CN108334110A - A kind of forestry disease monitoring method and apparatus based on unmanned plane - Google Patents
A kind of forestry disease monitoring method and apparatus based on unmanned plane Download PDFInfo
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- G05D1/101—Simultaneous control of position or course in three dimensions specially adapted for aircraft
Abstract
The forestry disease monitoring method and apparatus based on unmanned plane that the invention discloses a kind of, by carrying the double light cameras integrated by Visible Light Camera and near infrared camera on unmanned plane, the forest for treating monitoring region carries out monitoring of taking photo by plane, pass through the analysis to data of taking photo by plane, fully combine visible light image information and vegetation index orthophotoquad, apparent health or trees in heaven are selected with visible light image information, judged in conjunction with NDVI indexs are further, to quickly, dead tree that is accurate and efficiently determining region to be monitored and disease tree information, it is not high come judging efficiency caused by identifying forestry disease to overcome single use visible images or NDVI indexs, the lower present situation of accuracy, it can not be quick when forestry pests ＆ diseases occur to solve the prior art, the problem of being exactly found disease tree and dead tree.
Description
Technical field
The invention belongs to forestry pests ＆ diseases to monitor field, more particularly to a kind of forestry disease monitoring method based on unmanned plane
And device.
Background technology
Forest occupies an important position in national economy, it be only capable of providing timber needed for nation-building and people's lives and
Secondary product of forestry, but also bear release oxygen, regulate the climate, water conservation, conserve water and soil, check winds and fix drifting sand, beautifying the environment, only
Change air, reduce a variety of missions such as noise and touring health care.Meanwhile the essential condition of forest or farming and animal husbandry high and stable yields.
However, the example that forestry disease destroys large stretches of forests happens occasionally.Such as from the incoming north of chestnut epidemic disease before and after 1904
After U.S., is just destroyed less than 40 years and be equivalent to 54,000,000 mu or so of U.S. Chinese chestnut pure forest, kept an economic value very high
Seeds be difficult to continue on for afforesting.Early 20th century once made the white pine of this area a large amount of in the pine blister rust of North America prevalence
Death, so far still without appropriate prevention and treatment method.This disease is since the fifties, in the KOREAN PINE PLANTATIONS of Northeast Area of China
Constantly sprawling, some standing forest death rates have the tendency that increasingly extending up to 40% or more.For another example pine nematode in the U.S., adds
It puts on airs, Mexico, Japan, the states such as South Korea have generation, the 1980s to invade Hong-Kong, almost destroyed Hong Kong distribution
Extensive masson pine forest.Nineteen eighty-two is found for the first time in the Nanjing Zhongshan Tomb, then in succession on Anhui, Shandong, Zhejiang, Guangdong and other places
Several Disease Centers are formed, and are spread around, makes some areas generation of these provinces and prevalence is caused disaster, cause large quantities of pine trees withered
Extremely.The economic loss that pine nematode is brought to Anhui, two province of Zhejiang is up to 500,000,000~700,000,000 yuan.
Quickly, and communication media of disease itself colonizes on disease tree the spread speed of many forestry diseases again, therefore, right
It is exactly to find disease tree in time and extremely set, and disease tree and dead set are cut down into processing in preferably a kind of processing method of certain forestry diseases
(such as high-temperature process, medicament fumigating are handled), to prevent the sprawling of disease.
In the prior art, the mode that forest epidemic monitoring relies primarily on ground artificial generaI investigation and satellite monitoring is combined.
The area of woods in China is huge, and distribution poly combines in mountain area, and personnel are limited, thus it is very big by difficulty is monitored on foot, at
This is very high, it is difficult to be covered to forest zone comprehensively；In addition many forestry disease spreads are very fast, and artificial generaI investigation is unable to reach immediately
It was found that timely processing, can still cause greater loss.The ranges such as satellite remote sensing are big, but limited resolution, by cloud layer, water
The influence of the factors such as vapour, haze is very big, therefore the acquisition of high-precision image is more difficult.
