Canyon Wildfire Assessment at Vandenberg Air Force Base

I worked on this project recently with Haoyu Li at Clark University. Vandenberg Air Force Base had a quick burning fire pass by one of its rocket launch pads this past September. The fire started by an unknown source in the hills behind the launchpad and at its peak had over 1,000 fire fighters working to contain the fire. We used Landsat 8 for Pre and Post fire imagery, classification, and for NBR. We created training sites and used Maximum Likelihood Classification.

Pre Fire: Oct 1, 2015 Landsat 8

Post Fire: Oct. 3, 2016 Landsat 8

Pre Fire Maximum Likelihood Classification

Post Fire Maximum Likelihood Classification

Normalized Burn Ratio or NBR
Landsat 8 uses bands 5 and 7

Shows burn severity and change 

Source: Landsat 8

             Landscape Toolbox: Normalized Burn Ratio

Lake Shasta Water Levels Rising

The drought in California has been drying up reservoirs across the state over the last few years. This year was predicted to have a large El Nino effect this winter and spring, but it has not produced as much as hoped. Until earlier this month it had been a typical, almost average winter with snow levels averaging around 90% across the state of California. Over the last few weeks several rain and snow storms have passed through Northern California helping Lake Shasta rise to 86% capacity with over 1.8 million acre-feet of water pouring in since the middle of January. El Nino has been very kind to Northern California as of late and we hope it will continue! Check out the slider below to see the difference between water levels at Lake Shasta from last August and its current condition.

Sources: California Dept of Water Resources Data Exchange Center
Imagery: Landsat 8 via Google Earth Engine

European Space Agency showing Salt Lake City some remote sensing love

As a local to the Wasatch Front I spend a lot of time sailing, birding, and floating on the Great Salt Lake. As a Remote Sensing Specialist I also regularly use Sentinel imagery to study our earth. Sentinel is the ESA equivalent to Landsat. I am currently working on a project that highlights the health hazards of an expanding dry lake bed from the potential dust storms. As the lake gets lower the more dry lake bed is exposed and more dust is kicked up into the air. It is to the benefit of the people of the Wasatch Front to keep that lake wet. I love this video because it highlights just a few of my favorite things. Check it out for some info on the features and history of the Great Salt Lake, the Salt Lake Valley, as well as showing off Sentinel's impressive imagery.

If you are interested in learning more about the Great Salt Lake, here is a whitepaper published by Utah State University last week about the challenges posed by diverting flow to the GSL and the hazards associated with lower Great Salt Lake.

And if that isn't enough and you want to learn even more about the GSL, let me know, I have enough research to keep you busy for days.

Lake Superior Ice Jam

I was listening to a report on NPR yesterday about ice jamming up a shipping route on Lake Superior. Every year when ice forms on the lake, icebreakers are needed to create shipping lanes for the passing container ships. The lanes around Whitefish Bay (in focus below with a 6-5-4 false color composite) have become completely covered due to drifting ice from earlier storms that compacted all the ice on the eastern part of Lake Superior. Some of the ice was reported to be eight feet thick as pieces piled on top of one another forming bigger chunks.  

The shipping lanes are being navigated through and cleared by a team of US and Canadian vessels. In this image you can faintly see the shipping lane which runs about 37 miles through Whitefish Bay alone.

Source: NPR, USGS, Google Earth Engine

Louisiana can't find their boot

Terra MODIS true color imagery 2/15/15

Google Earth Imagery 4/9/13

Landsat 8 true color imagery mult images stitched from throughout Feb

USGS 2011 National Land Cover Database data, showing how much wetland is left in Louisiana.

Louisiana doesn't look like the maps I memorized growing up anymore. Loss of wetlands has caused a dramatic change in the coastline. Imagery from Landsat 8, Terra, and especially the USGS dataset show the true story, but it is interesting to me that even Google Earth shades the imagery to show an image that we are used to seeing. Aerial imagery such as this can be a powerful tool to show what the situation is really like. 

There are a lot of reasons the wetlands are receding, chemicals that are dumped in the Mississippi River have caused problems in the area, as well as poor land management. Loss of wetlands allows for stronger hurricanes to hit the mainland, not to mention the loss of habitat to hundreds of animals

Here is an article that outlines the whole story - 
https://medium.com/matter/louisiana-loses-its-boot-b55b3bd52d1e

Wasatch Front Temperature

Summer of 2013 was one of the hottest on record for Utah. Normally the locals escape to the canyons for relief, since it is usually 20 degrees cooler than the valleys. But 20 degrees cooler than 107 is still very hot. Nighttime lows only got to about 75.  In an area that is not used to such extreme heat, it was difficult for many to cope. 

Images above show The Wasatch Front and Great Salt Lake on July 22, 2013. First image is a true color, second shows night land surface temperature represented by a color ramp and the third is daytime temperature. 

The bodies of water heat up and cool down slower than land, so during the day the water is cooler than it's surroundings and during the night it is warmer. 

