Education

PhD 2014	Remote Sensing	University of Connecticut
MS 2009	GIScience	University of Connecticut
BS 2005	Geology	University of Peradeniya, Sri Lanka

Professional Experience

2020 - Present	Assistant Professor in Residence, Department of Natural Resources and the Environment, University of Connecticut
2018 - 2020	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

Courses Taught

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

Research Interests

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.

Teaching Philosophy

I aim to harness cutting-edge geospatial innovations & technologies as transformative learning instruments to nurture students’ learning competencies to holistically understand complex interactions between human and environment and to scientifically query how those interactions simultaneously shape ecological equilibrium, economic prosperity, and social wellbeing. I am a strong advocate of the idea of that most part of knowledge comes through fingers rather through eyes.  It is my ultimate goal that students completing my course(s) depart with the knowledge, skills, and especially the motivation to help them to become successful professionals and – equally important – informed citizens. Within my teaching space, I embody diversity and multicultural experience in the teaching and learning process. I commit to create a culturally inclusive climate, which respects diversity and inclusivity, and offers equitable and supportive learning experience for all students. I believe that my role is not only one as a teacher, but also one as a facilitator, encouraging students to question, examine, explore, and hopefully develop the level of enthusiasm – and love – that I have for what I teach.

Current or Pending Recent Research Grants

Awarded

• PI (UConn): Collaborative Research: The Permafrost Discovery Gateway: Navigating the New Arctic Tundra through Big Imagery, Artificial Intelligence and Cyberinfrastructure, NSF Office of Polar Programs. 2018-2021. (Univ. of Connecticut, Univ. of Alaska-Fairbanks, Univ. of Illinois Urbana-Champaign) (Total: $3M, UConn: $610,000).
• PI (UConn): Collaborative Research: Patterns, Dynamics, and Vulnerability of Arctic Polygonal Ecosystems: From Ice-Wedge Polygon to Pan-Arctic Landscapes, NSF Office of Polar Programs. 2018-2021. (Univ. of Connecticut, Univ. of Alaska-Fairbanks, Univ. of Virginia) (Total: $1.3M, UConn: $332,000).
• PI: PI: Protecting Critical Infrastructure from UAV Threats (Phase II) – Developing an Integrated Multi-Sensor System for UAV Detection. UConn Eversource Energy Center. 2019-2020. ($391,000).
• PI: Protecting Critical Infrastructure from UAV Threats (Phase I). UConn Eversource Energy Center. 2018-2019. ($150,000).
• PI: Evaluation of LiDAR and Alternative Technologies for Monitoring Roadside Vegetation and Utility Infrastructure (Phase III). UConn Eversource Energy Center. 2018-2020. ($245,000).
• PI: Monitoring Stand- and Tree-Level Forest Change and Plant Invasions using Satellite, Aircraft, UAS Imaging Technologies and Advanced Data Analytics. South Central Connecticut regional Water Authority. 2020-2021. ($15,000)
• PI: State View Program Development and Operations for the State of Connecticut. DOI/United States Geological Survey/America View. 2019-2020. ($23, 500).
• Co-PI: Assessing Temporal Dynamics of Disturbance Interactions as a Driver of a Novel Forest Mortality Event. NSF Division of Environmental Biology. 2019-2020. ($58,000)
• Co-PI: Promoting Water Conservation with Remote Sensing and Hydrological Modeling. Eversource Energy Center. 2019-2020. ($150,000)
• 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: Creating Catalog of Point Clouds for Public Buildings in Enfield, Connecticut. National Institute of Standards and Technology. 2018-2020. ($130,000).
• Co-PI: Evaluation of Airborne and Mobile LiDAR Technologies for Monitoring Roadside Vegetation and Utility Infrastructure (Phase I). 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: State View Program Development and Operations for the State of Connecticut. DOI/United States Geological Survey/America View. 2018-2019. ($23, 500).
• PI: Exploring opportunities to develop a web-based adaptive learning environment to harness remote sensing in Connecticut’s K-12 education. DOI/United States Geological Survey/America View. 2017-2018. ($7,500).