Invention content
The forestry disease monitoring method and apparatus based on unmanned plane that the present invention provides a kind of, it is intended that overcoming existing
The problem of having in technology that Health of Tree situation can not monitor in real time in woodland area, and can not effectively determining disease position.
The present invention adopts the following technical scheme that：
A kind of forestry disease monitoring method based on unmanned plane, includes the following steps：
Step 1：Obtain multiple continuous visible images and near-infrared image in region to be monitored simultaneously using unmanned plane；
By will be seen that light camera, near infrared camera are mounted on the unmanned plane, waited for described according to the course line of setting
Monitoring region is taken photo by plane, multiple continuous visible images, near-infrared images are obtained；
Step 2：Described multiple continuous visible images, near-infrared images are corrected and are spliced respectively, institute is obtained
State the visible light orthophotoquad and near-infrared orthophotoquad in region to be monitored；
Step 3：The area to be monitored is obtained by the visible light orthophotoquad and the near-infrared orthophotoquad
The vegetation-cover index NDVI of same position in domain builds the vegetation index orthography in the region to be monitored
Figure；
The vegetation-cover index is obtained by visible light orthophotoquad and near-infrared orthophotoquad；
Visible Light Camera obtains red spectral band data, the reflected value R of red spectral band；Near infrared camera obtains near infrared band
Data, the reflected value NIR of near infrared band；NDVI=(NIR-R)/(NIR+R)；
Step 4：Choose the position where N dead tree and N health tree respectively from the visible light orthophotoquad, and
The NDVI values that described N dead tree and N health tree are obtained from the vegetation index orthophotoquad, count institute
NDVI the mean values B, N >=2, N for stating NDVI mean values A and the N health tree that N is extremely set are positive integer；
Step 5：According to step 4 obtain A, B, to step 3 obtain vegetation index orthophotoquad into
Row forestry Disease Analysis obtains the Health of Tree situation in the region to be monitored；
From the vegetation index orthophotoquad, each position x in the region to be monitored is obtained successively
NDVI value NDVI (x), as 0≤NDVI (x)≤A, the trees for being located at x position are dead tree；As A ＜ NDVI (x) ＜ B, position
It is that disease is set in the trees of x position；As B≤NDVI (x)≤1, the trees for being located at x position are that health is set.
Further, the Health of Tree situation according to the region to be monitored, to the dead tree in the region to be monitored and disease
Tree sum, distribution and bottom class's information are counted.
In forestry, many bottom classes are divided into per a piece of forest farm, are a kind of organization units, such as finds a dead tree, it should
Trees may carry Bursaphelenchus xylophilus, need in time to dispose this dead tree at this time, geographical location of this tree be it is known, it
Corresponding bottom class (which bottom class is returned to be responsible for) is exactly known；
Further, the elevation information of height H and the region to be monitored are required according to the unmanned plane during flying of setting, are determined
Unmanned plane shoots course line；
The elevation information in the region to be monitored includes the height above sea level point for waiting for the monitoring region highs and lows
It Wei not C and D；
If H ＞ C-D, the unmanned plane flies in the region to be monitored according to the height above sea level of H+D；
If H≤C-D, the region to be monitored is divided into M region according to height above sea level, in j-th of region
The interior height above sea level according to jH+D is flown, wherein the height value of the peak in j-th of region and the difference of D are L, and (j-1)
H≤L ＜ jH, 1≤j≤M, M, j are positive integer.
