CN101900550A - Building elevation positioning control and precision evaluation method based on satellite images - Google Patents

Building elevation positioning control and precision evaluation method based on satellite images Download PDF

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CN101900550A
CN101900550A CN 201010230702 CN201010230702A CN101900550A CN 101900550 A CN101900550 A CN 101900550A CN 201010230702 CN201010230702 CN 201010230702 CN 201010230702 A CN201010230702 A CN 201010230702A CN 101900550 A CN101900550 A CN 101900550A
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乔刚
王卫安
李荣兴
欧建良
李元博
王伟
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Tongji University
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Tongji University
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Abstract

The invention relates to a building elevation positioning control and precision evaluation method based on satellite images, belonging to the fields of acquisition and updating of urban spatial data of satellite three-dimensional remote sensing data. The method comprises the following concrete steps: (1) carrying out the field survey by a GPS to acquire ground control point data; (2) carrying out block bundle adjustment on aerial images to acquire building roof coordinates; (3) integrating the acquired horizontal coordinate with the building roof vertical coordinate acquired by airborne LiDAR data to acquire a building roof control point; (4) geometrically positioning high-resolution satellite three-dimensional images based on a rational function model (RFM) in an image space to acquire three-dimensional coordinates of the ground and the building roof; and (5) acquiring the relation between the elevation of the control point and the elevation precision of the point pattern of a check point by adopting the building elevation positioning control and precision evaluation scheme based on the point pattern. The invention can promote the application of high-resolution satellite three-dimensional remote sensing images in the fields of acquisition and updating of urban spatial data.

Description

A kind of control of buildings elevation location and precision evaluation method based on satellite image
Technical field
The invention belongs to the three-dimensional remotely-sensed data city space data acquisition of satellite and upgrade application, relate to a kind of control of buildings elevation location and precision evaluation method, particularly a kind of control of high-resolution satellite stereopsis buildings elevation location and precision evaluation method based on RS data based on satellite image.
Background technology
High-resolution satellite image is one of most important spatial information source, present earth observation field, all become the research focus of association area at the research work of high-resolution satellite image each side, and high-precision geometry location is the basic and crucial of the various application of high-resolution satellite image, and up to the present its research obtained certain achievement.The rational function model RFM that extensively adopts has obtained effect preferably at present, and the definition of RFM model is as follows:
r n = P 1 ( X n , Y n , Z n ) P 2 ( X n , Y n , Z n ) (1)
c n = P 3 ( X n , Y n , Z n ) P 4 ( X n , Y n , Z n )
R wherein n, c nBe to be respectively standardized image ranks coordinate, unit is a pixel; X n, Y n, Z nNormalized coordinates for earth axes picture side coordinate.The standardisation process of coordinate uses following equation to calculate:
r n = r - r 0 r s c n = c - c 0 c s X n = X - X 0 X s Y n = Y - Y 0 Y s Z n = Z - Z 0 Z s - - - ( 2 )
R wherein 0, c 0Be the translation parameters of two image coordinate, r s, c sBe zooming parameter.Equally, X 0, Y 0, Z 0Be the translation parameters of three ground coordinatees, X s, Y s, Z sBe zooming parameter.
The maximum power of each ground coordinate is no more than 3 usually in the polynomial expression, and the summation of the power of each each coordinate components also is no more than 3.P i(i=1,2,3,4) are object space ground coordinate (X n, Y n, Z n) three rank polynomial functions, denominator term P 2And P 4Value two kinds of situation: P are arranged usually 2=P 4, P 2≠ P 4For each polynomial expression, following form is arranged:
P ( X , Y , Z ) = Σ i = 0 m 1 Σ j = 0 m 2 Σ k = 0 m 3 d ijk X i Y j Z k = d 0 + d 1 Y + d 2 X + d 3 Z + d 4 XY + d 5 YZ + d 6 XZ + d 7 Y 2
+ d 8 X 2 + d 9 Z 2 + d 10 XYZ + d 11 Y 3 + d 12 YX 2 + d 13 YZ 2 - - - ( 3 )
+ d 14 Y 2 X + d 15 X 3 + d 16 X Z 2 + d 17 Y 2 Z + d 18 X 2 Z + d 19 Z 3
D wherein IjkBe polynomial coefficient, be called rational polynominal coefficients R PC (Rational Polynomial Coefficients).
