Research

Dr. Dixon's Research and Publications

Barnali M. Dixon
GIS and Remote Sensing
Professor, Ph.D., University of Arkansas, 2001
Phone: (727) 873-4025 (O), or (727) 873-4863 (Lab)

Dr. Barnali Dixon is a Professor at School of Geosciences and contributes to Geography and Environmental Science and Policy programs. Dr. Barnali Dixon is the Director of the Geospatial Analytics Lab (G-SAL) and also the Executive Director and PI for the Initiative on Coastal Adaptation and Resilience (iCAR) at USF. Her research focuses on the development and application of Environmental Decision Support Systems (EDSS) integrated with Geospatial Technologies and geocomputation for modeling and managing land-water interfaces for water contamination and vulnerability, with a particular focus on the terrestrial source and aquatic sinks in the context of extreme weather events and climate change (including sea level rise). Dr. Dixon is particularly interested in modeling land-water interface under climate change in the context of planning, adaptation, and resilience with a particular emphasis on the human dimension analysis in the context of coastal flooding, adaptation, and resilience. Her current projects include an analysis of contamination levels in the coastal waters of Florida ( viz. identifying the potential for failure of septic systems and their environmental impacts in the context of compound inundation including sea level rise and climate change) using GIS, and integrative analysis of biophysical and socioeconomic vulnerabilities. Her current AT&T-funded project includes the development of an integrated Community Resiliency Information System (CRIS). CRIS integrates biophysical and socioeconomic vulnerability maps along with environmental justice indicators and real-time sensor data that collects and displays weather and air quality data.

She has extensive experience in the application and teaching of GIS, remote sensing, GPS, geostatistics, and machine learning tools such as fuzzy logic, artificial neural networks, neuro-fuzzy, support vector machine, random forest, etc for environmental modeling. She has worked with applied environmental models including soil erosion, surface and ground water quality, ground-water vulnerability, watershed risk assessment and management (soils, land-use and water quality relationship), contaminant transport processes, land-use and ground-water recharge, rainfall- runoff simulation, and land use planning (urbanization, soils and water quality relationship).

Books:

  • Dixon, B. (2025) Interdisciplinary Environmental Solutions: Using geospatial technologies for bridging disciplines, scale and data. Springer International Publishing (in press)
  • Samui, P, Dixon, B and B. T Die (Editors) Basics of computational geophysics. Elsevier Publishing https://www.elsevier.com/books/basics-of-computational-geophysics/samui/978-0-12-820513-6)
  • Dixon B. and Uddameri, V.  2016. GIS and Geocomputation for Water Resources Science and Engineering. ISBN 978-1-118-35414-8 – John Wiley & Sons. 1st Edition Feb. 2016, 504p 

Selected Publications:

  • Colarusso, A and Dixon B. 2025. An Assessment of Potential Environmental Impacts of Climate Change and Sea Level Rise on Decentralized Waste Water Treatment Infrastructures: A Broward County Case Study, FL, USA In: Climate Change Effects on Infrastructure  Eds: GuhaRay A, Samui P., Asteris, P.G. Armaghani, D. J and Kumar S. Elsevier (in press)
  • Meirose III, L., Dixon, B., & Brown, C. A. 2024. Next to or through your house?: Comparison of statistical and spatial results to understand the effects of DEM resolution on stream delineation. Journal of Hydrology, 130976.
  • Alegria, H. Dixon, B. R. Johns, A. Collarusso, and M. Hancock. 2024. Using a smart city framework to advance justice: applying an equity lens to compare air quality in neighbourhoods of different socioeconomic profiles. [Local Environment]. 10.1080/13549839.2024.2360729
  • Salim, M. , Qiang, Y., Dixon, B., & Collins, J. 2024. A Disparate Disaster: Spatial Patterns of Building Damage Caused by Hurricane Ian and Associated Socio-Economic Factors. Remote Sensing, 16(20), 3792.
  • Dalkilic, H.Y., Kumar, D., Samui, P. B. Dixon et al. 2023. Application of deep learning approaches to predict monthly stream flows. Environ Monit Assess 195, 705n. https://doi.org/10.1007/s10661-023-11331-5  
  • McKenna, K, Johns, and B. Dixon. 2022. Evaluating Forms of Engagement in Adult Environmental Education in Florida, The Florida Geographer. Vol. 53 No. 1 (2022): Winter
  • R. Johns, M. Vierra and B. Dixon. 2022. Police Violence as Containment of Black Bodies during Urban Renewal: a spatial analysis of civilian deaths by police in Florida". [In Press: Social Justice: Southeaster Geographer] 
  • Neshat,A. Bordbar,M.,Javadi, S, Pradhan, B. Dixon, B. and S. Paryani. 2021 Improving the Coastal Aquifers’ Vulnerability assessment using SCMAI ensemble of three machine learning approaches. Natural Hazards https://doi.org/10.1007/s11069-021-05013-z
  • Dixon, B., R. Johns and A. Fernandez. (2021). The Role of Crowdsourced Data, Participatory Decision-Making and Mapping in Resilience to Flooding. Applied Geography. https://doi.org/10.1016/j.apgeog.2021.102393
  • Haghbin, M., Sharafati A., B. Dixon, and V. Kumar. 2020. A State of the Art: Application of Soft Computing Methods for Appraisal of Groundwater Vulnerability and Nitrate Contamination, Past Trends and Future Opportunities. Archives of Computational Methods in Engineering. https://link.springer.com/article/10.1007/s11831-020-09513-2
  • Johns, R. A. Dixon, B. and R. Pontes. 2020. Tale of Two Neighborhoods: Biophysical and Socio-Economic Vulnerability to Climate Change in Pinellas County, Florida. Local Environment: the International Journal of Justice and Sustainability. 25(9): 697-924. https://doi.org/10.1080/13549839.2020.1825356
  • Flanagan K1, Dixon, B, Rivernbark, T^ and D. Griffin. 2019. An integrative GIS approach to analyzing the impacts of septic systems on the coast of Florida, USA, Physical Geography. https://doi.org/10.1080/02723646.2019.1671297.
