A Free Look at the Luxor Hotel in Las Vegas

A while back, I wrote a brief post on FUSION LIDAR viewing software.  In this post, I will use real world data with the FugroViewer, freeware from the Dutch company Fugro.  

I downloaded LIDAR data from EarthExplorer -- focusing on downtown Las Vegas, specifically the pyramidal Luxor Hotel. The hotel's shape is so constraining that it needs specialized elevators, which tilt and shimmy, up to visitors' rooms. Of course, it is noteworthy to mention that LIDAR is also being utilized to search for ancient lost pyramids.

At first glance, the Luxor hotel is hard to pick out.  However, increasing the point display size from the menu helps to highlight its unique shape. Alternatively, I could also have tried turning off some returns or chosen to highlight specific values for different LIDAR attributes. Redder points have higher elevation values.  Click on the screenshots below to magnify them. 

Can you see the Luxor Hotel?

LIDAR points can be converted into TINs to help visualize what we are looking for.  The three panes below show three different views: overhead (left), a cross-section profile (upper right), and 3-D (bottom right).

Left: Overhead view with a view selected with the Profile tool.  Top Right: View from the Profile Tool.  Bottom Right: A 3-D view of the TIN generated from the LIDAR data clearly showing the Luxor Hotel and nearby attractions.

A slightly cleaned up 3-D view of the Luxor Hotel.

Lastly, LIDAR can be used to measure dimensions with great precision and accuracy.  The Luxor Hotel is listed at 107m.  Using the measurement tool, a height of ~ 107m  (104.7m) is calculated.

How tall is the Luxor Hotel?  Here, a quick measurement calculates about 105 meters-close to its actual 107m.

UPDATE on 1/25: I was able to add in imagery in Fugro viewer.  It has to be a single-band georeferenced image.

NEW: LIDAR data with satellite imagery underneath.

Google Street View of the Luxor and surrounding area

See also:
FUSION Viewer
LIDAR Exercises

Be Weather-Ready...The Open-Source Way...

More snow is on the way for the east coast, but it is not the 5 to 6 inches of snow that has me excited!  Weather forecasts and data are probably one of the best examples of an open-source philosophy.  Sure there is privatization, since there is always a new innovation or buck to be made, but the amount of data collection, visualization, and analysis is growing more and more impressive.  Even large companies such was the Weather Channel turn to open source.

Maps play a vital role in communicating location-based weather-related risks.  A lot of web-based weather maps and and apps are out there. I won't dare creating a list, since I will probably miss your favorite. A quick Google search even reveals OpenWeatherMap.org complete with an API.

The National Weather Service (NWS) has several different open web-based mapping options.  Most recently, I stumbled upon their ESRI-based app:NWS Enhanced Data Display.  Since it is a simple, easy-to-use well designed app, it is worth a blog post!  Click on the image below to magnify the screenshot.  It is an improvement over other NWS products and similar maps out on the web, because it is designed with the user(s) in mind.

The NWS Enhanced Data Display - Snow Predictions

First, different types of users--whether concerned with basic hazards, fire, marine, or aviation risks, can be selected.  The choice of user changes the app to focus on what different users need to see (and more importantly what they don't need to see!).  Brillant!

Clicking on individual weather stations, or searching for one, brings up all the needed forecasts and hourly graphs.  Users can also add their own map files and draw polygons to get forecasts for specific regions, which may cross several state boundaries. There are also some basic storm-tracking/analytical functions such as a storm's time of arrival. Lastly, when a user is done, they can even share the map by clicking a "Save/Share" button at the bottom of the screen. A small url is generated and can be shared.

Hour-by-Hour Predictions...

Overall, a simple weather map that is easy to use is one that will be used more!  So, next time you hear your local forecast, don't forget to log-on to the the web to check out the specifics and even share a map with family and friends!

Also check out:
NWS GIS Data Portal
NWS Aware Report

Happy New Year!...What's Ahead This Year...

