aerial survey parameter: aerial survey scale bar is 1:500, course line number >=4,0.05 cm of ground resolution.
1.2.3 remote sensing goes out graph parameter: coordinate system uses WGS 1984, and elevation uses 1985 state height reference projection sides
Formula selects transverse Mercator projection (utm projection).Image band number 3-5, image pixel depth 8bit, pixel value 0-255, figure
It is tiff that piece, which saves format,.
2, Inversion Calculation is carried out to sargassum thunbergii kelp bed using the method for the present invention combination ArcGIS, ENVI software.
2.1 determine sargassum thunbergii kelp bed distributed area
2.1.1 it establishes sargassum thunbergii distribution area file: remote sensing images is inputted into 10.0 software of ArcGIS, it is new in Catalog
Shapefile formatted file is built, Distribution is named as, attribute is face file, and coordinate system uses WGS 1984, UTM to throw
Shadow.
2.1.2 editor's sargassum thunbergii is distributed area file: Distribution file is edited in Editor tool, image is shown
Ratio is set as 1:100, draws sargassum thunbergii distribution situation (see figure 2) according to remote sensing images, saves after the completion of editor
Distribution file.
2.2 determine biological photo control point
2.2.1 it establishes sargassum thunbergii biology photo control point file: successively being established in Catalog according to photo control point number
Shapefile formatted file is named as XKD_ number, and attribute is face file, and coordinate system uses WGS 1984, utm projection.
2.2.2 it edits sargassum thunbergii biology photo control point file: successively editing files is numbered according to photo control point, according to the life of record
Object photo control point GPS information draws sargassum thunbergii biology photo control point file (see figure 3), saves file after the completion of editor.
2.3 establish remote-sensing inversion computation model
2.3.1 ENVI software extracts the image information of biological photo control point
Remote sensing images are inputted into ENVI4.7 software, biological photo control point file are loaded in ENVI4.7 software, and will be biological
Photo control point file saves as ROI(concern area Region Of Interest) file.(in Available Vectors List
Middle selection " File ", " Export files to ROI ... ")
Then the ROI the file information of ASCII fromat is exported in remote sensing images file.(in remote sensing images " Tool ",
" Region Of Interest ", " Output ROI to ASCII ... ".)
Corresponding color value information (respectively R value, G value, B are found in the ROI file of the ASCII fromat extracted
Value), image element information item number.
2.3.2 statistical analysis establishes Inversion Calculation model
Using color value as independent variable, seaweed quantity is dependent variable, to the color of image value (R value, G value, B value) extracted and
Photo control point seaweed quantity information carries out linear multiple regression statistical analysis, obtains and looks back equation:
Y=(aR+bG+cB+d) × n
Y makes a living object photo control point sargassum thunbergii quantity；
R, G, B are respectively R value, G value, the B value in ROI image colouring information；
A, b, c, d are respectively regression calculation computational constant coefficient；
N value is that ROI image extracts image element information item number.
As the regression coefficient r of regression analysis equation2When >=0.8, Inversion Calculation model is more accurate, if r2< 0.8, then
It needs to add photo control point or transformation returns statistical model.
2.4 calculate sargassum thunbergii kelp bed stock number using model
2.4.1 ENVI software extracts sargassum thunbergii distributed area image information
Remote sensing images are inputted into ENVI4.7 software, sargassum thunbergii is loaded in ENVI4.7 software and is distributed area file, and will be given birth to
Image control dot file saves as ROI(concern area Region Of Interest) file.(in Available Vectors
" File " is selected in List, " Export files to ROI ... ")
Then the ROI the file information of ASCII fromat is exported in remote sensing images file.(in remote sensing images " Tool ",
" Region Of Interest ", " Output ROI to ASCII ... ".)
Corresponding color value information (respectively R value, G value, B are found in the ROI file of the ASCII fromat extracted
Value), image element information item number.
2.4.2 sargassum thunbergii stock number is estimated using model
The color value information input model equation (R value, G value, B value) in the sargassum thunbergii distributed area of extraction is first calculated into single picture
Then the corresponding seaweed quantity of member calculates sargassum thunbergii algae bed total resources again.Wherein Y is sargassum thunbergii algae bed total resources, and n is picture
Metamessage item number, YiFor the seaweed quantity of single pixel.
Embodiment 2 is using appraisal procedure of the present invention measuring and calculating intertidal zone sargassum thunbergii algae bed stock number
1, unmanned aerial vehicle remote sensing:
Default 15 biological photo control points, 1 × 1 m of photo control point sample area are needed before flight2, and complete photo control point GPS letter
Breath and the acquisition of sargassum thunbergii quantity information, biological photo control point choose the representative sample prescription of different abundance, each abundance photo control point
>=3.
Use fixed-wing formula unmanned plane Shandong Rongcheng (E 122.5；N 37.2) coastal 1.2 km2Region carry out remote sensing inspection
It surveys, aerial survey selection spring tide is completed in withered damp 45 minutes phases, 25000-40000lx of intensity of illumination when aerial survey, and 3 grades of wind-force.Aerial survey
Scale bar is 1:500, and course line number 32,0.05 cm of ground resolution, flying height is 200 m, and ship's control 80% is other
To degree of overlapping 60%.