  • B. Dixon and R. Johns. 2019. Vision for a Holistic Smart City (HSC)- Integrating Resiliency Framework via Crowdsourced Community Resiliency Information System (CRIS). ACM ISBN 978-1-4503-6954-1/19/11 https://doi.org/10.1145/3356395.3365541
  • Brown, C.A., H. N. Hansen, X. J. Jiang, F. Blateyron, J. Berglund, N. Senin, Bartkowiak, , B. Dixon, , G. L. Goïc, , Y. Quinsat, E. Savio, W. J. Stemp,  M. K. Thompson, P. S. Ungar, E. H. Zahouani. (2018).  Multiscale analyses and characterizations of surface to topographies. CIRP Annals Manufacturing Technology. (https://doi.org/10.1016/j.cirp.2018.06.001)
  • Douglas S. B. Dixon and D. Griffin. 2017. Assessing Intrinsic and Specific Vulnerability Models Ability to Predict Groundwater Vulnerability to Groups of Similar Pesticides: a Comparative Study. Physical Geography. 10.1080/02723646.2017.1406300
  • Pruden, J, R. Mbatu, R. Johns and B. Dixon. 2017. Measuring conservation success beyond the traditional biological criteria: Case of conservation projects in Costa Rica, Mekong Valley, and Cameroon. Natural Resources Forum. 10.1111/1477-8947.12132
  • Naghibi, S. A.,  H. R. Pourghasemi and B. Dixon. 2016. A comparative assessment between classification and regression tree, random forest and boosted regression tree data mining models for groundwater spring potential mapping in the Koohrang Watershed, Iran. Environmental Monitoring and Assessment 188(1):1 – 27.
  • MouLeong T, Ficklin D. L, Dixon, B. Ab Latif Ibrahim and Zulkifli Yusop. 2015. Impacts of DEM resolution, source and resampling technique on SWAT-simulated streamflow. Applied Geography Journal. 63: 357-368 (http://www.sciencedirect.com/ science/article/pii/ S0143622815001794)
  • Üstüner M., F. Balık Şanlı, and B. Dixon. 2015. Application of Support Vector Machines for Landuse Classification Using High-Resolution RapidEye Images: A sensitivity Analysis. European Journal of Remote Sensing.  48:403-422 (http://www.tandfonline.com/doi/abs/10.5721/EuJRS20154823)
  • Baumstark, R.,  Dixon B., Carlson P., Palandro, D., and K. Kolasa. 2013. Alternative spatially enhanced integrative techniques for mapping seagrass in Florida’s marine ecosystem. International Journal of Remote Sensing. 34(4), 1248–1264.
  • Fijani E., Moghaddam A. A. Tsai, Frank T.-C.  Nadiri, A., and B. Dixon. 2013. Optimization of DRASTIC Model by Supervised Committee Machine Artificial Intelligence for Groundwater Vulnerability Assessment in Maragheh-Bonab Plain Aquifer, Iran. Journal of Hydrology. 503:89-100
  • Johns R, Dixon, B., and C. McHan  2013. Evaluating Food Desert in Saint Pertesrburg. The Florida Geographer. Volume 44: 15 – 37 (http://journals.fcla.edu/flgeog/article/view/82367)
  • Casper F., B. Dixon, Steimle, E.T, Hall, M.L, and R.N. Conmy. 2012. High Resolution Mapping of the Spatial Variability of Water Quality in a River: Improvements from Integration of Geospatial and Sensor Technologies with Unmanned Surface Vehicles. Applied Geography. 32(2): 455 – 464.
  • Dixon B and Earls, J. 2012. Effects of Urbanization on Streamflow Using SWAT with Real and Simulated Meteorological Data. Applied Geography Journal. 35(1): 174-190.
