CN104062644A - Method for extracting tree height from laser radar Gaussian echo data - Google Patents
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- CN104062644A CN104062644A CN201310598367.3A CN201310598367A CN104062644A CN 104062644 A CN104062644 A CN 104062644A CN 201310598367 A CN201310598367 A CN 201310598367A CN 104062644 A CN104062644 A CN 104062644A
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S7/00—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00
- G01S7/48—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S17/00
- G01S7/483—Details of pulse systems
- G01S7/486—Receivers
- G01S7/487—Extracting wanted echo signals, e.g. pulse detection
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S17/00—Systems using the reflection or reradiation of electromagnetic waves other than radio waves, e.g. lidar systems
- G01S17/88—Lidar systems specially adapted for specific applications
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Abstract
The invention relates to the field of remote sense surveying and mapping and provides a method for extracting tree height from laser radar Gaussian echo data. The method comprises the steps of: selecting a plurality of calibration reference sites belonging to the same region type with a site where the tree height is to be measured; extracting a distance wc from a waveform centroid to an echo end position and an edge length l from the laser radar Gaussian echo data according to actual tree height values H corresponding to the plurality of sites one by one and a terrain index g under a digital elevation model; performing function fitting on H that is equal to a0*(wc-a1*g+a2*l) to obtain a group of best fitting parameters a0, a1 and a2; working out the tree height measured value H' of the site where the tree height is to be measured by a formula, H' is equal to a0*(w'c-a1*g'+a2*l'), according to the distance w'c from the waveform centroid to the echo end position, the edge length l', the terrain index g' of the site and the best fitting parameters a0, a1 and a2. According to the method, the tree height can be extracted from laser radar Gaussian echo data of large slope regions.
Description
Technical field
The present invention relates to remote sensing survey field, be specifically related to a kind of method of extracting the height of tree from laser radar Gauss echo data.
Background technology
Laser radar, as the active remote sensing equipment that adopts detecting technique means, is widely used in the field such as forestry, mapping science with its high-resolution feature.For example GLAS(GeoscienceLaser Altimeter System, geoscience laser-measured height instrument system), be equipped on the First satellite-bone laser radar sensor on the scientific experiment satellite ICEsat of U.S. 2003 transmitting, can obtain continuously the echo data on atmosphere and ground.The echoed signal (time-density curve) of digitizer wherein record within the scope of from satellite to earth's surface 765km, can extract transponder pulse and surface echo with analyzing after filtering.Its 1064nm wave band echo data has comprised the vertical stratification information including elevation information.Researcher adds an estimated bias by laser radar echo with the stack that mathematical form is expressed as several Gauss's echo functions, the corresponding elevation information of crest location of each Gauss's echo data component, thereby can from laser radar Gauss echo data, extract as vegetation vertical stratification information such as the height of trees, see through such data and can evaluate well global vegetation biomass and carbon cycle.
Generally, in existing height of tree extraction scheme, most initial positions of Gauss's echo of getting are height of tree extraction result with the difference of ground echo position (all judge and find out in Gauss's echo data), and this result is generally considered and the immediate result of calculation of Forest Canopy height.
But there are some researches show, the gradient acquires a certain degree and can produce make a big impact (Harding, 1994 to described Gauss's echo data; Heyder, 2005).General, in the time that ground exists the gradient, ground echo crest location is not obvious, now directly uses the method from Wave data, to extract the height of tree and can cause very large error.Its reason is mainly, in the time that terrain slope exceedes certain limit, ground echo mixes mutually with vegetation echo, in addition the decay of laser radar sensor cause echo obtain with decompose all very difficult.Especially a lot of these experiments on the one hand are at present all obtain data and complete under the more smooth physical features in North America, and compare, and the relief in domestic some areas is larger, may have some inapplicable situations on existing data extraction algorithm.Therefore, the area large to relief according to laser radar Gauss echo data, such as forest survey and the research in area, mountain region are one of current Research Challenges.
Summary of the invention
(1) technical matters solving
For the deficiencies in the prior art, the invention provides a kind of method of extracting the height of tree from laser radar Gauss echo data, realize the extraction of the height of tree in the laser radar Gauss echo data of gradient larger area.
