IKONOS Pre-Processing

The twelve IKONOS images covering the study area were imported into the PCI Geomatica environment. The multispectral and panchromatic images were visually examined. For some areas of special interest, panchromatic and multispectral channels were fused using the IHS (intensity, hue, saturation) transformation in order to produce colour images at 1 m resolution. This pan-sharpening had the purpose to enhance the possibilities of visual interpretation for training areas and accuracy assessment and to help to recognise the position in the real world (in the field) on the images.

Paper prints of images at reduced and full resolution were produced and used during the field work (chapter 5.2). The IKONOS images of the whole UCRYN were also used as reference for the Landsat classification and accuracy assessment.

For reasons of time and disk space, the IKONOS data were not further processed for the whole catchment area. Only subsets of two of the twelve images were used to test high resolution image processing methods. These two test areas were selected because they were of special ecological and economical interest. The subsets of one image of the eastern and one of the western UCRYN show a large variety of forest types, including plantations, natural and semi-natural forests, and other land cover types of the UCRYN. The IKONOS data covering these areas were of good quality (low cloud cover and atmospheric contamination), and the information density through field work and ancillary data was particularly high for these areas, especially for the eastern test area, which was used as the main IKONOS test area. This area includes the land cover types of the Scientific Reserve Ebano Verde and its buffer zone, from the agriculturally used slopes on both sides of the Río Jimenoa in the west to the centre of the reserve with the cloud forest of the ‘Loma La Sal’ and

‘Loma La Golondrina’ in the east of this test area. The western test area is located to the west of the town of Manabao and includes areas of coffee and pine plantations and the natural forest at the edges of the Armando Bermúdez National Park.

No radiometric distortions or striping were noticeable in the images. No atmospheric correction was conducted for the reasons mentioned in chapter 6.1 (a possible atmospheric correction would not change the relationship between the classes in the feature space). The high sun elevation angles (68.3° in the eastern image and 75.1° in the western image) lead to relatively consistent illumination conditions in the images so that, also in view of the fact that the resolution of the available DEM was very much coarser than that of the IKONOS images, no topographic normalisation was attempted.

The IKONOS data were converted from 11 bit to 8 bit radiometric resolution. The distribution of the grey levels in the visible multispectral IKONOS bands (bands one to three) did not make use of the 11 bit radiometric resolution. Excluding extreme values that belonged only to cloud areas, the data spanned only between 250 and 500 grey levels, i.e. about 8 to 9 bit. The range of values in the NIR and panchromatic bands was somewhat larger, with up to about 1000 grey levels representing the objects of interest (again excluding clouds). All bands were scaled down to 8 bit before further processing in order to make the data more manageable and reduce processing times. In the case of the eastern test area, automatic normalised quantisation was used to reduce the radiometric resolution to 8 bit. This algorithm maps the median value of the input image to the middle of the output range and renders the central portion of the data range with little distortion while gradually compressing the high and low portions of the input range (PCI 2001).

Geometric correction of IKONOS data

The IKONOS images, being ‘Geo products’, were already resampled to the UTM projection. They do, however, contain some residual positional errors and they are not corrected for terrain effects.

Geometric errors of some tens of metres could still be found even in those images acquired with relatively high collection angles (low off nadir angles), rising to hundreds of metres in images with less favourable collection parameters. This requires additional geometric corrections, especially if the data are intended to be combined with other georeferenced data.

The eastern IKONOS image has a high nominal collection angle of 81.3°, resulting in only moderate relief displacement (15 m per 100 m elevation, corresponding to 10 m to the west and 12 m to the south at the nominal collection azimuth of 220.2°). In view of the fact that no high quality DEM was available, this image was not orthocorrected (Toutin 2004) but geometrically corrected using a polynomial transformation. To do this, both the panchromatic and the multispectral image were subset to an area of high ground truth density (eastern test area). 26 ground control points were identified on the panchromatic image using reference points measured with the GPS in the field as well as points identified on the topographic map. Choosing a first order polynomial transformation resulted in an RMSE of 6.73 m in the x-direction and 9.21 m in the y-direction.