  • Samui P. and Dixon B. 2012. Application of Support Vector Machine and Relevance Vector Machine to Determine Evaporative losses in reservoir. Hydrological Processes.  Volume 26, Issue 9, pages 1361–1369. (DOI: 10.1002/hyp.8278, Sep8, 2011)
  • Casper A.F, B. Dixon, J. Earls, and J.A. Gore. 2011. Linking a spatially explicit watershed model (SWAT) with an in-stream fish habitat model (PHABSIM): A case study of setting minimum flows and levels in a low gradient, sub-tropical river. Rivers Research and Applications. 27(3):269-282 (DOI: 10.1002/rra.1355, 2010, Feb, 1st)
  • Williams N., B. Dixon and A. J. Pyrtle. 2011. Estimating Soil Loss from Two Coastal Watersheds in Puerto Rico with RUSLE. Interdisciplinary Environmental Review (IER) 1(4) 108 – 127.
  • Dixon B. 2009. A Case Study Using SVM, NN and Logistic Regression in a GIS to Predict Wells Contaminated with Nitrate-N. Hydrogeology Journal. 17:1507 – 1520.
  • Dixon B. and Earls, J1. 2009. Resample or not?! Effects of Resolution of DEMs In Watershed Modeling. Hydrological Processes.  23(12): 1714 – 1724.
  • Dixon B. and Candade N. 2008. Multispectral landuse classification using neural networks and support vector machines: one or the other or both? International Journal of Remote Sensing. 29(4) 1185 – 1206.
  • Earls J. and Dixon B. 2008. A Comparison of SWAT Model-Predicted Potential Evapotranspiration: Using Real and Modeled Meteorological Data. Vadose Zone Journal: Special issue paper. Multiscale Mapping: Physical Concepts and Mathematical Techniques. Soil Science Society of America. 7(2):570–580
  • Earls J. and Dixon, B. 2008. Using the Fractal Dimension to Differentiate Between Natural & Artificial Wetlands. Interdisciplinary Environmental Review (IER), Vol. X, (no. 1): 33-44.
  • Dixon B. and Earls, J. 2007. Examining Spatio-Temporal Relationships of landuse change, population growth and water quality in the SWFWMD. Interdisciplinary Environmental Review (IER). Vol. IX (no.11) : 71 – 93.
  • Dixon B., Li D., Earls, J and Xinhua Liu. 2007. The Study on Groundwater Vulnerability Assessment Method. Environmental Protection Science. 33 (5): 50 – 55.
  • Dixon B. 2005. Applicability of Neuro-fuzzy techniques in predicting ground water vulnerability: A sensitivity analysis. Journal of Hydrology. 309: 17 – 38
  • Dixon B. 2004. Prediction of Ground Water Vulnerability using an integrated GIS-based neuro-fuzzy techniques. Journal of Spatial Hydrology. 4(2):1 – 38.
  • Dixon B. 2004. Ground water vulnerability mapping: a GIS and fuzzy rule based integrated tool. Journal of Applied Geography. 25: 327 – 347.
  • Dixon B., H.D. Scott, J.C. Dixon, and K.F. Steele. 2002. Prediction of Aquifer Vulnerability to Pesticides Using Fuzzy Rule-Based Models at the Regional Scale. Physical Geography 23:130 – 152.
  • Mitra B., H. D. Scott, J.C. Dixon and J.M. McKimmey. 1998. Application of fuzzy logic to the prediction of soils erosion in a large watershed. Geoderma. 86:183 – 209.