(2) technical scheme
A method of extracting the height of tree from laser radar Gauss echo data, is characterized in that, the method comprises:
Step 101: choose the some calibration references place that belongs to a regional population with height of tree place to be measured, and obtain the actual measurement height of tree value at this some calibration references place place;
Step 102: obtain under the laser radar Gauss echo data in these some places and digital elevation model and these some places topographic index g one to one;
Step 103: extract and obtain the distance w of waveform barycenter to echo end position from described laser radar Gauss echo data
cwith edge length l;
Step 104: with H=a
0× (w
c-a
1× g+a
2× l) for fitting function, some groups of H, g, wc and the l in these some places of correspondence are carried out to Function Fitting, obtain one group of best fit parameters a
0, a
1and a
2;
Step 105: for this height of tree place to be measured, first obtain its laser radar Gauss echo data, and therefrom extract the distance w ' of waveform barycenter to echo end position
cwith edge length l ';
Step 106: in conjunction with topographic index g ' and the described best fit parameters a in this place under digital elevation model
0, a
1and a
2by formula H '=a
0× (w '
c-a
1× g '+a
2× l ') calculate the height of tree measured value H ' in this place.
Preferably, described extraction waveform barycenter comprises to the distance of echo end position: the position of waveform barycenter be vegetation echo waveform half of the area place horizontal ordinate position; Set threshold value that Gauss echo finishes and be the mean value that finishes noise add its standard deviation and, start to search for backward from last echo position, if the value of Wave data is less than the threshold value that Gauss's echo finishes, determine that horizontal ordinate is herein echo end position; Described extraction waveform barycenter is the poor of the position of described waveform barycenter and described echo end position to the distance of echo end position.
Preferably, described extraction edge length comprises: set threshold value that Gauss echo finishes and be the mean value that finishes noise add its standard deviation and, start to search for backward from last echo position, if the value of Wave data is less than the threshold value that Gauss's echo finishes, determine that horizontal ordinate is herein echo end position; Start to search forward an echo position from described echo end position, make the difference of itself and described echo end position be greater than the half-breadth of laser pulse, described edge length size equals the poor of this echo position and described echo end position.
Preferably, described in carrying out for certain place, obtain topographic index g step and comprise: to should place, obtain the mean size of earth's surface elevation under the sample window of 5 × 5 sizes in digital elevation model as topographic index g.
Preferably, described in, carry out Function Fitting and comprise that use Lenvenberg-Marquardt non-linear fitting method carries out Function Fitting.
Preferably, described in, belonging to a regional population comprises and belongs to a gradient type.
Preferably, described in, belonging to a regional population comprises and belongs to a vegetation pattern.
(3) beneficial effect
The present invention at least has following beneficial effect:
In the formula that the present invention adopts, add this parameter of topographic index at height of tree place to be measured place, namely also give certain consideration for the terrain effect in height of tree extraction problem, make the height of tree under different gradient extract the correction that problem has corresponding this place topographic index in various degree to bring, make the Reduced susceptibility of height of tree extraction accuracy for the gradient, improved the precision of the extraction algorithm of the height of tree in the laser radar Gauss echo data of gradient larger area;
And the present invention uses waveform centroid position in the selection of vegetation echo, there is result of study to show, this processing makes the height of tree value extracted lower to the susceptibility of the gradient, to relatively stable (Heyder, 2005) of gradient larger area result;
The present invention also introduces edge length l the problem of great slope area ground echo half-breadth increase is revised, and has obtained reasonable effect after improvement.The result that in 55 sampling sampling points taking reservoir area of Three Gorges in GLAS pin point, the height of tree is extracted is as example, the root-mean-square error (RMSE) of the height of tree value while finally distinguishing vegetation pattern under each gradient of regions with complex terrain reaches 0.696, the root-mean-square error of the height of tree value while not distinguishing vegetation pattern has reached 0.737 0.59-0.69 that generally can reach compared to background method, and result is more satisfactory.