Manufacturer can provide translation parameters, zooming parameter and rational polynominal coefficients R PC in high-resolution satellite image.After the RPC of the left and right sides image that utilizes stereogram has set up RFM, need carry out three-dimensional intersection based on RFM, go out corresponding topocentric volume coordinate according to corresponding image points as coordinate Calculation.
Because the RPC coefficient among the RFM generally only adopts satellite orbit parameter to calculate and obtains, generally can only obtain the precision about 20m, at this problem, utilize the reference mark that original RFM model is carried out geometry correction usually, the object space that has commonly used is proofreaied and correct and the image space correction.RFM geometric correction model in picture side can add transformation parameter and obtain on the basis of formula (1):
( r + A 0 + A 1 r + A 2 c + A 3 rc + A 4 r 2 + A 5 c 2 ) - r 0 r s = P 1 ( X n , Y n , Z n ) P 2 ( X n , Y n , Z n ) (4)
( c + B 0 + B 1 c + B 2 r + B 3 rc + B 4 r 2 + B 5 c 2 ) - c 0 c s = P 3 ( X n , Y n , Z n ) P 4 ( X n , Y n , Z n )
Transformation parameter in the formula (4) has following four kinds of selections:
1) A 0, B 0, expression is represented translation model as square coordinate translation;
2) A 0, A 1, B 0, B 1, expression is the translation zoom model as square coordinate translation and convergent-divergent;
3) A 0, A 1, A 2, B 0, B 1, B 2, expression is as square affined transformation model;
4) A 0, A 1... A 5, B 0, B 1... B 5, expression is as square second order polynomial model.
At present the main region of high-resolution satellite image geometry location is positioned at the fairly simple area of terrain and its features, and is as the Plain of spaciousness and coastland etc., also rarely found at the urban area that buildings is intensive.For the urban area, the investigation of the height of buildings seems particularly important with control for city planning, functional localization etc.Simultaneously, ground, urban area substantially flat, high-resolution satellite image geometry location Ground Control Information obtains easily, but for high-rise, because a variety of causes, to directly obtain top control information difficulty relatively, carry out geometry location in this case, exist vertical accuracy is required difficulty high and that the top of building control information is difficult to obtain.
GPS measures can provide high-precision topocentric coordinates as ground control point and check point, aviation image also can provide high-precision horizontal direction geometry location information now, and airborne LiDAR (Light Detection And Ranging) cloud data can provide high-precision vertical direction locating information, aviation image combined with airborne LiDAR data can obtain the control information of high-precision buildings roof, as the control of high-resolution satellite image buildings geometry location with check information.
Summary of the invention
In order to solve the deficiency of existing high-resolution satellite image in buildings close quarters geometry location technology, the object of the invention is to provide a kind of control of buildings elevation location and precision evaluation method based on satellite image, it is in conjunction with GPS measurement, aviation image and airborne LiDAR cloud data, and then obtains the relation between building controls point height and the check point vertical accuracy.
For reaching above purpose, solution of the present invention is:
A kind of control of buildings elevation location and precision evaluation method based on satellite image, obtain area, down town ground control point by adopting the measurement of GPS field operation, carry out aviation image regional network bundle adjustment, integrated aviation image and airborne LiDAR data are obtained the high-precision control information of buildings roof, then based on obtaining ground and the accurate three-dimensional coordinate of buildings roof as the high-resolution satellite stereopsis geometry location of square rational function model RFM, adopt control of buildings elevation location and precision evaluation scheme at last based on a group, obtain the relation between reference mark elevation and the check point point group vertical accuracy, may further comprise the steps:
(1) the Ground Control point data is obtained in the measurement of GPS field operation;
In satellite stereo image and aviation image regional extent, choose the ground point of the same name of some equably, measure its coordinate on satellite stereo image and many scapes aviation image, and measure the volume coordinate of these points in WGS84 (WorldGeodetic System 1984) by GPS.
