Hogland's Spatial Solutions

Publications (Peer Reviewed):

Reynolds-Hogland, M.; Brooks, C.; Ramsey, A.B.; Hogland, J.; Pilgrim, K.L.; Engkjer, C.; Ramsey, P.R., 2024 Long-term video genetic data yield insights into complex sociality of a solitary large carnivore, Behavioral Processes, 214: 104972.
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

Publications (Other):

Hogland, J. 2025. Implementing one pass gray level co-occurrence matrix (GLCM for any bit depth, without using a co-occurrence probability matrix, jupyter notebook, online: https://github.com/jshogland/SpatialModelingTutorials/blob/main/Notebooks/glcm.ipynb, last accessed 2/24/2025
Hogland, J. 2025. Local, Rgional, and Global Moran's I and Geary's C spatial statistics, jupyter notebook, online: https://github.com/jshogland/SpatialModelingTutorials/blob/main/Notebooks/spatialstats.ipynb. last accessed 2/24/2025.
Hogland, J. 2024. Estimating kernel weights using PCA and a defined analysis window, jupyter notebook, online: https://github.com/jshogland/SpatialModelingTutorials/blob/main/Notebooks/kernel_pca.ipynb, last accessed 2/24/2025.
Hogland, J. 2024. Percent Tree Canopy Cover Notebook, online: https://github.com/jshogland/SpatialModelingTutorials/blob/main/Notebooks/ShawneeNF_TCC.ipynb, llast accessed 2/24/2025.
Bunt, F., Hogland, J., Johnson, J. 2024. UM-RMRS/raster_tools updates. Online: https://github.com/UM-RMRS/raster_tools. Last Accessed 9/20/2024.
Bunt, F., Hogland, J., Johnson, J. 2024. UM-RMRS/pc_rasterize. Online: UM-RMRS/pc-rasterize: Rasterize point clouds in Python in parallel. (github.com). Last Accessed 9/20/2024.
Bunt, F., Hogland, J., Johnson, J. 2024. UM-RMRS/raster_tools documentation. Online: Welcome to raster_tools’ documentation! — raster_tools 0.9.2 documentation (um-rmrs.github.io). Last Accessed 9/20/2024.
Hogland, J. 2024. Spatial Modeling Tutorials updates. Online: https://github.com/jshogland/SpatialModelingTutorials. Last Accessed 9/20/2024.
Bunt, F., Hogland J., 2024 Raster-Tools releases, Online: https://pypi.org/project/raster-tools/. Last Accessed 9/20/2024.
Hogland, J. 2024. Hilbert space filling curves and potential ways we can use them, jupyter notebook, online: https://github.com/jshogland/SpatialModelingTutorials/blob/main/Notebooks/hilbert_curve.ipynb, last accessed 2/24/2025.
Hogland, J. 2024. Handling Errors Notebook, Online: SpatialModelingTutorials/Notebooks/HandlingErrors.ipynb at main · jshogland/SpatialModelingTutorials (github.com), Last Accessed 9/20/2024
Hogland, J. 2024. Errors notebook, Online: https://github.com/jshogland/SpatialModelingTutorials/blob/main/Notebooks/errors.ipynb, Last Accessed 9/20/2024
Hogland, J. 2024. Getting Rest Data notebook, Online: SpatialModelingTutorials/Notebooks/GetRestData.ipynb at main · jshogland/SpatialModelingTutorials (github.com), Last Accessed 9/20/2024
Hogland, J. 2024. Knn Sample Design notebook, Online: https://github.com/jshogland/SpatialModelingTutorials/blob/main/Notebooks/knn_sample_design.ipynb, Last Accessed 9/20/2024
Hogland, J. 2024. Knn Create Model notebook, Online: https://github.com/jshogland/SpatialModelingTutorials/blob/main/Notebooks/knn_create_model.ipynb, Last Accessed 9/20/2024
Hogland, J. 2024. Delivered Cost Model gethub repo, Online: jshogland/DeliverdCostGUI: Binder test (github.com), Last Accessed 9/20/2024
Hogland, J. 2024. Delivered Cost GUI Appliation, Online https://mybinder.org/v2/gh/jshogland/DeliverdCostGUI/HEAD?urlpath=voila%2Frender%2FDeliveredCost.ipynb, Last Accessed 9/20/2024
Hogland, J. 2024. Sample Design Gui Application, Online: https://mybinder.org/v2/gh/jshogland/DeliverdCostGUI/HEAD?urlpath=voila%2Frender%2FSampleDesign.ipynb, Last Accessed 9/20/2024
Hogland, J.; Lister, A.; Scott, C. 2024. Angola sample design dataset and notebook https://colab.research.google.com/drive/1SLLiZfAJBn5fJOQhePuNTiQWn-iWwGME?usp=sharing, Last Accessed 9/20/2024
Hogland, J., 2024. Fire Resilience (Sante Fe, NM), jupyter notebook, online: https://github.com/jshogland/SpatialModelingTutorials/blob/main/Notebooks/SantaFe.ipynb, last accessed 2/24/2025.
