Jordan S. Borak

1.2k total citations
18 papers, 779 citations indexed

About

Jordan S. Borak is a scholar working on Atmospheric Science, Global and Planetary Change and Ecology. According to data from OpenAlex, Jordan S. Borak has authored 18 papers receiving a total of 779 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Atmospheric Science, 7 papers in Global and Planetary Change and 6 papers in Ecology. Recurrent topics in Jordan S. Borak's work include Remote Sensing in Agriculture (6 papers), Cryospheric studies and observations (6 papers) and Plant Water Relations and Carbon Dynamics (4 papers). Jordan S. Borak is often cited by papers focused on Remote Sensing in Agriculture (6 papers), Cryospheric studies and observations (6 papers) and Plant Water Relations and Carbon Dynamics (4 papers). Jordan S. Borak collaborates with scholars based in United States, Taiwan and Brazil. Jordan S. Borak's co-authors include Michael F. Jasinski, Jacques Descloitres, Min Zheng, David P. Roy, Sadashiva Devadiga, Robert E. Wolfe, Sujay V. Kumar, C. D. Peters‐Lidard, David M. Mocko and Shugong Wang and has published in prestigious journals such as Remote Sensing of Environment, Water Resources Research and Journal of Hydrology.

In The Last Decade

Jordan S. Borak

17 papers receiving 741 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Jordan S. Borak United States 12 459 339 276 266 121 18 779
Steve Foga United States 4 469 1.0× 533 1.6× 243 0.9× 219 0.8× 78 0.6× 6 919
Alex O. Onojeghuo United Kingdom 17 300 0.7× 441 1.3× 240 0.9× 141 0.5× 85 0.7× 28 814
J. Latham Italy 6 402 0.9× 335 1.0× 196 0.7× 246 0.9× 33 0.3× 12 713
Eugene A. Fosnight United States 5 477 1.0× 401 1.2× 221 0.8× 127 0.5× 85 0.7× 10 721
Lori White Canada 16 501 1.1× 415 1.2× 357 1.3× 170 0.6× 76 0.6× 36 933
Vincent Debaecker Germany 9 356 0.8× 515 1.5× 307 1.1× 168 0.6× 52 0.4× 23 829
Calli B. Jenkerson United States 7 409 0.9× 429 1.3× 237 0.9× 128 0.5× 47 0.4× 10 692
H. Karszenbaum Argentina 15 375 0.8× 341 1.0× 367 1.3× 214 0.8× 54 0.4× 60 812
Tim Danaher Australia 13 740 1.6× 583 1.7× 454 1.6× 138 0.5× 224 1.9× 20 1.1k
Mads Olander Rasmussen Denmark 15 284 0.6× 325 1.0× 286 1.0× 207 0.8× 61 0.5× 22 658

Countries citing papers authored by Jordan S. Borak

Since Specialization
Citations

This map shows the geographic impact of Jordan S. Borak'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 Jordan S. Borak with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jordan S. Borak more than expected).

Fields of papers citing papers by Jordan S. Borak

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jordan S. Borak. 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 Jordan S. Borak. The network helps show where Jordan S. Borak may publish in the future.

Co-authorship network of co-authors of Jordan S. Borak

This figure shows the co-authorship network connecting the top 25 collaborators of Jordan S. Borak. A scholar is included among the top collaborators of Jordan S. Borak 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 Jordan S. Borak. Jordan S. Borak is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

18 of 18 papers shown
1.
Tangdamrongsub, Natthachet, et al.. (2021). Optimizing GRACE/GRACE-FO data and a priori hydrological knowledge for improved global terrestial water storage component estimates. Journal of Hydrology. 598. 126463–126463. 13 indexed citations
2.
Stanley, Thomas, et al.. (2020). Building a landslide hazard indicator with machine learning and land surface models. Environmental Modelling & Software. 129. 104692–104692. 47 indexed citations
3.
Stanley, Thomas, et al.. (2019). A Landslide Climate Indicator from Machine Learning. AGU Fall Meeting Abstracts. 2019. 1 indexed citations
4.
Jasinski, Michael F., Jordan S. Borak, Sujay V. Kumar, et al.. (2019). NCA-LDAS: Overview and Analysis of Hydrologic Trends for the National Climate Assessment. Journal of Hydrometeorology. 20(8). 1595–1617. 27 indexed citations
5.
Kumar, Sujay V., David M. Mocko, Shugong Wang, C. D. Peters‐Lidard, & Jordan S. Borak. (2019). Assimilation of Remotely Sensed Leaf Area Index into the Noah-MP Land Surface Model: Impacts on Water and Carbon Fluxes and States over the Continental United States. Journal of Hydrometeorology. 20(7). 1359–1377. 95 indexed citations
6.
Kumar, Sujay V., Michael F. Jasinski, David M. Mocko, et al.. (2018). NCA-LDAS Land Analysis: Development and Performance of a Multisensor, Multivariate Land Data Assimilation System for the National Climate Assessment. Journal of Hydrometeorology. 20(8). 1571–1593. 86 indexed citations
7.
Kirschbaum, Dalia, et al.. (2017). Assessment of rainfall thresholds for landslide triggering in the Pacific Northwest: extreme short-term rainfall and long-term trends. AGU Fall Meeting Abstracts. 2017. 1 indexed citations
8.
Yatheendradas, Soni, C. D. Peters‐Lidard, Victor Koren, et al.. (2012). Distributed assimilation of satellite‐based snow extent for improving simulated streamflow in mountainous, dense forests: An example over the DMIP2 western basins. Water Resources Research. 48(9). 25 indexed citations
9.
Borak, Jordan S. & Michael F. Jasinski. (2008). Effective interpolation of incomplete satellite-derived leaf-area index time series for the continental United States. Agricultural and Forest Meteorology. 149(2). 320–332. 34 indexed citations
10.
11.
Jasinski, Michael F., Jordan S. Borak, & Richard D. Crago. (2005). Bulk surface momentum parameters for satellite-derived vegetation fields. Agricultural and Forest Meteorology. 133(1-4). 55–68. 18 indexed citations
12.
Borak, Jordan S., Michael F. Jasinski, & Richard D. Crago. (2005). Time series vegetation aerodynamic roughness fields estimated from modis observations. Agricultural and Forest Meteorology. 135(1-4). 252–268. 23 indexed citations
13.
Borak, Jordan S. & Alan H. Strahler. (2002). Feature selection using decision trees-an application for the MODIS land cover algorithm. 1. 243–245. 2 indexed citations
14.
Roy, David P., Jordan S. Borak, Sadashiva Devadiga, et al.. (2002). The MODIS Land product quality assessment approach. Remote Sensing of Environment. 83(1-2). 62–76. 232 indexed citations
15.
Muchoney, D., Jordan S. Borak, & Alan H. Strahler. (2002). Global landcover classification validation issues and requirements. 1. 233–235. 1 indexed citations
16.
Muchoney, D., Jordan S. Borak, M. A. Friedl, et al.. (2000). Application of the MODIS global supervised classification model to vegetation and land cover mapping of Central America. International Journal of Remote Sensing. 21(6-7). 1115–1138. 101 indexed citations
17.
Borak, Jordan S.. (2000). Identification of land-cover change and interannual climate variability in Africa from satellite imagery.
18.
Borak, Jordan S.. (1999). Feature selection and land cover classification of a MODIS-like data set for a semiarid environment. International Journal of Remote Sensing. 20(5). 919–938. 72 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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