(2) aviation image is carried out the regional network bundle adjustment and obtain buildings roof point coordinate;
On many scapes aviation image, choose equally distributed buildings roof point, measure its image coordinate, it is carried out bundle block adjustment with the ground point of choosing in the step 1 of the same name, topocentric WGS84 volume coordinate is known, can obtain the WGS84 volume coordinate of buildings roof point according to bundle block adjustment.
(3) the buildings roof point vertical coordinate that obtains of horizontal coordinate that aviation image is obtained and airborne LiDAR data integrates buildings roof reference mark;
WGS84 volume coordinate position according to the buildings roof point of asking on the aviation image in the step 2, in the airborne LiDAR data of same area, choose the same roof angle point zone of same building thing, and by asking the mean value of all LiDAR data points in this zone to obtain the vertical coordinate of buildings angle point, vertical coordinate in the buildings roof point coordinate that this coordinate replacement aviation image regional network bundle adjustment obtains obtains buildings roof reference mark.
(4), obtain ground and the accurate three-dimensional coordinate of buildings roof based on the high-resolution satellite stereopsis geometry location of picture side's rational function model;
On satellite stereo image, measure the pixel coordinate of the buildings roof point corresponding with aviation image, rational polynominal coefficient that provides according to high-resolution satellite stereopsis supplier and corresponding reference mark coordinate, row standing statue side rational function geometric correction model is found the solution the unknown ground point and the WGS84 volume coordinate of buildings roof point.
(5) employing obtains the relation between reference mark point group elevation and the check point point group vertical accuracy based on the control of buildings elevation location and precision evaluation scheme of a group.
Known WGS84 volume coordinate have a few, a given predefined elevation is divided into several some groups with all known points at interval, be arranged in same some group have identical elevation value range a little.This scheme comprises several experiments, for each experiment, all choosing several plane distribution from certain some group puts uniformly as the reference mark, carry out geometry location according to the described method of step (4), when precision evaluation, also be to be that the unit is estimated with a group for check point, evaluation index is the mean value of the elevation difference of all check points in the some group, the relation between controlled point height and the check point point group precision.
Described ground control point, when it was chosen, this point must be in satellite stereo image and many scapes aviation image exists simultaneously, and was image and goes up all tangible joint on the spot.
Described buildings roof point, when it was chosen, this point must all obviously exist in satellite stereo image, many scapes aviation image and airborne LiDAR data.
Owing to adopted such scheme, the present invention has following characteristics: the High Accuracy Control information that the present invention can the measurement of integrated GPS field operation, aviation image, airborne LiDAR data obtain ground, urban area and buildings, adopt rational function model to obtain the accurate three-dimensional coordinate of high-resolution satellite image buildings roof, relation between controlled point height and the check point point group elevation promotes the three-dimensional remote sensing image of high-resolution satellite in city space data and renewal Application for Field.
Description of drawings
Fig. 1 is the process flow diagram of the inventive method.
Fig. 2 finds the solution process flow diagram for proofreading and correct geometry location as square RFM among the embodiment.
Check point point group vertical accuracy distribution plan when Fig. 3 is positioned at ground for reference mark among the embodiment.
Check point point group vertical accuracy distribution plan when Fig. 4 is positioned at the buildings roof for reference mark among the embodiment.
Embodiment
The present invention is further illustrated below in conjunction with the accompanying drawing illustrated embodiment.
Referring to accompanying drawing 1, the present invention adopts the GPS field operation to measure and obtains the Ground Control point coordinate, and aviation image is carried out the regional network bundle adjustment obtain buildings roof point horizontal coordinate, the buildings roof point vertical coordinate that obtains with the LiDAR data integrates buildings roof point control information, employing is carried out geometry location as square RFM geometric correction model to the high-resolution satellite stereopsis, proposes based on the buildings elevation location control of a group and the relation between controlled point height of precision evaluation scheme and the check point point group vertical accuracy.
