CN105869152A - Method and device for measuring spatial distribution of crop plant heights through unmanned plane remote sensing - Google Patents
Method and device for measuring spatial distribution of crop plant heights through unmanned plane remote sensing Download PDFInfo
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/0002—Inspection of images, e.g. flaw detection
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- G—PHYSICS
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- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/10—Image acquisition modality
- G06T2207/10032—Satellite or aerial image; Remote sensing
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- G—PHYSICS
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- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/30—Subject of image; Context of image processing
- G06T2207/30181—Earth observation
- G06T2207/30188—Vegetation; Agriculture
Abstract
The invention provides a method and device for measuring the spatial distribution of crop plant heights through unmanned plane remote sensing, and the method comprises the steps: obtaining an image sequence, collected by an airborne image sensor of an unmanned plane, of a target region; obtaining the POS information of photographing positions of all images in the image sequence; building a conversion relation between the image plane coordinates and physical coordinates according to the POS information; respectively building a DSM (digital surface model), comprising crop canopy information, of a crop coverage region in the target region and a BSM (basic surface model), corresponding to the bottom of crops, of the target region according to the image sequence and the conversion relation; and obtaining the spatial distribution of the crop plant heights in the target region according to the DSM and BSM. The method can obtain the large-area crop plant heights of a crop region under the condition of complex farmlands through employing the flexible maneuvering characteristics of unmanned plane remote sensing, and can solve problems that manual observation takes points as a plane, consumes a large amount of manpower and a large number of material resources, is severely affected by the subjectivity of a person, and is not consistent in data precision.
Description
Technical field
The present invention relates to unmanned aerial vehicle remote sensing measure and technical field of image processing, particularly relate to one
Unmanned aerial vehicle remote sensing measures the method and device of Plants high spatial distribution.
Background technology
Crop plant height is the Main Agronomic Characters parameter characterizing Different Crop kind, at broadacre agriculture
In production, identical crop varieties can directly affect ultimate output due to the difference of plant height.It is the most former
Cause is that plant height is closely related with crop ground biomass, and ground biomass associates with yield, institute
It it is the important agronomy parameter weighing crop growing state with usual plant height.Additionally, occur at field-crop
When flood, disaster caused by a windstorm, it may appear that crop lodges in a large number, and lodging degree and spatial distribution complicated,
It is difficult to be globally observed position by artificial observation when carrying out lodging investigation.For crop breeding,
Plant height is also important phenotypic information, in addition to the yield having influence on breeding material, goes back and crop
The association of characteristics such as resistant to lodging, is also the important indicator of crop breeding screening.
At present, major part Plants high measurement method is all to utilize ground survey equipment or device,
At single-point enterprising row crop height-measuring.It practice, due to crop continuous space covering on farmland,
Only measure plant height by marginally cake and be difficult to representative, the problem that there is Points replacing surfaces；
Existing Plants high measurement method all standing can not measure all field-crop plant heights, to obtain final product
Less than plant height continuous space distributed intelligence；And existing Plants high measurement method expends a large amount of
Manpower and materials, especially for complicated farmland condition, plant height measurement is difficult to carry out.
In consideration of it, the spatial distribution of how measurement target region crop plant height, and solve artificial sight
Survey Points replacing surfaces, expend a large amount of manpower and materials, data precision big by artificial subjective impact differs
The problems such as cause become to be presently required and solve the technical problem that.
Summary of the invention
For defect of the prior art, the present invention provides a kind of unmanned aerial vehicle remote sensing to measure Plants
The method and device of high spatial distribution, utilizes unmanned aerial vehicle remote sensing maneuverability characteristic to obtain on a large scale
The spatial distribution of vegetation district plant height under the conditions of complicated farmland, it is possible to solve artificial observation with point
For face, expend a large amount of manpower and materials, big by artificial subjective impact, data precision is inconsistent etc. asks
Topic, the maneuverability characteristic measured due to unmanned aerial vehicle remote sensing, greatly reduce ground survey work
Make, and ensure that the precision and concordance that plant height extracts.
First aspect, the present invention provides a kind of unmanned aerial vehicle remote sensing to measure the distribution of Plants high spatial
Method, including:
Obtain the image sequence of the target area of the onboard image sensor acquisition of unmanned plane；
Obtain the POS information of each image-capturing positions in described image sequence；
According to described POS information, set up the transformational relation between image plane coordinate and geographical coordinate；
According to described image sequence and described transformational relation, build the vegetation in target area
The digital surface model DSM comprising crop canopies spatial information in region；
According to described image sequence and described transformational relation, it is right to build bottom target area and crop
The basic terrain model BSM answered；
According to described DSM and BSM, obtain the spatial distribution of target area crop plant height.