A kind of forestry disease monitoring device based on unmanned plane, including：
Image acquisition units, by will be seen that light camera, near infrared camera are mounted on unmanned plane, according to the course line of setting
It takes photo by plane to the region to be monitored, obtains multiple continuous visible images, near-infrared images；
First image processing unit, visible images, near-infrared image for obtaining the unmanned plane carry out respectively
Correction and splicing, obtain the visible light orthophotoquad and near-infrared orthophotoquad in region to be monitored；
Second image processing unit, for being obtained from the visible light orthophotoquad and the near-infrared orthophotoquad
The vegetation-cover index NDVI of same position in the region to be monitored builds the normalization difference vegetation in the region to be monitored
Index orthophotoquad；
Trees index determination unit, for choosing N dead tree and health tree respectively from the visible light orthophotoquad
The position at place, and obtain from the vegetation index orthophotoquad described N dead tree and it is described N it is strong
The NDVI values of Kang Shu determine that NDVI the mean values B, N >=2, N for the NDVI mean values A and the N health tree that described N is extremely set are
Positive integer；
Analytic unit returns second image processing unit according to A, B that trees index determination unit obtains
One, which changes difference vegetation index orthophotoquad, carries out forestry Disease Analysis, obtains the Health of Tree situation in the region to be monitored；
From the vegetation index orthophotoquad, each position x in the region to be monitored is obtained successively
NDVI value NDVI (x), as 0≤NDVI (x)≤A, the trees for being located at x position are dead tree；As A ＜ NDVI (x) ＜ B, position
It is that disease is set in the trees of x position；As B≤NDVI (x)≤1, the trees for being located at x position are healthy trees.
Further, further include statistic unit, Health of Tree situation of the statistic unit according to the region to be monitored,
Dead tree and disease tree sum, distribution and bottom class's information to the region to be monitored count.
Further, further include flying height planning unit, unmanned plane of the flying height planning unit according to setting
Flight requires the elevation information of height H and region to be monitored, determines that unmanned plane shoots course line；
The elevation information that the region to be monitored is obtained using elevation information collecting unit include the region to be monitored most
The height above sea level of high point and minimum point is respectively C and D；
If H ＞ C-D, the unmanned plane flies in the region to be monitored according to the height above sea level of H+D；
If H≤C-D, the region to be monitored is divided into M region according to height above sea level, in j-th of region
The interior height above sea level according to jH+D is flown, wherein the height value of the peak in j-th of region and the difference of D are L, and (j-1)
H≤L ＜ jH, 1≤j≤M, M, j are positive integer.
Advantageous effect
The forestry disease monitoring method and apparatus based on unmanned plane that the present invention provides a kind of, by being carried on unmanned plane
The double light cameras integrated by Visible Light Camera and near infrared camera, the forest for treating monitoring region carry out monitoring of taking photo by plane, pass through
Analysis to data of taking photo by plane fully combines visible light image information and vegetation index orthophotoquad, with visible
Light image information selects apparent health or trees in heaven, is judged in conjunction with NDVI indexs are further, to quick, accurate
Dead tree and the disease tree information for efficiently determining region to be monitored, overcome single use visible images or NDVI indexs to know
Judging efficiency caused by other forestry disease is high, the lower present situation of accuracy, and forestry disease pest is occurring to solve the prior art
Evil when can not quickly, be exactly found disease tree and extremely set the problem of.
Description of the drawings
Fig. 1 is a kind of flow diagram of the forestry disease monitoring method based on unmanned plane of the present invention；
Fig. 2 is the flow diagram that practical flight height is determined in the method for the invention；
Fig. 3 is a kind of structural schematic diagram of the forestry disease monitoring device based on unmanned plane of the present invention.
Specific implementation mode
Following will be combined with the drawings in the embodiments of the present invention, and technical solution in the embodiment of the present invention carries out clear, complete
Site preparation describes, it is clear that described embodiments are only a part of the embodiments of the present invention, instead of all the embodiments.It is based on
Embodiment in the present invention, it is obtained by those of ordinary skill in the art without making creative efforts every other
Embodiment shall fall within the protection scope of the present invention.
For solve the problems, such as the prior art when forestry pests ＆ diseases occur can not quickly, be exactly found disease tree, in conjunction with Fig. 1,
The forestry disease monitoring method based on unmanned plane that an embodiment of the present invention provides a kind of, this method include：
S101, multiple the continuous visible images and near-infrared figure for obtaining region to be monitored simultaneously using unmanned plane；
By will be seen that light camera, near infrared camera are mounted on the unmanned plane, waited for described according to the course line of setting
Monitoring region is taken photo by plane, multiple continuous visible images, near-infrared images are obtained；
Wherein, the double light cameras of UAV flight, double light cameras include Visible Light Camera and near infrared camera.