The present invention includes following steps:
(1) the Ground Control point data is obtained in the measurement of GPS field operation;
In satellite stereo image and aviation image regional extent, choose some ground points of the same name evenly distributedly, in satellite stereo image and many scapes aviation image, measure its image pixel coordinate respectively, and obtain its WGS84 volume coordinate, as ground control point by the GPS metering system.When choosing ground control point, should note, this point must exist in satellite stereo image and many scapes aviation image simultaneously, and be generally image and go up all tangible joint on the spot, as road junction, concrete angle point, and the rectangle object angle point, these unique points are convenient to recognize clearly and measure.
(2) aviation image is carried out the regional network bundle adjustment and obtain buildings roof point coordinate;
On many scapes aviation image, choose equally distributed buildings roof point, consider that simultaneously these buildings roof points need can find significantly in satellite stereo image and airborne LiDAR data, measure the image coordinate of these buildings roof points, it is carried out bundle block adjustment with ground point, topocentric WGS84 volume coordinate is known, can obtain the WGS84 volume coordinate of buildings roof point according to bundle block adjustment.
(3) the buildings roof point vertical coordinate that obtains of horizontal coordinate that aviation image is obtained and airborne LiDAR data integrates buildings roof reference mark;
The vertical coordinate that obtains with respect to aviation image regional network bundle adjustment, the vertical coordinate of airborne LiDAR cloud data has higher precision, so the present invention is integrated as the roof control information at the name a person for a particular job vertical coordinate of the horizontal coordinate of aviation image and airborne LiDAR data of buildings roof.
Aviation image and LiDAR data at first all are converted into the WGS84 coordinate system, then by the interactive process coupling aviation image buildings roof point corresponding with the LiDAR data.At first three-dimensional aviation image is amplified to the buildings that will mate, obtain the buildings angular coordinate by aviation image regional network bundle adjustment, then with airborne LiDAR data projection to 3-D view, and can observe same building object angle point significantly and manually confirm in addition.In the buildings angle point wicket after affirmation, choose near the LiDAR point data of some buildings roof angle points, and its vertical coordinate is averaged as the vertical coordinate of this buildings angle point.Horizontal coordinate and the integrated three-dimensional coordinate of this vertical coordinate that the aviation image adjustment is obtained as buildings roof point.
(4), obtain ground and the accurate three-dimensional coordinate of buildings roof based on the high-resolution satellite stereopsis geometry location of picture side's rational function model;
On satellite stereo image, measure the pixel coordinate of the buildings roof point corresponding with aviation image, RPC that provides according to high-resolution satellite stereopsis supplier and corresponding reference mark coordinate, row standing statue side rational function geometric correction model, as formula (4), find the solution the unknown ground point and the WGS84 volume coordinate of buildings roof point, solution procedure as shown in Figure 2.