Hogland, J., 2024. Classification and regression models using Hilbert distance, jupyer notebook, online: https://github.com/jshogland/SpatialModelingTutorials/blob/main/Notebooks/hilbet_model.ipynb, last accessed 2/24/2025.
Hogland, J., 2024. NASA EIC fire Interview and video, online: EIC Fire RC1_052424_GAW on Vimeo (5/24/2024).
Hogland, J., 2024. Using a neighborhood window and machine learning to estimate tree canopy cover, jupyter notebook, online: https://github.com/jshogland/SpatialModelingTutorials/blob/main/Notebooks/knn_create_model.ipynb, last accessed 2/24/2025.
Hogland, J. 2023. Getting Stac Data notebook, Online: SpatialModelingTutorials/Notebooks/getting_stac_data.ipynb at main · jshogland/SpatialModelingTutorials (github.com), Last Accessed 9/20/2024.
Hogland, J. 2023. Fire Resilience, juypter notebook, online: https://github.com/jshogland/SpatialModelingTutorials/blob/main/Notebooks/FireResilience.ipynb, Last Access 2/24/2025.
Hogland, J. 2023. Estimating BAA, jupyter notebook, online:https://github.com/jshogland/SpatialModelingTutorials/blob/main/Notebooks/EstimatingBaa.ipynb, Last Accessed 2/24/2025.
Hogland, J. 2023. Gopher Tortoise Restoration, jupyter notebook, online: https://github.com/jshogland/SpatialModelingTutorials/blob/main/Notebooks/FtStewartGopherTortious.ipynb, last accessed 2/24/2025.
Hogland, J. 2023. Fort Stewart SGA sample design example, jupyter notebook, online: https://github.com/jshogland/SpatialModelingTutorials/blob/main/Notebooks/FtStewartSampleDesign.ipynb, last accessed 2/24/2025.
Hogland, J. 2023. Get data from a rest api and open streetmaps. jupyter nootebook, availalble online: https://github.com/jshogland/SpatialModelingTutorials/blob/main/Notebooks/GetRestData.ipynb, last accessed 2/24/2025.
Hogland, J. 2023. Getting cloud based data, jupyter notebook, online: https://github.com/jshogland/SpatialModelingTutorials/blob/main/Notebooks/getting_stac_data.ipynb, last accessed 2/24/2025
Hogland, J. 2023. Get Lidar Data from USGS 3Dep (Microsoft Planetary Computer), juypeter notebook, online: https://github.com/jshogland/SpatialModelingTutorials/blob/main/Notebooks/LidarDownload.ipynb, last accessed 2/24/2025.
Hogland, J. 2023. Processing Lidar Data form USGS 3Dep program, jupyter notebook, online: https://github.com/jshogland/SpatialModelingTutorials/blob/main/Notebooks/LidarProcessing.ipynb, last accessed 2/24/2025.
Hogland, J. 2023. Sample Design (Microsoft Planetary Computer), jupyter notebook, online: https://github.com/jshogland/SpatialModelingTutorials/blob/main/Notebooks/SampleDesign.ipynb, last accessed 2/24/2025.
Medley, P.; Drake, J.; St. Peter, J.; Vernon, J.; Hogland, J.; Battle, B.; Broadbent, E.; Zambrano, A; Ibeanusi, V.; Chen, G.; Prata, G.; Crandall, C., Wu, Y.; Abood, S.; Awowale, E.; Prasai, R. 2023. Tate's Hell Strategy 1 Ecological and Hydrological Restoration Planning Component: Phase 1 of the Apalachicola Regional Restoration Initiative, GTR.
Anderson, N.; Hogland, J. 2022. Resources to improve the efficiencies of forest operations. Science You Can Use (in 5 Minutes), Fort Collins, CO: U.S. Department of Agriculture, Forest Service, Rocky Mountain Research Station. 2 p. Contributions; conceptualization, data curation, formal analysis, investigation, methodology, software, validation, visualization, writing—original draft, writing—review and editing (4D1: 9, 18).