Vegetation has different absorptions and reflection spectrum characteristic in different wave bands.Such as in visible light wave range, in
It is Chlorophyll absorption peak that cardiac wave length, which is respectively in two bands of a spectrum of 0.45 μm (blue) and 0.65 μm (red), (green at 0.54 μm
Color) nearby there are one reflection peaks.In the infrared stage of spectrum, the spectral response of green plants is mainly by 1.4 μm, 1.9 μm and 2.7
The strong absorption band of water near μm is dominated.
Floor vegetation has apparent Huanghe River Estuary, is different from soil, water body and other typical features, vegetation pair
The response of electromagnetic wave is determined by its chemical feature and morphological feature, the development of this feature and vegetation, health status with
And growth conditions is closely related.
Therefore, by the data of the visible light wave band of trees, in conjunction with the data of near infrared light spectral band, so that it may with
The health degree of trees in forest is accurately differentiated.
Wherein, in aviation is taken pictures, to ensure the requirement of resolution ratio, it is seen that light camera usually requires high pixel, supports GPS
Position and be collocated with large capacity internal memory card and tight shot.
Near-infrared, English name near infrared, be defined as wavelength 780~3000nm ranges electromagnetic wave.To planting
Object reflected light is very sensitive.
Near-infrared industrial camera has the technical advantages such as stable and reliable for performance, is to be applied to industrial occasions, exists to wavelength
The digital imaging apparatus of the electromagnetic wave induction sensitivity of 780-3000nm ranges.The output of near-infrared industrial camera is uncorrected data, is fitted
Close the applications such as the image processing algorithm, such as Machine Vision Detection for carrying out high quality.
Near infrared camera enhances sensitivity, particularly suitable for taking pictures to vegetation, perceives spectral signature.Pass through
The feature of disease and normal plant compares, the characteristic information extracted, and analysis is digitized according to the result taken pictures.
By carrying Visible Light Camera and near infrared camera on unmanned plane, aviation bat is carried out to monitored forest region
According to obtaining multiple continuous visible images, near-infrared images, the analysis foundation as Health of Tree degree.
S102, described multiple continuous visible images, near-infrared images are corrected and are spliced respectively, described in acquisition
The visible light orthophotoquad and near-infrared orthophotoquad in region to be monitored；
In conjunction with the positioning and orientation system (English of unmanned plane acquisition back：Positioning and Orientation
System, referred to as：POS) data, to multiple continuous visible images, the near-infrareds of unmanned plane acquisition back in step S101
Image spliced respectively, correction process, obtains the visible light orthophotoquad and near-infrared orthophotoquad in region to be monitored.
S103, it is obtained in region to be monitored together by the visible light orthophotoquad and the near-infrared orthophotoquad
The vegetation-cover index NDVI of one position builds the vegetation index orthophotoquad in the region to be monitored；
The vegetation-cover index is obtained by visible light orthophotoquad and near-infrared orthophotoquad；
Vegetation index (English：Normalized Difference Vegetation Index, referred to as：
NDVI) obtained by red spectral band reflectance value in visible light and carrying out operation to multispectral interior near infrared band reflectance value
It arrives, specific expression formula is：NDVI=(NIR-R)/(NIR+R)；
Wherein, NIR is near infrared band reflectance value, and R is red wave band reflectance value.
It is the best indicator of plant growth state and vegetation spacial distribution density, is in line with vegetation distribution density
Property it is related.
Normalization refers to being limited between [- 1,1], is easy to use, including assigns pseudo-colours and computer program operation.
Wherein negative loop indicates that covered ground is cloud, water, snow etc., to visible light high reflection；0 indicates rock, soil or extremely
The trees etc. died；Positive value indicates vegetative coverage, as numerical value increases coverage rate and health degree increase.NDVI can largely disappear
Except the reasons such as angular error, landform and cloud layer caused by optical aberrations, equipment of taking photo by plane caused by sun altitude and atmospheric oscillation
Caused by available light error influence, the shade of structure of community and radiation interference.