Recent Presentation:

  • Colarusso, A., Dixon, B.,   Yan, E. , and S. Covarubias. Use of Static Cameras to Predict Flood Height and Extent: A Comparison between Helene and Milton. American Association of Geographers Detroit, MI. March 24 - 29
  • Dixon B.,  Zhu M. and S. Guhathakurta. 2025. Community Knowledge Matters? Reimagining  Citizen Science in the Context of Smart and Resilient City for Community Engagement. American Association of Geographers Detroit, MI. March 24 - 29
  • Andrews, J., Dixon B., Withlow, D. and S. Guhathakurta. 2025.Extraction of Flood Height using ML from Crowdsourced Photo using a Custom Flood App: Preliminary results. American Association of Geographers Detroit, MI. March 24 – 29
  • Colarusso, A. and Dixon B. 2025 Estimating Flood Impact, Residence Times, and Recession Rates using an Integrated Camera Monitoring Network and Digital Twin. Florida Society of Geographers Gainsville, Feb 21-23
  • Amponos A. C and Dixon, B. 2025. Machine Learning Applications Integrated with GIS for Flood Prediction. Florida Society of Geographers Gainsville, Feb 21-23. Poster
  • Licea M and Dixon B. 2025. Reimagining Vulnerability and Resilience at Neighborhood Level: Post Helene and Milton. Florida Society of Geographers Gainsville, Feb 21-23. Poster
  • Dixon. B. 2024. Exploring Spatial Variability of Community-Engaged Co-creation and Implementation of CRIS-Hazard to Drive Policy Decisions. 35th International Geographical Congress Dublin, Ireland,  August 24 - 30
  • Dixon. B. 2024. Moving the Needle on Gender Equity in Academia: Tracking the Status of Women and Marginalized Groups in Geography. Panelist. American Association of Geographers Honolulu, HI. April 16 - 20
  • Dixon. B. and S. Guhathakurta. 2024. From CRIS to CRIS-HAZARD - Development of a Near Real-Time Community Crowdsourced Resilience Information System for Enhancing Community Resilience – An overview of the conceptual framework. American Association of Geographers Honolulu, HI. April 16 - 20
  • Colarusso A. and Dixon, B. 2024. CRIS-Hazard: A Web-based platform for Integration of Near-real Time Camera Images via IOT to Aid Flood-related Resilience Planning. American Association of Geographers Honolulu, HI. April 16 – 20
  • Colarusso A. and Dixon, B. 2024. OSTDS Environmental Impacts Assisted By Arcnlet: A Broward County Case Study. Florida Society of Geographers Saint Augustine, Feb 16 - 18
  • Dixon, B. 2023. Panelist. Status of Women in Geography Panel “Revisiting the Status of Women in GeographStatus of Women and Geography Panel. American Association of Geographers Denver,  CO. March 23 - 27
  • Dixon, B. 2023. Geospatially Integrated IOT framework to advance justice: applying an equity lens to compare air quality at neighborhood-scale. American Association of Geographers Denver,  CO. March 23 - 27
  • Colarusso A. and  Dixon, B. 2023. MODFLOW or hydrostatic-bathtub models? Identifying OSTDS vulnerability using GIS-based MCDM . American Association of Geographers Denver,  CO. March 23 – 27
  • Colarusso A and Dixon, B. 2023. Who Will be Impacted? Analysis of OSTDS failure due to Sea-Level Rise and other inundation factors: An integrated Geo-Spatial Analysis. Florida Society of Geographers, Saint Augustine, FL. Feb 17 – 19.
  • Laczko O., L. Shanley and B. Dixon. 2023. Updated Analysis of Food Deserts in St. Petersburg Using GIS Data Visualization as a Means of Recommending Policy Remedies. Florida Society of Geographers, Saint Augustine, FL. Feb 17 – 19. Poster.
  • Cheek, L & B. Dixon. 2023. Equity of Access to Public Living Shorelines in Pinellas County: A GIS-Based Analysis. Poster Presentation]. AEESP 2023. Boston, MA, United States. June 20-23).  Poster.
  • Johns. R. and B. Dixon. 2022. Empowering Marginalized Communities for Climate Literacy, Justice and Resilience. Building Leadership for Environmental Literacy. NAAEE. Tucson AZ. Oct 12 – 15. Poster.
  • Cheek, L., B. Dixon, and M. Trotz. 2022. Equity of Living Shoreline Access in Pinellas County: A GIS-Based Analysis. Coastal & Estuarine Summit, Hosted by Restore America's Estuaries. New Orleans, LA December 4-8. Poster
  • Colarusso A. and B. Dixon. 2021. Sea Level Rise, OSTDS Vulnerability Zones and Potential for Failure, and Environmental Impacts: A Coastal Watershed-Based Study.Annual Conference, American Water Resources Association, Virtual, Nov 7-10

