Environmental layers for Great Smoky Mountains National Park. Includes Environmental Protection Agency Level 4 Ecological Regions, 12 digit hydrologic unit watershed boundaries, temperature variances, trails, and forest threats (North Carolina only). Also includes waypoints for Appalachian balds (grassy areas at elevation)
A discussion thread I started in January, 2014: https://groups.google.com/forum/#!topic/blacklight-development/Ax0840hBeUA
Hello,I’ve poked around a bit and did not see anything about support for geospatial search.I became interested in Blacklight after visiting the Environment Australia Web site.Their site is built on PostgreSQL relational database, and since it pertains to the environment, I thought they might have spatially explicit data.They do have “Search by Region,” but it is just a linked list of regions.Thanks for any tips,Tanner
I got a few responses asking for more information and potential use cases so I added (in July 2014):
My opinion is any geographic representation of a collection constitutes value-added.
I am interested building a functional SKOS ontology based on the relationships between EPA ecological regions and protected areas of the United States. There are a few hierarchical levels which the ontology could describe. There are also relationships between protected areas and each ecological region.
For example, Great Smoky Mountains National Park on the North Carolina and Tennessee belongs to two main ecological regions: Ridge and Valley (67) ,and Blue Ridge (66). A full accounting of Level III ecological regions is available at <ftp://ftp.epa.gov/wed/ecoregions/cec_na/NA_LEVEL_III.pdf>.
The Level III ecological regions can be further divided into Level IV ecoregions, a higher level of granularity, available at <ftp://ftp.epa.gov/wed/ecoregions/us/Eco_Level_IV_US.pdf>.
Using the Smokies again as the exemplar, new ecological sub-regions at the Level IV resolution emerge: High mountains (66i), Southern sedimentary ridges (66e), Limestome Valleys and Coves (66f), Southern Metasedimentary mountains (66g), Broad basins (66j), and Southern Dissected Ridges and Knobs (67i), Southern sandstone ridges (67h), Southern Shale Valley (67g).
These regions can be linked via an ontology to other protected areas, allowing environmental information resources to be grouped based on meaningful ecological relationships. For example, a search in an information retrieval system for “High Mountains (66i)” would retrieve results from relevant protected areas: Roane Mountain State Park, Pisgah National Forest, Cherokee National Forest, AND Great Smoky Mountains National Park, and perhaps any location built in to the ontology as a member of the given ecological region’s footprint. This represents a sophisticated query with minimal effort on behalf of the user.
Along with providing a framework for information retrieval via “regions” as the Australia site does, the ontology would have useful text mining and automated spatial metadata creation applications.
Potential use cases include:
- DataONE ONEmercury metadata clearinghouse, which runs on Solr – <https://cn.dataone.org/onemercury/>
- National Park Service’s DataStore portal – https://irma.nps.gov/App/
- U.S. Forest Service’s “Treesearch” database: http://www.treesearch.fs.fed.us/
I wanted to do a Masters thesis on the impact of an ontology on search and retrieval, but after discussing with my thesis coordinator who indicated this was more of a PhD level undertaking, I opted to instead pursue comprehensive exams as my exit strategy.
I still think this is a worthwhile area of research and I am happy to see the example you have shared, and that there are others interested in the topic.
Discussion Number Two for Introduction to the GeoWeb
Geoportals, Open Data sites, and online repositories provide access to data in a variety of formats. More and more popular is the KML file. Explore online and locate three sources that offer KML downloads. Please provide links and description of the dataset. Note: some of these sources may help with your Google Earth map!.
Due June 27th.
For a course in Geographic Information Management and Processing, I modelled potential habitat for hemlock using Maxent and ArcGIS. I used 10 environmental layers including 5 categorical (vegetation class, cover, soils, etc.) and 5 continuous (precipitation, solar radation, etc). That project is discussed at length in other posts.
For this assignment, I’d like to continue looking at the Great Smoky Mountains National Park, primarily because it is well-studied and there is an abundance of data, but also because there is a strong elevation gradient which makes for interesting geographic phenomenon. Also, I know a lot about the processes and patterns in the area because I grew up in Sevierville, attended school in Gatlinburg, and spent many weekends hiking in the Park as a college student.
From some previous work, I know there are three datasets that I am interested in. First, I’m interested in a temperature and precipitation model I knew was around – so I did a quick search in Google:
precipitation AND great smoky mountains filetype:kmz
Note the “filetype” operator. I did not find what I wanted, so I changed my search.
“great smoky mountains” filetype:kmz
I did find what I wanted, plus some other interesting datasets I had forgotten about.
