International Archives of Photogrammetry and Remote Sensing, Vol. 32, Part 7-4-3 W6, Valladolid, Spain, 3-4 June, 1999 
185 
1.1. Digital forest inventory mapping 
Actual stand borders are delineated with the aid of BAV 
orthophotos, generated from periodically acquired imagery for 
updating topographic maps. The low spectral response of the 
panchromatic images are not appropriate for delineating forest 
stand borders. 
1.2. High resolution satellite data 
Nearly every nation active in space technology has the tendency 
of developing high resolution optical satellite stereo systems 
(Konecny and Schiewe, 1997). Recently, high resolution optical 
satellite data is made available for civil applications and the 
trend will definitely improve in near future. The era of high 
resolution satellite data already started with the launch of the 
Indian satellite IRS-1C in 1995. The expected start of the 
commercial era of high resolution Earth Observing satellites at 
the end of the year 1997 (Fritz, 1996) was delayed up to now 
due to failed missions (EarlyBird®). 
The recently launched IKONOS-1 also failed. Space Imaging® 
is however confident that with the launch of IKONOS-2 they 
will achieve their goal. The IKONOS-2 mission will be 
followed by the missions of QuickBird® and OrbView®-3 later 
this year with a spatial resolution between 1 and 4m (see Table 
1). 
Most of the systems do not only provide a very high spatial 
resolution but also stereo capability, which offers the possibility 
not only to extract two-dimensional spatial information but also 
height information. In addition, a large number of satellites with 
similar capabilities will also reduce the weather dependency due 
to the more frequent area coverage by all satellites together. 
Some people expect that operation of the above mentioned high 
resolution satellite systems will substitute many applications of 
aerial photography. In particular, it is expected that the price of 
satellite products will be lower than those derived from aerial 
photography (Fritz, 1996). In addition, satellite data provide 
direct digital use and integration in existing digital databases. 
1.3. Sensor fusion 
Due to technical reasons, optical satellite data have either a high 
spectral or a high spatial resolution. In order to use the benefit of 
both, several data fusion techniques have been developed to 
integrate information from different datasets in one dataset. 
Sensor Fusion is a part of the wider defined term Data Fusion. 
The following definition of Data Fusion was adopted by the 
EARSeL - SEE - EMP working group (Wald, 1998): 
"data fusion is a formal framework in which are expressed 
means and tools for the alliance of data originating from 
different sources. It aims at obtaining information of greater 
quality; the exact definition of ’greater quality’ will depend 
upon the application". 
This definition emphasizes explicitly data from different 
sources. If these data are from imaging sensors, the fusion is 
described by the term Sensor or Image Fusion. A definition is 
given by van Genderen and Pohl (1994): 
" Image Fusion is the combination of two or more different 
images to form a new image by using a certain algorithm." 
At the end of the 70s, Dailly et al. (1979) tried to combine 
Landsat MSS and SIR-A radar data and Chavez et al. (1986) 
fused Landsat TM and panchromatic aerial photographs. A list 
of fusing different image types is given by Jensen (1996) and 
Pohl (1996). 
Standard pixel-based image fusion procedures (Pohl and van 
Genderen, 1998) like IHS, PC A and Brovey have been applied 
System 
IRS-1C+D 
MOMS-2P 
Earth Watch 
Space Imaging 
Orbital Sciences 
Characteristics 
’QuickBird’ 
Tkonos-2’ 
’OrbView-3’ 
Panchromatic 
0.50 - 0.75 
0.52 - 0.76 
0.45 - 0.90 
0.50 - 0.90 
0.45 - 0.90 
Spectral bands: 
Blue 
0.449-0.511 
0.45 - 0.52 
0.45 - 0.52 
0.45 - 0.52 
Green 
0.52 - 0.59 
0.532 - 0.576 
0.53 - 0.59 
0.52 - 0.60 
0.52 - 0.60 
Red 
0.62 - 0.68 
0.645 - 0.677 
0.63 - 0.69 
0.63 - 0.69 
0.63 - 0.69 
NIR 
0.77 - 0.86 
0.772-0.815 
0.77 - 0.90 
0.76 - 0.90 
0.76 - 0.90 
SWIR 
1.55 - 1.70 
(1.55 - 1.75) 
Resolution (m) 
Pan (Nadir) 
5.8 
6 
1+2 
1 
1 
Spectral 
23.5 
18 
4 
4 
4 
Stereo capability 
No 
Along track 
Along track 
Along track 
Along track 
Orbit 
Sun-syn. 
+/- 28.5 ° 
Sun-syn. 
Sun-syn. 
Sun-syn. 
Flying height (km) 
817 
ca. 296 
600 
680 
470 
Scene coverage 
70x70(p) 
78 
6x6 / 30x30 
60x60 
15x15 
(km 2 ) 
142x142 (m) 
Mission duration 
1994-2000 
1995-1999 
from 1999 
from 1999 
from 1999 
Repetition (days) 
24 
16-20 
14 
14-16 
Table 1. Description of present and near-future high resolution satellite systems (spectral bands in pm).