Recent Invited Speaker:

  • B. Dixon. 2024.   Stakeholder Perspective of Local Societal Needs. 2024 USCRP Decadal Visioning Workshop. US Coastal Reaserch Program (USCRP) – June 11th, 2024
  • B. Dixon. 2024. CRIS-HAZARD: A Tool for Community Engagement and Crowdsourced Data Collection to Enhance Resilience in the Face of Flooding and Other Extreme Events. NSF S&CC Annual PI Meeting, Feb 28-29, Nashville, TN. Panelist: Citizen science session
  • B. Dixon. 2019. Innovative and integrative Modelling of Land - Water Interfaces Under Climate Change. Thailand Space Week, Bangkok, Thailand, Aug 27-28th, 2019. This was part of Fulbright Specialist program.
  • B. Dixon. 2019. Coastal Adaptation, Resilience & Disaster Response : role of geospatial technologies in customizable and scalable solution. GISTDA, Bangkok, Thailand. Aug, 22, 2019. This was part of Fulbright Specialist program.
  • B. Dixon,  2019. Socio-economic marginalization, participation in governance and resiliency: a flooding related case study. NSF funded Workshop on Community Geography, Univeristy of Georgia, Jan 25 -26, Atlanta, GA
  • Dixon. 2018. Interdisciplinary application of geospatial technologies for water resources modeling under climate change to enhance planning, adaption and resilience. Seminar at Vivsa Bharati Univeristy, Santiniketan, India Dec. 4th
  • Dixon. 2018. Opportunities and limitations of water resources modeling under climate change to enhance planning, adaption and resilience NIT Patna, India, Dec 7th.
  • Dixon. 2018. Rising together: thoughts on climate change, coastal resilience and adaptation. TEDxYouth@ShengjingRoad. Event theme Hello Future!, Shenyang, China, Sep, 1st.
  • Dixon. 2018. Mapping Biophysical and Social Vulnerability in Pinellas County, Florida  Frank, E. Duckwall Lecture series: Assessing Climate Resilience through Community Engagement in the Tampa Bay Region. St. Petersburg, April 23
  • Dixon, B and V. Uddameri. 2016. GIS-based Integrated Modeling Approach:  DRASTIC, Fuzzy Logic and Logistic Regression. International Conference on Water and Environment. Shanghai, China,July 23-26
  • Dixon 2015. Integration of AI with Geospatial Technologies. Center for disaster mitigation and management, VIT, India, Feb 24-27
  • Williams, N1£.  Dixon and A. Johnson. 2012. Linking Soil Loss to Sediment Delivery in the Jobos Bay Estuary, Puerto Rico. National Estuarine Research Reserve System (NERRS). NOAA’s Estuarine Reserves Division and the National Estuarine Research Reserve Association (NERRA). Shepherdstown, WV. Nov 27 – 30.
  • Dixon, B. 2012. Statistical Regional modeling of nitrate in groundwater. Impacts of Excess Nitrogen in the Environment on Human Health: RCN Human Health Conference. National Institutes of Health (NIH), North Bethesda. MD. Nov 14 – 15.
  • Dixon, B. 2012. Mapping the Tribes and the Terrain: Geospatial Analysis/Human Geography Consideration of Yemeni Tribes. Tribal Dynamics III Yemen Workshop: USSOCOM’s Interagency Task force. University of South Florida’s Citizenship Initiative and the Center for the Study of International Languages and Cultures (CSILC). Tampa, FL, April 23-24.
     

Invited papers:

  • Samui P. and Dixon B. 2014. Determination of Contaminated Wells: A Relevance Vector Machine Approach. [Accepted: Journal of Urban and Environmental Engineering (JUEE)] http://www.journal-uee.org/
  • Williams N. B., B. Dixon and A. Johnson. 2010. Developing a conceptual framework for linking soil erosion to sediment deposition: Patterns in coastal ecosystems in the Caribbean.  IMPACT 20 (4):15-16
  • Li D. Dixon, B., Earls, J. F. Bradley and Xinghua, Liu. 2007.  The Study on Vulnerability Assessment in Groundwater Recharge Area of Jinan. Environmental Protection, 378(8B):59 – 61. Environmental Protection of China Press.
  • Earls J. and Dixon, B. 2005. A comparative study of the effects of input resolution on the SWAT model. Pages 213 – 222. In (C. A. Brebbia, and J. S. Antunes do Carmo eds.) River Basin Management III. WIT Press, Southampton, UK.
  • Dixon B. 2004. Can an integrated ground water vulnerability mapping tool facilitate sensitivity analysis in a spatial domain?? In (J. F. Martin-Daque; C. A. Brebbia; A. e. Godfrey and J.R. Diaz de Teran eds.) Geo Environment. WIT Press, Southampton, UK.
  • Dixon B. 2002. Application of Neuro-Fuzzy techniques to predict ground water vulnerability. Pages 485 – 495. In (C. A. Brebbia, ed.) Risk Analysis III. WIT Press, Southampton, UK.
  • Mitra B., J. M. McKimmey and H. D. Scott. 1997. Development and use of digital databases in agricultural research. Trends in Agronomy, 1:1-17.