Great Smoky Mountains National Park Hiking Trails as Google Earth / Virtual Globe KMZ file
First, I’m interested in the GRSMNP trails, represented as a KMZ file. This is available from Dunigan’s Web site, which has some excellent resources on the Park and was formerly hosted by the EECS department at the University of Tennessee (I’m sad to note that UT no longer supports his site; which is unfortunate since I think it was a public service). However Dunigan’s data is now available at tnlandforms.us.
This is the trails file:
Some other files are available, but in my opinion the trails have the most significance because anyone who has visited the trails can follow along and understand what particular part of the “virtual globe” they have visited.
When you couple the trails with the landmarks file, then you can easily see destinations and origins, along with interesting facts about the landmarks (elevation, for example):
There is not a search / retrieval feature on the site and I actually had a hard time finding it (though for future reference, it’s right on the front page of the site!)
Along the way, I found data from the Forest Service that I thought could be useful for comparing with the models I generated for Hemlock distribution.
This site is the tree atlas, which generated models for tree distributions under six climate change scenarios (the scenarios are also models).
Here’s the citation:
Prasad, A. M., L. R. Iverson., S. Matthews., M. Peters. 2007-ongoing. A Climate Change Atlas for 134 Forest Tree Species of the Eastern United States [database]. http://www.nrs.fs.fed.us/atlas/tree, Northern Research Station, USDA Forest Service, Delaware, Ohio.
There is a related study here:
Iverson, L. R., A. M. Prasad, S. N. Matthews, and M. Peters. 2008. Estimating potential habitat for 134 eastern US tree species under six climate scenarios. Forest Ecology and Management. 254:390-406. http://www.treesearch.fs.fed.us/pubs/13412
There are 134 trees available. At 6 models each, that should be a minimum of 804 KML files. For the purposes of this assignment, I would like to download and look at Eastern Hemlock (Tsuga canadensis) in particular. The individual HTML page for this tree is here: http://www.nrs.fs.fed.us/atlas/tree/gearth_261.html.
Interestingly, there are actually 10 KML files: Current, 3 models high and low, and average of all three high and low models together.
Forest Inventory Analysis (Current Distribution).
I want to download these and see if they have associated metadata; I’m a bit disappointed in the titles supplied. I have heard of “Hadley” model but I feel the other acronyms are somewhat inaccessible.
I downloaded them – let me open up my next dataset, the temperature models from Syracuse University.
There are a few models to choose from, but I am most interested in cold. The reason is that Hemlock Wooly adelgids and other forest pests don’t really like the cold – in fact a lot of the adelgids died during the “Polar Vortex” of Winter 2014. Those that survived experienced significantly reduced fecundity. So, I would like to look at this dataset showing the range of temperatures in the Park from July 2005 to October 2006:
The final data I want to add is snow! I love to snowboard, and hike in the snow, the final data source / dataset I want to add to this exploration of the Park as a virtual globe is the National Snow and Ice Data Center’s virtual globe page.
Just for fun, I was hiking on the Mount Cammerer Trail in 2005, so I want to pull in the snow cover for North America in Winter 2005/2006 (January). Let’s have a look at that data!
Also for future reference – there are two other items I am interested in looking at:
http://www.nrs.fs.fed.us/atlas/tree/gearth_12.html (Balsam fir)
Trails.kmz – there is not metadata in “Get Info,” no legend, clicking a trail gives the contents of the table attributes.
FIA/GCM Scenario: Actual – sad, no metadata in the “Get Info, no legend.”
Range.kmz – no metadata in “Get Info,” and there is not a legend.
MODIS_mod10cm_2006_static.kml starts with the map centered on the North Pole.
Inside the file, there is a network link.
There is not information in the “Get Info” which is unfortunate – mainly because I think it’s necessary to use the time slider feature.
I can’t get it to work – there is a red icon and I’m wondering if that means the network is offline.
Let me compare it to the EPA Waters map:
The direct link to the file:
For starters, just from the Web page, the EPA has strong documentation.
This one is by far the most fascinating KMZ dataset. It serves national data on a network that refreshes when you zoom in. Opening up the KMZ file shows sophisticated inner working. There’s a legend, surfacewater features including streams, canals, pipelines, waterbodies, coastlines, catchments, hydrologic units. There’s also EPA water program features including 303(d) impaired waters (lovely I live next to a few of them) 305 B Assessed waters, Beaches, Clean Watersheds needs survey, facilities that discharge to waters, fish consumption advisories, fish tissue data, TMDLs on imparied waters, monitoring locations, nonpoint source projects, and a legend. Even an EPA logo.
This is a level of content delivery expertise I’d like to operate at. Because the information is in Google Earth, and links off via the table to additional EPA data, I think it’s really maximizing the ability of Virtual Globes to serve as a digital representation or access point to more information – it’s almost like a “second life” world when you can explore a variety of concepts related to water quality in near real-time.
So I’m disappointed I could not look at snow cover, I may check back in a few days – but for now I’m assuming that the network link was not functioning properly.