You can also notice that the mountains are much cooler than the low valleys, still warm by Wasatch Front standards, but it beats sitting in triple digit heat all day. 

My new Google Earth Pro

East Canyon Reservoir  8/11/11

East Canyon Reservoir 10/7/2014

Here is a comparison over the years of a reservoir in the Wasatch Mountains using Google Earth Pro. Google just offered their high end Google Earth Pro license free for anyone. Which means you get to use their imagery for whatever purpose you want, which in this case, is for my high end blog that is viewed by millions every day. Thanks Google!

Utah, like most of the Western US has had a hard time with a water shortage. Our dismal snowpack this year shows us that things aren't going to get better any time soon. These two images, taken at roughly the same time of year 3 years apart show the change in water level, and it doesn't look good. I measured the surface area of the water by hand using Google Earth Pro and in 2011 the surface area measured 1.04 square miles, 2014? .58 square miles, almost half. I measured it by hand, not using any fancy classification, so it's not 100% accurate, but that's still not a good sign.

The Many Band Combinations of Landsat 8

SOURCE: EXELIS BLOG

Landsat 8 is the most recent satellite in the Landsat program. The data quality (signal-to-noise ratio) and radiometric quantization (12-bits) of the Landsat 8 Operational Land Imager (OLI) and Thermal Infrared Sensor (TIRS) are higher than previous Landsat instruments (8-bit for TM and ETM+). Since it's launch on February 11, 2013, Landsat 8 has been providing some truly stunning images of the earth's surface. Beyond their beauty, these images are packed with information which can be manipulated to extract features and discern changes to the earth's surface over time.

When working with Landsat imagery, a logical first step is to load an image into an image analysis program and begin to visualize what is in the scene. The OLI sensor aboard Landsat 8 has nine bands for capturing the spectral response of the earth's surface at discrete wavelengths along the electromagnetic spectrum. Additionally, the TIRS sensor aboard Landsat 8 collects information at two discrete wavelengths within the thermal infrared portion of the electromagnetic spectrum. These wavelengths have been chosen carefully based on years of scientific research.

Standard digital cameras are designed to replicate what we see with the human eye, so they capture light only in the red, green and blue wavelengths and then apply red, green and blue filters (also known as channels) to these wavelengths, respectively, that when combined generate a natural looking RGB image. With a multispectral image from a sensor system such as Landsat 8, we have a lot more information to work with. Different wavelengths can often help us discern some features better than others or even help us "see through" features such as clouds or smoke. For example, the Near Infrared (NIR) wavelength is one of the most commonly used wavelengths on multispectral sensors because vegetation reflects so strongly in this portion of the electromagnetic spectrum that this information proves very useful when performing vegetation analyses. The Shortwave Infrared (SWIR) bands aboard Landsat 8 are very useful for discerning differences in bare earth and for telling what is wet and what is dry in a scene. There are many other examples of the advantages of the available bands in Landsat images, but what I would like to do here is simply show how loading different combinations of these bands into the red, green and blue channels makes different features stand out. I am not the first to do this, but I just thought I would add an additional resource to the world wide web for showing how these band combinations can be used to visualize Landsat 8 images.

4 , 3 , 2 - Natural Color Image, Fresno, California

This band combination is as close to "true color" as you can get with a Landsat OLI image. One unfortunate drawback with this band combination is that these bands tend to be susceptible to atmospheric interference, so they sometimes appear hazy.

5, 4, 3 - Traditional Color Infrared (CIR) Image, Colorado/Utah

Note how vegetation really pops in red, with healthier vegetation being more vibrant. It's also easier to tell different types of vegetation apart than it is with a natural color image. This is a very commonly used band combination in remote sensing when looking at vegetation, crops and wetlands.

7, 6, 4 - False Color useful for visualizing urban environments, Los Angeles, California

Because this band combination makes use of both of the SWIR bands aboard Landsat 8, the image is much more crisp than band combinations that make use of bands in shorter wavelengths, which are more susceptible to haze.

5, 6, 4 - False Color good for picking out land from water, Hudson Bay, Canada

In this false color image, land appears in shades of orange and green, ice stands out as a vibrant magenta color, and water appears in shades of blue.

7, 5, 3 - False color image with good atmospheric penetration, Washington/Oregon

This band combination is similar to the 5, 6, 4 band combination shown above, but vegetation shows up in more vibrant shades of green. This band combination was used for the global Landsat mosaic created by NASA.

6, 5, 2 - False color for agriculture, Fruita, Colorado

This band combination is useful for the monitoring of agricultural crops, which appear as a vibrant green. Bare earth appears as a magenta color and non-crop vegetation appears as more subdued shades of green.

7, 5, 2 - False color often used for visualizing forest fire burn scars, Rim Fire, California

This band combination is similar to the 6, 5, 2 band combination shown above, but by pushing further into the SWIR range of the electromagnetic spectrum, there is less susceptibility to smoke and haze generated by a burning fire.

