Although they only cover ~6% of the Earth's ice-free land surfaces (~8.6 millions km2), natural wetlands and rice paddies play a key role in climate and hydrological processes. Firstly, they represent the world's largest methane source (CH4), the only one dominated by climate variations and account for ~40% of CH4 emitted annually to the atmosphere. In addition, wetlands play a major role for local hydrological system as they contribute in part of the fresh water input in the Oceans by river discharge that greatly influences the ocean circulation through the evolution of the Sea Surface Temperature. Approximately 60% of wetlands are only inundated at some period in the year leading to large uncertainties on their seasonal and inter-annual extents. This is particularly the case for tropical regions subject to the annual rain season as well as Boreal regions subject to the snow melt period. Despite the recognition of their role in climate and hydrological process, as well as their importance in water resources management, wetlands extent and dynamic databases still suffer of a lack of reliable information at global or regional scales over long time period. Characterizing wetlands and their dynamics over large geographical region has been investigated using different techniques with varying degrees of success. Datasets based on soil and vegetation observations represent realistic global wetland distributions, but unfortunately they suffer from a lack of information on temporal and spatial dynamics. In that context, satellite observations provide a means of monitoring wetlands and their dynamics at global and regional scales over long time periods. The objective of this study is to present a new globally applicable remote sensing technique, considering a suite of complementary satellite observations developed to quantify spatial and temporal dynamics of wetlands. The technique it self is based on the detection of inundations at the global scale using the passive microwave land-surfaces emissivities estimated from SSM/I observations, and the use of ERS scatterometer and AVHRR visible and near infrared reflectances to estimate the vegetation contribution to the passive microwave signal. Monthly wetlands extents are now estimated at the global scale over the 9-years 93-2001 period and analyzed regarding to spatial patterns and temporal evolutions. A first results evaluation is made using independent datasets such as land surfaces databases, rain fall rate from GPCP products and water level from radar altimeter measurements. The spatial and temporal wetlands estimations, comprising natural wetlands, irrigated rice culture and lake/river are relevant when compare to static wetlands observations databases. Over the globe, the results show also a high correlation with the GPCP rain data product over the 9 years of study. The correlation over specific regions will be discussed. When focusing around specific areas such as the river basins of the Ganges, the Amazon or Parana Rivers or the Congo-Niger regions, the analysis based on the comparison with water river levels derived from radar altimeter observations show a similar seasonal cycle over the 9 years. These results are encouraging and future studies could now focus on wetlands dynamics as a proxy to study for instance the impacts of ENSO or the monsoons regimes on continental processes. A promising synergy with radar altimetry that could also bring new information related to hydrological parameters, such as river discharges, is under now investigation. Finally, this study stresses the need for development of quality longer satellite estimated wetlands dynamics till upcoming days.