519 
USE OF SS M/I PASSIVE MICROWAVE DATA FOR THE STUDY OF 
ALPINE REGIONS 
Daniel Hiltbrunner w , Christian Mätzler 1 
1 University of Bern 
Institute of Applied Physics 
Sidlerstrasse 5 
CH-3012 Bern 
Switzerland 
Tel. +41 31 631 45 90 
Fax. 441 3163137 65 
2 University of Bern 
Department of Geography 
Hallerstrasse 12 
CH-3012 Bern 
Switzerland 
Tel. 441 31 631 85 54 
e-Mail: hiltbrunner@giub.unibe.ch 
ABSTRACT: 
Passive microwave data from the SSM/I sensor are used to investigate the temporal behavior 
of the earth surface in the Swiss Alps and the Central Plains. The inversion of the geophysical parameters from 
the satellite data and their interpretation are based on long-term in-situ measurements of the spectral 
microwave signatures of several different earth surface types. In order to study the temporal behavior of the 
snow-covered and snow-free land surface, the surface microwave emissivity has to be derived from the SSM/I 
brightness temperatures. For that purpose, the physical temperature of land surface has to be determined. We 
present three different approaches for estimating land surface temperatures. A first approach uses brightness 
temperatures from the thermal infrared channels onboard the NOAA and Meteosat satellites. The second 
method is based on the Kriging interpolation of temperatures measured by meteorological ground-stations. The 
third algorithm linearly combines SSM/I-brightness temperatures at 19 GHz as an estimator of the physical 
land surface temperature. Comparisons between estimated and measured physical temperatures suggest that the 
last method showing rms values between 2.5 and 3.5K, is mostly suited for our purposes. The temporal 
behavior of the microwave emission of a large forested area near Mulhouse (France) is discussed using 
emissivity parameters derived from the SSM/I data for Winter 1990/91. Emissivity values at 19 and 37 GHz 
(vertical polarisation) are temporally very constant (0.94 and 0.93, respectively). A singular decrease in 
emissivity at 37 GHz is attributed to shallow snow layers within the observed footprint 
KEY WORDS: SSM/I, passive microwaves, land surface temperature, NOAA, Meteosat 
1 INTRODUCTION 
earth surface in Europe, especially the alpine regions, using passive microwave data from the Special Sensor 
Microwave/Imager (SSM/I) onboard the Defense Meteorological Program Satellites (DMSP, Hollinger et al., 
1987). Because of the heterogenous composition of the land surface within a SSM/I footprint a mixed signature 
algorithm was developed, which compares the observed SSM/I brightness temperatures with modelled values 
using a-priori knowledge of the radiative properties of forest and open water. In this paper, we will focus on the 
retrieval of the physical surface temperature, which is closely related to the microwave brightness temperature. 
As a test of this retrieval we will show how the estimated physical temperature can be used to monitor the 
microwave emission from of a large forested area at 19 and 37 GHz by means of SSM/I data. If the physical 
temperature of a certain surface type is known, we can estimate its emissivity from the remotely sensed 
brightness temperature at different frequencies. This spectral information allows to infer the physical state of 
the observed surface types. 
continuous surface temperature field over parts of the Switzerland. The first method uses thermal infared data 
from the polar-orbiting NOAA-AVHRR and the geostationary Meteosat satellite recorded at the satellite 
receiving station of the Department of Geography (University of Bern, Switzerland; cf. BAUMGARTNER & 
FÜHRER, 1990). The second approach is based on ground-measurements of meteorological stations operated 
by the Swiss Meteorological Institute. The SSM/I data used in the third method are „Wentz-tapes“ provided by 
esrin (Frascati, Italy). The microwave brightness temperatures were spatially interpolated to a 8.6 x 5.4 km grid 
using the algorithm proposed by POE (1990) in order to facilitate the spatial matching of the SSM/I data and 
the ground-based point-measurements. 
The aim of our study is to monitor the temporal behaviour of the snow-covered and snow-free 
In the following sections, we will describe three different approaches to retrieve a spatially