Alternatively, in described image sequence, consecutive frame image degree of overlapping is more than the first preset value, institute
State degree of overlapping between unmanned plane adjacent course line and be more than or equal to the second preset value；
And/or,
Described POS information, including: longitude, latitude, elevation, roll, pitching and course.
Alternatively, the POS information of each image-capturing positions in the described image sequence of described acquisition,
Including:
Utilize aerial triangulation method, obtain each image-capturing positions in described image sequence
POS information.
Alternatively, described according to described POS information, set up image plane coordinate and geographical coordinate it
Between transformational relation, including:
According to described POS information, set up image plane coordinate based on geometry collinearity equation and sit with geographical
Transformational relation between mark.
Alternatively, described according to described image sequence with described transformational relation, build target area
In the digital surface model DSM comprising crop canopies spatial information in vegetation region, bag
Include:
According to described transformational relation, obtain each image vegetation region in described image sequence
The geographical coordinate that each pixel is corresponding；
Utilize triangular net method TIN, to the whole geographical coordinates on described vegetation region
Point carries out networking, and that sets up the vegetation region in target area comprises crop canopies space letter
The digital surface model DSM of breath；
Wherein, described DSM represents that the earth's core is to the crop canopies in vegetation region in target area
The height at top.
Alternatively, described according to described image sequence with described transformational relation, build target area
The basic terrain model BSM corresponding with bottom crop, including:
Choose in described image sequence and be in same horizontal plane bottom crop on each image earth's surface
Pixel, and according to described transformational relation, the earth's surface selected by acquisition is in bottom crop
The geographical coordinate that the pixel of same horizontal plane is corresponding；
Utilize triangular net method TIN, on selected earth's surface with crop bottom be in identical
The geographical coordinate point that the pixel of horizontal plane is corresponding carries out networking, sets up at the bottom of target area and crop
The basic terrain model BSM that portion is corresponding；
Wherein, described DSM represents that the earth's core is to the crop canopies in vegetation region in target area
The height of bottom, the overlay area of the BSM set up comprises the area of coverage of set up DSM
Territory.
Alternatively, described according to described DSM and BSM, obtain target area crop plant height
Spatial distribution, including:
Described DSM is deducted described BSM, obtains the work in vegetation region in target area
The spatial distribution of thing plant height.
Second aspect, the present invention provides a kind of unmanned aerial vehicle remote sensing to measure the distribution of Plants high spatial
Device, including:
First acquisition module, for obtaining the target area of the onboard image sensor acquisition of unmanned plane
The image sequence in territory；
Second acquisition module, for obtaining the POS of each image-capturing positions in described image sequence
Information；
Transformational relation sets up module, for according to described POS information, set up image plane coordinate with
Transformational relation between geographical coordinate；
First builds module, for according to described image sequence and described transformational relation, builds mesh
The digital surface model comprising crop canopies spatial information in the vegetation region in mark region
DSM；
Second builds module, for according to described image sequence and described transformational relation, builds mesh
The basic terrain model BSM that mark region is corresponding with bottom crop；
3rd acquisition module, for according to described DSM and BSM, obtains target area crop
The spatial distribution of plant height.
Alternatively, in described image sequence, consecutive frame image degree of overlapping is more than the first preset value, institute
State degree of overlapping between unmanned plane adjacent course line and be more than or equal to the second preset value；
And/or,
Described POS information, including: longitude, latitude, elevation, roll, pitching and course.
