Suspended matter plays an important role in water quality management since it is related to total primary production and fluxes of heavy metals and micropollutants such as PCBs. Synoptic information on suspended matter at a regular frequency is difficult to obtain from the routine in situ monitoring network since suspended matter is (like chlorophyll) a spatially inhomogeneous parameter. This can be solved by the integrated use of remote sensing data, in situ data and water quality models. A methodology previously developed for integrating information from remote sensing, and models (Vos and Schuttelaar, Neth Remote Sensing Board (1995) report 95-19), was applied for the assessment of suspended matter concentrations in the southern Frisian lakes in the Netherlands. The model is a one-dimensional network model. Remote sensing data (Landsat-TM5 and SPOT-HRV) were atmospherically corrected and converted to total suspended matter maps. The algorithms are based on analytical optical modelling, using the in situ inherent optical properties. This methodology enables the development of multi-temporal algorithms for estimating seston dry weight concentration in lakes from remotely sensed data; thus satellite data can now become an independent measurement tool for water management authorities.