What can you look forward to from the Open Source GIS Blog--in the year ahead?  Well I hope to get the New Year off to a good start by finishing some R code for cleaning messy address fields. 

Most importantly, I will be featuring more ArcGIS vs. Open Source GIS "showdowns/throw downs"--comparing similar features in paid vs. free and open source GIS software, focusing on spatial analysis and other features.  These are one of my favorite posts to write but usually take the most time to create.  Here, you can check out one past post about kernel density in ArcGIS vs CrimeStat. I cannot guarantee open source GIS will win every time, but the journey will be fun!  In addition, we will be taking a look at download and using Landsat 8 data.  I also plan on posting more book reviews on books about open source GIS and other relevant topics.

Announcement:  If you are interested in Android App Development, check out the Coursera course "Programming Mobile Applications for Android Operating Systems" from the University of Maryland.  I will taking it and hope to see you there!  The course is free.  However, Coursera offers a Verified Certificate for $49--which may be worthwhile for professional development.  The course beings on January 21st, and lasts 8 weeks, so if you are interested get registered now!  Check out the video below!

I started this blog about two years ago...this will be third year!  Each year, I try to post higher quality information so stay tuned.  By the numbers, a few statistics:

• The blog has had a modest 5,700 page views since its first creation in February 2012. 
• Viewers have come from many different countries. 
• The most frequent users hail from my home county of the US, Latvia (real or bots/spam?), Germany, UK, Russia, France, Canada, Australia, China, and India.  However, many different countries have viewers including: Brazil, Portugal, and South Korea, and the list goes on! 
• There have been 56 posts - each with an important piece of information, software, analysis, web map, or links to great resources.
• By browser: 35% of page views have been in Firefox, 27% from Chrome Browsers, 23% from Internet Explorer, and the remainder from other mobile browsers.
• By operating system, most users are using Windows (74%), Mac (8%)--with reminder from Linux and mobile OS.

If there is something you would like to see on the blog, feel free to write in the comments below.  Again, happy new year!

Book Review: Learning QGIS 2.0

The best place to discover QGIS is "Learning QGIS 2.0" by Anita Graser for its brevity and attention to detail.  Making great maps using QGIS, a free and open source desktop GIS, is only a few steps away using this book.  Released in September 2013, it is the most up-to-date reference on how to get the results you want using QGIS.  I finally had a chance to read the e-book in its entirety and here is what I think.

The book was written for a range of audiences--including newcomers and more seasoned veterans.  It covers basic and advanced topics from installing QGIS, whether a user or developer and  Ubuntu/Linux or Windows, to adding and editing map data.  In addition, the book contains color screenshots to illustrate what actions are being performed.

The book proceeds logically and words are used efficiently. It helps users add different types of GIS-related data, understand how QGIS treats projections, and highlights vital mapmaking tasks such as symbolizing and labeling.   It also covers QGIS' plugins, notably the Open Street Map plugin for using common basemaps and the Heatmap plugin for density analysis.

Later topics include using the Map Composer (analogous to Layout View in ArcGIS) and the Graphical modeler (Model Builder in ArcGIS). 

Two potential criticisms of open source software are that they tend be harder to use than their paid counterparts.  In addition, some programs lack easy-to-read and authoritative documentation.  With "Learning QGIS 2.0", these barriers no longer exist.   The timing of the book could not be more perfect with the release of QGIS 2.0 Dufour.

When you finish the book, be sure to visit Anita Graser's blog at: http://anitagraser.com/.  It is a real treat!  There you can gain even more advanced knowledge.

To purchase Learning QGIS 2.0 visit Packt Publishing or Amazon.com and Kindle.  The book is available both in e-book formats and physical paper copies/softcover.  E-book formats run about $12.  You can also get a physical copy of the book and all e-book formats for ~$25 on the publisher's site.  Released Sept 2013, 110 pages.