Coordinate system uses WGS 1984, and elevation selects transverse Mercator projection using 1985 state height reference projection modes
(utm projection).Image band number 3-5, image pixel depth 8bit, pixel value 0-255, it is tiff that picture, which saves format,.
2, Inversion Calculation is carried out to sargassum thunbergii kelp bed using the method for the present invention combination ArcGIS, ENVI software.
2.1 establish inverse model
Biological photo control point file is respectively created first with ArcGIS software, biology picture control is then used in ENVI software
It is for statistical analysis that dot file extracts color value (RGB).It is as follows:
R, G, B are respectively R value, G value, the B value in ROI image colouring information；
Y makes a living object photo control point sargassum thunbergii quantity；
N is pixel number.
Regression analysis equation:
Y/N = 0.072 R – 0.139 G + 0.059 B
That is: Y=(+0.059 B of 0.072 R -0.139 G) × N
Regression coefficient r2 = 0.884 ≥0.8
2.2 Inversion Calculation
It is distributed area file using ArcGIS software creation sargassum thunbergii, sargassum thunbergii distributed area text is then used in ENVI software
Part extracts color value (RGB), pixel color value is substituted into the regression equation of inverse model and Y is calculatediValue, then calculates
It is 61.2 ten thousand plants to the survey region sargassum thunbergii stock number.
Claims (4)
1. a kind of appraisal procedure of intertidal zone sargassum thunbergii algae bed stock number comprising following steps:
1) remote sensing images acquire: presetting multiple biological photo control points, control 1 × 1m of biological photo control point sample area2, biological photo control point
The representative sample prescription of different abundance, each abundance photo control point >=3 are chosen, and complete biological photo control point GPS information and mouse
The acquisition of tail algae quantity information；Intertidal zone sargassum thunbergii kelp bed is monitored using unmanned aerial vehicle remote sensing, obtains remote sensing images；
2) remote sensing images are inputted into 10.0 software of ArcGIS, shapefile formatted file is created in Catalog, coordinate system is adopted
With WGS 1984, utm projection, image display scale is set as 1:100, draws sargassum thunbergii distribution situation, editor according to remote sensing images
It saves after the completion and obtains remote sensing images file；Shapefile format text is successively established in Catalog according to photo control point number
Part is drawn according to photo control point number and sargassum thunbergii quantity information successively editing files according to the biological photo control point GPS information of record
Remote sensing images are inputted ENVI4.7 software by sargassum thunbergii biology photo control point file, and biological photo control point is loaded in ENVI4.7 software
Then file exports the ROI the file information of ASCII fromat, in the ROI of the ASCII fromat extracted in remote sensing images file
Corresponding color value information and image element information item number are found in file；The color value information includes R value, G value, B value；With face
Color value is independent variable, and sargassum thunbergii quantity is dependent variable, to the color of image value and photo control point sargassum thunbergii quantity information extracted into
The analysis of line Multiple regression statistics, obtains model equation:
Y=(aR+bG+cB+d) × n
Wherein Y makes a living object photo control point sargassum thunbergii quantity；R, G, B are respectively R value, G value, the B value in ROI image colouring information；a,
B, c, d are respectively regression calculation computational constant coefficient；N value is that ROI image extracts image element information item number；When regression analysis equation
Regression coefficient r2When >=0.8, Inversion Calculation model is more accurate, if r2< 0.8, then need to add photo control point or transformation returns
Statistical model；
3) remote sensing images are inputted into ENVI4.7 software, remote sensing images file is loaded in ENVI4.7 software, then in remote sensing figure
ROI the file information as exporting ASCII fromat in file, finds corresponding face in the ROI file of the ASCII fromat extracted
Colour information and image element information item number, the color value information R value, G value, B value；By the color in the sargassum thunbergii distributed area of extraction
Value information input model equation first calculates the corresponding seaweed quantity of single pixel, then calculates sargassum thunbergii algae bed total resources again.
2. the appraisal procedure of sargassum thunbergii algae in intertidal zone as described in claim 1 bed stock number, which is characterized in that described nobody
Machine configuration should be able to meet following condition: fixed-wing formula unmanned plane, speed per hour >=50km/h, cruise duration >=1.5h, observing and controlling half
Diameter >=10km, wind loading rating >=4 grade, sensor valid pixel >=24,000,000, peak of flight >=2000m.
3. the appraisal procedure of sargassum thunbergii algae in intertidal zone as described in claim 1 bed stock number, which is characterized in that described nobody
Flight parameter of machine during aerial survey: flying height 150-300m, ship's control 80%, sidelapping degree 60%；Boat
It surveys in selection of time spring tide withered damp phase 0.5-2h and carries out, intensity of illumination >=10000lx when flight selects fine day wind-force≤4 grade.
4. the appraisal procedure of intertidal zone sargassum thunbergii algae bed stock number as described in claim 1, which is characterized in that remote sensing goes out to scheme ginseng
Number are as follows: coordinate system uses WGS 1984, and elevation uses 1985 state height benchmark, and projection pattern selects transverse Mercator projection；
Image band number 3-5, image pixel depth 8bit, pixel value 0-255, it is tiff that image, which saves format,.
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