This paper reports on research to estimate leaf area index (LAI) in Swedish forests with satellite sensor data. The study is part of a research programme that aims at generating input data for process-oriented forest carbon models. Field-work was carried out in two areas in Sweden about 530 km apart, in the nemoral and boreo-nemoral forest regions. Various ways of estimating LAI in the field were tested, including litter-traps, allometric equations, and light transmission measurements. The capability of Landsat TM and ETM+ for LAI-mapping was investigated with the Nilson and Kuusk forest reflectance model. Results point to channel 3 and the mid-IR channels as particularly important for LAI estimation in coniferous stands, however, modelled reflectances were strongly influenced by background reflectances (particularly at low densities) and leaf optical properties. Top-of-canopy reflectances were derived from Landsat TM and ETM+, and their relationships with field-estimated LAI analysed. Among several vegetation indices tested, the Moisture Stress Index (TM5 / TM4) was one of the best indices for LAI in coniferous stands. In deciduous stands relationships based on the Simple Ratio were superior, however, the explanatory power in deciduous stands was lower than in coniferous stands.