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Richard Becker
600 Points

Contributions by role

Editor 600

Contributions by subject area

Natural Resource Management
Environmental Impacts
Spatial and Geographic Information Science
Ecosystem Science
Soil Science
Food, Water and Energy Nexus
Agricultural Science
Biogeochemistry
Forestry

Richard H Becker


Summary

Richard Becker's research interests center around integrating remote sensing techniques with a wide variety of ground based techniques to investigate the interplay between natural and human systems on local and regional scales, both from a water resource and a hazard perspective. He is interested in investigating the nature and origin of water resources, where they are available, how human activities and climate change can affect their sustainable use, and how alterations in surface water systems can affect the surroundings and the environment at large. In addition, he applies this integrated approach to assess hazards generated by human and natural causes. At the environmental remote sensing lab he makes use of and teaches an interdisciplinary approach, which involves integrating remote sensing (from satellite to UAV scale), GIS, hydrologic modeling, geochemistry, geophysics, ecological observations and field techniques to investigate a wide range of geological and environmental problems related to water resources and the impacts of water utilization practices.

Biosphere Interactions Coupled Natural & Human Systems Ecohydrology Environmental Contamination & Remediation Environmental Impacts Environmental Sciences Spatial & Geographic Information Science

Past or current institution affiliations

Western Michigan University

Work details

Associate Professor

University of Toledo
August 2008
Department of Environmental Sciences

Principal Research Associate

Western Michigan University
August 2004 - August 2008
Department of Geosciences

Websites

  • Environmental Remote Sensing at University of Toledo
  • ResearcherID
  • Google Scholar
  • LinkedIn
  • BBGeospatial

PeerJ Contributions

  • Edited 4

Academic Editor on

April 28, 2020
Estimation of soil salt content by combining UAV-borne multispectral sensor and machine learning algorithms
Guangfei Wei, Yu Li, Zhitao Zhang, Yinwen Chen, Junying Chen, Zhihua Yao, Congcong Lao, Huifang Chen
https://doi.org/10.7717/peerj.9087 PubMed 32377459
February 20, 2020
Multidimensional evaluation of the TRMM 3B43V7 satellite-based precipitation product in mainland China from 1998–2016
Ziteng Zhou, Bin Guo, Youzhe Su, Zhongsheng Chen, Juan Wang
https://doi.org/10.7717/peerj.8615 PubMed 32117637
October 17, 2018
Machine-learning-based quantitative estimation of soil organic carbon content by VIS/NIR spectroscopy
Jianli Ding, Aixia Yang, Jingzhe Wang, Vasit Sagan, Danlin Yu
https://doi.org/10.7717/peerj.5714 PubMed 30357023
May 28, 2018
Tea cultivar classification and biochemical parameter estimation from hyperspectral imagery obtained by UAV
Yexin Tu, Meng Bian, Yinkang Wan, Teng Fei
https://doi.org/10.7717/peerj.4858 PubMed 29868272