117,437 research outputs found
Evaluating spaceborne L-band pol tomo SAR for forest biomass retrieval based on airborne SAR data
No full textThis paper presents an evaluation of L-band tomographic synthetic-aperture radar (TomoSAR) data for forest biomass retrievals. Tomograms are processed from multiple synthetic-aperture radar (SAR) data sets from the Krycklan forest site, located in the north and south of Sweden. Tomographic performance is matched to possible future spaceborne SAR configurations such as SAOCOM-CS. Ivol, the integrated volumetric backscatter between 10 m and 30 m, is found to result in improved biomass retrievals compared to those based on slope corrected SAR intensity γ0from the original airborne E-SAR system
Calibration of a Ground-Based Array Radar for Tomographic Imaging of Natural Media
No full textGround-based tomographic radar measurements provide valuable knowledge about the electromagnetic scattering mechanisms and temporal variations of an observed scene and are essential in preparation for space-borne tomographic synthetic aperture radar (SAR) missions. Due to the short range between the radar antennas and a scene being observed, the tomographic radar observations are affected by several systematic errors. This article deals with the modelling and calibration of three systematic errors: mutual antenna coupling, magnitude and phase errors and the pixel-variant impulse response of the tomographic image. These errors must be compensated for so that the tomographic images represent an undistorted rendering of the scene reflectivity. New calibration methods were described, modelled and validated using experimental data. The proposed methods will be useful for future ground-based tomographic radar experiments in preparation for space-borne SAR missions
Sensitivity of P- and L-Band SAR Tomography to Above-Ground Biomass in a Hilly Temperate Forest
No full textTomographic synthetic aperture radar (TomoSAR) is a promising technique for the estimation of forest above-ground biomass (AGB), but knowledge gaps still remain concerning the effects of forest type and ground topography. This article presents new results at P- and L-bands based on data acquired during the TomoSense campaign. The study area is a temperate forest, predominantly beech and spruce, with ground slopes ranging up to 40°. Analysis of vertical reflectivity profiles shows distinct differences for spruce and beech. Three AGB retrieval methods are analyzed, i.e., total vertical backscatter I tot, canopy backscatter from a height layer Ic, and the ratio Icr= Ic/Itot. All three methods show sensitivity to AGB for spruce, whereas for beech, this is only true for the two latter methods. For the P-band, a significant ground slope effect is observed, while less so for the L-band. The highest R2 is obtained for spruce with HV polarization, Ic and ground slopes less than 10°, i.e., R2 = 0.86 and RMSE =15.6% for P-band and R2 = 0.75 and RMSE =12.5% for L-band. Corresponding results by including all forest types are R2 = 0.77 and RMSE =11.4% for P-band and R2 = 0.54 and RMSE =12.0% for the L-band. Moreover, the performance of using I cr is similar to that of Ic. The ratio I cr can be determined without absolute radiometric calibration which relaxes system requirements. This article reinforces the potential of TomoSAR for forest AGB estimation and draws attention to important effects of tree species and ground slope
Sleep disordered breathing - A hidden co-morbidity in patients with atrial fibrillation?
No full textJeroen ML Hendriks, Peter Johansson, Anna Strömberg, Martin Ulander, Anders Broströ
Evaluating P-Band TomoSAR for Biomass Retrieval in Boreal Forest
No full textP-band synthetic aperture radar (SAR) is sensitive to above-ground biomass (AGB) but retrieval accuracy has been shown to deteriorate in topographic areas. In boreal forest, the signal penetrates through the canopy to interact with the ground producing variations in backscatter depending on ground topography, forest structure, and soil moisture. Tomographic processing of multiple SAR images Tomographic SAR (TomoSAR) provides information about the vertical backscatter distribution. This article evaluates the use of P-band TomoSAR data to improve AGB retrievals from backscattered intensity by suppressing the backscattered signal from the ground. This approach can be used even when the tomographic resolution is insufficient to resolve the vertical backscatter profile. The analysis is based on P-band data from two campaigns: BioSAR-1 (2007) in Remingstorp, southern Sweden, and BioSAR-2 (2008) in Krycklan (KR), northern Sweden. BioSAR airborne data were also processed to correspond as closely as possible to future BIOMASS TomoSAR acquisitions, with BioSAR-2-based results shown. A power law AGB model using volumetric HV polarized backscatter performs best in KR, with training residual root mean-squared error (RMSE) of 30%-36% (27-33 t/ha) for airborne data and 38%-39% for simulated BIOMASS data. Airborne TomoSAR data suggest that both vertical and horizontal tomographic resolution are of importance and that it is possible to greatly reduce AGB retrieval bias when compared with airborne P-band SAR backscatter intensity-based retrievals. A lack of significant ground slopes in Remningstorp reduces the benefit of using TomoSAR data which performs similar to retrievals based solely on P-band SAR backscatter intensity
Going Beyond Counting First Authors in Author Co-citation Analysis
No full textThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Square Dancing with the Stars to Enhance Dynamic Hirschman Linkages?
No full textIn this Presidential Address, the author takes the reader on a reconnaissance of his life and time as a regional scientist. He points out scenery he found scintillating along the way, hoping that some may pick up the banner and chew on a few of the ideas for a while. He suggests a revisit to Albert O. Hirschman’s notion of key sectors and more empirical analysis related to Marcus Berliant’s and Masahisa Fujita’s notion of knowledge creation and transfer.Presidential Address, San Antonio, Texas, March 29, 2014 (53rd Meetings of the Southern Regional Science Association
Appropriate Similarity Measures for Author Cocitation Analysis
No full textWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
MODEL-BASED ESTIMATION OF TROPICAL FOREST BIOMASS FROM NOTCH FILTERED P-BAND SAR BACKSCATTER
No full textThis paper presents a new algorithm for forest biomass estimation from P-band synthetic-aperture radar (SAR) backscatter data, notch-filtered at ground-level. A semi-empirical model is fitted to spatial and polarization trends in the backscatter data and no reference biomass data are needed for training. An evaluation on airborne P-band SAR data from a tropical test site in Gabon results in a root-mean-square error lower than 20% and a correlation better than 90%
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