Certainly, implement arbitrary product of the present invention or method and must not necessarily need to reach above-described all advantages simultaneously.
Brief description of the drawings
In order to be illustrated more clearly in the embodiment of the present invention or technical scheme of the prior art, to the accompanying drawing of required use in embodiment or description of the Prior Art be briefly described below, apparently, accompanying drawing in the following describes is only some embodiments of the present invention, for those of ordinary skill in the art, do not paying under the prerequisite of creative work, can also obtain according to these accompanying drawings other accompanying drawing.
Fig. 1 is the method flow diagram of one embodiment of the invention;
Fig. 2 is the Gauss's echo data result schematic diagram in one embodiment of the invention;
Fig. 3 is the result that in one embodiment of the invention, in the sampling sampling points of in GLAS pin point 55, reservoir area of Three Gorges, the height of tree is extracted, and with the comparison of actual measured value.
Embodiment
Below in conjunction with accompanying drawing of the present invention, technical scheme of the present invention is clearly and completely described, obviously, described embodiment is only the present invention's part embodiment, instead of whole embodiment.Based on the embodiment in the present invention, those of ordinary skill in the art, not making the every other embodiment obtaining under creative work prerequisite, belong to the scope of protection of the invention.
Embodiment 1: the embodiment of the present invention has proposed a kind of method of extracting the height of tree from laser radar Gauss echo data, has demonstrated the height of tree leaching process with the GLAS Gauss echo data of Sanxia area.Referring to Fig. 1, the method comprises:
Step 101: choose the some calibration references place that belongs to a regional population with height of tree place to be measured, and obtain the actual measurement height of tree value at this some calibration references place place;
In practical operation, can obtain by a lot of means as the described actual measurement height of tree value H with reference to data, for example in the embodiment of the present invention, take the method for field survey, several sampling sampling points using reservoir area of Three Gorges in GLAS pin point, as calibration reference place, and have carried out height of tree measurement in these places.And in the embodiment of the present invention, described " areal type " specifically refers to same gradient type, or same vegetation pattern, or same gradient type and same vegetation pattern.
Step 102: obtain under the laser radar Gauss echo data in these some places and digital elevation model and these some places topographic index g one to one;
GLAS data are processed to the method that obtains Gauss's echo data to be had a variety of, the present embodiment is taked following method: first by Gaussian filter low-pass filtering, again based on histogram estimating background noise comprising, after searching in data flex point and utilizing flex point screening, find some Gauss's crests, then after rejecting invalid signals, merge into six Gauss's crests by area, finally by data after filtering, it is carried out to Lenvenberg-Marquardt nonlinear fitting, obtain final Gauss's echo data.Result is (four groups of laser radar Gauss echo datas (solid line) of the different terrain of Sanxia area and vegetation pattern and original smothing filtering function (dotted line) are expressed as (a) vegetation in Figure of description: gently, (b) without vegetation: tableland, (c) are without vegetation: level land, (d) vegetation: abrupt slope) as shown in Figure 2.
Topographic index g refers to the mean size of earth's surface elevation in the lower digital terrain model (DEM) of corresponding a certain size sample window of certain place (3 × 3,5 × 5 and 7 × 7).Its value has represented the vertical height on this ground, position.Adopt in embodiments of the present invention the topographic index data under 5 × 5 sample windows.Wherein, digital terrain model (DEM) is known auxiliary data base, and the latitude and longitude coordinates of corresponding ground can be read the ground elevation in this place.
Step 103: extract and obtain the distance w of waveform barycenter to echo end position from described laser radar Gauss echo data
cwith edge length l;
That describes with background technology is identical, and Gauss's echo data adds an estimated bias with the stack that mathematical form is expressed as several Gauss's echo functions, the corresponding elevation information of crest location (horizontal ordinate) of each Gauss's echo data component.Thereby Gauss's echo data as shown in Figure 2 equally for taking the time as horizontal ordinate, signal intensity is ordinate, a series of Gauss's echoes of arranging in chronological order.(corresponding minimal time) echo wherein keeping left is most that vertical height is the highest, and what keep right most is minimum.Thereby according to convention, generally leftmost Gauss's echo is vegetation echo, rightmost Gauss's echo is ground echo, what echo position referred to is exactly the horizontal ordinate position at echo crest place, and echo initial position and end position are exactly the most left in echo data and rightmost point.But for being used mathematical method, guarantee precision accurately judges these data in practical operation.