Pending

• Co-PI (UConn): NNA Research: Arctic Change and Human-Build Physical Infrastructure: A Pan-Arctic Integrated Economic Assessment using Geospatial Big Data, AI and Citizen Science. NSF NNA-Navigating the New Arctic program. (Univ. of Connecticut, Univ. of Alaska-Fairbanks). (Total: $3M)
• PI (UConn): Collaborative Research: A Web-GIS Tool for Evaluating Vegetation Risk and Mitigation Strategies to Guide Electric Grid Resilience Efforts. NSF Humans, Disasters, and the Built Environment program. (Univ. of Connecticut, Univ. of Rhode Island). (Total: $150,000)
• Co-PI (UConn): IUCRC Planning Grant University of Connecticut: Center for Weather Innovation, Smart Energy and Resilience (WISER). NSF IUCRC Industry-University Cooperative Research Centers Program. (Univ. of Connecticut, Univ. of Albany).
• PI (UConn): Linkages of Arctic Riparian Shrub Expansion to Water, Permafrost and Soil Microbiom. NSF Office of Polar Programs. 2019 -2022. (Univ. of Connecticut, Univ. of Alaska-Fairbanks). (Total: $2.3M,  UConn: $390,000)
• PI (UConn): Collaborative Research: Water and Carbon Flux Resulting from Thaw-driven Geomorphic Evolution of Water Tracks on Arctic Hillslopes. NSF Office of Polar Programs. 2019 -2022. (Univ. of Connecticut, Univ. of Alaska-Fairbanks).  (Total: $1.7M, UConn: $100,000)

Publications

Google Scholar Profile

Peer-Reviewed:

• Witharana, C., M. A. E. Bhuiyan, A. K. Liljedahl, M. Kanevskiy, T. Jorgenson, B. M. Jones, R. Daanen, H. E. Epstein, C. G. Griffin, and K. Kent. 2021. An Object-Based Approach for Mapping Tundra Ice-Wedge Polygon Troughs from Very High Spatial Resolution Optical Satellite Imagery. Remote Sensing. 2021, 13, 558.
• Witharana, C., M. A. E. Bhuiyan, A. K. Liljedahl, M. Kanevskiy, H. E. Epstein, B. M. Jones, R. Daanen, C. G. Griffin, K. Kent, and M. K. W. Jones. 2020. Understanding the synergies of deep learning and data fusion of multispectral and panchromatic high resolution commercial satellite imagery for automated ice-wedge polygon detection. ISPRS Journal of Photogrammetry and Remote Sensing
• Witharana, C., M. A. E. Bhuiyan, and A. K. Liljedahl. 2020. Big Imagery and High Performance Computing as Resources to Understand Changing Arctic Polygonal Tundra. The International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences 44:111-116.
• Bhuiyan, M. A. E., C. Witharana, A. K. Liljedahl, B. M. Jones, R. Daanen, H. E. Epstein, K. Kent, C. G. Griffin, and A. Agnew. 2020. Understanding the Effects of Optimal Combination of Spectral Bands on Deep Learning Model Predictions: A Case Study Based on Permafrost Tundra Landform Mapping Using High Resolution Multispectral Satellite Imagery. Journal of Imaging 6(9):97.
• Bhuiyan, M. A. E., C. Witharana, and A. K. Liljedahl. 2020. Use of Very High Spatial Resolution Commercial Satellite Imagery and Deep Learning to Automatically Map Ice-Wedge Polygons across Tundra Vegetation Types. Journal of Imaging 6(12):137.
• Strycker, N., M. Wethington, A. Borowicz, S. Forrest, C. Witharana, T. Hart, and H. J. Lynch. 2020. A global population assessment of the Chinstrap penguin (Pygoscelis antarctica). Nature Scientific reports 10(1):1-11.
• Parent J., T. Meyer. J. Volin, R. Fahey, C. Witharana, 2019. An Analysis of Enhanced Tree Trimming Effectiveness using a Geospatial Approach. Journal of Environmental Management. doi.org/10.1016/j.jenvman.2019.04.027
• 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, A.K. Liljedahl, M. Kanevskiy.  2018. Deep convolutional neural networks for automated characterization of Arctic ice-wedge polygons in very high spatial resolution aerial imagery, Remote Sensing.
• 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.

Conferences

• Witharana, C., W. Zhang. 2019. Automated Characterization of Ice-Wedge Polygons from Very-High-Resolution Imagery, ASPRS Annual Conference (IGTF2019), Denver, CO.
• Witharana, C., W. Ouimet, 2019, Object-Based Detection of Southern New England 18th to late 19th-Century  Charcoal Hearths from Lidar Data, ASPRS Annual Conference (IGTF2019), Denver, CO.
• Witharana C., J. Parent, 2019, Automated Mapping of Electric Utility Infrastructure from Multi-Source Remote Sensing Data
• Witharana, C, W. Zhang, A.K. Liljedahl, 2018, From Ice-Wedge Polygons to Pan-Arctic Landscapes: Intensive Mapping of Ice-Wedge Polygons at Extensive Spatial Scales Using Very High-Resolution Remote Sensing Imagery, AGU Fall Meeting, Washington DC.
• 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.
• 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

• Director, 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, Remote Sensing of Environment, 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.