H-Index & Metrics Best Publications

H-Index & Metrics

Discipline name H-index Citations Publications World Ranking National Ranking
Environmental Sciences D-index 60 Citations 12,450 189 World Ranking 1122 National Ranking 541

Overview

What is he best known for?

The fields of study he is best known for:

  • Statistics
  • Meteorology
  • Remote sensing

Wade T. Crow mainly investigates Water content, Remote sensing, Data assimilation, Radiometer and Meteorology. He combines subjects such as Soil science, Soil water, Satellite imagery, Evapotranspiration and Surface runoff with his study of Water content. His work on Radiometry as part of general Remote sensing research is frequently linked to Scale and Current, thereby connecting diverse disciplines of science.

His Data assimilation research is multidisciplinary, incorporating perspectives in Moisture, Kalman filter, Errors-in-variables models and Anomaly. His study in Radiometer is interdisciplinary in nature, drawing from both Soil map, Rain gauge, Precipitation and Brightness temperature. His Soil map research includes themes of Atmosphere, Correlation coefficient, Carbon sink, Calibration and Data retrieval.

His most cited work include:

  • The Soil Moisture Active Passive (SMAP) Mission (1780 citations)
  • Upscaling sparse ground‐based soil moisture observations for the validation of coarse‐resolution satellite soil moisture products (411 citations)
  • Assessment of the SMAP Passive Soil Moisture Product (273 citations)

What are the main themes of his work throughout his whole career to date?

Wade T. Crow focuses on Water content, Remote sensing, Data assimilation, Meteorology and Soil science. His research in Water content intersects with topics in Radiometer, Soil water, Atmospheric sciences, Precipitation and Moisture. His research integrates issues of Soil map, Water balance and Brightness temperature in his study of Radiometer.

His research in the fields of Radiometry overlaps with other disciplines such as Scale. His Data assimilation study combines topics from a wide range of disciplines, such as Kalman filter, Streamflow and Surface runoff. His Meteorology research incorporates elements of Mean squared error and Flood forecasting.

He most often published in these fields:

  • Water content (69.76%)
  • Remote sensing (42.34%)
  • Data assimilation (34.27%)

What were the highlights of his more recent work (between 2017-2021)?

  • Water content (69.76%)
  • Atmospheric sciences (14.52%)
  • Remote sensing (42.34%)

In recent papers he was focusing on the following fields of study:

His main research concerns Water content, Atmospheric sciences, Remote sensing, Data assimilation and Precipitation. His work carried out in the field of Water content brings together such families of science as Soil science, Radiometer, Streamflow, Evapotranspiration and Brightness temperature. His Atmospheric sciences research focuses on subjects like Moisture, which are linked to Soil water.

In general Remote sensing study, his work on Synthetic aperture radar often relates to the realm of High resolution, thereby connecting several areas of interest. In Data assimilation, Wade T. Crow works on issues like Surface runoff, which are connected to Infiltration. His Precipitation study combines topics in areas such as Drainage basin and Normalized Difference Vegetation Index.

Between 2017 and 2021, his most popular works were:

  • Development and assessment of the SMAP enhanced passive soil moisture product (140 citations)
  • Global-scale Evaluation of SMAP, SMOS and ASCAT Soil Moisture Products using Triple Collocation. (60 citations)
  • Exploiting soil moisture, precipitation and streamflow observations to evaluate soil moisture/runoff coupling in land surface models. (33 citations)

In his most recent research, the most cited papers focused on:

  • Statistics
  • Meteorology
  • Remote sensing

Water content, Remote sensing, Data assimilation, Atmospheric sciences and Soil science are his primary areas of study. In his work, he performs multidisciplinary research in Water content and Scale. The study incorporates disciplines such as Active passive, Retrieval algorithm and Brightness temperature in addition to Remote sensing.

His biological study spans a wide range of topics, including Kalman filter, Adaptive filter and Monte Carlo method. His work in Soil science covers topics such as Surface runoff which are related to areas like Storm and Infiltration. He has included themes like Soil map and Meteorology in his Correlation coefficient study.

This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.