In addition, experiment shows that NDVI is more sensitive to the variation of Soil Background；It is vegetation pattern in unit pixel,
The concentrated expression of form, upgrowth situation etc. is covered, size depends on the elements such as vegetation coverage and leaf area index；NDVI pairs
The detection amplitude of vegetation coverage is wider, there is preferable time and space adaptability.
It should be noted that the acquisition of NDVI needs two kinds of data of NIR and R.R data can pass through visible light orthophotoquad
It obtains, NIR can be obtained by near-infrared orthophotoquad.
S104, the position for choosing N dead tree and N health tree place respectively from the visible light orthophotoquad, and
The NDVI values that described N dead tree and N health tree are obtained from the vegetation index orthophotoquad, count N
The NDVI mean values A extremely set and NDVI the mean values B, N >=2, N of the N health tree are positive integer；
Visible light orthophotoquad can clearly, intuitively show the growth conditions of trees and healthy shape in region to be monitored
State is set by choosing more apparent dead trees and healthy trees from visible light orthophotoquad by this more dead trees and health
Location information of the wood in visible light orthophotoquad finds this more disease trees and healthy trees in NDVI orthophotoquads
Corresponding position, to obtain the NDVI values corresponding to this more disease trees and healthy trees.
NDVI is the best indicator of vegetation growth state and vegetation coverage, by counting from visible light positive photograph picture
The average value of the NDVI values of the average value A of the NDVI values for the more apparent disease trees chosen in figure and more apparent healthy trees
B.As the foundation by region NDVI orthography map analysis plant health state in region to be monitored to be monitored, can be quickly found out
Disease tree in region to be monitored and dead tree.
A, B that S105, foundation obtain carry out forestry disease prison to the vegetation index orthophotoquad of acquisition
It surveys, obtains the Health of Tree situation in region to be monitored；
From vegetation index orthophotoquad, the NDVI values of each position x in region to be monitored are obtained successively
NDVI (x), as 0≤NDVI (x)≤A, the trees for being located at x position are dead tree；As A ＜ NDVI (x) ＜ B, it is located at x position
Trees are that disease is set；As B≤NDVI (x)≤1, the trees for being located at x position are healthy trees.
It therefore, can by analyzing visible light orthophotoquad and vegetation index orthophotoquad
Disease tree that is accurate and quickly obtaining region to be monitored and dead tree information, disease tree and dead tree information are including but not limited to be monitored
The disease tree in region and dead tree sum, distribution and geography information and bottom class's information.
In forestry, many bottom classes are divided into per a piece of forest farm, are a kind of organization units, when one dead tree of discovery or disease tree
Afterwards, it when which may carry the propagated stronger forestry disease such as Bursaphelenchus xylophilus, needs this dead tree processing at this time in time
To fall, geographical location of this tree is known, known to bottom class corresponding to it (which bottom class is returned to be responsible for) is exactly, so as to
The sprawling of enough effectively containment pest and disease damages.
In addition, to woodland area to be monitored carry out image taking when, due to the height above sea level in region to be monitored there may be
Difference needs the height above sea level to different zones, is carried out control as follows, as shown in Figure 2, it is ensured that nothing to the flying height of unmanned plane
It is man-machine to obtain clear complete image.
There are many technical indicators for judging picture quality, such as image resolution ratio, image scale.According to unmanned plane institute
The purposes differences of the data of acquisition, function difference etc. are also different to the quality requirement of image.It is had determined that in the requirement of picture quality
When, according to parameters such as the pixels, the endlap rate of flight, sidelapping rate of unmanned plane double light cameras mounted, in conjunction with existing
The flight standard that some computational methods can calculate unmanned plane requires height H.
For example, when 50,600,000 pixel silent frame Visible Light Cameras collocation 35mm tight shots, it is desirable that obtain 0.1 meter
Ground resolution, and endlap 80% is needed, it is high then can to calculate flight by existing computational methods for sidelapping 60%
About 844 meters, i.e. H=844 meters of degree.
