Broadband Access

I currently connect to the Internet with a wireless carrier.  I get around one megabit down and 128 k up, not the best but much better than dial-up.  I have been trying to convince Time Warner that my area needs to have cable, however they informed me that there neds to be at least 15 houses per mile for them to consider laying cable in the area.  Using www.cablemover.comI mapped out the houses in my area that have cable and those that do not as well as how many homes are on each mile increment of road.  There seems to be a few exceptions to the 15 buildings per mile.  Unfortunately, Time Warner is not going to be running cable in my area anytime soon.

Endangered Runaways

On Sunday night I watched a few news stories on MSNBC concerning sexual slavery and prostitution, including “Sex Slaves in the Suburbs.”  The premise of this show was that young females are being kidnapped and forced into prostitution against their will.  Additionally, law enforcement treats the kidnappings as runaways.  The show was quite moving with a particularly emotional testimony by a young female.

I was curious how prevalent cases of runaways were in the United States.  I went to the National Center for Missing & Exploited Children (NCMEC) website and performed a search for all “Endangered Runaways” in the US that occurred between 1/1/2008 and 2/9/2009.  I found 621 individuals, both male and female.  The Department of Justice (DOJ) defines an endangered runaway as a runaway that has certain “factors such as substance dependency, use of hard drugs, sexual or physical abuse, presence in a place where criminal activity was occurring, or extremely young age (13 years old or younger).”

Endangered Runaways 01/01/2008 - 02/09/2009

One of the only studies I found concerning runaways was the DOJ study, Runaway/Thrownaway Children: National Estimates and Characteristics.  According to the report there were quite a few more endangered runaways back in 1999 that my findings at NCMEC’s website seem suspect.  The report states that there is “suggestive evidence” that the incidences of runaways have  declined in recent years.  But it seems my findings are quite low compared to the number of expected endangered runaways based on the report.  I am not sure the discrepancy, however it is probable that some of the endangered children in the DOJ report were recovered but still reported which is in contrast to the NCMEC which only lists currently missing endangered runaways.  Also there is the possibility that  the NCMEC and various state agencies have not identified the children as endangered, simply runaways.

GeoCommons

I have been tinkering with GeoCommons Finder and Maker of late.  Finder is a data repository where users upload spatial data (either csv, shapefile or kml) and others can easily view and download the same data.  If a user desires to map the data they can use Maker to create single variate or multivariate maps.

In the past when I have wanted to visualize data on the fly I either had to load up my GIS and create a base map, import the data and then make it pretty.  This process (especially if a base map was not present) could take quite a bit of time.  Google Maps was available to map small datasets.  If I took the time I could create a mashup and put it on a hosted site.  However, this can take a little bit of time, especially when I did not had a website to use for hosting.

Geocommons allows neophyte and experienced users a location to find data, or upload data and then quickly create a pleasing cartographic map.  Of course if the data is not available you will have to create or find the data.  Once found the data will probably need to be cleaned; it seems most datasets need a little cleaning.  Obviously if you are upload a shapefile or KML the data has spatial element, however if you are uploading a csv file (such as a list of businesses) you will have to geocode the list to obtain the latitude and longitude of each location.  Finder has some great tutorials on their site that show users how to use services such as Batch Geocoder to find the geographic locations of your data.

For my project I uploaded and mapped out the US Government’s fiscal year 2009 per diem rates.  The per diem rates show how much the government will pay its employees for lodging and meals while they are traveling the country on business.  For those locations that do not have any data the rate is $70 for lodging and $39 for meals and incidental, per day.

ArcGIS Flash Tutorials

Recently a friend asked me how to move a dataset from one feature to another in ArcGIS. I threw together the following tutorials utilizng Wink which is a tutorial and presentation software that creates flash shows. The files are relatively small and they can be put together without too much hassle.

How to Trace features in ArcGIS

Copy and Paste data into a dataset

Load data into a dataset from ArcCatalog

QGIS 1.0.0

On the 10thof this month QGIS 1.0.0 was released, this is very exciting. I first started using QGIS a couple years ago.  However, since I had access to the ArcGIS suite of programs I rarely used QGIS.  Mostly for those times where I needed a portable GIS to visulize shapefiles on a computer that did not have a GIS already installed.

Recently I have had to rely on QGIS and GvSIG as my sole GIS platforms, for various reasons.  While QGIS is not perfect, it is steadilygetting better with each subsequentrelease.  I was planning on sharing my thoughts about version 0.9 but now that 1.0 has been released I think I will go over how this new version compares with previous versions. 

For more information on the current release, the QGIS’ blog  is an excellent resource as is the newly updated manual.

Portable GIS

What do you do when you need a GIS but for whatever reason you do not have access to a commercial GIS and you cannot install software on your computer? Use a portable application. Though there may be more portable GISs’ than I mention here, these are the ones I am familiar with.