The position of waveform barycenter be vegetation echo waveform half of the area place horizontal ordinate position, and echo end position is determined by following methods: set threshold value that Gauss's echo finishes and be the mean value that finishes noise add its standard deviation and.Start to search for backward from last echo position, if the value of Wave data is less than the threshold value that Gauss's echo finishes, determine that horizontal ordinate is herein echo end position.
Edge length l is the half-breadth of ground echo, computing method are for to start to search forward an echo position from echo end position, make the difference of itself and echo end position be greater than the half-breadth of laser pulse, this echo position is the position of ground echo, edge length size just equals the poor of this echo position and echo end position, is ground echo half-breadth.
H, g, w
coriginally be m with the unit of tetra-parameters of l, but w wherein
cneed to carry out by the on year-on-year basis conversion of time to height with reference to the GLAS description of product with l.But in this method owing to there being parameter a
0, a
1and a
2therefore all conversions on year-on-year basis are all unnecessarily carried out, only need in the time of image data, keep scale consistent, remaining all transfer process on year-on-year basis can lie in parameter a
0, a
1and a
2in.
Step 104: with H=a
0× (w
c-a
1× g+a
2× l) be some group Hs, g, the w of fitting function to these some places of correspondence
ccarry out Function Fitting with l, obtain one group of best fit parameters a
0, a
1and a
2;
The approximating method that this method embodiment adopts is Lenvenberg-Marquardt non-linear fitting method.Every group of fitting parameter is all corresponding to a kind of regional population, and the fitting parameter between the type of different regions has different, for ensureing that height of tree extraction accuracy must adopt the place in area of the same type to do calibration reference place as much as possible.
Step 105: for this height of tree place to be measured, first obtain its laser radar Gauss echo data, and therefrom extract the distance w ' of waveform barycenter to echo end position
cwith edge length l ';
Identical with step above of extracting method in this step.
Step 106: in conjunction with topographic index g ' and the described best fit parameters a in this place under digital elevation model
0, a
1and a
2by formula H '=a
0× (w '
c-a
1× g '+a
2× l ') calculate the measurement height of tree value H ' in this place.
Identical with step above, topographic index g ' remains the mean size of earth's surface elevation in digital terrain model (DEM), and corresponding to the latitude and longitude coordinates in height of tree place to be measured, sample window size is similarly 5 × 5.Fitting parameter in formula provides in Function Fitting process, just can obtain the measured value of this place height of tree in conjunction with the laser radar Gauss echo data in height of tree place to be measured and corresponding topographic index.
As a whole, the method that the embodiment of the present invention proposes can be divided into parameter fitting (step 101 is to 104) and two steps of data substitution (step 105 is to 106) haply.And parameter fitting is only according to the sampled result of calibration reference landform, the fitting parameter in fitting function to be obtained or calibrated, that is to say for the height of tree and extract only one group of needs parameter comparatively accurately of speech, and be not that the extraction of the height of tree each time all needs to carry out primary calibration.For the embodiment of the present invention, in fact the leaching process of the height of tree only includes step 105 to 106, and the parameter of just using in leaching process is obtained or calibrated to 104 by step 101.
In embodiment of the present invention step 103, said topographic index adopts the topographic index data under 5 × 5 sample windows, because compared with the correlativity of the topographic index under 5 × 5 sample windows during the experimental data of the embodiment of the present invention shows forest land and actual measurement floor level difference 3 × 3 and 7 × 7 higher, referring to table 1.In table 1: 0 °, 45 °, 90 °, 135 ° and full window represent five kinds of sampling patterns under same big or small sample window.The quantity of sampled point is 14 of coniferous forests, 12 of broad-leaf forests, 4 of mixed forests.All in all, (but do not reach yet 0.6 except the degree of correlation under 7 × 7 sample windows in the sampled result of broad-leaf forest is higher, therefore broad-leaf forest partial data is not made emphasis in the embodiment of the present invention), the degree of correlation under 5 × 5 sample windows is all higher, therefore choose this big or small sample window.
