Landsat-8 imagery tools (FREE!)

News Release:
Rapidly Making Colorful Landsat-8 Imagery Composite with Free Advanced Image Stretching
and Pan-sharpening Software from GeoSage
Sydney, Australia – 17 June 2013:
Latest high-quality Landsat-8 satellite imagery freely available from the U.S. Geological Survey (USGS)
provides enormous potential for innovation and applications. There is a great demand for new software
tools that can analyze the imagery in a straightforward way.
Currently, while there are many image processing software tools on the market, very few can quickly
make beautiful, detail-rich imagery composites with adaptive image stretching and advanced image pansharpening.
One may spend hours to produce something that ought to be handy in the first place. For
many GIS users, it is often hard to find right capable tools (i.e. band combination, image stretching and
pan-sharpening) in GIS packages. And for casual users and the general public, dedicated tools to process
the vast Landsat imagery archive are lacking.
GeoSage is pleased to release Spectral Transformer tool sets for Landsat-8 imagery to fill in this gap.
The standalone tools are powerful and easy to use, and perform three steps of analyses:
 Step 1: Simple band combination to make three-band imagery composite
 Step 2: Adaptive linear and non-linear image stretching to make colorful imagery composite
 Step 3: Advanced and fast image pan-sharpening to make spatially sharper and colorful
The tools specifically target Landsat-8 imagery in GeoTIFF format directly downloaded from the USGS
Landsat-8 distribution portals, e.g. GloVis. The processed (stretched and pan-sharpened) imagery at
30m- and 15-mresolution in GeoTIFF format can be readily used in all GIS and mapping platforms (e.g.
ArcGIS, MapInfo and Google Earth)

Landsat-8 captures about 400 scenes per day. The U.S. Geological Survey (USGS)  distributes Landsat-8 data in three very accessible ways:

The USGS Landsat portal also provides comprehensive FAQs in relation to the new Landsat-8 imagery and its comparison with the previous Landsat series. It is important to read these before conducting proper image processing. Landsat-8 products are delivered as 16-bit images with the panchromatic band at 15m resolution and multispectral bands at 30m resolution, and band combinations are unique (e.g. bands 4/3/2 refer to red/green/blue, respectively).

An overview of some common band combinations for better discriminating various ground features is provided here, there.

New analysis tools

While the imagery source is magnificent, more work needs to be progressed on how to use the imagery in a straightforward way.

  • There are many remote sensing and image processing software tools on the market, but it is fair to say that very few can efficiently make beautiful, detail-rich imagery composites with adaptive image histogram stretching and advanced image pan-sharpening. One may spend hours to produce something that is of high quality.
  • For many GIS users, it is often hard to find right capable tools (i.e. band combination, image stretching and image pan-sharpening) in GIS software packages.
  • And for casual users and the general public, dedicated tools to process the vast Landsat imagery archive are lacking.

Spectral Transformer tools for Landsat-8 imagery fill in this gap.

Standalone tool set performs three steps of analyses:

    • Step 1 – Band combination (to make three-band imagery composite)
    • Step 2 – Image histogram stretching (to make colourful composite)
    • Step 3 – Image pan-sharpening (to make spatially sharper and colourful composite)

We believe these tools are very useful for a wide range of users who are interested in analysing the Landsat-8 imagery.

– See more at:

MapQuest Professors Host “Hour of Code” Academy  DENVER — (BUSINESS WIRE) — December 8, 2014

MapQuest, Inc., today launched a weeklong program dedicated to providing Denver Public School students with an “Hour of Code” instruction. Over the course of Computer Science Week (Dec. 8-14), each MapQuest employee in its headquarter office will lead an “Hour of Code” session providing code curriculum, an introduction to real careers that STEM education can lead to, mentoring, a completion certificate and homework to continue the learning. The experience is meant to provide actual tactical knowledge, as well as reduce the barriers to STEM higher education and careers for students everywhere of every age.

