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Dr. Chandi Witharana

Assistant Research Professor

Department of Natural Resources & the Environment

University of Connecticut
U-4087, 1376 Storrs Road
Storrs, CT 06269-4087


Phone: (860) 486-2840
Fax: (860) 486-5408
Chandi.Witharana@uconn.edu

 

Education

Ph.D. 2014 Remote Sensing University of Connecticut
M.S. 2009 GIScience University of Connecticut
B.S. 2005 Geology University of Peradeniya, Sri Lanka

Courses Taught

NRE 3535 Remote Sensing of the Environment
NRE 4535 Remote Sensing Image Processing
NRE 4695 Object-based Image Analysis for Remote Sensing

Work Experience

2018 - Present Assistant Research Professor, Department of Natural Resources and the Environment, University of Connecticut
2016 - 2018 Visiting Assistant Professor, Department of Natural Resources and the Environment, University of Connecticut
2014 - 2016 Postdoctoral Research Fellow, Department of Ecology and Evolution, SUNY Stony Brook 
2006 - 2013 Graduate Research and Teaching Assistant, Center for Integrative Geosciences, University of Connecticut
2005 - 2006 GIS Analyst, United Nations (UN) Office for the Coordination of Humanitarian Affairs

Research Interest

My research efforts broadly capture the methodological developments and adaptations to unseal faster, deeper, and more accurate analysis of large volumes of high-resolution remote sensing data. Object-based image analysis, point cloud analytics, machine learning, unmanned aerial systems (UAS) stand out as some of the key pitches in my agenda. I conduct interdisciplinary remote sensing research with high international visibility, speaking equally to the transformational uses of remote sensing in environmental, industrial, agricultural, and humanitarian applications. My scope is global. Diversity is an integral part of myself, as well as my research. Some of my work includes mapping ice-wedge polygonal Arctic tundra from sub-meter satellite imagery, on-demand censusing of Antarctic wildlife from space, 3D infrastructure analytics for electric utility industry, unmanned aerial spectroscopy for integrated pest management applications, and on-demand censusing of refugees in armed-conflicted areas in South Asia. Thinking beyond its research and industrial merits, I always value the strengths of remote sensing to address the requirements of the Next Generation Science Standards via the key elements from physics and engineering. I am actively seeking creative ways, such as imagery-enabled lesson plans to harness remote sensing in K-12 STEM education.


Current or Pending Recent Research Grants

  • Awarded
    • Collaborative PI: Collaborative Research: Patterns, Dynamics, and Vulnerability of Arctic Polygonal Ecosystems: From Ice-Wedge Polygon to Pan-Arctic Landscapes, NSF Arctic System Science Program. 2018-2021. (Univ. of Connecticut, Unvi. of Alaska-Fairbanks, Univ. of Virginia) ($1.3M).
    • Co-PI: Detection of UAV Threats to Critical Infrastructure. UConn Eversource Energy Center. 2018-2019. ($350,000).
    • Co-PI: Evaluation of Airborne and Mobile LiDAR Technologies for Monitoring Roadside Vegetation and Utility Infrastructure (Phase II). UConn Eversource Energy Center. 2018-2019. ($245,000).
    • Co-PI: Evaluation of Airborne and Mobile LiDAR Technologies for Monitoring Roadside Vegetation and Utility Infrastructure. UConn Eversource Energy Center. 2016-2018. ($338,000).
    • Co-PI: Integrated Systems Research and Development in Automation and Sensors for Sustainability of Specialty Crops. Hatch Multistate, USDA National Institute for Food and Agriculture. 2018-2021 ($90,000).
    • Co-PI: Development of a model system for scouting potato leafhopper using unmanned aerial system technology: UConn Office of the Vice President for Research. 2018-2019. ($50,000)
    • PI: Exploring opportunities to develop a web-based adaptive learning environment to harness remote sensing in Connecticut’s K-12 education. AmericaView/USGS. ($7,500). 
  • Pending
    • Collaborative PI: Collaborative Research: Ecohydrological Linkages of Arctic Riparian Shrub Expansion to Water, Permafrost and Soil Microbiome. NSF Arctic Natural Sciences program. (Univ. of Connecticut, Unvi. of Alaska-Fairbanks). ($2.5M)
    • PI: Crowdsourcing drones for digital crop scouting. Bill and Melinda Gates Foundation. ($100,000).
    • Co-PI: Creating Catalog of Point Clouds for Public Buildings in Enfield, Connecticut. National Institute of Standards and Technology. ($130,000).
    • PI: Leveraging High Resolution Geospatial Data to Improve Understanding of Anthropogenic Perturbations and Habitat Extent along Coastal Long Island Sound, CT/NY Sea Grant. ($180,000)

