The ISOPHOT experiment onboard the ISO satellite generated a complete view of the Small Magellanic Cloud (SMC) at 170 mum with 1.5 arcmin resolution. The map is analysed using an automated photometry program enabling accurate photometric characterization of the far infrared ( FIR) emitting regions. An integrated FIR luminosity of 8.5 x 10(7) L-. is obtained, leading to a star formation rate of SFRFIR = 0.015 M-./yr. With an average dust temperature of < T-D,T-170/100 = 20.5 K >, the total dust mass follows to M-D = 3.7 x 10(5) M-.. In this paper, the sources detected at 170 mum are compared with those obtainable from the IRAS satellite data. For this purpose, the 12 mum, 25 mum, 60 mum, and 100 mum IRAS high resolution (HiRes) maps of the SMC are re-examined using the same method. In contrast to former studies, this provides an all-band ISO/IRAS source catalog which is no longer based on eyeball classification, but relies on an algorithm which is capable of automated, repeatable photometry, even for irregular sources. In the mid infrared IRAS bands numerous bright FIR emitting regions in the SMC are detected and classified: 73 sources are found at 12 mum, 135 at 25 mum ( most of them with F-v < 1.0 Jy). All three FIR bands at 170 μm, 100 μm, and 60 μm reproduce the overall morphological structure of the SMC similarly well, in contrast to the 12 μm and 25 μm maps which only contain a limited number of extended sources and do not trace the main body of the SMC. 243 sources are detected in the ISO 170 μm map, 155 of them with F-v ≥ 2.0 Jy. Comparable numbers are found for the two FIR IRAS maps at 60 μm (384) and 100 μm (338) with fluxes up to 450 Jy. 70 of the 243 170 μm sources are assigned a general SED type ("cold", "warm", i.e., < 30 K, > 30 K) for the first time. A comparison with earlier IRAS results suggests that many source flux densities in those studies have been under- or overestimated because of non-standardized fitting methods. Many sources with flux densities up to 40 Jy listed in former catalogs cannot be identified in our data.