MapQuest’s participation in the global “Hour of Code” underscores its belief in investing in STEM education for all and creating more opportunities for girls to choose a STEM field. Science, technology, engineering and mathematics (STEM) studies are essential to day operations at MapQuest affecting every department, every project, and every product and service offered to consumers.

“Hour of Code” is an initiative by CSEdWeek and to introduce computer programming to 10 million students and encourage them to learn programming. Curriculum and instruction tips were provided by and several other accredited organizations, and technologists across the country were encouraged to offer time, instruction and mentoring to students in their communities.

MapQuest and AOL volunteers in Denver, Dulles, San Francisco and New York will be instructing one-hour classes around code that is pre-accredited, engaging and a baseline for future computer science study and development.

“While I’m happy these students will walk away with a general understanding of how code works, I’m happier the kids have a mentor and a friend to help them understand how and why code is cool,” said Brian McMahon, general manager, MapQuest. “Obstacles and intimidation prevent so many from learning the basics of code, and this immersion will help lay the foundation that computer science is fun, interesting and the future of nearly every industry.”

Representatives from the Department of Children’s Affairs, City of Denver; Colorado Technology Association; Denver Public Schools, and University Preparatory charter school students attended a pep rally at MapQuest before kicking off the inaugural hour of code in Denver.

Learning sessions will continue throughout the week with on- and offline lessons taught by the MapQuest Professor teams. Host to numerous student groups throughout the year, MapQuest hopes to create an easy architecture and network of Colorado technology businesses that can support STEM activities within the community going forward.  Full link here.

Watch highlight footage here:

The secret of Google Maps’ accuracy revealed

Greg Miller in  9 Dec 2014 (TOH GISCafe)

The maps we use to navigate have come a long way in a short time. Since the ’90s we’ve gone from glove boxes stuffed with paper maps to floorboards littered with Mapquest printouts to mindlessly obeying Siri or her nameless Google counterpart.

The maps behind those voices are packed with far more data than most people realize. On a recent visit to Mountain View, I got a peek at how the Google Maps team assembles their maps and refines them with a combination of algorithms and meticulous manual labor — an effort they call Ground Truth. The project launched in 2008, but it was mostly kept under wraps until just a couple years ago. It continues to grow, now covering 51 countries, and algorithms are playing a bigger role in extracting information from satellite, aerial, and Street View imagery.
A few of the features that can be extracted algorithmically from Google Street View dataGoogle Maps
Street View, which launched in 2007, was conceived as a way to improve the user experience by letting people see what the area around their destination looked like, says Brian McClendon, Google Maps VP. “But we soon realized that one of the best ways to make maps is to have a photographic record of the streets of the world and refer back to those whenever there’s a correction,” McClendon said.

And as the data collected by Street View grew, the team saw that it was good for more than just spot-checking their data, says Manik Gupta, group product manager for Google Maps. Street View cars have now driven more than 7 million miles, including 99 percent of the public roads in the U.S. “It’s actually allowing us to algorithmically build up new data layers from information we’ve extracted,” Gupta said.
Invisible to ordinary users, information about turn restrictions are built into Google mapsGoogle Maps
Those algorithms borrow methods from computer vision and machine learning to extract features like street numbers painted on curbs, the names of businesses and other points of interest, speed limits and other traffic signs. “Stop signs are trivial, they’re made to stick out,” McClendon said. Turn restrictions — which directions you can turn at a given intersection — are a big deal for navigation, but they’re trickier to capture with algorithms. Sometimes the arrows that tell you which turns are legal are painted on the road, sometimes they’re overhead. They can be different colours and sizes. “Lane markers are harder because they’re not consistent, but we’re getting much smarter about that,” McClendon said.

Street signs are a big deal too. Drivers can follow the app’s verbal directions more easily if what they hear matches what they see. but sometimes the spelling or abbreviation used on street signs varies. “Matching what’s written on the signs is actually a hard and important problem,” McClendon said.