Selected Publications

  • Google Scholar Profile
  • Peer-Reviewed:
    • Witharana, C., Ouimet, W.B. and Johnson, K.M., 2018. Using LiDAR and GEOBIA for automated extraction of 18th-late 19th century relict charcoal hearths in southern New England. GIScience & Remote Sensing: doi.org/10.1080/15481603.2018.1431356.
    • Zhang, W., C. Witharana, W. Li, C. Zhang , X. Li, J. Parent. 2018. Using deep learning to identify geographic objects and estimate their locations from Google Street View images: A case study of utility poles with crossarms. Sensors.
    • Witharana, C., LaRue, M.A. and Lynch, H.J., 2016. Benchmarking of data fusion algorithms in support of earth observation based Antarctic wildlife monitoring. ISPRS Journal of Photogrammetry and Remote Sensing, 113: 124-143.
    • Witharana, C. and H.J. Lynch., 2016. An object-based image analysis approach for detecting penguin guano from very high spatial resolution satellite images. Remote Sensing 8(5): 375.
    • Witharana, C., D. L. Civco., and T. Meyer., 2014, Evaluation of data fusion and image segmentation in earth observation based rapid mapping workflows, ISPRS Journal of Photogrammetry and Remote Sensing, 87(2014):1-18.
    • Witharana, C. and D. L. Civco,. 2014, Optimizing multi-resolution segmentation scale using empirical methods: Exploring the sensitivity of a supervised discrepancy measure, ISPRS Journal of Photogrammetry and Remote Sensing, 87(2014):108-121.
    • Witharana, C., D. L. Civco, and T. Meyer., 2013. Evaluation of Pansharpening Algorithms in Support of earth observation based rapid mapping workflows, Applied Geography, 37(2013):63-87.
  • In-Press/In Review:
    • Zhang, W., C. Witharana, A.K. Liljedahl, M. Kanevskiy. Deep convolutional neural networks for automated characterization of Arctic ice-wedge polygons in very high spatial resolution aerial imagery, Remote Sensing (in-press).
    • Parent J., T. Meyer. J. Volin, R. Fahey, C.Witharana. An Analysis of Enhanced Tree Trimming Effectiveness using a Geospatial Approach. IEEE Transactions on Power Delivery (in-review).
  • Conference Proceeding:
    • Parent, J., C. Witharana, 2017, Exploring the Costs and Capabilities of Geiger and Conventional LiDAR and Photogrammetry in Mapping Utility Infrastructure and Roadside Vegetation, ASPRS Annual Conference (IGTF2017), Baltimore, MD.
    • Witharana, C., W. Ouimet, 2017. LiDAR, GEOBIA, and Archaeology: Remote sensing of southern New England’s lost archaeological landscape, ASPRS Annual Conference (IGTF2017), Baltimore, MD.
    • Witharana, C., H.J. Lynch, 2017. Transferability of GEOBIA rulesets for detecting penguin guano in very high spatial resolution satellite images, ASPRS Annual Conference (IGTF2017), Baltimore, ME.
    • Witharana, C., H.J. Lynch, 2016. Real-time streaming data on penguin abundance and distribution using very high spatial resolution satellite imagery, ASPRS Annual Conference, Fort Worth, TX.
    • Lynch, H.J., C. Hantz, and C. Witharana, 2016. Geospatial technologies meet K-12 STEM curricula: Use of Remote Sensing as a pedagogical tool in earth and environmental science education, ASPRS Annual Conference, Fort Worth, TX.
    • Witharana, C., D. Tiede and D.L. Civco 2013. Optimizing multi-resolution segmentation algorithm using empirical methods: Exploring the sensitivity of supervised discrepancy measures. Proc. SPIE Remote Sensing Europe, Dresden, Germany.
    • Witharana, C., M. Neubert, and D.L. Civco,2013. Value-added humanitarian information delivery from earth observation data: Investigating synergies of data fusion and image segmentation in rapid mapping workflows. Proc. SPIE Remote Sensing Europe, Dresden, Germany.
    • Witharana, C., 2012. Who Does What Where? Advanced Earth Observation for Humanitarian Crisis Management, Proceedings of the 6th International Conference on Information and Automation. Beijing, China. IEEE paper no. ICIAfS'12 1569613211.
    • Witharana, C., and D.L. Civco, 2012. Evaluating remote sensing image fusion algorithms for use in humanitarian crisis management, Proc. SPIE Remote Sensing Europe, Edinburgh, United Kingdom. DOI:10.1117/12.973745.
    • Civco, D.L and C. Witharana., 2012. Assessing the spatial fidelity of resolution-enhanced imagery using Fourier analysis: a proof-of-concept study, Proc. SPIE Remote Sensing Europe, Edinburgh, United Kingdom. DOI: 10.1117/12.974703
    • Witharana, C. and T. Meyer., 2010 Developing customized ArcGIS tools for disaster management. In Proc. of the IEEE ICIAfS10, Colombo, Sri Lanka.
    • Witharana, C., T. Meyer, D. Civco, and J. Osleeb, 2010. Developing a new ArcGIS Tool to Quantify Building-Content Vulnerability from Storm-Surge Inundation. In Proc. of the ASPRS 2010 Annual Conference, San Diego, California, USA.
    • Witharana, C., T. Meyer, D. Civco, and J. Osleeb, 2010. Developing customized ArcGIS tools for disaster management, In Proc. of the ESRI International User Conference, San Diego, California, USA.
  • Technical Reports
    • Parent, J., C. Witharana, D. Wanik. 2017. Review of Remote Sensing Systems and Approaches for Monitoring Infrastructure and Vegetation. White Paper. Eversource Energy.
    • Witharana C. and J. Hurd. 2017. Exploring opportunities to develop a web-based adaptive learning environment to harness remote sensing in Connecticut’s K-12 education, Project Report, AmericaView.
    • Auster, P.J., K.B. Heinonen, C. Witharana and M. McKee, 2009. A habitat classification scheme for the Long Island Sound region. Long Island Sound Study Technical Report. EPA Long Island Sound Office, Stamford, Connecticut.