Topographic index under the different sample windows of table 1 and the correlativity of surveying floor level difference
In step 101, to 104 processing, the fitting result of illustrating in the data of the embodiment of the present invention is referring to table 2, wherein R
2for degree of fitting, represent the laminating degree of sampled point to fitting result.
The parameter fitting result that table 2 is illustrated
In method, adopt the waveform barycenter of vegetation echo and do not adopt the reason of echo initial position to be, have research to point out, this processing makes the height of tree value of extraction lower to the susceptibility of the gradient, relatively stable to gradient larger area result.And in gentle slope or roughness larger in the situation that, earth's surface echo half-breadth increases, echo end position moves backward with certain proportion, can impact the extraction of the height of tree.Thereby introduce edge length l, the fitting effect before and after introducing in the data of the embodiment of the present invention is as shown in table 3.Visible, the degree of fitting for same vegetation pattern after improvement is obviously more better.
Table 3 is introduced the fitting effect signal of edge length l
The corresponding height of tree is extracted result referring to Fig. 3, and Fig. 3 is the result that in 55 sampling sampling points of reservoir area of Three Gorges in GLAS pin point, the height of tree is extracted, and height of tree extraction result and ground measured data in GLAS laser radar echo data is contrasted simultaneously.Visible, reservoir area of Three Gorges GLAS to the measurement result of Forest Canopy height except having individually deviation, major part is more satisfactory.
The result that in 55 sampling sampling points for reservoir area of Three Gorges in GLAS pin point, the height of tree is extracted, the error statistics of dividing by slope grade (angle of gradient) is as shown in table 4.The embodiment of the present invention contrasts utilize 30 GLAS laser radar Gauss echo data reason direct measurement gained height of tree extraction values and the ground measured data that are less than under 20 degree slope grades, and average error result is as table 5-8.It is the highest that the visible gradient is less than 5 precision while spending; The gradient is greater than 5 while spending, due to the impact of landform, causes standing forest canopy height measuring accuracy to decline.Meanwhile, along with the gradient increases, its measuring error also increases gradually.
The each slope grade height of tree of table 4 different vegetation types extraction value error statistics (unit: m)
Generally speaking, the embodiment of the present invention has realized the extraction of the height of tree in the laser radar Gauss echo data of great slope area, and root-mean-square error reached 0.696, and as previously mentioned, reason is mainly that barycenter is lower to the susceptibility of the gradient.And by not distinguishing Forest Types, the root-mean-square error of the method has reached 0.737, the 0.59-0.69 that generally can reach compared to background method, result is more satisfactory.
It should be noted that, in this article, relational terms such as the first and second grades is only used for an entity or operation to separate with another entity or operational zone, and not necessarily requires or imply and between these entities or operation, have the relation of any this reality or sequentially.And, term " comprises ", " comprising " or its any other variant are intended to contain comprising of nonexcludability, thereby the process, method, article or the equipment that make to comprise a series of key elements not only comprise those key elements, but also comprise other key elements of clearly not listing, or be also included as the intrinsic key element of this process, method, article or equipment.The in the situation that of more restrictions not, the key element being limited by statement " comprising ... ", and be not precluded within process, method, article or the equipment that comprises described key element and also have other identical element.
Above embodiment only, in order to technical scheme of the present invention to be described, is not intended to limit; Although the present invention is had been described in detail with reference to previous embodiment, those of ordinary skill in the art is to be understood that: its technical scheme that still can record aforementioned each embodiment is modified, or part technical characterictic is wherein equal to replacement; And these amendments or replacement do not make the essence of appropriate technical solution depart from the spirit and scope of various embodiments of the present invention technical scheme.
