Soil moisture is required to improve meteorological and climate predictions. Global soil moisture maps are nowadays produced daily from SMOS satellite data, with a basic spatial resolution of ~50 km. Recently, using data fusion techniques between SMOS and MODIS data, an operational service has been implemented at the SMOS-Barcelona Expert Center to downscale SMOS data down to 1 km over the Iberian peninsula [1]. However, despite SMOS operates in the passive microwave 'protected' band from 1400 to 1427 MHz, radio frequency interference may degrade the quality of the soil moisture (and sea salinity) retrievals or even prevent them [2]. Signals of opportunity transmitted from Global Navigation Satellite Systems (GNSS) can be used for soil moisture, vegetation, snow, water level. monitoring after reflection (GNSS-R) on the Earth's surface. In principle, even though these signals can also be jammed, their structure and the way they are processed, makes them more robust in front of radio-frequency interference, while at the same time -in principle- can achieve also a better spatial resolution. In this work, the few different GNSS-R techniques are first revised, including their pros and cons. Then a few applications are revised, with special emphasis -but not exclusively- in those in which the UPC Remote Sensing Lab has been working.