Hogland J.; Affleck, D.L.R. 2021. Improving estimates of natural resources using model-based estimators: impacts of sample design, estimation technique, and strengths of association, remote sensing, 13(19), 3893. https://www.mdpi.com/2072-4292/13/19/3893

Hogland, J.; Dunn, C.J.; Johnston, J.D. 2021. 21st Century Planning Techniques for Creating Fire-Resilient Forests in the American West, forests, 12, 1084. https://www.mdpi.com/1999-4907/12/8/1084

Palaiologou, P.; Essen, M.; Hogland, J. Kalabokidis, K. 2020. Locating forest management units using remote sensing and geostatistical tools in North-Central Washington, USA. sensors, 20(9), 2454. https://www.mdpi.com/1424-8220/20/9/2454

Hogland, J.; Affleck, D.L.; Anderson, N.; Seielstad, C.; Dobrowski, S.; Graham, J.; Smith, R. 2020. Estimating forest characteristics for longleaf pine restoration using normalized remotely sensed imagery in Florida, USA. forests, 11, 426. https://www.mdpi.com/1999-4907/11/4/426

Hogland, J. 2019. Estimates of forest characteristics derived from remotely sensed imagery and field samples: applicable scales, appropriate study design, and relevance to forest management. Graduate Student Theses, Dissertations, & Professional Papers, 11505. https://scholarworks.umt.edu/etd/11505

Thompson, M.; Wei, Y.; Calkin, D.; O’Conner, C.D.; Dunn, C.J.; Anderson, N.M.; Hogland, J.S. 2019. Risk management and analytics in wildfire response. Current Forestry Reports, 5 226-239. https://www.fs.usda.gov/treesearch/pubs/59834

Hogland, J.; Anderson, N.; Affleck, D.; St. Peter, J. 2019. Using forest inventory data with Landsat 8 imagery to map longleaf pine forest characteristics in Georgia, USA, remote sensing, 11(15), 1803. https://www.mdpi.com/2072-4292/11/15/1803

Hogland, J.; Affleck, D.L. 2019. Mitigating the impact of field and image registration errors through spatial aggregation, remote sensing, 11(3): 222. https://www.mdpi.com/2072-4292/11/3/222

Ahl, R.; Hogland, J., Brown, S. 2019. A comparison of standard modeling techniques using digital aerial imagery with national elevation datasets and airborne LiDAR to predict size and density forest metrics in the Sapphire Mountains MT. USA, International Journal of Geo-Information, 8(1): 24. https://www.mdpi.com/2220-9964/8/1/24

St. Peter, J.; Hogland, J.; Hebblewhite, M.; Hurley, M.; Hupp, N.; Proffitt, K. 2018. Linking phenological indices from digital cameras in Idaho and Montana to MODIS NDVI, remote sensing, 10, 1612. https://www.mdpi.com/2072-4292/10/10/1612

Hogland, J.; Anderson, N.; Chung, W. 2018. New geospatial approaches for efficiently mapping forest biomass logistics at high resolution over large areas, International journal of Geo-Information, 7(4): 156. https://www.mdpi.com/2220-9964/7/4/156

Hogland, J.; Anderson, N.; St. Peter, J; Drake, J.; Medley, P. 2018. Mapping forest characteristics at fine resolution across large landscapes of the southeastern United States using NAIP imagery and FIA field plot data, International journal of Geo-Information, 7(4): 140. https://www.mdpi.com/2220-9964/7/4/140

St. Peter, J; Hogland, J.; Anderson, N.; Drake, J.; Medley, P. 2018. Fine resolution probabilistic land cover classification of landscapes in the southeastern United States, International journal of Geo-Information, 7(3): 107. https://www.mdpi.com/2220-9964/7/3/107

Hogland, J.; Anderson, N. 2017 Function modeling improves the efficiency of spatial modeling using big data from remote sensing. Big Data and Cognitive Computing, 1(3): 1-14. https://www.mdpi.com/2504-2289/1/1/3