Available from Packt Publishing and Amazon/Amazon Kindle

Fighting the MOOCDEMIC with Open Source GIS

The MOOCDEMIC, billed as the world's first online epidemic, is an web-based app that simulates infectious disease dynamics--part of a Coursera course.  Coursera courses are free massive open online courses. 

Moreover, the app is also GIS based and anyone can participate.  Participants "scan" for infection from their present position with a mobile device.  How cases are being seeded or created has not yet made been clear to participants.  So, stay tuned... The course creators also created a game called "Vax" showing differences between vaccination strategies.

The epidemic is about half-way over, at least in terms of course time, and here are a few physical and online maps that I have produced using QGIS and CartoDB. The course instructors have released a basic *.text file of date/times and coordinates for crowd sourced analysis.  CartoDB allows for beautiful maps to be created quickly, has CartoCSS elements, but does not require the expertise and time as other packages such as MapBox/TileMill.

What I chose and why:  I chose to use QGIS as my desktop GIS platform.  In addition, I chose Natural Earth for my base layers.  Using both, I knew that any of my tens of thousands classmates could duplicate my work for no cost.  Furthermore, they maintain accuracy worldwide but keep details to a minimum, so I could work with them quickly.  I did not need to be bogged down with huge layers or downloads. 

The physical maps are below and a link to one interactive map with cases can be found here:  http://cdb.io/17C1sKA.  Click on the maps below to enlarge them.



Week 1 Map: Early in the epidemic...

 

Hong Kong: Generated/fake "cases" appear to be located in
 the water through error or perhaps how they are being generated.

 

 

Quantum GIS 2.0 Dufour Released

This entry is out-of-date.  Please read: http://opensourcegisblog.blogspot.com/2014/07/qgis-24-chugiak-released.html

Quantum GIS or QGIS 2.0 has been released!  Be sure to check it out on the newly redesigned QGIS website: http://www.qgis.org/en/site/.

New Sleek Looking QGIS Website

The user interface has undergone some improvements aesthetically and functionally.  Several of the plugins appear to be working better--including the heat map add-on--for getting your spatial analysis started. The user can even choose the type of kernel function.  Symbolizing layers also has improved and appears to be easier.

A Heat/Density Map of Healthy Food Stores in Philadelphia

 For a full list of the new features, go here: http://www.qgis.org/en/docs/user_manual/preamble/whats_new.html

If you have not used QGIS before, be sure to check out the user's section: http://www.qgis.org/en/site/forusers/index.html

Lastly a new e-book and book in print has been published by a top QGIS blogger.  Be sure to check it out, even if you have some experience using QGIS before! http://www.packtpub.com/learning-qgis-2-0-to-create-maps-and-perform-geoprocessing-tasks/book

Trivia: Previous releases of QGIS have been named after places.  However, this release is named after a famous cartographer: http://en.wikipedia.org/wiki/Guillaume-Henri_Dufour

Open data combined with open source GIS is an extremely powerful and versatile platform!

Cleaning Address Fields with R String Functions

I have been surprised by the lack of solutions for cleaning addresses in the open source world. So, I decided to look into R Statistical Program.  Whether in R or other statistical programs, both have string/character functions that allow for splitting fields.  The stringr R package is also very helpful.

Dirty address fields can be a symptom of problems with data collection (lack of defined fields, standardization, minor errors) or something simple--like  typographical errors -- which can be compounded over time. 

These mistakes can affect matching of addresses to reference datasets and ultimately any analysis that is performed. If addresses are so poorly collected, no analysis may actually be able to be done or simply have results that are two unreliable to interpret.

Before geocoding addresses, it is best to get the data as "clean" as possible.  If you have a database setup properly with data being entered by automation or by hand, validation rules, or warning messages about potential conflicts, then you should be in relatively good shape. 

Hopefully, in the coming weeks, I will have some sample data and R code posted illustrating common problems and solutions.