Conference Proceeding:

  • King, C, and B. Dixon. 2011. Integrating Virulo model and virus parameters in mapping ground water contamination risk to pathogens. Vol. 34, pages 267 – 275. In (Jay. Lee, Editor). Papers of The Applied Geography Conferences. Redlands, CA.
  • Williams, N.B, B. Dixon and A.  Johnson. 2010. Linking watersheds’ hydrologic response to sediment delivery: A conceptual framework. In (Garcia, Pedro M. Editor). International Specialty Conference and 8th Caribbean Islands Water Resources Congress on Tropical Hydrology and Sustainable Water Resources in a Changing Climate (Proceedings). American Water Resources Association Technical Publication, Middleburg, Virginia, TPS-10-2, CD-ROM. ISBN 1-882132-83-1
  • Dixon, B, Earls, J. A. F. Casper, J. A Gore. 2009. Integrating Spatially Explicit Watershed Models With In-Stream Habitat Models: A Discussion on Constraints With Regard to the Resolution of Data. AWRA Spring Specialty Conference: Managing Water Resources and Development is a Changing Climate.  Paper in AWRA conference CD. May 4 – 6th Anchorage, Alaska. http://www.awra.org/tools/members/Proceedings/0905conference/oral.html
  • Dixon, B and Earls J. 2008. An estimation of Regional Soils Erosion Vulnerability using RUSLE-V. Papers of IASTED International Conference on Applied Simulation and Modeling. Corfu, Greece, June 23rd – 25th.
  • Earls, J. and B. Dixon. 2008. The Influence of Resolution on the SWAT Model: Examining Neighboring Basins. Spring Specialty Conference GIS and Water Resources V.  San Mateo, CA, Mar 17-19, 2008. Paper on Conference CD AWRA.
  • Earls, J and B. Dixon. 2007. Application of the Soil and Water Assessment Tool (SWAT) in modeling the effects of landuse change on watershed hydrology. Vol. 30, pages 541-522. In (L. Harrington & J. Harrington, Jr, eds.). Papers of The Applied Geography Conferences. Indianapolis, IN.
  • Earls, J and B. Dixon. 2007. Spatial Interpolation of Rainfall Data Using ArcGIS: A Comparative Study. 27th Annual ESRI International User Conference. http://www10.giscafe.com/link/display_detail.php?link_id=22230.  San Diego, June 18-22, 2007.
  • A.F. Casper, M.L. Hall, B. Dixon and E.T. Steimle. 2007. Combining Data Collection from Unmanned Surface Vehicles with Geospatial Analysis: Tools for Improving Surface Water Sampling, Monitoring, and Assessment. Proceedings of OCEANS 2007 MTS/IEEE Vancouver. 2007ISBN CD-ROM: 0-933957-35-1,Vancouver, British Columbia. September 29 – October 4
  • Earls J., N. Candade1 and B. Dixon. 2006. A Comparative Study of Landsat 5 TM Landuse Classification Methods including Unsupervised Classification, Neural Network and Support Vector Machine for Use in a Simple Hydrologic Budget Model. ASPRS  Annual Conference – Prospecting for Geospatial Information Integration – Reno, NV – May 1-5.
  • Earls J and Dixon, B. 2006 The Influence of Resolution on the SWAT Model: Examining Neighboring Basins.  In (Maidment, David R. and John S. Grounds III, eds). GIS and Water Resources IV. Proceedings of the American Water Resources Association’s 2006 Spring Specialty Conference. American Water Resources Association, Middleburg, Virginia, TPS-06-1, CD-ROM. ISBN 1-882132-70-X
  • Earls, J and Dixon, B. 2006. Comparison of annual calibration of SWAT model at differing resolutions. In (Mark Colosimo & Donald F. Potts, eds). Adaptive Management of Water Resources.  AWRA Summer Specialty Conference MT, June 26-28. ISBN:  1-882132-71-8.
  • Earls, J1. and Dixon, B. 2005. Calculation of Evapotranspiration and Hydrologic budget from Landsat TM derived landuse maps for two unique drainage basins. Vol. 28, pages 413-422. In (G. A. Tobin and B. E. Montz, eds.). Papers of the Applied Geography Conferences. Washington D.C.
  • Dixon, B. and Candade, N1. 2004. Comparison of Neural Network and Neuro-fuzzy Techniques in Ground Water Vulnerability Mapping: A Case Study. Pages 1 – 10. In (Kenneth J. Lanfear and David R. Maidment, eds.) AW RA’s 2004 Spring Specialty Conference “Geographic Information Systems (GIS) and Water Resources III.” American Water Resources Association, Middleburg, Virginia, TPS-04-1, CD-ROM.
  • Candade, N and Dixon, B. 2004. Multispectral classification of Landsat images: Comparison of Support Vector Machine and Neural Network classifiers. Presentation.  ASPRS Annual Meeting. Denver, May 2004. Mira Digital Publishing. Bethesda, Maryland. ISBN 1-57083-072-X.
  • Dixon, B. 2003. Can contamination potential of ground water to pesticides be identified from hydrogeological parameters?  Vol. 26, pages 237 – 247. In (B. E. Montz and G. A. Tobin, eds.) Papers and Proceedings of The Applied Geography Conferences. University of Colorado at Colorado Springs, Colorado Springs, Co.
  • Dixon, B. 2002. Can ground water sampling strategy be improved by incorporating fuzzy logic in a GIS? Vol. 25, Pages 254 – 264. In  (B. E. Montz and G. A. Tobin, eds.) Papers and Proceedings of The Applied Geography Conferences. Binghamton University, Binghamton, NY