Wells, L.; Chung, W.; Anderson, N.; Hogland, J. 2016. Spatial and temporal quantification of forest residue volumes and delivered costs. Canadian Journal of Forest Research. 46: 832-843. https://www.fs.usda.gov/treesearch/pubs/50967

Hogland, J.; Billor, N.; Anderson, N. 2013. Comparison of standard maximum likelihood classification and polytomous logistic regression used in remote sensing. European Journal of Remote Sensing. 46: 623-640. https://www.tandfonline.com/doi/abs/10.5721/EuJRS20134637

Reynolds M.; Hogland J; Mitchell, M. 2008. Evaluating intercepts from demographic models to understand resource limitation and resource thresholds. Ecological Modeling. 211(3): 424-432. https://www.sciencedirect.com/science/article/abs/pii/S0304380007004978

Hussain, A.; Armstrong, J.; Brown, D.; Hogland, J. 2007. Land-use pattern, urbanization and deer-vehicle collisions in Alabama. Human-Wildlife Conflicts, 1(1):89-96. https://www.jstor.org/stable/24875057

Hogland, J. 2021. Rumple Index, Juypter Notebook, Online: https://colab.research.google.com/drive/1xfQM-aCjCR7JPj45ukXYv38xr4XJu5Wi?usp=sharing

Hogland, J. 2021. Ensemble Generalizd Additive Models (EGAM), Juypter Notebook, Online: https://colab.research.google.com/drive/1GnRagruTUCoPJQZSkZ2vMKS9aAKgnhEw?usp=sharing

Hogland, J. 2021. Getting Started With R in Google's Colab, Juypter Notebook, Online: https://colab.research.google.com/drive/16eUtWkLmyjdAvsncCDSNqNXjskFT17pb?usp=sharing

Hogland, J. 2021. Automating Your Workflow, Classroom, Online: https://classroom.google.com/c/MjY5OTM3NjI5ODc0?cjc=txxshis.

Hogland, J. 2021. Python Modules: Trail Camera, Classroom, Online: https://classroom.google.com/c/MTE5MTc5MzgzMjUx?cjc=axn2z4b.

Hogland, J. 2021. Delivered Cost Model. Classroom, Online: https://classroom.google.com/c/MTIyNjkxOTI5Njgw?cjc=igys6jc.

St. Peter, J.; Hogland, J.; Haight, K.; 2021, Spatial Modeling Gopher Tortoise Habitat, Tutorial, Online: https://www.google.com/url?q=https%3A%2F%2F1drv.ms%2Fu%2Fs!AsFbCMD8yzdhjRuojMTpcxWhhWqs%3Fe%3DeKpLlq&sa=D&sntz=1&usg=AFQjCNE1KhaW8EmIxsJkXnRl2UezBbvoMA

Hogland, J.; 2020. What is Google Classroom, Classroom, Online: https://youtu.be/EE-mZ-pzgDk.

Hogland, J. 2020. Building Virtual Classes Workshop, Classroom, Online: https://classroom.google.com/c/MTE5MTUwNDg2MzAw?cjc=uej2dec.

Hogland, J.; Anderson, N.; St. Peter, J. 2019. The big picture: new perspectives on restoring landscapes. Rocky Montanan Research Station; Science You Can Use Bulletin. Online: https://www.fs.usda.gov/rmrs/big-picture-new-perspectives-restoring-landscapes

Hogland, J.; 2019. Beyond automation: building python modules to enhance data collection, spatial modeling, and help in decision making. Online: https://www.magip.org/BigSkyGeoConWorkshops2019#Py.

Hogland, J; St. Peter, J. 2019. Predicting culvert cost using the raster utility toolbar and batch processing. Online: https://www.magip.org/BigSkyGeoConWorkshops2019#Batch.

St. Peter, J.; Hogland, J. 2019. Identifying open pine areas using raster utility toolbar and batch processing. Online: https://www.magip.org/BigSkyGeoConWorkshops2019#Batch.

Hogland, J.; Ahl, R. 2018. Image processing and classification. Online: https://www.magip.org/BigSkyGeoCon2018.

