Mihai A. Tanase

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The SMAPEx experiments were conducted in a semi-arid agricultural and grazing area located in southeastern Australia, timed so as to acquire data over a seasonal cycle at various stages of the crop growth. Airborne L-band brightness temperature (∼1 km) and radar backscatter (∼10 m) observations were collected over an area the size of a single SMAP footprint(More)
A study was carried out to investigate the utility of L-band SAR data for estimating aboveground biomass in sites with low levels of vegetation regrowth. Data to estimate biomass were collected from 59 sites located in fire-disturbed black spruce forests in interior Alaska. PALSAR L-band data (HH and HV polarizations) collected on two dates in the(More)
21 NASA's Soil Moisture Active Passive (SMAP) mission will carry the first combined spaceborne L-22 band radiometer and Synthetic Aperture Radar (SAR) system with the objective of mapping near-23 surface soil moisture and freeze/thaw state globally every 2-3 days. SMAP will provide three soil 24 moisture products; (i) high-resolution from radar (~3km), (ii)(More)
This study investigated the effectiveness of frequently used parametric and non-parametric models for biomass retrieval from L-band radar backscatter. Two areas, one in Spain and one in Australia, characterized by different tree species, forest structure and field sampling designs were selected to demonstrate that retrieval error metrics are similar for(More)
—The backscatter predicted by three common surface scattering models (the Integral Equation Model (IEM), the Dubois, and the Oh models) was evaluated against fully polarized L-band airborne observations. Before any site-specific calibration, the Oh model was found to be the most accurate among the three, with mean errors between the simulated and the(More)
This study has compared preliminary estimates of effective leaf area index (LAI) derived from fish-eye lens photographs to those estimated from airborne full-waveform small-footprint LiDAR data for a forest dataset in Australia. The full-waveform data was decomposed and optimized using a trust-region-reflective algorithm to extract denser point clouds. LAI(More)
models were developed to model relationships between biomass and radar/lidar data. Overall, lidar data provided lower estimation errors (17.2 t · ha −1 , 28% relative) when compared with radar data (30.3 t · ha −1 , 61% relative). However, for the 30– 100 t · ha −1 biomass range, the relative error from radar-based models was only 9% higher than that from(More)
Mediterranean pine forests in Spain experience wildland fire events with different frequencies, intensities, and severities which result in diverse socio-ecological consequences. In order to predict fire severity, spectral indices derived from remotely sensed images have been used extensively. Such spectral indices are usually used in combination with(More)
—TerraSAR-X (TSX) dual-polarized synthetic aperture radar (SAR) data from a test site in Spain have been investigated to determine the relationship between forest burn severity and SAR backscatter. The role of the local incidence angle on the backscatter coefficient has been also studied. Burn severity was estimated by means of composition burn index plots(More)