The present invention illustrates the three-dimensional reconstruction process as square calibration model to be example as square affined transformation RFM model:
Can obtain by formula (4):
r + A 0 + A 1 r + A 2 c = r s · P 1 ( X n , Y n , Z n ) P 2 ( X n , Y n , Z n ) + r 0 c + B 0 + B 1 c + B 2 r = c s · P 3 ( X n , Y n , Z n ) P 4 ( X n , Y n , Z n ) + c 0 - - - ( 5 )
Order
F = r n = P 1 ( X n , Y n , Z n ) P 2 ( X n , Y n , Z n ) (6)
G = c n = P 3 ( X n , Y n , Z n ) P 4 ( X n , Y n , Z n )
Obtain
r + A 0 + A 1 r + A 2 c = r s · F + r 0 c + B 0 + B 1 c + B 2 r = c s · G + c 0 - - - ( 7 )
Following formula Taylor single order is launched to obtain
r + A 0 + A 1 r + A 2 c ≈ r ~ + ∂ r ∂ X · ΔX + ∂ r ∂ Y · ΔY + ∂ r ∂ Z · ΔZ c + B 0 + B 1 c + B 2 r ≈ c ~ + ∂ c ∂ X · ΔX + ∂ c ∂ Y · ΔY + ∂ c ∂ Z · ΔZ - - - ( 8 )
So the error equation of single scape image is:
v r = ∂ r ∂ X · ΔX + ∂ r ∂ Y · ΔY + ∂ r ∂ Z · ΔZ - ( A 0 + A 1 r + A 2 c ) - ( r - r ~ ) v c = ∂ c ∂ X · ΔX + ∂ c ∂ Y · ΔY + ∂ c ∂ Z · ΔZ - ( B 0 + B 1 c + B 2 r ) - ( c - c ~ ) - - - ( 9 )
In the following formula
∂ r ∂ X = r s ∂ F ∂ X = r s ∂ F ∂ X n dX n dX = r s ∂ X s ∂ F ∂ X n = r s X s ∂ p 1 ∂ X n p 2 - p 1 ∂ p 2 ∂ X n p 2 p 2
∂ r ∂ Y = r s ∂ F ∂ Y = r s ∂ F ∂ Y n dY n dY = r s Y s ∂ F ∂ Y n = r s Y s ∂ p 1 ∂ Y n p 2 - p 1 ∂ p 2 ∂ Y n p 2 p 2
∂ r ∂ Z = r s ∂ F ∂ Z = r s ∂ F ∂ Z n dZ n dZ = r s Z s ∂ F ∂ Z n = r s Z s ∂ p 1 ∂ Z n p 2 - p 1 ∂ p 2 ∂ Z n p 2 p 2
∂ c ∂ X = c s ∂ G ∂ X = c s ∂ G ∂ X n dX n dX = c s X s ∂ G ∂ X n = r s X s ∂ p 3 ∂ X n p 4 - p 3 ∂ p 4 ∂ X n p 4 p 4
∂ c ∂ Y = c s ∂ G ∂ Y = c s ∂ G ∂ Y n dY n dY = c s Y s ∂ G ∂ Y n = c s Y s ∂ p 3 ∂ Y n p 4 - p 3 ∂ p 4 ∂ Y n p 4 p 4
∂ c ∂ Z = c s ∂ G ∂ Z = c s ∂ G ∂ Z n dZ n dZ = c s Z s ∂ G ∂ Z n = c s Z s ∂ p 3 ∂ Z n p 4 - p 3 ∂ p 4 ∂ Z n p 4 p 4
The form of each partial derivative is:
∂ P ( X , Y , Z ) ∂ X = a 2 + a 4 Y + a 6 Z + 2 a 8 X + a 10 YZ + 2 a 12 YX + a 14 Y 2 + 3 a 15 X 2 + a 16 Z 2 + 2 a 18 XZ
∂ P ( X , Y , Z ) ∂ Y = a 1 + a 4 X + a 5 Z + 2 a 7 X + a 10 XZ + 3 a 11 Y 2 + a 12 X 2 + a 13 Z 2 + 2 a 14 YX + 2 a 17 YZ
∂ P ( X , Y , Z ) ∂ Z = a 3 + a 5 Y + a 6 X + 2 a 9 Z + a 10 XY + 2 a 13 YZ + 2 a 16 XZ + a 17 Z 2 + a 18 X 2 + 3 a 19 Z 2
Then by the identical point coordinates (r of left and right sides photo 1, c 1), (r 2, c 2), can list following four error equations:
v rl v rr v d r cr 1 r c 0 0 0 0 0 0 0 0 0 ∂ r l ∂ X ∂ r l ∂ Y ∂ r l ∂ Z 0 0 0 1 c r 0 0 0 0 0 0 ∂ r r ∂ X ∂ r r ∂ Y ∂ r r ∂ Z 0 0 0 0 0 0 1 r c 0 0 0 ∂ c l ∂ X ∂ c l ∂ Y ∂ c l ∂ Z 0 0 0 0 0 0 0 0 0 1 c r ∂ c r ∂ X ∂ c r ∂ Y ∂ c r ∂ Z A 0 A 1 A 2 B 0 B 1 B 2 C 0 C 1 C 2 D 0 D 1 D 2 ΔX ΔY ΔZ - r l - r ^ l r r - r ^ r c l - c ^ l c r - c ^ r - - - ( 10 )
So the least squares equation that coordinate correction is counted Δ is
V＝AΔ-l (11)
Δ＝(A TA) -1A Tl (12)
Wherein
A = 1 r c 0 0 0 0 0 0 0 0 0 ∂ r l ∂ X ∂ r l ∂ Y ∂ r l ∂ Z 0 0 0 1 c r 0 0 0 0 0 0 ∂ r r ∂ X ∂ r r ∂ Y ∂ r r ∂ Z 0 0 0 0 0 0 1 r c 0 0 0 ∂ c l ∂ X ∂ c l ∂ Y ∂ c l ∂ Z 0 0 0 0 0 0 0 0 0 1 c r ∂ c r ∂ X ∂ c r ∂ Y ∂ c r ∂ Z , l = r l - r ^ l r r - r ^ r c l - c ^ l c r - c ^ r
Determining of initial value: owing to resolve the mathematical model of topocentric coordinates employing is the later model of linearization, need carry out iteration for obtaining optimum solution.Initial value (the X of ground coordinate (0), Y (0), Z (0)) can use the standardization translation parameters mean value of the RFM of left and right sides image correspondence.