Watts, A.; Anderson, N.; Chung, W.; Hogland, J,; Keefe, R.; Becker, R.; Twitchell, J. 2022. There’s more to harvesting than green timber and sawlogs: Engineering forest operations for 21st-century forest management. Science You Can Use Bulletin, Issue 53. Fort Collins, CO: U.S. Department of Agriculture, Forest Service, Rocky Mountain Research Station. 11 p. Contributions; conceptualization, data curation, formal analysis, investigation, methodology, software, validation, visualization, writing—original draft, writing—review and editing (4D1: 8, 9, 18).
Hogland, J. 2022. Spatial Modeling Tutorials. Online: https://github.com/jshogland/SpatialModelingTutorials. Last Accessed 9/20/2022.
Bunt, F., Hogland J., Raster-Tools, Online: https://pypi.org/project/raster-tools/. Last Accessed 9/20/2022.
Hogland, J. 2022. Open source parallel processing and delayed reading libraries, web based GIS, and an update on high performance computing pilot, Online: https://youtu.be/Ee5aQd37PvE, Last Accessed 9/20/2022 Video.
Hogland, J. 2022. 21st century planning notebook, Online: https://youtu.be/vFPLiR1rOvQ, Last Accessed 9/20/2022 Video.
Hogland, J. HPC Pilot SharePoint Site, online: https://usdagcc.sharepoint.com/sites/fs-wo-rdim/SitePages/HPC-Pilot.aspx, Last Accessed 9/20/2022 Video.
Hogland, J. 2022. Machine Learning and Spatial Modeling using raser_tools, Jupyter Notebook, Online: https://github.com/jshogland/SpatialModelingTutorials/blob/main/Notebooks/ANF_ML.ipynb, Last Accessed 9/20/2022.
Hogland., J. 2022. 21st Century Planning Techniques for Creating Fire-Resilient Forest in the American West, Jupyter Notebook, Online: https://github.com/jshogland/SpatialModelingTutorials/blob/main/Notebooks/PODs_Integration.ipynb,. Last Accessed 9/20/2022.
Hogland J. 2022. Python Automation Short Course, Jupyter Notebook, online: https://github.com/jshogland/SpatialModelingTutorials/blob/main/Notebooks/Python_Automation_ANFS.ipynb, Last Accessed 9/20/2022.
Hogland, J. 2022, TCSI Potential Cost Demonstration: Notebook, Jupyter Notebook, online: https://github.com/jshogland/SpatialModelingTutorials/blob/main/Notebooks/Accel.ipynb, Last Accessed 9/20/2022.
Hogland, J. 2022, It is easy to code in R using Colab, jupyte notebook, online: https://github.com/jshogland/SpatialModelingTutorials/blob/main/Notebooks/quick_example_in_R.ipynb, last accessed 2/24/2025.
Bunt, F., Hogland, J., Johnson, J. 2021. UM-RMRS/raster_tools updates. Online: https://github.com/UM-RMRS/raster_tools. Last Accessed 9/20/2022.
Hogland, J. 2021. Special assignment - 9/15/2021 – 12/15/2021 Improving information technology products and services for R&D
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>

Presentations:

Hogland, J.; Johnson, J.; Bunt, F. 2024. Raster Tools: Geospatial, ML Parallel Processing, presented to AI COE (virtual, 6/28/2024).
Hogalnd, J. 2024. Spatially Explicit Fine Grained Delivered Cost Model, presented to BIL Wood Innovation Meeting (virtual, 12/6/2023).
Hogland, J. 2024. Raser Tools – Remote Sensing, Delivered Cost, Planning, presented to Fast 500 Team, (virtual, 8/4/2024)
Hogland, J.; Affleck, D.; Johnson, J.; Bunt, F.; Anderson, N. 2024. Transforming data into useful information for natural resources decision making, presented at FOSS4Gna, (St Louis, MO; 9/10/2024).
Hogland, J. 2024. Environment setup and predictive modeling, workshop presented at FOSS4Gna, (St Louis, MO; 9/10/2024).
Hogland, J. 2024. Project Jupyter, presented to Geo-scripting community, (virtual, 4/10/2024)
Hogland, J. 2024. Integrating Field Data, remote sensing, geospatial analysis, and machine learning into a standardized workflow workshop, presented at Big Sky GeoCon (Billings, MT, 4/16/2024).
