Abstract The Multi-Year Reanalysis of Remotely Sensed Storms (MYRORSS) dataset blends radar data from the WSR-88D network and Near-Storm Environmental (NSE) model analyses using Multi-Radar Multi-Sensor (MRMS) framework. MYRORSS uses archive starting in 1998–2011, processing all valid single-radar volumes to produce a seamless three-dimensional reflectivity volume over entire contiguous United ...

In Australia, remotely sensed Landsat data is routinely used for mapping and monitoring the change in extent of woody perennial vegetation. Time-series remotely sensed satellite imagery and ground information is used to form multi-temporal classifications of presence/absence of woody cover, typically for state-based management and reporting of clearing. More recently, there has been increased i...

This is an update to the special section “Remote Sensing for Vadose Zone Hydrology—A Synthesis from the Vantage Point” [Vadose Zone Journal 12(3)]. Satellites (e.g., Soil Moisture Active Passive [SMAP] and Soil Moisture and Ocean Salinity [SMOS]) using passive microwave techniques, in particular at L-band frequency, have shown good promise for global mapping of near-surface (0–5-cm) soil moistu...

Land-cover datasets are crucial for earth system modeling and human-nature interaction research at local, regional and global scales. They can be obtained from remotely sensed data using image classification methods. However, in processes of image classification, spectral values have received considerable attention for most classification methods, while the spectral curve shape has seldom been ...

The majority of the aboveground biomass on Earth’s land surface is stored in forests. Thus, forest plays a critical role global carbon cycle. Yet accurate estimate (FAGB) remains elusive. This study proposed new conceptual model to map FAGB using remotely sensed data from multiple sensors. model, which provides guidance for selecting data, based principle estimating ground allometry, needs spec...