H. Karszenbaum

1.1k total citations
60 papers, 812 citations indexed

About

H. Karszenbaum is a scholar working on Environmental Engineering, Atmospheric Science and Aerospace Engineering. According to data from OpenAlex, H. Karszenbaum has authored 60 papers receiving a total of 812 indexed citations (citations by other indexed papers that have themselves been cited), including 42 papers in Environmental Engineering, 29 papers in Atmospheric Science and 21 papers in Aerospace Engineering. Recurrent topics in H. Karszenbaum's work include Soil Moisture and Remote Sensing (37 papers), Precipitation Measurement and Analysis (25 papers) and Synthetic Aperture Radar (SAR) Applications and Techniques (20 papers). H. Karszenbaum is often cited by papers focused on Soil Moisture and Remote Sensing (37 papers), Precipitation Measurement and Analysis (25 papers) and Synthetic Aperture Radar (SAR) Applications and Techniques (20 papers). H. Karszenbaum collaborates with scholars based in Argentina, Italy and Netherlands. H. Karszenbaum's co-authors include Francisco Grings, Patricia Kandus, Juan C. Jiménez‐Muñoz, Leonardo Paolini, José A. Sobrino, P. Ferrazzoli, Ignácio Gasparri, Domingo A. Gagliardini, Julio Jacobo-Berlles and Javier Tiffenberg and has published in prestigious journals such as Nature, Remote Sensing of Environment and IEEE Transactions on Geoscience and Remote Sensing.

In The Last Decade

H. Karszenbaum

51 papers receiving 764 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
H. Karszenbaum Argentina 15 375 367 341 214 131 60 812
Francisco Grings Argentina 14 382 1.0× 299 0.8× 249 0.7× 209 1.0× 112 0.9× 72 717
Lori White Canada 16 501 1.3× 357 1.0× 415 1.2× 170 0.8× 188 1.4× 36 933
F.J. Ahern Canada 13 388 1.0× 453 1.2× 524 1.5× 143 0.7× 168 1.3× 48 881
T. Letoan France 6 253 0.7× 593 1.6× 300 0.9× 155 0.7× 368 2.8× 13 880
Sarah Banks Canada 16 330 0.9× 237 0.6× 312 0.9× 188 0.9× 97 0.7× 30 701
J.J. van der Sanden Canada 19 453 1.2× 579 1.6× 564 1.7× 430 2.0× 213 1.6× 50 1.3k
Pat Scaramuzza United States 8 595 1.6× 324 0.9× 661 1.9× 314 1.5× 190 1.5× 15 1.2k
R. R. Navalgund India 17 233 0.6× 412 1.1× 315 0.9× 292 1.4× 226 1.7× 67 945
S. S. Saatchi United States 14 226 0.6× 662 1.8× 368 1.1× 249 1.2× 315 2.4× 53 969
E. Podest United States 17 474 1.3× 551 1.5× 387 1.1× 524 2.4× 184 1.4× 50 1.2k

Countries citing papers authored by H. Karszenbaum

Since Specialization
Citations

This map shows the geographic impact of H. Karszenbaum's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by H. Karszenbaum with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites H. Karszenbaum more than expected).

Fields of papers citing papers by H. Karszenbaum

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by H. Karszenbaum. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by H. Karszenbaum. The network helps show where H. Karszenbaum may publish in the future.

Co-authorship network of co-authors of H. Karszenbaum

This figure shows the co-authorship network connecting the top 25 collaborators of H. Karszenbaum. A scholar is included among the top collaborators of H. Karszenbaum based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with H. Karszenbaum. H. Karszenbaum is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Ruscica, Romina, Jan Polcher‬, Anna A. Sörensson, et al.. (2020). Spatio-temporal soil drying in southeastern South America: the importance of effective sampling frequency and observational errors on drydown time scale estimates. International Journal of Remote Sensing. 41(20). 7958–7992. 13 indexed citations
2.
Grings, Francisco, et al.. (2015). Land Intercalibration and Drift Monitoring of MWR Radiometer on Board SAC-D/Aquarius. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. 8(12). 5462–5467. 1 indexed citations
3.
Grings, Francisco, et al.. (2015). Validation Strategies for Satellite-Based Soil Moisture Products Over Argentine Pampas. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. 8(8). 4094–4105. 11 indexed citations
4.
Grings, Francisco, et al.. (2014). A Bayesian approach for a SAC-D/aquarius soil moisture product. 1. 1–4.
5.
6.
Ferrazzoli, P., et al.. (2013). Effect of Forward/Inverse Model Asymmetries Over Retrieved Soil Moisture Assessed With an OSSE for the Aquarius/SAC-D Mission. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. 7(3). 943–949. 1 indexed citations
7.
Grings, Francisco, et al.. (2013). Monitoring Vegetation Moisture Using Passive Microwave and Optical Indices in the Dry Chaco Forest, Argentina. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. 7(2). 421–430. 14 indexed citations
8.
9.
Grings, Francisco, et al.. (2011). Estimating flooded area and mean water level using active and passive microwaves: the example of Paraná River Delta floodplain. Hydrology and earth system sciences. 15(8). 2679–2692. 12 indexed citations
10.
Grings, Francisco, et al.. (2011). A Bayesian methodology for soil parameters retrieval from SAR images. 32. 1215–1218.
11.
Rahmoune, R., et al.. (2010). Sensitivity to Soil Moisture Variations of Microwave Radiometric Signatures over the Argentinian Chaco Forest. 686. 107.
12.
Ferrazzoli, P., et al.. (2010). AMSR-E observations of rain and flood events over vegetated areas of LA Plata basin. Cineca Institutional Research Information System (Tor Vergata University). 31. 63–66. 2 indexed citations
13.
Ferrazzoli, P., et al.. (2010). Investigating the sensitivity to soil moisture variations of microwave radiometric signatures over the Argentinian Chaco Forest. Cineca Institutional Research Information System (Tor Vergata University).
14.
Karszenbaum, H., et al.. (2009). Datos satelitales ópticos y de radar para el mapeo de ambientes en macrosistemas de humedal. Americanae (AECID Library). 35–51. 9 indexed citations
15.
Grings, Francisco, et al.. (2008). Exploring the capacity of radar remote sensing to estimate wetland marshes water storage. Journal of Environmental Management. 90(7). 2189–2198. 28 indexed citations
16.
Karszenbaum, H., Francisco Grings, P. Ferrazzoli, et al.. (2005). ASAR Multitemporal and Dual Polarization Observations of Wetland Marshes. 572. 2 indexed citations
17.
Martínez, Jean-Michel, H. Karszenbaum, Thuy Le Toan, et al.. (2002). Detecting anthropogenic and natural disturbances in wetland ecosystems with multitemporal ERS 2 data. 475. 111–115. 1 indexed citations
18.
Kandus, Patricia, et al.. (1999). Land cover classification system for the Lower Delta of the Parana River (Argentina) : Its relationship with landsat thematic mapper spectral classes. Journal of Coastal Research. 15(4). 909–926. 24 indexed citations
19.
Gagliardini, Domingo A. & H. Karszenbaum. (1987). The importance of the NOAA-AVHRR data in resources inventories and environmental monitoring in Argentina and neighboring countries. Advances in Space Research. 7(3). 7–10. 1 indexed citations
20.
Karszenbaum, H. & Domingo A. Gagliardini. (1975). Galactic X-ray sources and the ionospheric D region. Nature. 257(5521). 34–35. 2 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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