Hogland, J. 2024. Wildfire and resilient landscapes: new tools for detailed analyses, presented at Science You Can Use webinar, (virtual, 2/14/2024)
Hogland, J. Johnson, J. 2024. Task Group 1 March progress report, presented at Smart Forestry Project Meeting (virtual, Umatilla NF, OR, 3/15/2024)
Johnson, J.; Hogland, J. 2024. Task Group 1 September progress report, presented at Smart Forestry Project Meeting (virtual, John Day NF, OR, 9/24/2024)
Hogland, J., Spread and Balance: Impact on Design and Model Based Estimates, presented at University of Montana’s Computer Science Department, (Missoula MT, 4/22/2024)
Hogland, J. Johnson, J. Bunt, F. 2024. Raster Tools Geospatial Python Library: Automated Parallel Processing of Geospatial, Statistical, and Machine Learning Algorithms at Scale, presented to DOI’s Open-Source geospatial Team, (virtual, 3/5/2024)
Hogland, J. 2024. WCS R3 – Raster Tools, Fire Resilient Landscapes, & Costs, presented to WCS R3 project leads, (virtual, 9/18/2024)
Hogland, J. 2024. PODs BIL - DFCs, PODs, and Costs, presented to WO (4/26/2024)
Hogland, J. 2024. Web apps: Github, JupyterHub, BinderHub, Voila, Raster-Tools, Ipywidgets, presented to WRMS lab (virtual, 1/16/2024)
Hogland, J. 2023. Raster Tools Geospatial Python Library: Automated Parallel Processing of Geospatial, Statistical, and Machine Learning Algorithms at Scale, as part of the DOI Open-Source Geospatial seminar series, (invited, virtual, 9/28/2023).
Hogland, J. 2023. Python Errors, presented as part of the geo-scripting working group seminar series (virtual, 9/18/2023).
Hogland, J.; Johnson, J. 2023. Smart Forestry: paving the way from forest restoration to mass timber, as part of the March-September Smart Forestry Progress Report (virtual, 9/14/2023).
Hogland, J.; Johnson, J.; Bunt, F. 2023. Raster Tools: transforming data into useful information, presented at ESRI User conference in San Diego, CA (7/12/2023).
Hogland, J.; 2023. Raster Tools: Desktop tools for evaluating landscape change, presented at Malheur Monitoring and Research Symposium (5/17/2023).
Hogland, J.; Johnson, J. 2023. Smart Forestry: paving the way from forest restoration to mass timber, as part of the September-March Smart Forestry Progress Report (virtual, 3/21/2023).
Hogland, J. 2023 Transforming data into useful information for wildfire decision-making; improving the utility of remote sensing products at tactical and planning scales, invited Missoula MT. Fire Lab seminar series (2/23/2023).
Hogland, J. 2023. Raster Tools: machine learning, image processing, webhosting, presented at WRMS seminar series (virtual, 2/21/2023).
Hogland, J. 2023. Raster Tools: PODs & Making Fire Resilient Landscapes, presented at WITS (virtual, 2/6/2023).
Sloggy, M.; Manley, P.; Hogland, J. 2022. Calculating Nature’s Benefits, presented as part of CWAC project (virtual, 11/12/2022).
Hogland, J; Johnson, J;Bunt, F. 2022. Spatial explicit delivered cost, presented as part of the Accel Data Products: Webinar 3, (virtual, 10/18/2022).
Hogland, J.; Johnson, J. 2022. Task group 1: mapping solutions, as part of the SSmart Forestry EDA project, (OSU, 11/14/2022).
O’conner, C.; Pietruszka, B.; Hogland, J.; Calkin, D.; Thompson, M.; Dunn, C.; Caggiano, M.; Gannon, B. 2022. Strategic Fire Planning and Response with PODs, presented at USFS Fire Science Research Community, 3/17/2022 (invited virtual).
Hogland, J. 2022. Python Automation: focus on reusable code, presented at MAGIP GeoCon, Missoula, MT., 4/4/2022 (invited presentation and short course).
Hogland, J., 2022. Complex Spatial & Machine Learning Analyses, presented at MAGIP GeoCon, Missoula MT., 4/5/2022 (invited presentation and short course).
Hogland, J. 2022. Open-source parallel processing and delayed reading libraries, web-based GIS, and an update on high performance computing pilots, presented at the Research GIS Community meeting, 2/22/2022 (presentation, virtual)
Hogland, J.; Johnson, J.; Bunt, F. 2022. Raster-Tools: a new open source, python based, optimize, delayed reading, parallel processing library for complex spatial, statistical, and machine learning analyses, MAGIP 2022 Big Sky GeoCon, Missoula MT., 4/6/2022 (presentation).
Hogland, J.; Young J. 2021. Data, Spatial Modeling, Existing Conditions, DFCs, Costs, Revenues – Data Driven Decision Making, presented at WMRA lab meeting 10/21/2021 (presentation, virtual).
Hogland, J. 2021. High Performance Computing, presented at the Southern Research Station Management Council, 10/20/2021 (invited, virtual).
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).