(5) employing obtains the relation between reference mark elevation and the check point point group vertical accuracy based on the control of buildings elevation location and precision evaluation scheme of a group.
Known WGS84 volume coordinate have a few, a given predefined elevation is divided into several some groups with all known points at interval, be arranged in same some group have identical elevation value range a little.This scheme comprises several experiments, for each experiment, all choosing several plane distribution from certain some group puts uniformly as the reference mark, carry out geometry location according to the described method of step (4), when precision evaluation, also be to be that the unit is estimated with a group for check point, evaluation index is the mean value of the elevation difference of all check points in the some group, the relation between controlled point height and the check point point group precision.
The elevation of integrated ground that obtains of GPS in the present embodiment and aviation image and LiDAR and buildings roof point is as shown in table 1, comprises 200 known points altogether, and wherein the ground point elevation is less than 50m, and totally 22, all the other all are buildings roof point.
Elevation scope characteristic distributions according to the present embodiment data, get elevation and be spaced apart 50m, consider that a some 360.76m and all the other point heights that elevation is the highest differ too big, itself and 200～250m point are combined as a some group, then always have 0～50m, 50～100m, 100～150m, 150～200m, 5 points of 200～360.76m group.The elevation status of the point of each some group is as shown in table 2:
Reference mark of adopting among table 1 embodiment and the tabulation of the elevation of check point
Period Elevation (m) Period Elevation (m) Period Elevation (m) Period Elevation (m) Period Elevation (m)
1 12.07 41 75.49 81 89.40 121 106.35 161 121.73
2 12.92 42 75.78 82 89.69 122 107.23 162 121.94
3 12.94 43 76.64 83 89.79 123 107.27 163 122.52
4 12.99 44 76.65 84 89.97 124 107.36 164 123.23
5 13.04 45 77.07 85 90.15 125 107.38 165 124.25
6 13.15 46 77.79 86 90.56 126 107.76 166 125.64
7 13.16 47 77.84 87 90.60 127 109.27 167 125.74
8 13.18 48 78.20 88 90.92 128 109.63 168 125.83
9 13.25 49 79.14 89 90.95 129 109.97 169 126.82
10 13.28 50 79.26 90 91.04 130 110.03 170 127.05
11 13.35 51 79.80 91 91.66 131 110.15 171 130.04
12 13.38 52 79.98 92 92.26 132 110.27 172 130.66
13 13.51 53 80.21 93 92.27 133 110.58 173 132.04
14 13.55 54 80.50 94 92.46 134 111.04 174 135.63
15 13.56 55 80.63 95 92.86 135 111.29 175 135.75
16 13.62 56 80.67 96 92.88 136 112.04 176 137.05
17 13.77 57 81.24 97 94.10 137 112.30 177 137.53
18 13.80 58 81.60 98 94.44 138 113.14 178 137.62
19 13.90 59 82.18 99 94.46 139 113.28 179 137.99
20 14.23 60 82.83 100 94.88 140 113.35 180 138.67
21 14.48 61 83.95 101 95.09 141 113.51 181 139.12
22 15.38 62 84.42 102 96.09 142 113.54 182 140.22
23 54.01 63 84.51 103 96.19 143 113.66 183 151.15
24 54.80 64 85.06 104 96.23 144 114.68 184 153.53
25 61.79 65 85.20 105 96.31 145 114.90 185 154.18
26 61.82 66 85.97 106 96.85 146 115.14 186 158.72
27 63.62 67 86.43 107 98.76 147 115.86 187 159.15
28 64.69 68 86.51 108 99.43 148 116.46 188 162.63
29 65.11 69 86.55 109 99.83 149 117.54 189 163.81
30 68.38 70 86.71 110 102.17 150 118.59 190 164.17
31 69.91 71 87.04 111 102.29 151 118.87 191 164.53
32 70.00 72 87.26 112 102.39 152 119.53 192 181.31
33 70.73 73 87.83 113 102.48 153 119.65 193 189.25
34 72.28 74 88.00 114 102.57 154 120.34 194 190.81
35 73.81 75 88.21 115 103.01 155 120.50 195 193.82
36 74.01 76 88.24 116 103.45 156 120.54 196 214.11
37 74.55 77 88.25 117 103.77 157 120.75 197 216.90
38 74.57 78 88.28 118 104.47 158 120.87 198 235.64
39 74.67 79 88.59 119 105.13 159 120.98 199 244.64