Determine the elevation information in region to be monitored；
Elevation refers to that certain point along the distance in plumb line direction to absolute datum, claims absolute elevation, abbreviation elevation.With Hai Ping
Face is that the elevation of absolute datum is absolute elevation, also referred to as height above sea level.Determine the elevation information in region to be monitored, mainly really
The height above sea level D of the height above sea level C and minimum point of the peak in fixed region to be monitored；
The elevation information that height H and region to be monitored are required according to the unmanned plane during flying of setting determines unmanned plane shooting boat
Line；
The unmanned plane during flying requires height that should meet image quality requirements, or is better than image quality requirements；
The elevation information in the region to be monitored includes that the height above sea level of region highs and lows to be monitored is respectively C
And D；
If H ＞ C-D, the unmanned plane flies in the region to be monitored according to the height above sea level of H+D；
If H≤C-D, the region to be monitored is divided into M region according to height above sea level, in j-th of region
The interior height above sea level according to jH+D is flown, wherein the height value of the peak in j-th of region and the difference of D are L, and (j-1)
H≤L ＜ jH, 1≤j≤M, M, j are positive integer.For example, the absolute elevation value C of region peak to be monitored is 500 meters, most
The absolute elevation value D of low spot is 100 meters, is 844 meters by the way that H is calculated, then height above sea level path difference C-D=400 meters of ＜ H, at this point,
In entire region to be monitored according to 844 meters of the relative altitude with minimum point D, i.e., 944 meters of height above sea level is flown unmanned plane
Row operation；
If the absolute elevation value C of region peak to be monitored is 1300 meters, the absolute elevation value D of minimum point is 100 meters, then
The height above sea level path difference of the highest point and the lowest point is 1200 meters, if it is 844 meters that aircraft flight requirement height H, which is calculated, H≤C-
D, at this point, region to be monitored is divided into two regions, the 1st height value of region peak and the difference of D should be L1,0≤L ＜
844, unmanned plane flies in first region according to the height above sea level of 944 (i.e. H+D) rice；The difference of Two Areas peak and D
Value is L2, then 844 L2≤1688 ＜, then unmanned plane flies in the region of Two Areas according to the height above sea level of 2H+D.
It should be noted that when dividing region, the lowest elevation in j-th of region should be greater than (j-1) H+D, could make
The data in the collected all regions to be monitored of unmanned plane all meet set picture quality.But in practical applications, due to
Monitoring area is wide, topography is complicated, and it is inevitable the problem of fraction region cannot meet picture quality occur.
It should be noted that above-described embodiment is only a kind of embodiment, other other realities based on the embodiment of the present invention
Mode is applied, C is 1300 meters in example as above, when D is 100 meters, is arrived at 1300 meters in the flight height above sea level of Two Areas aircraft
Can meet the needs of resolution ratio between 1788 meters (2H+D), such embodiment also should protection scope of the present invention it
In.
In addition to this, the problem of being also contemplated that minimum enroute I.F.R. altitude when planning course line, in general, unmanned plane exists
The height above sea level of region flight to be monitored should be not less than 150 meters to 250 meters with the altitude difference of the region peak.
The forestry disease monitoring method based on unmanned plane that an embodiment of the present invention provides a kind of, by navigating in flight preplanning
Line, the elevation information for treating monitoring region is analyzed, when the height value of the peak in region to be monitored and the elevation of minimum point
When the difference of value is very big, the mode of stratified operation is taken, to ensure the image quality requirements of acquired data.By to height
The image of quality carries out processing analysis, and disease tree can not be by timely, efficient, accurate after solving generation forestry disease in the prior art
The problem of finding.
