III. Land cover and land use mapping on the basis of color aerial photograph
III.3 Results
III.3.1 Generation of orthophotos and mosaic
Table III.1 displays the RMS errors for all 295 aerial photographs after fiducial setting. On 98% (289) of the aerial photographs a RMS error smaller than 1 pixel was obtained. The six aerial photographs scanned with the desktop scanner had RMS errors between 4-5 pixels. Al-though this was an unsatisfactory result, the errors had to be accepted as fiducial measurement could not be improved on these images due to the bad geometric accuracy on the desktop scanner.
TABLE III.1. Root mean square (RMS) errors after fiducial setting on each aerial photograph
RMS error classes
Exterior orientation – GCPs, tie points and aerial triangulation
The 557 measured GCPs were found on two to eight aerial photographs (Table III.2).
121 GCPs were just present on two aerial photographs as they had been collected at the edge of the block. 97 GCPs were placed on six aerial photographs. This is the standard inside a block with a stereoscopic overlap of 60%, a sidelap of 20% and accurate flight performance.
12 GCPs were positioned in more than six aerial photographs.
TABLE III.2. GCPs positioned on number of aerial photographs (in parenthesis number of GCPs used for aerial triangulation)
could not be sampled. 57.3% (169) of the aerial photographs counted between one and 37 GCPs. The aerial photographs with the majority of GCPs were the ones along the northern border outside the national park with clearly to identify cultural objects.
TABLE III.3. Number of GCPs in aerial photographs
Number of GCPs GCPs in aerial photographs
GCPs in aerial photographs
absolute % absolute %
0 126 42.71 14 12 4.07
1 3 1.02 15 7 2.37
2 14 4.75 16 4 1.36
3 15 5.08 17 5 1.69
4 7 2.37 18 7 2.37
5 6 2.03 19 4 1.36
6 9 3.05 20 1 0.34
7 7 2.37 21 4 1.36
8 13 4.41 23 2 0.68
9 8 2.71 24 1 0.34
10 8 2.71 25 1 0.34
11 7 2.37 26 1 0.34
12 9 3.05 29 1 0.34
13 12 4.07 37 1 0.34
Tie points
The more GCPs existed in the stereoscopic overlaps, the more successful was the automatic tie point search algorithm of Imagine LPS 9.2. Heterogeneity of the image content also influ-enced automatic tie point collection positively. In areas with a high amount of cultural objects as in flight lines 29-31 outside the national park 40-50 tie points were correctly positioned in overlap areas with three or more GCPs. Figure III.6 presents 19 correctly placed automatic tie points (all red circles) in two adjacent aerial photographs taken near La Ciénaga.
Line 32, Photo 61 Line 32, Photo 62
FIGURE III.6. Correct placement of automatically set tie points (all red circles) in two adjacent aerial photographs with GCPs and with heterogeneous image content outside of ABNP
However, aerial photographs with little differentiation in the image content as given in the flight lines 32-37 inside the national park and without measured GCPs, the automatic tie point algorithm produced numerous errors and delivered 10 tie points at most, mainly incorrect. Up to 10 tie points had to be set manually in the stereoscopic overlaps to produce 10-25 automat-ic tie points that had to be checked again. Figure III.7 displays the correct (red circle, no frame) and incorrect (red circle, yellow frame) automatic placement of two tie points in the overlap area of the photos 40-41 in flight line 34 without any GCPs. The image contents con-sisted of close dense pine forests with significant brightness differences.
Line 34, Photo 40 Line 34, Photo 41
FIGURE III.7. Correct (red circle, no frame) and incorrect (red circles in yellow frames)placement of automatically set tie points in two adjacent aerial photographs without GCPs and dense pine cover
Unsatisfactory results were produced by the automatic transfer of tie points in the sidelaps of the flight lines (Figure III.8). Here most of the time tie points had to be transferred manually despite existing GCPs. The positions of the automatically transferred tie points from photo 46, line 29 to photo 46, line 30 were completely incorrect (example: red circle, yellow frame).
Due to the different flight directions in adjacent lines the features appear “upside down” and feature identification can turn out to be complicated.
Line 29, Photo 46 Line 30, Photo 46
FIGURE III.8. Incorrect transfer of tie points (red circle, yellow frames) in the sidelap between two flight lines with heterogeneity in image content and with GCPs
Tie point search in three adjacent images at the same time rarely delivered good results. Diffi-cult was also the automatic tie point search in adjacent aerial photographs taken on different dates. Figure III.9 displays the results for photos 38 and 39 of line 31, taken on January 16th, 2003 and January 28th, 2004 along the northern border of the national park. Of the four tie points two were positioned correctly and two incorrectly (red circles, yellow frames 1 and 2).
Line 31, Photo 38 Line 31, Photo 39
FIGURE III.9. Correct and incorrect placement of automatically set tie points in two adjacent aerial photographs of different dates
The tie points for the six images scanned on the desktop scanner had to be set manually as the image correlation techniques applied for automatic tie point search were sensitive to the geo-metric and scan/image quality. Altogether 17,051 tie points were set homogeneously over the block, one third manually and two thirds automatically.