Hogland, J.; 2018. Automating our workflow using python. Online: https://www.magip.org/BigSkyGeoCon2018.

Hogland, J.; Anderson, N.; Affleck, D.; St. Peter. 2018. Ft. Steward Longleaf Pine Mapping Project Final Report: Using FIA plot and remotely sensed data to map longleaf extent and condition: emphasizing high resolution outputs for cross-ownership planning, monitoring, and restoration.

Hogland, John S.; St. Peter, Joe R.; Anderson, Nathaniel M. 2018. Raster surfaces created from the Ft. Stewart project. Fort Collins, CO: Forest Service Research Data Archive. Online: https://www.fs.usda.gov/rds/archive/catalog/RDS-2018-0039.

St. Peter J.; Hogland, J; Haight, K; 2017. Prioritization of open pine red cockaded woodpecker habitat, self-guided tutorial and presented as part of the deliverables of the Longleaf mapping project.

Hogland, John S.; St. Peter, Joe R.; Anderson, Nathaniel M. 2017. Raster surfaces created from the longleaf mapping project. Fort Collins, CO: Forest Service Research Data Archive. https://doi.org/10.2737/RDS-2017-0014.

Hogland, J.; St. Peter, J.; Anderson, N.; 2017. RMRS and intermountain region (Region 4) bighorn sheep contact ESRI add-in repair and Update.

Hogland, J; St Peter, J; Anderson, N. 2017. Longleaf pine mapping and monitoring final report - cost-effective mapping of longleaf extent and condition using NAIP imagery and FIA data: a pilot project in the heart of the longleaf range.

Hogland, J.; Anderson, N., St. Peter, J; 2017. Estimating BAA: focus on workflow, self-guided tutorial and presented as part of the deliverables of the longleaf mapping project.

Hogland, J.; Haight, K; St. Peter, J. 2017. Image based classification using the RMRS Raster Utility toolbar: focus on workflow, self-guided tutorial and presented as part of the deliverables of the longleaf mapping project.

St. Peter; J. Haight, K; Hogland, J; 2017. Identifying open pine areas using RMRS Raster Utility toolbar and batch processing, self-guided tutorial and presented as part of the deliverables of the Longleaf mapping project.

Hogland, J.; Anderson, N. 2015. Estimating FIA plot characteristics using NAIP imagery, function modeling, and the RMRS Raster Utility coding library. In: Stanton, Sharon M.; Christensen, Glenn A., comps. 2015. Pushing boundaries: new directions in inventory techniques and applications: Forest Inventory and Analysis (FIA) symposium 2015. 2015 December 8-10; Portland, Oregon. Gen. Tech. Rep. PNW-GTR-931. Portland, OR: U.S. Department of Agriculture, Forest Service, Pacific Northwest Research Station: 340-344.931. Portland, OR: U.S. Department of Agriculture, Forest Service, Pacific Northwest Research Station: 340-344.

Hogland, J.; Anderson, N.; Chung, W.; Wells, L. 2014. Estimating forest characteristics using NAIP imagery and ArcObjects. In: Proceedings of the 2014 ESRI Users Conference; July 14-18, 2014, San Diego, CA. Redlands, CA: Environmental Systems Research Institute. Online: http://proceedings.esri.com/library/userconf/proc14/papers/155_181.pdf,

Hogland, J.; Anderson, N. 2014. Improved analyses using function datasets and statistical modeling. In: Proceedings of the 2014 ESRI Users Conference; July 14-18, 2014, San Diego, CA. Redlands, CA: Environmental Systems Research Institute. Online: http://proceedings.esri.com/library/userconf/proc14/papers/166_182.pdf.

Miller, S.; Essen, M.; Anderson, N.; Chung, W.; Elliot, B.; Page-Dumroese, D.; Han, H.; Hogland, J.; Keyes, C. 2014. Burgeoning biomass: creating efficient and sustainable forest biomass supply chains in the Rockies. Science You Can Use Bulletin, Issue 13. Fort Collins, CO: Rocky Mountain Research Station. 10 p.