Alternatively, described second acquisition module, specifically for
Utilize aerial triangulation method, obtain each image-capturing positions in described image sequence
POS information；
And/or,
Described transformational relation sets up module, specifically for
According to described POS information, set up image plane coordinate based on geometry collinearity equation and sit with geographical
Transformational relation between mark；
And/or,
Described first builds module, specifically for
According to described transformational relation, obtain each image vegetation region in described image sequence
The geographical coordinate that each pixel is corresponding；Utilize triangular net method TIN, to described vegetation
Whole geographical coordinate points on region carries out networking, sets up the vegetation region in target area
The digital surface model DSM comprising crop canopies spatial information；
Wherein, described DSM represents that the earth's core is to the crop canopies in vegetation region in target area
The height at top；
And/or,
Described second builds module, specifically for
Choose in described image sequence and be in same horizontal plane bottom crop on each image earth's surface
Pixel, and according to described transformational relation, the earth's surface selected by acquisition is in bottom crop
The geographical coordinate that the pixel of same horizontal plane is corresponding；Utilize triangular net method TIN, to institute
Geographical coordinate point corresponding with the pixel being in same horizontal plane bottom crop on the earth's surface chosen
Carry out networking, set up the basic terrain model BSM that target area is corresponding with bottom crop；
Wherein, described DSM represents that the earth's core is to the crop canopies in vegetation region in target area
The height of bottom, the overlay area of the BSM set up comprises the area of coverage of set up DSM
Territory；
And/or,
Described 3rd acquisition module, specifically for
Described DSM is deducted described BSM, obtains the work in vegetation region in target area
The spatial distribution of thing plant height.
As shown from the above technical solution, the unmanned aerial vehicle remote sensing measurement Plants high spatial of the present invention divides
The method and device of cloth, by the target area of the onboard image sensor acquisition to unmanned plane
Image sequence processes, and build the vegetation region in target area comprises crop hat
The digital surface model DSM of sheaf space information and the target area basis corresponding with bottom crop
Terrain model BSM, and then the space of target area crop plant height is obtained according to DSM and BSM
Distribution, it is possible to solve artificial observation Points replacing surfaces, expend a large amount of manpower and materials, by artificial subjective
The problems such as impact is big, data precision is inconsistent, the maneuverability measured due to unmanned aerial vehicle remote sensing is special
Property, greatly reduce ground survey work, and ensure that the precision and concordance that plant height extracts.
Accompanying drawing explanation
Fig. 1 measures the distribution of Plants high spatial for the unmanned aerial vehicle remote sensing that one embodiment of the invention provides
The schematic flow sheet of method；
Fig. 2 measures the distribution of Plants high spatial for the unmanned aerial vehicle remote sensing that one embodiment of the invention provides
The structural representation of device.
Detailed description of the invention
For making the purpose of the embodiment of the present invention, technical scheme and advantage clearer, below will knot
Close the accompanying drawing in the embodiment of the present invention, the technical scheme in the embodiment of the present invention is carried out clear,
Be fully described by, it is clear that described embodiment be a part of embodiment of the present invention rather than
Whole embodiments, based on the embodiment in the present invention, those of ordinary skill in the art are not having
Every other embodiment acquired on the premise of making creative work, broadly falls into the present invention and protects
The scope protected.
Fig. 1 shows that the unmanned aerial vehicle remote sensing that one embodiment of the invention provides measures Plants high spatial
The schematic flow sheet of the method for distribution, as it is shown in figure 1, the unmanned aerial vehicle remote sensing of the present embodiment is measured
The method of Plants high spatial distribution, including:
101, the image sequence of the target area of the onboard image sensor acquisition of unmanned plane is obtained.
In a particular application, in described image sequence, consecutive frame image degree of overlapping is preset more than first
Value, between described unmanned plane adjacent course line, degree of overlapping is more than or equal to the second preset value.
Specifically, described first preset value is preferably 75%, and described second preset value is preferable
It is 30%.
In a particular application, the onboard image sensor of the present embodiment unmanned plane is preferably face battle array
High-definition digital camera, its pixel count is higher than 20,000,000 prime numbers.
In a particular application, in order to meet follow-up photogrammetric spatial trangulation needs, can root
According to unmanned plane during flying height, flight speed, the digital camera angle of visual field (FOV) size, calculate
Go out the frequency acquisition V (Hz) of onboard image sensor:
Wherein, S be unmanned plane during flying speed (m/s), H be unmanned plane during flying height (m), FOV
For digital camera angle of visual field size (radian), r is the image degree of overlapping needed for aerial triangulation
(%).
102, the POS information of each image-capturing positions in described image sequence is obtained.
In a particular application, described step 102, may include that
Utilize aerial triangulation method, obtain each image-capturing positions in described image sequence
POS information.
It will be appreciated that shoot image degree of overlapping, ground same point according to onboard image sensor
Can imaging on multiple photos, can use traditional photography measure and aerial triangulation method,
Accurately solving the accurate POS information of each coloured image camera site, described POS information can
To include: longitude (XPOS), latitude (YPOS), elevation (ZPOS)；RollPitching
(ω), course (κ) etc..