Other algorithms extract building footprints and heights from satellite and aerial imagery. The majority of buildings in the U.S. are now on Google Maps. For landmarks like Seattle’s Space Needle, computer vision techniques extract detailed 3D models (see below). Google has said that its recent acquisition of Skybox, the high-resolution satellite imagery company, at least initially, is to improve the accuracy of its maps.
Google uses computer vision techniques to extract 3D models of landmark buildings from satellite and aerial imageryGoogle Maps
Yet satellites and algorithms only get you so far. Google employs a small army of human operators (they won’t say exactly how many) to manually check and correct the maps using an in-house program called Atlas. Few people outside the company have seen it in use, but one of the most prolific operators on the map team, Nick Volmar, demonstrated the program during my visit. (There’s also a fascinating demo in this video from Google’s 2013 developers conference).  Click here to continue reading.

FAA’s Treatment Of Amazon Proves Congress Must Act Or Companies Will Take Drone Research Abroad

Gregory S. Neal 12/10/2014 @654PM in

Amazon wants the FAA to allow them to fly their drones. The company believes that by 2015, their PrimeAir drones will be ready to deliver products to customers within 30 minutes.
Amazon wants the FAA to allow them to fly their drones. The company believes that by 2015, their PrimeAir drones will be ready to deliver products to customers within 30 minutes. Inc, has begun utilizing outdoor testing facilities outside the United States and has told the FAA that America’s current regulatory environment will force the company to move more research and development abroad unless substantial progress is quickly made on efforts to integrate drones into the national airspace.

Amazon’s statement came in a letter from Paul Misener, Amazon’s Vice President for Global Public Policy.  The letter, which Forbes obtained a copy of, is a stunning example of a company begging for a way to keep jobs in the United States, pitted in a fight with a federal agency that has opposed them at every turn.  Sadly, the lesson one learns from reading the letter is that taking drone research abroad is a smarter business move than fighting with an agency that does not want to accommodate innovation.  Unfortunately, not every company can afford to fight the FAA or take their jobs abroad — that’s why the only way to fix the problems at the FAA is for Congress to act.  Click here to continue reading.

Google throws its weight behind cheap Cardboard virtual reality

How long until we take virtual reality + geospatial beyond Yelp?  – MK


Stacked up against high-cost and high-tech virtual reality headsets such as the Oculus Rift or Sony’s Project Morpheus, Google Cardboard — the company’s low-cost VR viewer, made out of actual cardboard — sounds a bit like a joke. But today Google has shownthat it’s serious about Cardboard, launching a new page that collects some of the best apps for download, and releasing new SDKs for Android and Unity so developers can more easily make apps for Android smartphones that work with the DIY headset.

Google’s Cardboard app, also updated today, now highlights Google’s favorite Cardboard-compatible Android apps. These selections include “Volvo Reality,” the Swedish car manufacturer’s attempt to show people the inside of its latest SUVs by strapping a smartphone to their face, and a Paul McCartney concert as seen from the stage. Google hopes to make the creation of these apps easier in the future by releasing new SDKs for developers that the company says simplifies VR-specific issues like lens distortion correction, head tracking, and side-by-side rendering. Cardboard already had a limited Android SDK — the updated version offers more tools — but the Unity SDK is brand new, and could allow developers to create good-looking 3D worlds with relative ease.


The headset, originally developed in the weeks leading up to Google’s I/O conference, is available to buy for around $20, but Google also allows people to build their own versions. The company today published new building specifications for those who want to make their own Cardboard viewers, with guidelines for those cutting shapes with lasers, machines, or blades.

All Cardboards, bought or home-built, still require a compatible Android smartphone to function, and the headset might never allow experiences as impressive as the Oculus Rift — but with Google’s renewed support, and a price of entry that borders on free, it’s a cheap window into interesting new virtual worlds.