Since the RMSE was not reduced by applying higher order models, the registration was performed using a first order polynomial transformation and the nearest neighbour resampling technique. The GCPs were saved and the same set of GCPs was used to geometrically correct the multispectral image using the same parameters. In order to be able to integrate Landsat and IKONOS data, a Landsat subset of this area was tied down to the corrected panchromatic IKONOS image. 73 GCPs were identified both in the 15 m resolution panchromatic Landsat channel and in the IKONOS image, achieving RMS errors of 0.30 (4.5 m) in the x-direction and 0.32 (4.8 m) in the y-direction using a fourth order polynomial transformation. All three images were then trimmed to a common rectangular area, which will be referred to as ‘eastern test area’ in the following.

Most of the other IKONOS images of the UCRYN have lower nominal collection angles than this eastern image. The western IKONOS image (Manabao) for example has a nominal collection angle of 66.9°, resulting in a relief displacement of 43 m per 100 m elevation difference (corresponding to 26 m displacement to the west and 34 m to the north at a collection azimuth of 332°). This made the use of orthocorrection necessary if an acceptable geometric accuracy was to be achieved in this high relief area. A test was conducted to orthorectify this image with the available DEM.

Orthocorrection was performed on a subset of the western IKONOS image using the Rational Functions Model (PCI Geomatics 2001). This model uses ratios of two polynomial functions respectively to compute image row and column. The model was computed from 25 GCPs identified on the pan-sharpened 1 m resolution image (figure 13). The DEM used was a DEM with 10 m grid spacing which had been generated from the 50 m resolution DEM using the kriging method for the interpolation (PCI 2001). The number of coefficients used in the fitted polynomial was 4. This resulted in an overall RMS error of 19.86 m (13.41 m in the x-direction and 14.65 m in the y-direction). This is accurate to within one Landsat ETM pixel, but not close to sub-pixel-accuracy

regarding the IKONOS data. However, sub-pixel accuracy is not a realistic objective for IKONOS data even in flat terrain (Toutin & Cheng 2001) and even when using high quality DEMs (Davis &

Wang 2003). In high-resolution imagery like this, GCPs cannot always be placed on the image with sub-pixel accuracy. The limited accuracy of the GPS which measured GCP locations in the field and of the 1:50000 topographic map used as a basis for part of the GCP coordinates contribute to errors, and the DEM used introduces additional error. Considering the limitations of the underlying data, the above mentioned accuracy seems reasonable and is certainly much better than the accuracy of the non-orthocorrected Geo product.

Figure 13: Distribution of GCPs in the western sub-image during orthocorrection (OrthoEngine environment).

6.3 Digital Elevation Model

The DEM was imported into the PCI Geomatica file format, resulting in a 16 bit data channel with 50 m spatial resolution and digital numbers corresponding to the elevation in metres. As the DEM

had been derived from digitised contours of the same topographical maps which were used as reference for the geometric correction of the satellite images, its UTM coordinates were already correct. The DEM was subset to an area corresponding to the rectangular Landsat subset of the UCRYN. The elevation values were checked for overall agreement with the topographical maps.

Some obvious artefacts in the area of Jarabacoa (where the valley was rendered as a convex form) were manually corrected.

Kriging is a useful interpolation method when the surface is not adequately sampled (Robinson 1994). It was used for the generation of a DEM with 10 m grid spacing needed for orthorectification of the western image (chapter 6.2). A DEM with 8 m grid spacing for processing together with the IKONOS data of the eastern test area was also generated through kriging.

When gridded DEMs are created from contours without identification of drainage lines and ridge lines, flat areas along curved contours can be created by triangulation or during interpolation (Robinson 1994). There is evidence of this effect in the histogram of the DEM used here for the area of the UCRYN which shows sharp peaks at the digitised contour values, especially at 300, 500, 600 and 800 m. This effect is going to introduce errors in slope and aspect calculations, but there is no evidence of it in the more mountainous areas above 800 m, including the eastern test area, because of the reduced horizontal distance between the 100 m contour lines.

In the future, the SRTM 90-m DEM of the world might be a better quality alternative for correcting medium resolution satellite data, but its resolution is not sufficient to combine it with IKONOS data. High resolution DEMs for high quality IKONOS corrections would have to be derived from optical high resolution stereo data (e.g. IKONOS stereo product), but that would make them rather expensive. (The IKONOS Stereo product is 4 to 5 times as expensive as the Geo product.)