Tropical forests, which provide important ecosystem functions and services, are increasingly threatened by anthropogenic pressures. This has resulted in an urgent need to understand tree species diversity of those forests. Where knowledge of that diversity is largely from the botanical surveys and local ecological studies, data must inevitably be up-scaled from point observations to the landscape and regional level if a holistic perspective is required. This thesis explores aspects of the spatio-temporal heterogeneity of canopy reflectance patterns over the forests of French Guiana, in order to assess whether this information could help defining an ecologically consistent forest typology. To gain insight into both the spatial and temporal heterogeneity of French Guiana’s forests, instrumental artefacts affecting the satellite data first had to be addressed. Data used in this study represent the spectral response of forest canopies, and the way in which such data are captured makes them susceptible to the ‘bi-directional reflectance distribution function’ (BRDF). BRDF indicates that objects do not reflect light in equal proportions in all directions (isotropically). Thus, forest canopies will reflect light anisotropically depending on factors including canopy roughness, leaf optical properties and inclination, and the position of the sun relative to the sensor. The second chapter of this thesis examines how BRDF affects the canopy reflectance of forests in French Guiana, and how not correcting for BRDF affects spectral classifications of those forests. When monthly reflectance data corrected for the artefact are examined, these suggest seasonally-occurring changes in forest structure or spectral properties of French Guiana’s forests. The third chapter of this thesis thus examines temporal effects of BRDF, and used cross-regional comparisons and plot-level radiative transfer modelling to seek to understand the drivers of the monthly variation of the forests’ canopy reflectance. For the latter, the Discrete Anisotropic Radiative Transfer (DART) model was used along with aerial laser scanning (ALS) observations over different forest structures, indicating that the observed variation in reflectance (and derivatives known as vegetation indices) could not be explained by monthly variations in solar direction. At the regional scale, it was also demonstrated that forests in the Guiana Shield possess temporal variation distinct from forests in central Africa or northern Borneo, forests also lying just above the Equator. Had the observed temporal variation in vegetation indices been the result of BRDF, it would have been expected that the forests in the three zones would have similar patterns of variation, which they did not. Central African forests appear to have their greening synchronized with rainfall, whereas forests in the Guianas appear synchronized with the availability of solar radiation. Further analysis of the vegetation index time-series of observations also indicated that different types of forests in French Guiana possess distinct patterns of temporal variation, suggesting that tropical forest types can be discriminated on the basis of their respective “temporal signatures.” That was exploited in the fourth chapter of the thesis, which maps forests in French Guiana based on their combined spatio-temporal canopy reflectance patterns and by so doing presents a novel way of addressing forest typology, based on ecologically meaningful information. The thesis presented demonstrates that it is possible to adequately address remote sensing data artefacts to examine patterns of spatial and temporal variation in tropical forests. It has shown that phenological patterns of tropical rainforests can be deduced from remote sensing data, and that forest types can be mapped based on spatio-temporal canopy reflectance patterns. It is thus an important contribution to understand the ecology of tropical forests in French Guiana and to improve the toolbox of scientists dealing with the identification of spatio-temporal patterns observable in forests at the landscape level.