Anna Knight wins AGU Outstanding Student Presentation Award

Congratulations Anna Knight on winning Outstanding Student Presentation at the 2018 American Geophysical Union Meeting for her poster “Geomorphic and disturbance controls on vegetation dynamics in Great Basin riparian ecosystems “. Click HERE to view Anna’s poster. You can read more about AGU’s Outstanding Student Presentation by clicking HERE.

AGU is a huge conference with thousands of students attending.  Anna's award is a testament to her hard work and innovative cutting-edge techniques.  Anna is completing her master's thesis under the advisement of Dr. Peter Weisberg.  You can view her webpage by clicking HERE.

Interesting finds in aerial photography

Every once in a while I encounter really interesting stuff when looking at digital elevation models and imagery in a GIS.  Today is one of those days. In the image below (40.8154 N 119.3856 W decimal degrees) the stream in the upper part of the image is flowing in two directions.  On the USGS topographic map it is named Rock Creek and flows to the south, but in the aerial photography it is quite evident that it also flows to the north at least some of the time.

In the image below I've zoomed in and see that a small jeep track may have caused an entire stream to shift from one basin into another (at least part of the time).

Interestingly, all of this is uphill and to the west of the cool and funky attraction known as Fly Geyser adjacent to the Black Rock Desert.

Remote sensing of cheatgrass die-offs featured on YouTube

This past Tuesday Owen Baughman gave a 1 hour talk as part of the  Great Basin Landscape Conservation Cooperative's Webinar series which you can view HERE. The talk was about cheatgrass (Bromus tectorum) die-offs and whether they  present an opportunity for ecological restoration, which is the topic he studied for his Master's thesis. Although the focus of the talk was on his field experiments, which I won't describe here (better to hear it in his own words by watching the YouTube video) he did take some time to show some of the preliminary results that came about from our cheatgrass die-off remote sensing study. I'll spare you the remote sensing details and save that for when our upcoming paper comes out, but I'm proud to say that our remote sensing method for mapping cheatgrass die-offs using Landsat imagery appears to be working very well.  We developed models for 2014 using the spectral signature of known die-offs and then applied them to 2015 imagery.  Sixteen out of seventeen predicted die-offs turned out to be real die-offs when visited in the field indicating a high level of accuracy.  You can see one of the example maps for predicted die-off events in 2015 below.

Updating 2013 NAIP Imagery in Nevada with Sun Elevation and Azimuth

NAIP imagery (National Agriculture Imagery Program of the US Department of Agriculture) constitutes a treasure trove of data that is underutilized by remote sensing analysts in my opinion. It is free, covers the entire state, and is updated regularly. So what's not to love? When it comes to image processing and classification, however, there are many challenges that people should be aware of before engaging in a major project. One challenge that I've grappled with is how to deal with differential illumination based on slope-aspect relative to the sun angle at the time of the collection. This problem can be remedied with Landsat data, because sun elevation and azimuth information is included in the metadata. The approach that we've been using in the Great Basin Landscape Ecology Lab involves creating an illumination raster (hillshade) that mimics the sun at the time of collection and then adjusts each band to its predicted brightness using linear regression.

This problem becomes more challenging with NAIP compared to Landsat, because NAIP images are flown over many months and at different times throughout the day. The result is that a single NAIP tile can have up to four different sun angles and these four regions of a single tile can have shadows pointing in four different directions. Obviously this poses a challenge to image classification.  Recently I learned that the USDA APFO now includes a seamline file for each state available for download on the Geospatial Data Gateway - https://gdg.sc.egov.usda.gov/. The approach that I'm now taking for topographic correction with NAIP involves downloading this seamline file, estimating latitude and longitude of center of each seamline polygon, and plugging this into some Excel formulas based on a NOAA spreadsheet (http://www.esrl.noaa.gov/gmd/grad/solcalc/calcdetails.html) that calculate sun elevation and azimuth.  I did this for the state of Nevada and joined the results back to the original shapefile to produce the maps below.

 

The above map shows sun elevation for NAIP flights in 2013. A higher sun elevation is good because it minimizes shadowing due to topography and vegetation. Exactly half of the area is estimated to have a sun angle between 20 and 40 degrees, with 13% below 20 degrees, and 37% greater than 40 degrees. Higher sun angles seem to be concentrated in areas north of Las Vegas and south of Tonopah. The map below shows sun azimuth. The vast majority of flights occurred when the sun was in the southeast, presumably because winds tend to be calm during the mornings.

 

The next steps involve plugging this into some tools that I've developed to topographically correct  brightness for each of the four bands and then perform classification.The caveats that come along with this analysis are as follows: 1) we assume latitude and longitude for the center of each polygon, 2) we average the beginning and end times for each polygon and plug that single time into the sun elevation and azimuth calculation, and 3) we use a 10 meter DEM because a 1 meter DEM is not available for the entire state.