Propagation of errors associated with scaling foliage biomass from field measurements to remote sensing data over a northern Canadian national park

2013 ◽  
Vol 130 ◽  
pp. 205-218 ◽  
Author(s):  
W. Chen ◽  
P. Zorn ◽  
Z. Chen ◽  
R. Latifovic ◽  
Y. Zhang ◽  
...  
Keyword(s):  
Remote Sensing ◽  
National Park ◽  
Remote Sensing Data ◽  
Field Measurements ◽  
Sensing Data ◽  
Propagation Of Errors

Atmospheric boundary layer parameters retrieval from Stepped Frequency Microwave Radiometer measurements in tropical cyclones

2020 ◽  
Author(s):  
Nikita Rusakov ◽  
Evgeny Poplavsky ◽  
Olga Ermakova ◽  
Yuliya Troitskaya ◽  
Daniil Sergeev ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Boundary Layer ◽  
Atmospheric Boundary Layer ◽  
Microwave Radiometer ◽  
Remote Sensing Data ◽  
Field Measurements ◽  
Radar Signal ◽  
Time And Space ◽  
Sensing Data ◽  
Radar Images

<p>Active microwave sensing using satellite instruments has great advantages, since in this range the absorption by clouds and atmospheric gases is noticeably reduced, it allows for round-the-clock and all-weather monitoring of the ocean. One of the main problems is concerned with obtaining the dependency between the RCS of radar signal scattered by the wavy water surface and the parameters of the atmospheric boundary layer in hurricane conditions. To obtain this dependence, we used field measurements of wind speed in a hurricane from falling NOAA GPS-sondes and SAR images from the Sentinel-1 satellite. However, there is the problem of correct collocation of remote sensing data with field measurements of the atmospheric boundary layer parameters, since they are separated in time and space. In this regard, the amount of data suitable for analysis is very limited, which forces us to look for new data sources for processing. A six-channel SFMR radiometer is also installed on board of NOAA research aircraft that measures the emissivity of the ocean surface beneath the aircraft. Thus, it becomes possible to relate the radiometric measurements of SFMR with the parameters of the atmospheric boundary layer in a tropical cyclone obtained from wind velocity profiles, since they are carried out as close as possible in time and space. Using this relation, the SFMR data and the hurricane radar images were analyzed together and an alternative method was found for constructing the dependence of the RCS on the parameters of the boundary layer.</p><p>This work was supported by the RFBR projects No. 19-05-00249, 19-05-00366, 18-35-20068 (remote sensing data analysis) and RSF No. 19-17-00209 (GPS-sondes data assimilation and processing).</p><p> </p>

scholarly journals Characterization and Mapping of Fuel Types for the Mediterranean Ecosystems of Pollino National Park in Southern Italy by Using Hyperspectral MIVIS Data

2006 ◽  
Vol 10 (13) ◽  
pp. 1-11 ◽  
Author(s):  
Rosa Lasaponara ◽  
Antonio Lanorte ◽  
Stefano Pignatti
Keyword(s):  
Remote Sensing ◽  
National Park ◽  
Remote Sensing Data ◽  
Ground Truth ◽  
Mediterranean Ecosystems ◽  
Remotely Sensed ◽  
Hyperspectral Data ◽  
Test Area ◽  
Sensing Data

Abstract The characterization and mapping of fuel types is one of the most important factors that should be taken into consideration for wildland fire prevention and prefire planning. This research aims to investigate the usefulness of hyperspectral data to recognize and map fuel types in order to ascertain how well remote sensing data can provide an exhaustive classification of fuel properties. For this purpose airborne hyperspectral Multispectral Infrared and Visible Imaging Spectrometer (MIVIS) data acquired in November 1998 have been analyzed for a test area of 60 km2 selected inside Pollino National Park in the south of Italy. Fieldwork fuel-type recognitions, performed at the same time as remote sensing data acquisition, were used as a ground-truth dataset to assess the results obtained for the considered test area. The method comprised the following three steps: 1) adaptation of Prometheus fuel types for obtaining a standardization system useful for remotely sensed classification of fuel types and properties in the considered Mediterranean ecosystems; 2) model construction for the spectral characterization and mapping of fuel types based on a maximum likelihood (ML) classification algorithm; and 3) accuracy assessment for the performance evaluation based on the comparison of MIVIS-based results with ground truth. Results from our analysis showed that the use of remotely sensed data at high spatial and spectral resolution provided a valuable characterization and mapping of fuel types being that the achieved classification accuracy was higher than 90%.

On the use of cross-polarized SAR and GPS-sonde measurements for wind speed retrieval in tropical cyclones

2020 ◽  
Author(s):  
Evgeny Poplavsky ◽  
Nikita Rusakov ◽  
Olga Ermakova ◽  
Yuliya Troitskaya ◽  
Daniil Sergeev ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Boundary Layer ◽  
Wind Speed ◽  
Atmospheric Boundary Layer ◽  
Remote Sensing Data ◽  
Field Measurements ◽  
Cross Polarization ◽  
Sar Images ◽  
Sensing Data ◽  
High Level

<p>The current investigation is concerned with the study of the dependence of the scattered cross-polarized microwave signal from the Sentinel-1 satellite on the parameters of the marine atmospheric boundary layer based on data obtained from falling NOAA GPS-sondes under tropical cyclone conditions.<br>Field measurements and remote sensing data for hurricanes in the Atlantic and Pacific oceans were analyzed for the period 2016 - 2018. Based on the analysis of data measured by GPS-sondes, averaged wind speed profiles were obtained, while the parameters of the atmospheric boundary layer (drag coefficient and wind friction velocity) were retrieved using the self-similarity property of velocity profiles from measurements in the “wake” part.<br>Sentinel-1 SAR images were used as remote sensing data. Images with cross polarization have a high level of thermal noise (NESZ), which leads to errors when retrieving the NRCS. In this regard, preliminary image processing was performed in the SNAP application.<br>Using the obtained parameters of the atmospheric boundary layer, the data of GRS-sonde measurements and Sentinel-1 SAR images on cross polarization were collocated and the dependences of the NRCS on the parameters of the atmospheric boundary layer were obtained.</p><div>This work was supported by the RFBR projects No. 19-05-00249, 19-05-00366, 18-35-20068 (remote sensing data analysis) and RSF No. 19-17-00209 (GPS-sondes data assimilation and processing).</div>

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