It will be appreciated that POS is the abbreviation of Position and Orientation System, it is low
Stable accuracy platform and high-precision attitude measure system, fixed by inertial measuring unit IMU and the whole world
Position system GPS combines.
103, according to described POS information, the conversion between image plane coordinate and geographical coordinate is set up
Relation.
In a particular application, described step 103, may include that
According to described POS information, set up image plane coordinate (row, column) based on geometry collinearity equation
And the transformational relation between geographical coordinate (longitude, latitude).
In a particular application, the transformational relation formula of stating specific as follows set up:
In formula,
Wherein, a1, a2, a3；b1, b2, b3；c1, c2, c3Represent geometry collinearity equation respectively
Middle pixel coordinate in geographical coordinate transformation process X, Y, Z tri-axle rotation, scale and flat
Shifting parameter；(M, N) is color image pixel coordinate；(X, Y, Z) is geographical coordinate after geometric correction；
F is the focal length of onboard image sensor.
104, according to described image sequence and described transformational relation, the crop in target area is built
The digital surface model DSM comprising crop canopies spatial information of overlay area.
In a particular application, described step 104, may include that
According to described transformational relation, obtain each image vegetation region in described image sequence
The geographical coordinate that each pixel is corresponding；
Utilize triangular net method TIN, to the whole geographical coordinates on described vegetation region
Point carries out networking, and that sets up the vegetation region in target area comprises crop canopies space letter
The digital surface model DSM of breath；
Wherein, described DSM represents that the earth's core is to the crop canopies in vegetation region in target area
The height at top.
105, according to described image sequence and described transformational relation, build at the bottom of target area and crop
The basic terrain model BSM that portion is corresponding.
In a particular application, owing to being blocked bottom crop, it is impossible to direct meter from image
Calculate, so described step 105, may include that
Choose in described image sequence and be in same horizontal plane bottom crop on each image earth's surface
Pixel (the exposed earth's surface that such as crop ridge exposed region in the ranks, or crop growing spots is adjacent),
And according to described transformational relation, the earth's surface selected by acquisition is in phase same level with bottom crop
The geographical coordinate that the pixel in face is corresponding；
Utilize triangular net method TIN, on selected earth's surface with crop bottom be in identical
The geographical coordinate point that the pixel of horizontal plane is corresponding carries out networking, sets up at the bottom of target area and crop
The basic terrain model BSM that portion is corresponding；
Wherein, described DSM represents that the earth's core is to the crop canopies in vegetation region in target area
The height of bottom, the overlay area of the BSM set up comprises the area of coverage of set up DSM
Territory.
106, according to described DSM and BSM, the spatial distribution of target area crop plant height is obtained.
In a particular application, described step 106 can particularly as follows:
Described DSM is deducted described BSM, obtains the work in vegetation region in target area
The spatial distribution of thing plant height.
It will be appreciated that owing to DSM and BSM is set up according to step 103
Transformational relation equation (2) is calculated, thus the space of DSM with BSM corresponding be identical,
All use unified Topography coordinates system, therefore for any point in vegetation district, the two X,
Y coordinate is all identical, different simply Z coordinate, i.e. elevation information.The former DSM is ground
The heart is to canopy overhead height, and the latter BSM is landform the earth's core to the height bottom crop canopies.Institute
With, only the two need to be subtracted each other plant height information H that i.e. can get arbitrfary point.
The unmanned aerial vehicle remote sensing of the present embodiment measures the method for Plants high spatial distribution, by nothing
The image sequence of the target area of man-machine onboard image sensor acquisition processes, and builds
The digital surface model comprising crop canopies spatial information in the vegetation region in target area
DSM and the target area basic terrain model BSM corresponding with bottom crop, and then according to DSM
With the spatial distribution that BSM obtains target area crop plant height, it is possible to solve artificial observation with a generation
Face, expend the problems such as a large amount of manpower and materials, big by artificial subjective impact, data precision is inconsistent,
The maneuverability characteristic measured due to unmanned aerial vehicle remote sensing, greatly reduces ground survey work,
And ensure that the precision and concordance that plant height extracts.