For solve the problems, such as the prior art when forestry pests ＆ diseases occur can not quickly, be exactly found disease tree, in conjunction with Fig. 3,
The embodiment of the present invention additionally provides a kind of forestry disease monitoring device based on unmanned plane, which includes：
A kind of forestry disease monitoring device based on unmanned plane, including：
Image acquisition units 301, by will be seen that light camera, near infrared camera are mounted on unmanned plane, according to setting
Course line takes photo by plane to the region to be monitored, obtains multiple continuous visible images, near-infrared images；
First image processing unit 302, visible images, near-infrared image for obtaining the unmanned plane respectively into
Row correction and splicing, obtain the visible light orthophotoquad and near-infrared orthophotoquad in region to be monitored；
Second image processing unit 303 waits supervising for obtaining from visible light orthophotoquad and near-infrared orthophotoquad
The vegetation-cover index NDVI for surveying same position in region, builds the vegetation index orthography in region to be monitored
Figure；
Trees index determination unit 304, for choosing N dead tree and health respectively from the visible light orthophotoquad
Position where setting, and obtain from the vegetation index orthophotoquad described N dead tree and N described
The NDVI values of health tree determine NDVI the mean values B, N >=2, N of the NDVI mean values A and the N health tree that described N is extremely set
For positive integer；
Analytic unit 305 obtains second image processing unit according to A, B that trees index determination unit obtains
Vegetation index orthophotoquad carry out forestry Disease Analysis, obtain the Health of Tree situation in region to be monitored；
From vegetation index orthophotoquad, the NDVI values of each position x in region to be monitored are obtained successively
NDVI (x), as 0≤NDVI (x)≤A, the trees for being located at x position are dead tree；As A ＜ NDVI (x) ＜ B, it is located at x position
Trees are that disease is set；As B≤NDVI (x)≤1, the trees for being located at x position are healthy trees.
The device further includes statistic unit 306 and flying height planning unit 307；
Health of Tree situation of the statistic unit 306 according to region to be monitored treats disease tree sum, the disease in monitoring region
Tree distribution and bottom class's information are counted.
The flying height planning unit 307 requires the height of height H and region to be monitored according to the unmanned plane during flying of setting
Journey information determines that unmanned plane shoots course line；
The elevation information that the region to be monitored is obtained using elevation information collecting unit 308 includes region highest to be monitored
The height above sea level of point and minimum point is respectively C and D；
If H ＞ C-D, the unmanned plane flies in the region to be monitored according to the height above sea level of H+D；
If H≤C-D, the region to be monitored is divided into M region according to height above sea level, in j-th of region
The interior height above sea level according to jH+D is flown, wherein the height value of the peak in j-th of region and the difference of D are L, and (j-1)
H≤L ＜ jH, 1≤j≤M, M, j are positive integer.
The above description is merely a specific embodiment, but scope of protection of the present invention is not limited thereto, any
Those familiar with the art in the technical scope disclosed by the present invention, can easily think of the change or the replacement, and should all contain
Lid is within protection scope of the present invention.Therefore, protection scope of the present invention should be based on the protection scope of the described claims.
Claims (6)
1. a kind of forestry disease monitoring method based on unmanned plane, which is characterized in that include the following steps：
Step 1：Obtain multiple continuous visible images and near-infrared image in region to be monitored simultaneously using unmanned plane；
By will be seen that light camera, near infrared camera are mounted on the unmanned plane, according to the course line of setting to described to be monitored
Region is taken photo by plane, multiple continuous visible images, near-infrared images are obtained；
Step 2：Described multiple continuous visible images, near-infrared images are corrected and are spliced respectively, are waited for described in acquisition
Monitor the visible light orthophotoquad and near-infrared orthophotoquad in region；
Step 3：It is obtained in the region to be monitored by the visible light orthophotoquad and the near-infrared orthophotoquad
The vegetation-cover index NDVI of same position builds the vegetation index orthophotoquad in the region to be monitored；
Step 4：Choose the position where N dead tree and N health tree respectively from the visible light orthophotoquad, and from institute
The NDVI values for obtaining described N dead tree and N health tree in vegetation index orthophotoquad are stated, the N is counted
The NDVI mean values A extremely set and NDVI the mean values B, N >=2, N of the N health tree are positive integer；
Step 5：According to A, B that step 4 obtains, woods is carried out to the vegetation index orthophotoquad that step 3 obtains
Industry Disease Analysis obtains the Health of Tree situation in the region to be monitored；
From the vegetation index orthophotoquad, each position x in the region to be monitored is obtained successively
NDVI value NDVI (x), as 0≤NDVI (x)≤A, the trees for being located at x position are dead tree；As A ＜ NDVI (x) ＜ B, it is located at x
The trees of position are that disease is set；As B≤NDVI (x)≤1, the trees for being located at x position are that health is set.