40 75.04 80 88.62 120 105.96 160 121.10 200 360.76
Table 2 reference mark and check point point Groups List
Point group elevation scope (m) 0-50 50-100 100-150 150-200 200-360.76
The point number 22 87 73 13 5
Minimum elevation (m) 12.07 54.01 102.17 151.15 214.11
Maximum elevation (m) 15.38 99.83 140.22 193.82 360.76
Dispersed elevation (m) 13.48 83.37 117.42 168.24 254.41
When the reference mark was positioned at the ground point group, the reference mark number in each some group of present embodiment was 5, makes it keep plane distribution even as far as possible.Carry out geometry location according to the described method of step (4), positioning result is analyzed according to the dispersed elevation and the dispersed elevation error of check point point group, then obtain Fig. 3.
From Fig. 3, can find clearly to have corresponding relation between the dispersed elevation of check point point group and the dispersed elevation error.The reference mark is positioned at ground, dispersed elevation is 13.01m, be positioned at this some group of 0～50m, the check point dispersed elevation error minimum of this some group as seen from the figure, be 0.57m, along with the increase of check point point group dispersed elevation, its corresponding dispersed elevation error also increases, when check point point group dispersed elevation reached the 254.41m of maximum, its dispersed elevation also reached maximum 1.37m.
When the reference mark is positioned at other 4 some groups of top of building, for each the some group in the table 2, select this point organize interior 5 equally distributed as the reference mark.Adopt the affine RFM model in picture side to add these 5 reference mark and improve geometric positioning accuracy.In this some group remaining have a few and all the other 4 some groups in point be used as check point, be used for the analysis and Control point when being positioned at a spot elevation group, in this some group with the vertical accuracy situation of the interior check point of all the other some groups.Carry out geometry location according to the described method of step (4), positioning result is analyzed according to the dispersed elevation and the dispersed elevation error of check point point group, then obtain Fig. 4.
As can be seen from Figure 4, there is tangible corresponding relation between the dispersed elevation of check point point group and dispersed elevation error and the corresponding reference mark elevation scope.For example, be the some group of 50～100m for the elevation scope, the check point of this some group has minimum dispersed elevation error 0.59m, and all the other some group dispersed elevation and this some group dispersed elevation difference are big more, then its dispersed elevation error is big more; When check point point group is 200～361m, maximum dispersed elevation error 1.06m is arranged.Other 3 kinds of situations among Fig. 4 also have identical conclusion.As seen use as square RFM model, when the reference mark is positioned at different some groups, different for the geometry correction result in all the other some groups.Check point in reference mark point class range has the highest elevation location precision.
The above-mentioned description to embodiment is can understand and apply the invention for ease of those skilled in the art.The person skilled in the art obviously can easily make various modifications to these embodiment, and needn't pass through performing creative labour being applied in the General Principle of this explanation among other embodiment.Therefore, the invention is not restricted to the embodiment here, those skilled in the art should be within protection scope of the present invention for improvement and modification that the present invention makes according to announcement of the present invention.