QGIS is a cross platform GIS that currently runs on Windows, various flavors of Linux and the Mac. The program is small enough to fit on most USB drives, for a GIS on the go. This GIS allows users to create, view and edit many of the popular spatial file formats to include shp, PostGIS and Grass files. While it is no ArcGIS it does allow a user to perform most common spatial analysis such as buffer, difference, dissolve, union along with other basic functions. QGIS is open source and if one knows what they are doing they can modify the core program, create plugins and become a contributing member of the QGIS community.

SpatialLite while not a traditional GIS complete with a GUI, it is a SQLite (DBMS) extension that supports spatial data. I have very little experience with Spatialite, but from working through the tutorial it has the ability to import and export shp files, and perform basic spatial analysis. However, Spatialite is primarily a command driven program that is executed from the shell. The results can be exported to a shp file and viewed after the fact, but for instant results all you get is text. There seems to be some real potential here based on my limited exposure.

I wish there was more selection and more functionality than these aforementioned programs. However, they are free and they allow me to use a GIS where I otherwise would not be able to. Until the big commercial GIS vendors are willing to create a portable application (and cheaper) I have to use these types of applications.

How to feel connected to the GIS “World”

Your level of everyday work in the GIS industry can help you feel connected to the rest of the spatial community. Obviously some jobs are much better at this than others. Attending conferences, training and interacting with others in your field can help this feeling. But who cares and why should they care? In my opinion everybody in the industry should care to some extent.

I receive quite a few new ideas on how I can do my job better by exposing myself to others; a new perspective can help. Associations such as The Urban and Regional Information Systems Association (URISA) can also help you interact with others in your field. Interacting with the industry has a positive effect on my level of excitement for things spatial; I am invigorated.

For myself, I find conferences and off-site training the most invigorating. However, both of these options can become quite expensive and as a consequence I do not utilize them often. Blog RSS feeds help bridge the gap, such as Planet Geospatial. Through my school I can go through online ESRI training. However, the best low cost method I have found is the A Very Spatial podcast.

During my last couple cross country trips I have loaded twenty plus hours into my car and listened to the show for hours at a stretch. This constant information stream bored my wife and kids to tears but invigorated my dedication to things spatial and helped me feel like I was a part of something bigger than myself.

Where have I been?

Well it has been a while since I last posted and honestly I am filled with wonder that people still are looking at this blog.  It has been a few months since I last posted.  Anyway, in the last couple of months I have relocated my family 2600 miles and then driven another 2600 for a temporary job.  Not much time has been devoted to anything else; including GIS.

However, school is starting in a few weeks so hopefully I will once again begin thinking in GIS and get back to this blog.

Viewsheds Compared

By comparing line of sight DEM based viewsheds with a manual viewshed the different amount of error associated with different types of DEMs becomes evident.  I compared a manual viewshed against a 30 meter DEM from the Shuttle Radar Topography Mission (SRTM), a 30 meter DEM from the National Elevation Dataset (NED), 10 meter DEM from the NED and 3 meter DSM created from a .7 meter lidar cloud.  The same location and elevation was used in all the different viewsheds, the manual viewshed was both created using Google Streetview and I physically went to the location to verify the viewshed.  

To create the viewsheds I used Military Analyst for ArcGIS, this allowed the resulting viewshed to be limited by a range and the output was in vector format instead of raster format.  In order to calculate differences between the viewsheds the vector data was converted to a raster format using the same cell size and clipped to the same area to make sure each viewshed had the same number of pixels.

To quantify these findings I compared the difference between the pixels in the manual viewshed and the DEM viewshed.  I counted the differences where the manual viewshed’s pixel was visible and the dem viewshed was non-visible (V/NV), this was repeated for for visible/visible (V/V), non-visible/non-visible (NV/NV), and non-visible/visible (NV/V).  This method was used to compare the total number of pixels between viewsheds and total percentage of similar pixels.

These findings are far from complete but a step towards understanding the strengths and weaknesses in viewshed creation.  Further work would be to accurately account for the manual viewshed not taking tops of trees and buildings into consideration and to clean up the lidar DSM model by removing non-view obstructing artifacts such as power lines that show up as fence like objects.

Google Street View Viewshed Validation

I validated the Google Street View based viewshed and found the viewsheds were correct to about 350-425 meters. After that point the images in Google Street View became too pixilated to reliably view the location where the image terminated. In the left image, the area in red highlights the area I could not see in the Goolgle Images but could when in person.

In the example to the right I could see to about 425 meters to the north and the south, beyond that point it became too blurry in the images. When I went to the location, the terrain was very flat and I was able to see approximately 2,000 meters to the south and make out the highway underpass and overpass with the aid of ten power binoculars. Looking to the north the image probably extended at least 2,000 meters but became too hazy to tell where the view terminated.

It should be noted that the distance limitation attributed to the Google Street View images may be too conservative but it was furthest I felt comfortable extending the viewshed based on the pixilation and discernable features in the imagery. Also for the purpose of these viewsheds I am most concerned about being able to discern person or vehicle sized objects on the ground, so I ignore if I can see the tops of trees or buildings.