2. according to the method described in claim 1, it is characterized in that, Health of Tree situation according to the region to be monitored, right
The dead tree and disease tree sum in the region to be monitored, distribution and bottom class's information are counted.
3. method according to claim 1 or 2, which is characterized in that the unmanned plane during flying according to setting requires height H and institute
The elevation information for stating region to be monitored determines that unmanned plane shoots course line；
The elevation information in the region to be monitored includes waiting for that the height above sea level of the monitoring region highs and lows is respectively C
And D；
If H ＞ C-D, the unmanned plane flies in the region to be monitored according to the height above sea level of H+D；
If H≤C-D, the region to be monitored is divided into M region according to height above sea level, is pressed in j-th of region
According to the height above sea level flight of jH+D, wherein the height value of the peak in j-th of region and the difference of D are L, and (j-1) H≤L
＜ jH, 1≤j≤M, M, j are positive integer.
4. a kind of forestry disease monitoring device based on unmanned plane, which is characterized in that including：
Image acquisition units, by will be seen that light camera, near infrared camera are mounted on unmanned plane, according to the course line of setting to institute
It states region to be monitored to take photo by plane, obtains multiple continuous visible images, near-infrared images；
First image processing unit, visible images, near-infrared image for obtaining the unmanned plane are corrected respectively
And splicing, obtain the visible light orthophotoquad and near-infrared orthophotoquad in the region to be monitored；
Second image processing unit, described in being obtained from the visible light orthophotoquad and the near-infrared orthophotoquad
The vegetation-cover index NDVI of same position in region to be monitored builds the vegetation index in the region to be monitored
Orthophotoquad；
Trees index determination unit, for choosing N extremely tree and health tree place respectively from the visible light orthophotoquad
Position, and obtain from the vegetation index orthophotoquad described N dead tree and the N health tree
NDVI values, determine that NDVI the mean values B, N >=2, N of NDVI mean values A that described N is extremely set and the N health tree are just whole
Number；
Analytic unit, according to A, B that trees index determination unit obtains, the normalization that second image processing unit is obtained
Difference vegetation index orthophotoquad carries out forestry Disease Analysis, obtains the Health of Tree situation in the region to be monitored；
From the vegetation index orthophotoquad, each position x in the region to be monitored is obtained successively
NDVI value NDVI (x), as 0≤NDVI (x)≤A, the trees for being located at x position are dead tree；As A ＜ NDVI (x) ＜ B, it is located at x
The trees of position are that disease is set；As B≤NDVI (x)≤1, the trees for being located at x position are healthy trees.
5. device according to claim 4, which is characterized in that further include statistic unit, the statistic unit is according to described in
The Health of Tree situation in region to be monitored, to the region to be monitored it is dead tree and disease tree sum, distribution and bottom class's information into
Row statistics.
6. device according to claim 4 or 5, which is characterized in that further include flying height planning unit, the flight is high
The elevation information that planning unit requires height H and region to be monitored according to the unmanned plane during flying of setting is spent, determines that unmanned plane is shot
Course line；
The elevation information that the region to be monitored is obtained using elevation information collecting unit includes the region peak to be monitored
Height above sea level with minimum point is respectively C and D；
If H ＞ C-D, the unmanned plane flies in the region to be monitored according to the height above sea level of H+D；
If H≤C-D, the region to be monitored is divided into M region according to height above sea level, is pressed in j-th of region
According to the height above sea level flight of jH+D, wherein the height value of the peak in j-th of region and the difference of D are L, and (j-1) H≤L
＜ jH, 1≤j≤M, M, j are positive integer.
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