Fig. 2 measures the distribution of Plants high spatial for the unmanned aerial vehicle remote sensing that one embodiment of the invention provides
The structural representation of device, as in figure 2 it is shown, the unmanned aerial vehicle remote sensing of the present embodiment measures crop
The device of plant height spatial distribution, including: first acquisition module the 21, second acquisition module 22, turns
The relation of changing is set up module 23, first and is built module the 24, second structure module 25 and the 3rd acquisition
Module 26；
First acquisition module 21, for obtaining the target of the onboard image sensor acquisition of unmanned plane
The image sequence in region；
Second acquisition module 22, for obtaining each image-capturing positions in described image sequence
POS information；
Transformational relation sets up module 23, for according to described POS information, sets up image plane coordinate
And the transformational relation between geographical coordinate；
First builds module 24, for according to described image sequence and described transformational relation, builds
The digital surface model comprising crop canopies spatial information in the vegetation region in target area
DSM；
Second builds module 25, for according to described image sequence and described transformational relation, builds
The basic terrain model BSM that target area is corresponding with bottom crop；
3rd acquisition module 26, for according to described DSM and BSM, obtains target area and makees
The spatial distribution of thing plant height.
In a particular application, in described image sequence, consecutive frame image degree of overlapping is preset more than first
Value, between described unmanned plane adjacent course line, degree of overlapping is more than or equal to the second preset value.
Specifically, described first preset value is preferably 75%, and described second preset value is preferable
It is 30%.
In a particular application, the onboard image sensor of the present embodiment unmanned plane is preferably face battle array
High-definition digital camera, its pixel count is higher than 20,000,000 prime numbers.
In a particular application, in order to meet follow-up photogrammetric spatial trangulation needs, can root
According to unmanned plane during flying height, flight speed, the digital camera angle of visual field (FOV) size, calculate
The frequency acquisition V (Hz) of onboard image sensor:
Wherein, S be unmanned plane during flying speed (m/s), H be unmanned plane during flying height (m), FOV
For digital camera angle of visual field size (radian), r is the image degree of overlapping needed for aerial triangulation
(%).
In a particular application, described second acquisition module 22, can be specifically for
Utilize aerial triangulation method, obtain each image-capturing positions in described image sequence
POS information.
It will be appreciated that shoot image degree of overlapping, ground same point according to onboard image sensor
Can imaging on multiple photos, can use traditional photography measure and aerial triangulation method,
Accurately solving the accurate POS information of each coloured image camera site, described POS information can
To include: longitude (XPOS), latitude (YPOS), elevation (ZPOS)；RollPitching
(ω), course (κ) etc..
It will be appreciated that POS is the abbreviation of Position and Orientation System, it is low
Stable accuracy platform and high-precision attitude measure system, fixed by inertial measuring unit IMU and the whole world
Position system GPS combines.
In a particular application, described transformational relation sets up module 23, can be specifically for
According to described POS information, set up image plane coordinate (row, column) based on geometry collinearity equation
And the transformational relation between geographical coordinate (longitude, latitude).
In a particular application, the transformational relation formula of stating specific as follows set up:
In formula,
Wherein, a1, a2, a3；b1, b2, b3；c1, c2, c3Represent geometry collinearity equation respectively
Middle pixel coordinate in geographical coordinate transformation process X, Y, Z tri-axle rotation, scale and flat
Shifting parameter；(M, N) is color image pixel coordinate；(X, Y, Z) is geographical coordinate after geometric correction；
F is the focal length of onboard image sensor.
In a particular application, described first builds module 24, can be specifically for
According to described transformational relation, obtain each image vegetation region in described image sequence
The geographical coordinate that each pixel is corresponding；Utilize triangular net method TIN, to described vegetation
Whole geographical coordinate points on region carries out networking, sets up the vegetation region in target area
The digital surface model DSM comprising crop canopies spatial information；
Wherein, described DSM represents that the earth's core is to the crop canopies in vegetation region in target area
The height at top.
In a particular application, owing to being blocked bottom crop, it is impossible to direct meter from image
Calculate, so described second builds module 25, can be specifically for
Choose in described image sequence and be in same horizontal plane bottom crop on each image earth's surface
Pixel (the exposed earth's surface that such as crop ridge exposed region in the ranks, or crop growing spots is adjacent),
And according to described transformational relation, the earth's surface selected by acquisition is in phase same level with bottom crop
The geographical coordinate that the pixel in face is corresponding；
Utilize triangular net method TIN, on selected earth's surface with crop bottom be in identical
The geographical coordinate point that the pixel of horizontal plane is corresponding carries out networking, sets up at the bottom of target area and crop
The basic terrain model BSM that portion is corresponding；
Wherein, described DSM represents that the earth's core is to the crop canopies in vegetation region in target area
The height of bottom, the overlay area of the BSM set up comprises the area of coverage of set up DSM
Territory.