6, 3, 2 - False color for distinguishing differences in bare earth, Canyonlands NP, Utah

This band combination is good for discerning variations in a landscape that does not contain an abundance of vegetation. It is good for geologic applications.

5, 7, 1 - False color for vegetation and water, Lake Victoria, Tanzania

This band combination makes use of the NIR, SWIR2, and Coastal Aerosol bands, respectively. The Coastal Aerosol band is unique to Landsat 8 and is used primarily to track fine particles like dust and smoke, and also to peer into shallow water. With this color combination, vegetation appears orange.

There are certainly several additional band combinations that would be useful for visualizing Landsat 8 scenes. In some situations, loading a grayscale image of a single band might also help to visualize specific features or phenomena. For example, in the grayscale image below, we are viewing the Thermal Infrared 1 band from the Landsat 8 TIRS sensor. This image, captured over Iceland, shows the Bardarbunga volcano in bright white in the top center of the image. Since we are using a thermal infrared band, this feature sticks out significantly from the ice sheet located just to the south of the lava flow.

With grayscale images, we also have the option of applying a color table to highlight features a little more clearly. In the image below we are viewing the same grayscale image of the Bardarbunga volcano, but now we have applied a color table that shows very cold extremes of the glacier in shades of deeper blue and very warm extremes of the lava flow in shades of deeper red.

There are many analysis techniques that can be applied to multispectral imagery to extract specific features of interest. These algorithms rely on the same principles of reflectivity and absorption at various wavelengths that allow us to see certain features when visualizing them with different band combinations. An important point to note is that if a particular band, or combination of bands, does a good job of helping you visualize a feature that is of interest to you, then it is highly likely that this band, or combination of bands, can be used to help you isolate that feature from your image. For more on this topic, please check out the section of our Documentation Center devoted to Spectral Indices.

East Coast Snow Line

Aqua Satellite 1-10-15 Resolution ~1km

E Coast USA snow line

East coast of USA 01-10-15 Aqua satellite

A large snowstorm hit most of eastern US on Jan 6-7, 2015. An interesting aftermath of the storm is a clear line where the snow coverage stops, almost along the latitudes. The snow does a good job of highlighting ridges in the Appalachian Mountains.

Sand Blasted Paradise

Sand Blasted Canary Islands 01/10/2015 MODIS

Sand from the Sahara is sometimes blown all across the Atlantic in wind storms.  Such storms and the rising warm and humid air can lift dust 5,000 meters or so above the Atlantic, blanketing hundreds of thousands of square miles of the eastern Atlantic Ocean with a dense cloud of Saharan sand, many times reaching as far as the Caribbean

This hot, oppressing dust and sand-laden wind is called the Calima by meteorologists and locals on the Canary Islands. It is particularly prevalent in winter. The Calima blows out of a high-pressure system over the Sahara and is drawn northwards ahead of a passing cold-front or depression north of the archipelago. It's fine yellowish-brown dust creeps through doors and windows. Outside visibility is often reduced to null.

This unnormal hot and humid Calima is a difficult part of life. The Canary people suffer from respiratory problems. On January 8, 2002, the international airport of Santa Cruz had to be closed because visibility dropped to less than 50 meters.

Crying: Acceptable at funerals and the Grand Canyon

Landsat 8 True color composite mosaic created from imagery dated 9-30-14 & 11-25-2014
Grand Canyon, AZ

Over 5 millions people go to sight-see the Grand Canyon every year. The Grand Canyon is 277 miles long, up to 18 miles wide, and is over 6,000 feet deep. It is estimated that over 2 billion years of earth's geologic history is exposed from the erosion caused by the Colorado River. The Colorado River started flowing through this area about 17 million years ago. The Grand Canyon is an easy landmark in case you are ever in orbit around the earth with no reference. You can only hope you'll be found in that situation one day. 

The Kaibab Plateau is the stretch of green that borders the canyon to the North. There are several species that are endemic to the plateau. 

Mosaic of Landsat 8 Imagery 11-15-2014 and USGS National Elevation Dataset 1/3 arc-second
Dark and light orange correspond with low and high elevation respectively
Same extent as imagery shown above

East Michigan Ice

Landsat 8 false color composite - East coast of Lake Michigan April 7, 2014
Spring Lake to the north and South Haven to the south.
Ice coverage shown as cyan. Vegetation shown as green.
Resolution ~30m

 This last winter was not your average season. The west experienced warmer than average temperatures and little precipitation while the east was stuck dealing with an 'arctic blast'. This caused frigid temperatures for most of the winter months and probably helped jetBlue post profits as they ferried everyone down to Florida and the Caribbean to enjoy some sun.

As a result of the high precipitation and low temperatures Lake Michigan had the highest ice coverage on record since 1973. The precipitation brought much needed relief to the area and I'm sure marina owners and shipping managers won't mind the higher lake levels.

Aqua false color composite - East coast of Lake Michigan April 8, 2014
Wabaningo to the north and Bridgman to the south.
  Ice coverage shown as cyan. Vegetation shown as green.
Resolution ~ 250m