Certain factors need to be taken into consideration when choosing which satellite sensor to use. These include spatial, spectral, temporal, and radiometric reso-lution, and not to mention price and availability. Optical satellite sensors were the most appropriate for this project as they have spectral resolutions that cover the visible and infrared bands which are good for detecting different vegetation types. The satellite would need to orbit over the study often as often as possible in order to acquire a good image from spring, summer, and autumn. The ideal satellite sensor for an individual application does generally not exist however, and compromises usually need to be made. Possible satellites for this project include Landsat and SPOT.
The Landsat satellite with both the Thematic Mapper (TM) and Enhanced The-matic Mapper (ETM)+ sensors on board was chosen for several reasons. Firstly because the Spot satellite with its High Resolution Visible (HRV) and High Res-olution Visible IR (HRVIR) detectors only have multispectral bands covering the equivalent of green, red, near infrared (NIR) and short wave infrared (SWIR) (20m resolution). SPOT 4 satellite also has a low-resolution wide-coverage veg-etation instrument however this product comes with1kmresolution which is too coarse for this project. The sensors TM and ETM+ on board the Landsat satel-lite however cover in addition the blue and Mid Infrared (MIR) bands. Secondly the Landsat satellite images are sold ”at cost” where as the SPOT satellite is a commercial venture and each image is sold from aroundUS$1−10,000(USGS, 2006). Thirdly, the Norwegian Computing Centre already had a large archive of
Landsat images available.
Landsat 5 and 7, launched in 1984 and 1999 respectively are currently the only two operational Landsat satellites. The Landsat satellites are travelling in sun-synchronous orbits at an altitude of approximately705km, with a period of around 100min and a repeat cycle of 16days. On board Landsat 5 are two earth obser-vation sensors the Multispectral Scanner (MSS) and TM, and on board Landsat 7 is the ETM+. Table (3.1) gives the wavelength bands and resolutions for Landsat TM and Landsat ETM+, the two sensors used in this thesis. For reference see the electromagnetic (EM) spectrum diagram in the background chapter, section 2.3.1.
The original scene sizes were approximately 170 x 183km.
In a study by Clark et al. (2001) a comparison of satellite systems for mapping plant communities was done between Landsat TM and SPOT HRV. A Maximum Likelihood Classifier (MLC) was used to classify 6 native and 2 non-native inter-mountain plant communities in Reynolds Creek in western US. When results were compared to ground reference points, the overall accuracy of the maps generated by SPOT and Landsat were statistically similar. de Colstoun et al. (2003) decided on using Landsat ETM+ for mapping vegetation in US National Parks (aiming at a solution for national mapping) because it provided well-calibrated, synoptic, multitemporal imagery for every National Parks Service (NPS) park unit at a cost of less than0.03US cents per hectare.
Sensor Bands Wavelength (µm) Resolution(m)
Thematic Mapper (TM)
Table 3.1: Wavelength regions and resolution corresponding to each original Landsat band for the TM and ETM+ sensors. (USGS, 2006).
The ideal dataset would have a cloud- and snow free image from spring, summer and autumn in order to cover the differences in the growing season. Trying to find a cloud free image over the mountains in Norway on the right date, however, is a
3.1 Satellite Images 33
challenging exercise. Although the Landsat satellites can produce images over the same region every 16 days, the largest number of acceptable images found for the extended mountain area around Venabygd for a particular season was three. Even finding one clear image in an entire growing season was sometimes not possible, so collected images over several years were obtained. Table 3.2 lists the images used.
The scenes stem from various Landsat imagery providers, common to them all is that they were acquired in the L1G format as specified by the Landsat 7 Sci-ence Data Users Handbook, see NASA (2006). In this format the Landsat data are radiometrically and systematically corrected. Although the L1G products are georeferenced, the georeferencing applied was not based on the use of ground control points and typically resulted in residual positional errors on the order of 250m. This was unacceptable and manual georeferencing was done to improve this. This georeferencing was performed using ERDAS Imagine (version 8.7, by Leica Inc.). Ground control points were selected in the uncorrected images and were matched with points of known position and altitude in a water mask (water mask based on the M711 series of maps). The water mask was made by The Nor-wegian Mapping Authority and used in conjunction with a 25m resolution digital elevation model (DEM) (also made by the Norwegian Mapping Authority). The images were geometrically corrected to the UTM coordinate system (zone 32) using the WGS84 datum (a global reference frame for the earth defined by the World Geodetic System). Geo-referencing was necessary in order to establish a correspondence between the satellite image pixels and the physical positions on the earths surface (Aurdal et al., 2005b).
A warping and interpolation was then performed using the bilinear interpolation approach, in the resulting image the geographic position of the upper left pixel was known and coincided with a fixed 25m grid so as to allow for easy compar-ison between files (e.g. the 25m DEM). The residual error in these corrected images was on the order of 25m. In the L1G product, the contents of all spectral channels were represented as 8 bit digital numbers (range 0 to 255). Before using the images, these digital numbers were scaled back to ’at satellite radiance’ (asr) values. This procedure is described in Chander and Markham (2003) and NASA (2006) for the Landsat TM and ETM data respectively.
A copy of the images was then converted to reflectance values using the calibration process described in Chander and Markham (2003) for converting Landsat radi-ance values to reflectradi-ance values. The images were also clipped to cover only the Venabygd area. All the pre and post processing of the images described here was done by the Norwegian computing centre (NR) in connection with other projects (Aurdal et al., 2005b).
Sensor Date Path Row Geometric correction Resolution
TM 24.07.1994 198 17 UTM 33 25m
TM 25.06.1995 198 17 UTM 33 25m
TM 17.08.1997 198 17 UTM 33 25m
TM 29.07.1999 199 17 UTM 32: reprojected to 33 25m
ETM+ 18.10.1999 198 17 UTM 33 25m
TM 23.05.2004 199 17 UTM 33 25m
Table 3.2: An overview of the Landsat TM and ETM+ images that were used in this thesis, along with their attributes. The wavelengths for each band of the TM and ETM sensors are described in the table above.