In a particular application, described 3rd acquisition module 26, can be specifically for
Described DSM is deducted described BSM, obtains the work in vegetation region in target area
The spatial distribution of thing plant height.
It will be appreciated that owing to DSM and BSM is set up according to step 103
Transformational relation equation (2) is calculated, thus the space of DSM with BSM corresponding be identical,
All use unified Topography coordinates system, therefore for any point in vegetation district, the two X,
Y coordinate is all identical, different simply Z coordinate, i.e. elevation information.The former DSM is ground
The heart is to canopy overhead height, and the latter BSM is landform the earth's core to the height bottom crop canopies.Institute
With, only the two need to be subtracted each other plant height information H that i.e. can get arbitrfary point.
The unmanned aerial vehicle remote sensing of the present embodiment measures the device of Plants high spatial distribution, utilizes unmanned
The sky of vegetation district plant height under the conditions of machine remote sensing maneuverability characteristic acquisition complicated farmland on a large scale
Between be distributed, it is possible to solve artificial observation Points replacing surfaces, expend a large amount of manpower and materials, artificially led
Viewing rings the problems such as big, data precision is inconsistent, the maneuverability measured due to unmanned aerial vehicle remote sensing
Characteristic, greatly reduces ground survey work, and ensure that precision that plant height extracts is with consistent
Property.
The unmanned aerial vehicle remote sensing of the present embodiment measures the device of Plants high spatial distribution, may be used for
Performing the technical scheme of embodiment of the method shown in earlier figures 1, it realizes principle and technique effect class
Seemingly, here is omitted.
" first ", " second " and " the 3rd " etc. is not to elder generation in embodiments of the present invention
Rear order makes regulation, simply title is made difference, in embodiments of the present invention, does not does
Go out any restriction.
One of ordinary skill in the art will appreciate that: realize the whole of above-mentioned each method embodiment or
Part steps can be completed by the hardware that programmed instruction is relevant.Aforesaid program can store
In a computer read/write memory medium.This program upon execution, performs to include above-mentioned each side
The step of method embodiment；And aforesaid storage medium includes: ROM, RAM, magnetic disc or light
The various medium that can store program code such as dish.
It is last it is noted that various embodiments above is only in order to illustrate technical scheme,
It is not intended to limit；Although the present invention being described in detail with reference to foregoing embodiments,
It will be understood by those within the art that: it still can be to described in foregoing embodiments
Technical scheme modify, or the most some or all of technical characteristic carried out equivalent replace
Change；And these amendments or replacement, do not make the essence of appropriate technical solution depart from the present invention each
The scope of embodiment technical scheme.
Claims (10)
1. the method that a unmanned aerial vehicle remote sensing measures the distribution of Plants high spatial, it is characterised in that
Including:
Obtain the image sequence of the target area of the onboard image sensor acquisition of unmanned plane；
Obtain the POS information of each image-capturing positions in described image sequence；
According to described POS information, set up the transformational relation between image plane coordinate and geographical coordinate；
According to described image sequence and described transformational relation, build the vegetation in target area
The digital surface model DSM comprising crop canopies spatial information in region；
According to described image sequence and described transformational relation, it is right to build bottom target area and crop
The basic terrain model BSM answered；
According to described DSM and BSM, obtain the spatial distribution of target area crop plant height.
Method the most according to claim 1, it is characterised in that phase in described image sequence
Adjacent two field picture degree of overlapping is more than the first preset value, and between described unmanned plane adjacent course line, degree of overlapping is more than
Equal to the second preset value；
And/or,
Described POS information, including: longitude, latitude, elevation, roll, pitching and course.
Method the most according to claim 1, it is characterised in that the described image of described acquisition
The POS information of each image-capturing positions in sequence, including:
Utilize aerial triangulation method, obtain each image-capturing positions in described image sequence
POS information.
Method the most according to claim 1, it is characterised in that described according to described POS
Information, sets up the transformational relation between image plane coordinate and geographical coordinate, including:
According to described POS information, set up image plane coordinate based on geometry collinearity equation and sit with geographical
Transformational relation between mark.
