Image of the Day September 26th, 2017

Both images show the extent of smoke caused by the forest fires on the West Coast. The top image was sourced from http://www.newsweek.com/wildfires-oregon-california-montana-smoke-jet-stream-660635  and the second, closer up image is from https://www.nasa.gov/image-feature/goddard/fires-and-smoke-in-washington-oregon-and-california.

The images were obtained on September 26th.

Image of the Day, Sept 27, 2017

The image was taken from the International Space Station on August 11, 2011 and shows Owens Lake in the southern part of Owens Valley, CA.  The mountain range at the bottom of the photo is the Sierra Nevada (Mt. Whitney is located out of frame to the lower left) and the range at the top is the Inyo Mountains. Owens River feeds the lake from the left. The image is oriented with north on the left side of the frame.  This is a true color image, and the red areas are actually where halophilic (salt loving) bacteria (and water) are found.  Most of the water sources for Owens Lake were diverted to Los Angeles in the early 20th Century (inspiration for the movie Chinatown), exposing the alkaline substrate and causing serious air pollution issues for the valley.  The upper areas showing as regular polygons were created to manage the dust by wetting the dry surface or planting vegetation.

https://earthobservatory.nasa.gov/IOTD/view.php?id=52072

Impacts of Hurricane Irma on Barbuda, September 2017

Images of Barbuda captured by Landsat 8 OLI on August 25, 2017 (top) and September 10, 2017 (bottom) showing the loss of vegetation after the storm passed.

For more information and images, go to:

https://earthobservatory.nasa.gov/IOTD/view.php?id=90952

Al Hawizeh Marsh, 1973-2000

 






























Take a closer look at today's image of the day, located in Iraq and Iran. 

If you'd like to find this spot in Google Earth, try the following (and zoom out quite a ways):
31°01'35.93" N  47°24'54.76" E

Interpretation question: 

What is the olive-brown area that appears in the 2000 image (bottom)?  What factors on the ground lead to this color? 

Image of the Day

The image is a drone image of the 6^th Street of Bogota, Colombia. The image is an oblique image, which allows us to see the mountainous terrain in the distance of the image. The color of the houses are mostly browns and are very densely packed. The colors of the homes give stark contrast to the open spaces of the park of the right side of the image and the vast avenues shown. The image also shows the development and growth of the city looking at the typical housing types that are closer to the avenue and comparing that to the high rise apartments seen further back in the image. The pattern of the housing types give way to the notable difference of the apartment buildings being the old ones out. It is also interesting to note the bright colors of the buses and taxis that stand out in this landscape. 

http://www.dronestagr.am/6th-street-bogota/

Image of the Day

This aerial photograph depicts a UNESCO world heritage site in the Yunnan, or southwest China. This shows the rice terraces filled with water late in the day causing the sunset colors to glisten off the still water. There is also evidence of greenhouses, showing a shift in growing techniques as the economy in China changes rapidly. Scale to the image is shown with the trees, proving how large these terraces are as well. Image was found here: https://www.picturecorrect.com/news/photo-sunset-over-rice-terraces/

Remote Sensing for the Future

This image was taken by a NASA satellite and covers glaciers in Bhutan's Himalayan Mountains.  It captures the ends (termini) of several glaciers in the range.  The image displays glacial flow pattern and direction.  You'll also notice lakes, which are relatively new, filled by melt water from the glaciers.  The imagery is important because it captures a process that can be used to measure and study climate change.  It shows the importance of understanding remotely sensed data and applying it to preparation for future planning.  In this application, studying the evolution of these glaciers is key to planning for water availability in Bhutan's communities that have historically been dependent on these glaciers. 

Sensing household income differences in Nairobi, Kenya (2016)

This 2016 image depicts a border between a wealthy neighborhood and a poor one in Nairobi, Kenya. Because it can be challenging to gather regular census data about household income in some areas of developing countries, a group of social scientists, economists, and computer scientists at Stanford University is analyzing daytime images like the one above to collect spatio-temporal data about poverty conditions. Using indicators such house size, road conditions, distance to water sources, markets, or agricultural fields, analyzing such images could support decisions about where and how to provide aide opportunities.

Hurricane Harvey post-disaster assessment

See additional images and media coverage at the Washington Post website:

https://www.washingtonpost.com/graphics/2017/national/harvey-photos-before-after/?utm_term=.fb39a3d4d22e