Keefe, R.; Anderson, N.; Hogland, J.; Muhlenfeld, K. 2014. Woody biomass logistics [Chapter 14]. In: Karlen, Douglas, ed. Cellulosic Energy Cropping Systems. West Sussex, UK: John Wiley and Sons. p. 251-279.

Hogland, J.; Anderson, N.; Jones, G. 2013. Function modeling: improved raster analysis through delayed reading and function raster datasets. In: Proceedings of the 36th Annual Meeting of the Council on Forest Engineering; July 8-10, 2013, Missoula, MT. Morgantown, WV: Council on Forest Engineering. Online: http://web1.cnre.vt.edu/forestry/cofe/documents/2013/Hogland_Anderson_Jones.pdf

Hogland, J.; Anderson, N.; Jones, G.; Golson, W. 2012. RMRS Raster Utility website. Online: http://www.fs.fed.us/rm/raster-utility/, Last Accessed 5/31/2016.

Hogland, J. 2012 RMRS Raster Utility: source code repository. Online: https://collab.firelab.org/software/projects/rmrsraster. Last Accessed 5/31/2016.

Kleiner, K.; Mackenzie, M.; Silvano, A.; Grand, J; Grand, J., Hogland, J; Irwin, E; Mitchell, M.; Taylor, B.; Earnhardt, T.; Kramer, E; Lee, J; McKerrow, A.; Rubino, M.; Samples, K.; Terando, A;. Williams, S. 2007. GAP landcover map of ecological systems for the state of Alabama (Provisional). Alabama Gap Analysis Project. Last Accessed 4/29/2008 from www.auburn.edu\gap

Hogland, J. 2005. Creating spatial probability distributions for longleaf pine ecosystems across east Mississippi, Alabama, the panhandle of Florida and west Georgia. Auburn University, Auburn, Alabama. 139 p. URL: <http://graduate.auburn.edu/auetd/search.aspx>

Hogland, J.; Dunn, C.J.; Johnston, J.D. 2021. 21st Century Planning Techniques for Creating Fire-Resilient Forests in the American West, presented at AFE, 11/30/2021, online: https://youtu.be/tp_1Cd9NawI?t=4556

Hogland, J. 2021. Capstone Project Proposal: Improved Spatial Modeling Using the RMRS Raster Utility, presented to University of Montana's CS department, 9/1/2021 (invited).

Hogland, J.; Johnson, J.; Bunt, F. 2021. New Python Based Delayed Reading & Parallelization Libraries for Geospatial, Statistical, and Machine Learning Analyses, presented at the Advanced Analytics COP, 8/31/2021 (video).

Hogland, J. 2021. Reducing Wildfire Risk: Informed Decision Making, presented to Malheur NF, 4/12/2021, (invited virtual).

Hogland, J. 2021. Reducing Wildfire Risk: Informed Decision Making, presented to Washington DNR, 4/6/2021 (invited virtual).

Hogland, J. 2021 Beyond automation: building python modules to enhance data collection, spatial modeling, and help in decision making, invited presentation and short course at MAGIP GeoCon, Missoula MT, 4/6/2021 (virtual).

Hogland, J. 2021. Automating your workflow using Python: focus on reusable code, invited presentation and short course at MAGIP GeoCon, Missoula MT, 4/5/2021 (virtual).

Hogland, J. 2020. RMRS Raster Utility, presented to PNW_IM group, 12/9/2020, (invited virtual).

Hogland, J.; Affleck, D. 2020. Mitigating the impact of field and image registration errors through spatial aggregation, USDA-NIFA Land-use project, Chicago, IL, 6/11/2020 (invited virtual workshop).

Hogland, J. 2020. Reducing wildfire risk: informed decision making, presented to Blue Mountain Forest Partners, John Day, OR, 4/14/2020 (invited virtual presentation).

Hogland, J.; Reynolds-Hogland, M. 2020. Automating your workflow using python: focus on reusable code, invited presentation and workshop at MAGIP GeoCon, Missoula, MT, 4/6/2020, (canceled due to COVID-19 outbreak).