Method the most according to claim 1, it is characterised in that described according to described image
Sequence and described transformational relation, build the vegetation region in target area comprises crop hat
The digital surface model DSM of sheaf space information, including:
According to described transformational relation, obtain each image vegetation region in described image sequence
The geographical coordinate that each pixel is corresponding；
Utilize triangular net method TIN, to the whole geographical coordinates on described vegetation region
Point carries out networking, and that sets up the vegetation region in target area comprises crop canopies space letter
The digital surface model DSM of breath；
Wherein, described DSM represents that the earth's core is to the crop canopies in vegetation region in target area
The height at top.
Method the most according to claim 1, it is characterised in that described according to described image
Sequence and described transformational relation, build the basic terrain model that target area is corresponding with bottom crop
BSM, including:
Choose in described image sequence and be in same horizontal plane bottom crop on each image earth's surface
Pixel, and according to described transformational relation, the earth's surface selected by acquisition is in bottom crop
The geographical coordinate that the pixel of same horizontal plane is corresponding；
Utilize triangular net method TIN, on selected earth's surface with crop bottom be in identical
The geographical coordinate point that the pixel of horizontal plane is corresponding carries out networking, sets up at the bottom of target area and crop
The basic terrain model BSM that portion is corresponding；
Wherein, described DSM represents that the earth's core is to the crop canopies in vegetation region in target area
The height of bottom, the overlay area of the BSM set up comprises the area of coverage of set up DSM
Territory.
Method the most according to claim 1, it is characterised in that described according to described DSM
And BSM, obtain the spatial distribution of target area crop plant height, including:
Described DSM is deducted described BSM, obtains the work in vegetation region in target area
The spatial distribution of thing plant height.
8. a unmanned aerial vehicle remote sensing measures the device that Plants high spatial is distributed, it is characterised in that
Including:
First acquisition module, for obtaining the target area of the onboard image sensor acquisition of unmanned plane
The image sequence in territory；
Second acquisition module, for obtaining the POS of each image-capturing positions in described image sequence
Information；
Transformational relation sets up module, for according to described POS information, set up image plane coordinate with
Transformational relation between geographical coordinate；
First builds module, for according to described image sequence and described transformational relation, builds mesh
The digital surface model comprising crop canopies spatial information in the vegetation region in mark region
DSM；
Second builds module, for according to described image sequence and described transformational relation, builds mesh
The basic terrain model BSM that mark region is corresponding with bottom crop；
3rd acquisition module, for according to described DSM and BSM, obtains target area crop
The spatial distribution of plant height.
Device the most according to claim 8, it is characterised in that phase in described image sequence
Adjacent two field picture degree of overlapping is more than the first preset value, and between described unmanned plane adjacent course line, degree of overlapping is more than
Equal to the second preset value；
And/or,
Described POS information, including: longitude, latitude, elevation, roll, pitching and course.
Device the most according to claim 8, it is characterised in that described second obtains mould
Block, specifically for
Utilize aerial triangulation method, obtain each image-capturing positions in described image sequence
POS information；
And/or,
Described transformational relation sets up module, specifically for
According to described POS information, set up image plane coordinate based on geometry collinearity equation and sit with geographical
Transformational relation between mark；
And/or,
Described first builds module, specifically for
According to described transformational relation, obtain each image vegetation region in described image sequence
The geographical coordinate that each pixel is corresponding；Utilize triangular net method TIN, to described vegetation
Whole geographical coordinate points on region carries out networking, sets up the vegetation region in target area
The digital surface model DSM comprising crop canopies spatial information；
Wherein, described DSM represents that the earth's core is to the crop canopies in vegetation region in target area
The height at top；
And/or,
Described second builds module, specifically for
Choose in described image sequence and be in same horizontal plane bottom crop on each image earth's surface
Pixel, and according to described transformational relation, the earth's surface selected by acquisition is in bottom crop
The geographical coordinate that the pixel of same horizontal plane is corresponding；Utilize triangular net method TIN, to institute
Geographical coordinate point corresponding with the pixel being in same horizontal plane bottom crop on the earth's surface chosen
Carry out networking, set up the basic terrain model BSM that target area is corresponding with bottom crop；
Wherein, described DSM represents that the earth's core is to the crop canopies in vegetation region in target area
The height of bottom, the overlay area of the BSM set up comprises the area of coverage of set up DSM
Territory；
And/or,
Described 3rd acquisition module, specifically for
Described DSM is deducted described BSM, obtains the work in vegetation region in target area
The spatial distribution of thing plant height.
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