Best Publications

The Soil Moisture Active Passive (SMAP) Mission

Dara Entekhabi;Eni G Njoku;Peggy E O'Neill;Kent H Kellogg.
Proceedings of the IEEE (2010)

2236 Citations

Upscaling sparse ground‐based soil moisture observations for the validation of coarse‐resolution satellite soil moisture products

Wade T. Crow;Aaron A. Berg;Michael H. Cosh;Alexander Loew.
Reviews of Geophysics (2012)

452 Citations

Assessment of the SMAP Passive Soil Moisture Product

Steven K. Chan;Rajat Bindlish;Peggy E. O'Neill;Eni Njoku.
IEEE Transactions on Geoscience and Remote Sensing (2016)

340 Citations

Performance Metrics for Soil Moisture Retrievals and Application Requirements

Dara Entekhabi;Rolf H. Reichle;Randal D. Koster;Wade T. Crow.
Journal of Hydrometeorology (2010)

314 Citations

Evaluating the Utility of Remotely Sensed Soil Moisture Retrievals for Operational Agricultural Drought Monitoring

J.D. Bolten;W.T. Crow;Xiwu Zhan;T.J. Jackson.
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing (2010)

312 Citations

The hydrosphere State (hydros) Satellite mission: an Earth system pathfinder for global mapping of soil moisture and land freeze/thaw

D. Entekhabi;E.G. Njoku;P. Houser;M. Spencer.
IEEE Transactions on Geoscience and Remote Sensing (2004)

272 Citations

An adaptive ensemble Kalman filter for soil moisture data assimilation

Rolf H. Reichle;Rolf H. Reichle;Wade T. Crow;Christian L. Keppenne;Christian L. Keppenne.
Water Resources Research (2008)

227 Citations

A new data assimilation approach for improving runoff prediction using remotely-sensed soil moisture retrievals

W. T. Crow;D. Ryu.
Hydrology and Earth System Sciences (2009)

209 Citations

A land surface data assimilation framework using the land information system : Description and applications

Sujay V. Kumar;Sujay V. Kumar;Rolf H. Reichle;Rolf H. Reichle;Christa D. Peters-Lidard;Randal D. Koster.
Advances in Water Resources (2008)

194 Citations

Estimating Spatial Sampling Errors in Coarse-Scale Soil Moisture Estimates Derived from Point-Scale Observations

Diego G. Miralles;Wade T. Crow;Michael H. Cosh.
Journal of Hydrometeorology (2010)

187 Citations

If you think any of the details on this page are incorrect, let us know.

Contact us

Best Scientists Citing Wade T. Crow

Dara Entekhabi

Dara Entekhabi

MIT

Publications: 128

Jeffrey P. Walker

Jeffrey P. Walker

Monash University

Publications: 118

Thomas J. Jackson

Thomas J. Jackson

Agricultural Research Service

Publications: 116

Michael H. Cosh

Michael H. Cosh

Agricultural Research Service

Publications: 115

Yann Kerr

Yann Kerr

Federal University of Toulouse Midi-Pyrénées

Publications: 102

Rolf H. Reichle

Rolf H. Reichle

Goddard Space Flight Center

Publications: 95

Andreas Colliander

Andreas Colliander

California Institute of Technology

Publications: 81

Rajat Bindlish

Rajat Bindlish

Goddard Space Flight Center

Publications: 79

Martha C. Anderson

Martha C. Anderson

Agricultural Research Service

Publications: 75

Christopher Hain

Christopher Hain

Marshall Space Flight Center

Publications: 71

Simon Yueh

Simon Yueh

California Institute of Technology

Publications: 69

Luca Brocca

Luca Brocca

Research Institute for Geo-Hydrological Protection

Publications: 65

Aaron A. Berg

Aaron A. Berg

University of Guelph

Publications: 65

Peggy E. O'Neill

Peggy E. O'Neill

Goddard Space Flight Center

Publications: 63

Jean-Pierre Wigneron

Jean-Pierre Wigneron

University of Bordeaux

Publications: 62

Wouter Dorigo

Wouter Dorigo

TU Wien

Publications: 62

Something went wrong. Please try again later.