Hogland, J.; Reynolds-Hogland, M. 2020. Beyond automation: building python modules to enhance data collection, spatial modeling, and help in decision making, invited presentation and workshop at MAGIP GeoCon, Missoula, MT, 4/6/2020, (canceled due to COVID-19 outbreak).

Hogland, J. 2020. Reducing wildfire risk: new tools and techniques, presented to Willamette National Forest, Springfield, OR, 4/3/2020 (invited, virtual presentation).

Hogland, J. 2020. Reducing wildfire risk, workshop presented at Stanislaus National Forest, Sonora, CA, 3/19/2020 (invited, virtual presentation).

Hogland, J. 2020. Estimating forest characteristics for longleaf pine restoration using normalized remotely sensed imagery in Florida USA, presented at FoSL Brown Bag seminar series, Missoula, MT, 2/25/2020 (invited presentation).

Hogland, J. 2020. Research data science: next generation solutions and information for data driven decision-making, presented at FSL, Missoula, MT, 2/7/2020 (invited presentation).

Hogland, J. 2019. Estimates of forest characteristics derived from remotely sensed imagery and field samples: applicable scales, appropriates study design, and relevance to forest management, presented at University of Montana as a dissertation defense, Missoula, MT, 12/3/2019.

Hogland, J.; Affleck, D.; Anderson, N.; Drake, J.; Medley, P. St. Peter, J. 2019. Estimates of forest characteristics derived from remotely sensed imagery and field samples: applicable scales, appropriate study design, and relevance to forest management, presented at Energy Water and Food Nexus, Tallahassee, FL, 11/7/2019.

Hogland, J. 2019. Recognizing the finer details of big data: the next generation of solutions for data drive decision making, presented at Agora, Missoula, MT, 5/29/2019 (invited presentation).

Hogland, J. 2019. NAIP-based evaluations of US lands, presented at USDA-NIFA Next Generation Land-Use Change Methodology Project Workshop, Chicago, IL 4/4/2019 (invited presentation).

Hogland, J. 2019. Beyond automation: building python modules to enhance data collection, spatial modeling, and help in decision making, presented at MAGIP, Butte MT, 4/1/2019 (invited short course).

Hogland, J.; St Peter, J. 2019 Batch Processing with the RMRS Raster Utility presented at MAGIP in Butte MT 4/1/2019 (invited short course).

Hogland, J. Automating spatial analysis using python: part 2, present at University of Montana, Missoula MT, 4/23/2018 – 4/27/2018, (guest lectures/labs).

Hogland, J.; Anderson, N.; Chung, W. New geospatial approaches for efficiently mapping of forest biomass logistics at high resolution over large areas, presented at MAGIP 2018 Big Sky GoeCon, Helena MT., 4/18/2018 (workshop).

Hogland, J. 2018. Automating our workflow using python, presented at MAGIP 2018 Big Sky GoeCon, Helena MT., 4/18/2018 (workshop).

Hogland, J; Ahl, R. 2018. Image processing and classification, presented at MAGIP 2018 Big Sky GoeCon, Helena MT., 4/16/2018 (workshop).

Hogland, J. Automating spatial analysis using python: part 1, present at University of Montana, Missoula MT, 4/9/2018 – 4/13/2018, (guest lectures/labs).

Hogland, J; Anderson, N. Behind the buttons: improved spatial modeling using concepts of lazy evaluation. Presented at University of Montana, Missoula MT. Spatial Modeling class 11/21/2017 (invited presentation).

Hogland, J; Anderson, N. Beyond the buttons: improved spatial modeling using concepts of lazy evaluation. Presented at University of Montana, Missoula MT. Geography department colloquium 11/14/2017 (invited presentation).

Hogland, J; Affleck, D.; Anderson, N. Simulated effects of co-registration errors: implications related to estimating forest characteristics using remotely sensed data. Presented at INGY, Coeur d’Alene 3/13/2016 (invited presentation).