Claims (7)
1. a method of extracting the height of tree from laser radar Gauss echo data, is characterized in that, the method comprises:
Step 101: choose the some calibration references place that belongs to a regional population with height of tree place to be measured, and obtain the actual measurement height of tree value at this some calibration references place place;
Step 102: obtain under the laser radar Gauss echo data in these some places and digital elevation model and these some places topographic index g one to one;
Step 103: extract and obtain the distance w of waveform barycenter to echo end position from described laser radar Gauss echo data
cwith edge length l;
Step 104: with H=a
0× (w
c-a
1× g+a
2× l) be some group Hs, g, the w of fitting function to these some places of correspondence
ccarry out Function Fitting with l, obtain one group of best fit parameters a
0, a
1and a
2;
Step 105: for this height of tree place to be measured, first obtain its laser radar Gauss echo data, and therefrom extract the distance w ' of waveform barycenter to echo end position
cwith edge length l ';
Step 106: in conjunction with topographic index g ' and the described best fit parameters a in this place under digital elevation model
0, a
1and a
2by formula H '=a
0× (w '
c-a
1× g '+a
2× l ') calculate the height of tree measured value H ' in this place.
2. method according to claim 1, is characterized in that, described extraction waveform barycenter comprises to the distance of echo end position:
The position of waveform barycenter be vegetation echo waveform half of the area place horizontal ordinate position;
Set threshold value that Gauss echo finishes and be the mean value that finishes noise add its standard deviation and, start to search for backward from last echo position, if the value of Wave data is less than the threshold value that Gauss's echo finishes, determine that horizontal ordinate is herein echo end position;
Described extraction waveform barycenter is the poor of the position of described waveform barycenter and described echo end position to the distance of echo end position.
3. method according to claim 1, is characterized in that, described extraction edge length comprises:
Set threshold value that Gauss echo finishes and be the mean value that finishes noise add its standard deviation and, start to search for backward from last echo position, if the value of Wave data is less than the threshold value that Gauss's echo finishes, determine that horizontal ordinate is herein echo end position;
Start to search forward an echo position from described echo end position, make the difference of itself and described echo end position be greater than the half-breadth of laser pulse, described edge length size equals the poor of this echo position and described echo end position.
4. method according to claim 1, is characterized in that, obtains topographic index g step comprise for certain place described in carrying out:
To should place, obtain the mean size of earth's surface elevation under the sample window of 5 × 5 sizes in digital elevation model as topographic index g.
5. method according to claim 1, is characterized in that, described in carry out Function Fitting and comprise and use Lenvenberg-Marquardt non-linear fitting method to carry out Function Fitting.
6. method according to claim 1, is characterized in that, described in belong to a regional population and comprise and belong to a gradient type.
7. method according to claim 1, is characterized in that, described in belong to a regional population and comprise and belong to a vegetation pattern.
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| CN111781605A (en) * | 2020-07-24 | 2020-10-16 | 江苏大学 | Tree canopy thickness detection method based on ultrasonic echo signals |
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| GB2599333B (en) * | 2020-07-24 | 2023-03-15 | Univ Jiangsu | Method for detecting thickness of tree canopy based on ultrasonic echo signal |
| WO2022017539A1 (en) * | 2020-07-24 | 2022-01-27 | 江苏大学 | Method for detecting tree crown width employing ultrasonic echo signal |
| GB2599333A (en) * | 2020-07-24 | 2022-03-30 | Univ Jiangsu | Method for detecting tree crown width emplying ultrasonic echo signal |
| CN111781605B (en) * | 2020-07-24 | 2022-07-22 | 江苏大学 | Tree canopy thickness detection method based on ultrasonic echo signals |
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| CN112800126A (en) * | 2021-01-13 | 2021-05-14 | 海南微氪生物科技股份有限公司 | Processing method and system of fluorescence photoelectric detection instrument for predicting detection time |
| CN113487636A (en) * | 2021-07-01 | 2021-10-08 | 广西大学 | Automatic extraction method for plant height and line spacing of wide-ridge crops based on laser radar |
| CN117031435A (en) * | 2023-07-31 | 2023-11-10 | 中国人民解放军国防科技大学 | Method and system for determining multi-channel echo waveform type of hyperspectral laser radar |
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