Professional Service

  • Principal Investigator, ConnecticutView Program
  • Editorial Advisory Board Member: ISPRS Journal of Photogrammetry and Remote Sensing
  • Proposal Review Panelist: Environmental Data Science, American Association for the Advancement of Science (AAAS)
  • Technical review committee member:
    • 2014 IEEE International Conference on Information and Automation for Sustainability
    • 2012 IEEE International Conference on Information and Automation for Sustainability
    • 2010 IEEE International Conference on Information and Automation for Sustainability
  • Reviewer for Peer-reviewed Journals:
    • Nature, ISPRS Journal of Photogrammetry and Remote Sensing/ Remote Sensing/ Journal of Applied Geography/ International Journal of Applied Earth Observation and Geoinformation/ Remote Sensing Letters/ Bulletin of Engineering Geology and the Environment/ Journal of Geosciences/ Sensors.

Professional Affiliation

  • International Society for Photogrammetry and Remote Sensing (ISPRS)

  • Institute of Electrical and Electronics Engineers (IEEE)

  • American Society for Photogrammetry and Remote Sensing (ASPRS)

  • American Geophysical Union (AGU)

  • New York Academy of Sciences (NYSA)

  • Ecological society of America (ESA)

  • American Association of Geographers (AAG)

Department of Natural Resources and the Environment
College of Agriculture and Natural Resources
University of Connecticut
1376 Storrs Road, Unit 4087
Storrs, Connecticut 06269-4087
Phone: 860-486-2840