During years a number of satellites have been developed to remotely sense Earth geophysical parameters for weather forecasting and other climate studies. In recent years the use of reflected Global Navigation Satellite System Signals (GNSS-R) has shown its potential to retrieve geophysical parameters over the ocean, mainly altimetry and sea state, and over land, mainly soil moisture. It is known that sea roughness has an impact on L-band radiometric measurements, and therefore on the retrieved sea surface salinity (SSS). GNSS-R is an interesting tool to help improving the sea state effect correction to reduce the final SSS retrieval error. To demonstrate this idea the Passive Advanced Unit (PAU) project was proposed to the European Scienc Foundation (ESF) under the EURYI 2004 call. The main objective was the study of the direct relationship between the radiometric brightness temperatures and some GNSS-R observables to perform the state correction without using emission/scattering models. Once this goal was successfully addressed, the PAU objectives were broaden including the development of new GNSS-R instruments and techniques, and the study of retrieving geophysical parameters from different surfaces. The present Ph.D. dissertation describes one of the research lines of the the PAU project, undertaken between February 2007 and December 2011, within the Passive Remote Sensing Group of the Remote Sensing Lab, at the Department of Signal Theory and Communications of the Universitat Politènica de Catalunya. The present Ph.D. dissertation focuses on GNSS-R techniques applied to the observation of different types of scattering surfaces (land surfaces: bare soils, vegetation-covered soils, snow-covered soils; inland-water surfaces and ocean surfaces) and the retrieval of different geophysical parameters. Two main GNSS-R techniques have been studied and applied to real data obtained during seven field experiments, the Delay-Doppler Map (DDM) processing technique and the Interference-Pattern Technique (IPT), selecting the one most appropriate to the observed surface. Furthermore, in the context of this Ph.D dissertation a new type of GNSS-R instrument has been developed, being the main tool for the application of the IPT and the retrieval of several geophysical parameters over land and inland-water surfaces. After an introduction on GNSS-R and the PAU-project, the methodology, the instruments and the techniques used to retrieve soil moisture, vegetation height and topography in agricultural areas, snow thickness, water level in reservoirs, and wind speed in ocean surfaces, are described. These retrievals show the potential that these opportunity signals have for monitoring a broad kind of effects. After that, some studies related to space-borne GNSS-R techniques are summarized. Finally a summary of the work performed in this Ph. D. dissertation, the main conclusions and the future work lines are presented. The presented results contribute to promote the use of the GNSS opportunity signals for monitoring geophysical parameters to increase the understanding of the Earth¿s water cycle, and position these techniques as suitable tools that enhance water resources management.