Hogland, J; Anderson N.; St. Peter, J.; Drake J.; Medley, P.; Gilbert, J; Abernethy, R; Knight, A.; Hipes, D; Cost-effective mapping of longleaf extent and condition using NAIP imagery and FIA data: a pilot project in the heart of the longleaf range, Presented at 11th Biennial Longleaf Alliance Regional Conference, Savanah GA 11/4/2016 (invited presentation).

Hogland, J; Anderson N.; St. Peter, J.; Drake J.; Medley, P.; Gilbert, J; Abernethy, R; Knight, A.; Hipes, D; Longleaf pine mapping and monitoring project, Presented LPC, Savanah GA 11/4/2016 (invited presentation).

Moderator of the mapping and monitoring session at 11th Biennial Longleaf Alliance Regional Conference, Savannah GA 11/3/2016.

Hogland, J.; St Peter, J.; Prioritization of open pine red cockaded woodpecker habitat, Presented at 11th Biennial Longleaf Alliance Regional Conference, Savanah GA 11/4/2016 (workshop).

Hogland, J. Field data collection for restore project: ArcPad data collection application, Presented via VTC to Region 8 National Forst, Tallahassee FL.Forest, Tallahassee FL. 8/l0/2017.Hogland, J.; Anderson, N. Resources and Ecosystems Sustainability, Tourist Opportunities, and Revived Economies Inventory Project, Presented at Region 8 National Forest, Tallahassee FL. 5/16/2016 (presentation).

Hogland, J.; Anderson, N. Delivered cost model part 2. Presented at BANR, Laramie, WY 10/3/2016 (presentation).

Hogland, J.; Anderson N.; Drake, J; Medley, P; Knight, A.; Gilbert, J. 2016. Cost-effective mapping of longleaf extent and condition using NAIP imagery and FIA data: a pilot project in the heart of the longleaf range. At NFWF. Presented by Hogland & Drake (presentation).

Hogland, J.; Anderson N.; Drake, J; Medley, P; Knight, A.; Gilbert, J. 2016. Longleaf pine mapping and monitoring project overview. At LPC. Presented by all (presentation).

Hogland, J.; Reynolds-Hogland, M; Chase, I; Phillippi, B.; Hughes, D.; Normand, D. 2016. Treasure hunt in the treasure state: GIS lesson plan. At MAGIP. Great Falls, MT. Presented by all (presentation).

Hogland, J.; Anderson, N; Drake, J; Medley, P; Knight, A.; Gilbert, J. 2016. Longleaf pine mapping and monitoring project update. Webinar. Presented by Hogland (presentation).

Hogland, J.; Anderson, N. 2016. Quantifying fine grained forest characteristics across broad extents using NAIP imagery and spatially located field plot. At INGY. Coeur d’Alene, ID. Presented by Hogland (presentation).

Hogland, J.; Anderson, N. 2016. Cost-effective mapping of longleaf extent and condition using NAIP imagery and FIA data: a pilot project in the heart of the longleaf range. First Progress Report to National Fish and Wildlife Foundation (report).

Hogland, J.; Anderson, N. 2016. Cost-effective mapping of longleaf extent and condition using NAIP imagery and FIA data: a pilot project in the heart of the longleaf range. Second Progress Report to National Fish and Wildlife Foundation (report).

Hogland, J.; Anderson, N. 2016. Cost-effective mapping of longleaf extent and condition using NAIP imagery and FIA data: a pilot project in the heart of the longleaf range. Third Progress Report to National Fish and Wildlife Foundation (report).

Hogland, J.; Anderson, N.; Chung, W.; Wells, L.; Han, H. 2016. Spatially explicit, fine grained, raster-based biomass supply chain analysis. At BRDI. Missoula, MT. Presented by Hogland (presentation).

Hogland, J.; Anderson, N.; Chung, W.; Wells, L.; Han, H. 2016. Spatially explicit, fine grained, raster-based biomass supply chain analysis. At BRDI. Missoula, MT. Presented by Hogland (poster).

Hogland, J.; Anderson, N. 2015. Estimating FIA plot characteristics using NAIP imagery, function modeling, and the RMRS Raster Utility coding library. At FIA symposium. Portland OR. Presented by Hogland (presentation).