Claims (8)

1. control of buildings elevation location and precision evaluation method based on a satellite image is characterized in that: specifically may further comprise the steps:
(1) the Ground Control point data is obtained in the measurement of GPS field operation;
(2) aviation image is carried out the regional network bundle adjustment and obtain buildings roof point coordinate;
(3) the buildings roof point vertical coordinate that obtains of horizontal coordinate that aviation image is obtained and airborne LiDAR data integrates buildings roof reference mark;
(4), obtain ground and the accurate three-dimensional coordinate of buildings roof based on the high-resolution satellite stereopsis geometry location of picture side rational function model RFM;
(5) employing obtains the relation between reference mark elevation and the check point point group vertical accuracy based on the control of buildings elevation location and precision evaluation scheme of a group.
2. control of buildings elevation location and precision evaluation method based on satellite image according to claim 1, it is characterized in that: described GPS field operation is measured and is obtained the Ground Control point data, be specially: in satellite stereo image and aviation image regional extent, choose the ground point of the same name of some equably, measure its pixel coordinate on satellite stereo image and many scapes aviation image, and measure its volume coordinate in WGS84 by GPS, as ground control point.
3. control of buildings elevation location and precision evaluation method based on satellite image according to claim 1, it is characterized in that: describedly aviation image is carried out the regional network bundle adjustment obtain buildings roof point coordinate, be specially: on many scapes aviation image, choose equally distributed buildings roof point, measure its image coordinate, it is carried out bundle block adjustment with ground point of the same name, topocentric WGS84 volume coordinate is known, obtains the WGS84 volume coordinate of buildings roof point according to bundle block adjustment.
4. control of buildings elevation location and precision evaluation method based on satellite image according to claim 1, it is characterized in that: the buildings roof point vertical coordinate that described horizontal coordinate that aviation image is obtained and airborne LiDAR data are obtained integrates buildings roof reference mark, be specially: according to the WGS84 volume coordinate position of the buildings roof point of trying to achieve on the aviation image, in the airborne LiDAR data of same area, choose the same roof angle point zone of same building thing, and by asking the mean value of all LiDAR data points in this zone to obtain the vertical coordinate of buildings angle point, vertical coordinate in the buildings roof point coordinate that the vertical coordinate replacement aviation image regional network bundle adjustment of this buildings angle point obtains obtains buildings roof point control coordinate.
5. control of buildings elevation location and precision evaluation method based on satellite image according to claim 1, it is characterized in that: described high-resolution satellite stereopsis geometry location based on picture side rational function model RFM, obtain ground and the accurate three-dimensional coordinate of buildings roof, be specially: the pixel coordinate of on satellite stereo image, measuring the buildings roof point corresponding with aviation image, rational polynominal coefficients R PC that provides according to high-resolution satellite stereopsis supplier and corresponding reference mark coordinate, row standing statue side rational function geometric correction model is found the solution the unknown ground point and the WGS84 volume coordinate of buildings roof point.
6. control of buildings elevation location and precision evaluation method based on satellite image according to claim 1, it is characterized in that: described control of buildings elevation location and precision evaluation scheme based on a group, obtain the relation between reference mark elevation and the check point point group vertical accuracy, be specially: known WGS84 volume coordinate have a few, a given predefined elevation at interval, all known points are divided into several some groups, be arranged in same some group have identical elevation value range a little; This scheme comprises several experiments, for each experiment, all choosing several plane distribution from certain some group puts uniformly as carrying out geometry location in the reference mark, when precision evaluation, be to be that the unit is estimated with a group for check point, evaluation index is the mean value of the elevation difference of all check points in the some group, the relation between controlled point height and the check point point group precision.
7. control of buildings elevation location and precision evaluation method based on satellite image according to claim 2, it is characterized in that: described ground control point, when it is chosen, this point must be in satellite stereo image and many scapes aviation image exists simultaneously, and is image and goes up all tangible joint on the spot.
8. control of buildings elevation location and precision evaluation method based on satellite image according to claim 3, it is characterized in that: described buildings roof point, when it was chosen, this point must all obviously exist in satellite stereo image, many scapes aviation image and airborne LiDAR data.
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