Projects

  • Title: Sediment Dynamics and Climate Change:  An Integrated Model Approach to Evaluating the Effects of Projected Precipitation Changes on Sediment Production, Transport and Deposition at the Catchment Scale. MS Student : Ms. Kimberly Lyons
  • Title: Modeling of groundwater contamination potential from septic tanks and golf courses: An integrated Geospatial Approach. MS Student: Mr. Steven Douglas.
    Elusive or Illusive Truth? The Role of Sensors and Sampling Strategies in Data Collection and its Implication for Science and the Pursuit of Truth. MS Student: Mr. Chris McHan
  • Title: Analyzing and Mapping of factors that influence success and failure of conservation practice: a multi-scale study. MS. Student: Ms. Jessica Gruber
  • Title: A Comparison of Natural vs. Mitigated Wetlands: A Spatially Integrated Decision Support Approach. MS Student: Ms. Elizabeth Merton
  • Title: A Spatial and Temporal Analysis of Tampa Bay Seagrass Populations Affected by Changes in Land Use, Imperviousness and Water Quality Using Habitat Suitability. Honors Thesis: Ms. Samantha Cope
  • Title: Multiscale and Statistical Analysis of the Effects of DEM Processing Methods/Resolution and Fractal Complexity on Slope Characterization. MS Student: Mr. Leo Meirose
  • Title: Integration of Terrestrial Source, Landuse, and Watershed Hydrogeology in Coastal MPA Management. MS Student: Mr. Kyle Flanagan
  • Title: Effects of DEM Resolution in Delineating Streams Using SWAT. BA Student : Mr. Mark Groom
  • Title: Development of risk assessment model of wildfires using GIS. Honors Thesis: Ms. Amada Fernandez
  • Title: Mapping of spatio-temporal variation of landcover-change within the Reservation  (Funded Project)
    Analysis of contamination from waste water treatment plants and septic systems in coastal water of Florida using GIS data (Funded Project)
  • Title: Role of ‘change’ in impervious surface on flooding within a watershed: a comparative study (Funded Project)

Courses:

GIS 3006: Computer Cartography
GIS 4035C: Remote Sensing of The Environment
GEO 4141C: Geographic Methods and Techniques
GIS 4043C: Geographic Information Systems
GIS 6038C: Advanced Remote Sensing
GIS 4300: Environmental modeling with GIS
GIS 5049: GIS for Non Majors
EVR 6936: Seminar in Environmental Science
EVR 6934: Soil, Water and Landuse
GIS 6306: Environmental Applications of GIS