Hogland, J.; Anderson, N. 2015. Delivered cost model. At BANR. Missoula MT. Presented by Hogland (presentation).

Hogland, J.; Anderson, N. 2015. Canopy cover: LiDAR vs NAIP. At MTDC R1 GIS Workshop. Missoula MT. Presented by Hogland (presentation).

Hogland, J.; Anderson, N. 2015. Function modeling: a fast and efficient spatial modeling framework. At IALE. Portland OR. Presented by Hogland (poster).

Hogland, J.; Anderson, N. 2015. RMRS Raster Utility project overview: Uncompahgre Plateau case study. Webinar. Presented by Hogland (presentation).

Hogland, J.; Anderson, N. 2015. RMRS Raster Utility. Webinar. Presented by Hogland (presentation).

Hogland, J.; Anderson, N. 2015. FIA Ogden workshop: estimating forest characteristics & Image based classification. Ogden Utah. Presented by Hogland (presentation).

Miller, S.; Essen, M.; Anderson, N.; Chung, W.; Elliot, B.; Page-Dumroese, D.; Han, H.; Hogland, J.; Keyes, C. 2015. Burgeoning biomass: creating efficient and sustainable forest biomass supply chains in the Rockies. Webinar. Presented by all (presentation).

Hogland, J.; Anderson, N. 2015. Function Modeling: a fast and efficient spatial modeling framework (Poster). At Roundtable on the Crown of the Continent. Missoula MT. Presented by Hogland (presentation).

Hogland, J.; Anderson, N.; Jones, G.; Chung, W.; Butler, E.; Wells, L.; Dongwook, K.; Han, H. 2015. Biomass research and development initiative spatial analysis of feed stock supply Part 3. At BRDI. Baton Rouge, LA. Presented by Hogland (presentation).

Hogland, J.; Ahl, Robert; Anderson, N. 2014. Image based classification using the RMRS Raster Utility toolbar: focus on workflow workshop. At MAGIP. Missoula MT. Presented by Hogland (workshop).

Hogland, J.; Anderson, N.; Chung, W.; Wells, L. 2014. Environmental Systems Research Institute (ESRI) Users Conference. At WO Research & Development Meeting. Webinar. Presented by Hogland (presentation).

Hogland, J.; Anderson, N.; Chung, W.; Wells, L. 2014. Estimating forest characteristics using NAIP imagery and ArcObjects. San Diego, CA. Presented by Hogland (presentation).

Hogland, J.; Anderson, N. 2014. Improved analyses using function datasets and statistical modeling, At ESRI UC. San Diego CA. Presented by Hogland (presentation).

Hogland, J.; Anderson, N.; Jones, G.; Chung, W.; Butler, E.; Wells, L.; Dongwook, K. 2014. Biomass research and development initiative spatial analysis of feed stock supply II. At BRDI. Spokane WA. Presented by Hogland (presentation).

Hogland, J.; Anderson, N.; Ahl, R. 2013 Using the RMRS Raster Utility toolbar to design a study, sample predictive variables, build a predictive model, interpret results, and create a predictive surface workshop. Helena MT. Presented by Hogland (workshop).

Hogland, J.; Anderson, N. 2013. New features of the RMRS Raster Utility toolbar: a focus on predictive modeling. Helena MT. Presented by Hogland (presentation).

Hogland, J.; Anderson, N.; Ahl, R. 2013. Inexpensive representative sample selection methods using a multivariate two sample Kolmogorov-Smirnov test. At MAGIP. Helena MT. Presented by Hogland (presentation).

Hogland, J. 2013. Orienteering workshop. At Dunrovin Ranch. Lolo, MT (workshop).

Hogland, J.; Anderson, N.; Jones, G. 2013. RMRS Raster Utility. At COFE. Missoula MT. Presented by Hogland (presentation).

Hogland, J.; Anderson, N.; Jones, G. 2013. Estimating forest characteristics using field samples, NAIP imagery, texture, and polytomous logistic regression. At COFE. Missoula MT. Presented by Hogland (presentation).

