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August 13th 2018



We've got an email from mailchimp to keep people informed if you don't want to check the wiki for updates.


This is Tennessee's second FOSS4G meeting.

It's an opportunity for Free and Open Source Software for GIS users in the area to get together and discuss projects, software, and get to know one another. The event is low cost. We are looking for sponsors (we'll make you famous).


Plant Biotech Building UT Ag Campus 2505 EJ Chapman Dr Knoxville, TN 37996


So this year we're charging $10 for admission to help defray some of the cost.


If the money is an issue with you attending let me (rjhale@northrivergeographic.com) and we will get it handled.



If you want to speak email rjhale@northrivergeographic.com and the committee will get back with you. Talks will be 20 minutes with 5 minutes for questions. I'll post the speakers and abstract up here as they come in.

Building an Open Geo Server - Randal Hale, NRGS - PostGIS is an extension to the postgresql database that allows you to store geographic Data. Geoserver is an open source server for sharing geospatial data. Using these two pieces of software (plus QGIS) we will create a very quick server application that will hold geospatial data and server it out using OGC Standards in 20 minutes or less...or the next one is free.

Fusing Geopolitics, Human Development, and Environmental Policy Data to Predict Population Stability through Open Source Software: A Case Study Across Africa - Dr. Hannah C. Gunderman, Advanced Short-Term Research Opportunities Program Participant at Oak Ridge National Laboratory - Although Africa has experienced notable successes in technology, healthcare, and transportation development, there remain several factors that threaten the stability of several countries within the continent. The role that geopolitics, human development, and environmental health play on population stability is significant. This research will demonstrate a methodology for providing a scenario-based population forecast for each of the 54 countries in Africa based on the data fusion of several geopolitical, environmental, and social metrics. Conducted 100% through Python in PyCharm, African countries are categorized on a 1-5 scale of scenario-based population stability for the next five years based on considerations of their population structure, their Human Development Index, Fragile States Index, and Environmental Performance Index scores, and if the country is experiencing geopolitical unrest. The resulting visualization, made exclusively in QGIS, allows geopoliticians, humanitarian researchers, and data scientists to devote increased attention toward predicted crisis areas on the continent.

Open Source Mapping Dashboard Using Leaflet and Esri REST Services - Mike McDougall:Blue Spatial - In this talk I will introduce Blue Leaflet, an open source mapping dashboard that uses Esri REST Map and Feature Services. This project brings together many Leaflet plugins to create a mapping dashboard template that can be delivered as a full solution out of the box. The dashboard includes plugins to enable many tools including: Measure, Print, Bookmarks, Fullscreen, Geolocate, Scalebar, Mouse Coordinates, Base Map Switching with OSM, Legend, and Minimap. The dashboard also includes client side styling for creating cluster, heat or bubble maps. The dashboard is divided into three sections which can be viewed individually or together including the map view, grid view and chart view. Each of these views synchronizes as features come in and out of view. Data can be filtered dynamically and exported to csv, excel or pdf. Other features include html template styling for popups and real time mapping capability via web sockets.

Landscape Level LiDAR and the National Land Cover Dataset - Doug Newcombe - Multiple LiDAR collections from Southeast Virginia analyzed for canopy height, relative vegetation density at 1-3m and 3-7m heights aggregated at 30m resolution aligned with the US National Land Cover Dataset (NLCD), 10m resolution nested inside the 30m cells and at 6.096 m. Forest/non - forest classes at 5m heights where compared to forest and shrub classifications present in the NLCD.

“Tennessee’s Public Lidar Data” - Paul Dudley, State of Tennessee - The State of Tennessee has an amazing project underway to collect statewide Lidar data in a partnership with the USGS 3D Elevation Program. This data is in the public domain and is easily downloaded. Presentation will cover project specifics, available data products, access and common data use cases.

Understanding patterns of vegetation structure and distribution across Great Smoky Mountains National Park using LiDAR and meteorology data - Jitendra Kumar - Great Smoky Mountains National Park (GSMNP) in Tennessee is a biodiversity hotspot and home to a large number of plant, animal and bird species. Driven by gradients of climate (ex. temperature, precipitation regimes), topography (ex. elevation, slope, aspect), geology (ex. soil types, textures, depth), hydrology (ex. drainage, moisture availability) etc. GSMNP offers a diverse composition and distribution of vegetation which in turn supports an array of wildlife. Understanding the vegetation canopy structure is critical to understand, monitor and manage the complex forest ecosystems like the Great Smoky Mountain National Park (GSMNP). Vegetation canopies not only help understand the vegetation, but are also a critically important habitat characteristics of many threatened and endangered animal and bird species that GSMNP is home to. Using airborne Light Detection and Ranging (LiDAR) we characterize the three-dimensional structure of the vegetation. LiDAR based analysis gives detailed insight in the canopy structure (overstory and understory) and its spatial variability within and across forest types. Vegetation structure and spatial distribution show strong correlation with climate, topographic, and edaphic variables and our multivariate analysis not just mines rich and large LiDAR data but presents ecological insights and data for vegetation within the park that can be useful to forest managers in their management and conservation efforts.

Convolutional Neural Network Approach for Mapping Arctic Vegetation using Multi-Sensor Remote Sensing Fusion - Forrest M Hoffman - Accurate and high-resolution maps of vegetation are critical for projects seeking to understand terrestrial ecosystem processes and land–atmosphere interactions in Arctic ecosystems, such as the U.S. Department of Energy’s Next Generation Ecosystem Experiment (NGEE) Arctic. However, most existing Arctic vegetation maps are at a coarse resolution and with a varying degree of detail and accuracy. Remote sensing-based approaches for mapping vegetation, while promising, are challenging in high latitude environments due to frequent cloud cover, polar darkness, and limited availability of high-resolution remote sensing datasets (e.g., 5 m). This study proposes a new remote sensing-based multi-sensor data fusion approach for developing high-resolution maps of vegetation in the Seward Peninsula, Alaska. We focused the detailed analysis and validation study around the Kougarok River, located in the central Seward Peninsula of Alaska.


  • North River Geographic Systems, Inc.
  • University of Tennessee Department of Geography
  • UT County Technical Assistance Service