Aerial triangulation
Only 445 out of the 557 measured GCPs fulfilled the accuracy criteria and entered in aerial triangulation. The final convergence criterion of 0.001 m was met during the fourth iteration of aerial triangulation with a Total Image Unit-Weight RMSE of 0.508 m after having cor-rected, set inactive and deleted spatially incorrect GCPs and tie points. The final solution ex-ceeded the spatial ground resolution of a pixel by 10 cm. The mean GCP RMSE was 2.63 m for the x-coordinates, 2.86 m for the coordinates and 9.21 m for the z-values. The x and y-coordinates of the tie points had an RMSE of 0.595 m and 0.662 m respectively.
Orthophotos
The elevation values of the DSM differed up to 1,000 m compared to the elevation values of the contour lines of the topographic maps. Figure III.10 shows a cutout of the DSM for the overlap area of the photos 40-41 of line 34 at elevations between 1,200-2,500 m a.s.l.. The dark pixels denote areas of low elevation, the bright pixels areas of high elevation. The model did not have clear height structures and looked blurred. Vertical differences of 800 m were measured along a horizontal distance of 300 m which is not real in the Cordillera Central.
Thus, the model could not be used for orthorectification.
FIGURE III.10. DSM of the stereopair of the photos 40-41, line 34 derived from aerial photographs (left) and position of the presented result in the block (right)
The DTM derived from the contour lines at a spacing of 100 m of the topographic maps were highly accurate on steep slopes of the high mountains as the contour lines were close here.
Less accurate were the results of the DTM in the lower and flat areas along the border of the national park. The DTM result for the photos 40-41 of line 34 is presented in Figure III.11. In comparison to the DSM derived from the aerial photograph, the DTM had a clear elevation structure and did not contain large elevation differences between adjacent pixels. Of the 100 random points more than 55% coincided with the topographic contour lines between 0-10 m (Table III.4). Three of the random points had deviations of 30-40 m. The final corrected DTM used for orthorectification is displayed in Figure III.12.
FIGURE III.11. DTM of the stereopair of the photos 40-41, line 34 derived from the 100 m spacing contour lines of the topographic maps at 1:50,000 (Source: ICM 1983/1984)
TABLE III.4. Comparison of elevation of 100 random points on DTM and topographic maps
Range of elevation differences (m) Number of random points
0–5 31
6–10 24
11–20 24
21–30 18
31-40 3
Sum 100
FIGURE III.12. Final DTM derived from 100 m contour lines of Armando Bermúdez National Park used for orthorectification (Source: DTM derived in this study; Boundaries of ABNP from Law 64-00; Peaks, contour lines ICM 1983/1984)
The results of spatial matching between the orthophotographs and the topographic maps are shown in Table III.5. 59% of the evaluation points had a spatial matching of 0-20 m and 41%
of 21-50 m. On trail or road intersections where GCPs had been collected, the orthophoto coordinates matched best with the topographic maps. The spatial mismatch between the two data sources is considered as acceptable for the aims of this study – the interpretation of land cover and land use of a national park.
TABLE III.5. Spatial matching between orthophotographs and topographic maps evaluated at 100 points
Range of spatial matching (m) Number of random points
0–10 32
11–20 27
21–30 17
31-40 16
41-50 8
Sum 100
Mosaicking
Figure III.13 demonstrates the results of image dodging techniques for two orthophotos of different dates, one scanned on a photogrammetric scanner and the other one on a desktop scanner. The left images present the two adjacent orthophotos before mosaicking and the right image after mosaicking. Color balancing and brightness histogram matching techniques were applied, but the seam could not be concealed.
Orthophotos Mosaick
Line 31, Photo 51 Line 31, Photo 52 Line 31, Photo 51 Line 31, Photo 52 FIGURE III.13. Result of color balancing and histogram matching of orthophotos of different dates,
scanned on a photogrammetric scanner (Photo 51, January 28th, 2004) and on a desk-top scanner (Photo 52, December 24th, 2002)
In Figure III.14 the color and brightness differences of two orthophotos taken on the same date, scanned on a photogrammetric scanner and on a desktop scanner are shown. The origi-nal images had considerable variations in color and brightness. After applying image dodging techniques the colors and tones were slightly adjusted, but the seam was still notable.
Orthophotos Mosaick
Line 33, Photo 37 Line 33, Photo 38 Line 33, Photo 37 Line 33, Photo 38 FIGURE III.14. Result of color balancing and histogram matching of orthophotos of the same date,
scanned on a photogrammetric scanner (Photo 37) and desktop scanner (Photo 38)
Figure III.15 shows a satisfactory image matching result of two aerial photographs of the same date and both scanned on a photogrammetric scanner. The brightness differences before matching are still notable while the mosaicked composition is homogeneous in color and has better contrasts than the original orthophotos.
Orthophotos Mosaick
Line 33, Photo 51 Line 33, Photo 52 Line 33, Photo 35 Line 33, Photo 52 FIGURE III.15. Result of color balancing and histogram matching of orthophotos of the same date,
both scanned on a photogrammetric scanner
The final controlled and enhanced mosaic of all 295 aerial photographs had a spatial resolu-tion of 0.4 m and an overall dimension of 40 km (maximum north-south) by 80 km (maxi-mum east-west), requiring 35.1 GB of storage in the Leica image format (Figure III.16). Color and brightness matching techniques adjusted the differences between the 295 aerial photo-graphs to a certain degree. The visual interpretability was given.
FIGURE III.16. Final color corrected mosaic of 295 orthophotos of Armando Bermúdez National Park (Source: Mosaic derived in this study; Boundaries of ABNP from Law 64-00)