Hogland, J.; Anderson, N.; Jones, G. 2012. RMRS Raster Utility workshop. At MAGIP. Helena MT. Presented by Hogland (presentation).

Hogland, J.; Anderson, N.; Jones, G. 2012. Estimating forest characteristics for the Uncompahgre National forest in western Colorado using field samples, NAIP imagery, and texture. At MAGIP. Helena MT. Presented by Hogland (presentation).

Hogland, J.; Anderson, N.; Jones, G.; Chung, W.; Butler, E.; Wells, L.; 2012. Biomass research and development initiative spatial analysis of feed stock supply. At BRDI. Spokane WA. Presented by Hogland (presentation).

Anderson, N.; Hogland, J. 2012 (primary author). Biomass estimation and mapping using novel regression methods applied to NAIP orthoimagery and FIA data. Midterm project report for RMRS CRI Uncompahgre Plateau Project (report).

Hogland, J.; Billor, N. 2012. A comparison between standard maximum likelihood classification techniques and polytomous logistic regression. At ForestStat. Corvallis OR. Presented by Hogland (presentation).

Hogland, J.; Anderson, N.; Jones, G. 2012. Function modeling: improved raster analysis through delayed reading and function raster datasets. At ForestStat. Corvallis OR. Presented by Hogland (presentation).

Hogland, J.; Anderson, N.; Jones, G. 2012. Estimating basal area, trees, and above ground biomass per acre for common tree species across the Uncompahgre Plateau using NAIP CIR imagery. At Timber Measurements Society. Coeur d’Alene, ID. Presented by Hogland (presentation).

Hogland, J.; Anderson, N.; Jones, G. 2012. Estimating above ground tree biomass for the Uncompahgre Plateau in western Colorado using NAIP imagery and a series of textural and probabilistic metrics. At ESA in Portland OR. Presented by Hogland (presentation).

Anderson, N.; Jones, G.; Chung, W.; Hogland, J. 2012. Project update: Rocky Mountain Research Station competitive research initiative Uncompahgre Plateau project. Montrose CO. Presentation by Anderson & Hogland (presentation).

Hogland, J. 2011. Uncompahgre Plateau (UP) biomass estimation. At RMRS in Missoula MT. Presented by Hogland (presentation).

Hogland, J. 2011. Coding a digital enterprise: design, tips, and tricks from a coding perspective. Montana association of geographic information professionals. Missoula MT. Presented by Hogland (presentation).

Hogland, J.; MacKenzie, M. 2005. Creating spatial probability distributions for longleaf pine ecosystems across east Mississippi, Alabama, the panhandle of Florida, and west Georgia. Ecological Society of America. Ecological Society of America URL: http://www.esa.org/montreal/ Compact disc August 12, 2005. Presented by Hogland (presentation).

Hogland, J.; MacKenzie, M. 2004. Identifying longleaf ecosystems using remote sensing and GIS: management implications. Longleaf Alliance Report No. 8: Presented by Hogland (presentation).

Hogland, J.; MacKenzie, M. 2004. Determining the current distributions of critically endangered longleaf ecosystems: A regional approach using remote sensing techniques. Longleaf Alliance Report No. 8: (poster).

Hogland, J.; MacKenzie, M. 2004. Using remote sensing techniques to delineate the current distribution of longleaf (Pinus palustris) ecosystems across Alabama, west Georgia, and east Mississippi. Southeastern Biology Bulletin 51(2):197. Presented by Hogland (presentation).

Hogland J; MacKenzie, M. 2004. Identifying longleaf ecosystems using polytomous logistic regression. GAP Bulletin (report).

Hogland, J.; MacKenzie. M. 2003. Using remote sensing techniques to delineate the

current distribution of longleaf (Pinus palustris) ecosystems across Alabama, west Georgia, and east Mississippi. Longleaf Alliance Report No. 7: 69. Presented by Hogland (presentation).

Hall, R.; Hogland, J. 2001. GIS for urban forestry. Georgia URISA. Presented by Hall and Hogland (presentation).