Archive for the ‘remote sensing’ Category

Rural Internet in Caribou ME

February 3, 2012 Leave a comment

Been a while eh?  A while back (June of 2011) I mapped out who could get Time Warner service in Caribou ME and who couldn’t.  I used the 2010 NAIP imagery to digitize all the homes in Caribou.  The homes in the rural areas I verified that they appeared to be used as well as the location where the cable seemed to terminate on the telephone lines.  Furthermore those homes/buildings that were set further back than 300 feet were also excluded since according to Time Warner this is too far to install cable for free.  These findings were compared with the results from to make sure I wasn’t excluding or adding any homes that did/did not have cable.  Based on this methodology Caribou had 3200 building of which 320 did not have access to cable.

By measuring where the cable stopped and which buildings did not have cable I estimated that for the whole city to be serviced an additional 218,726 feet, or 41.43 miles of cable would need to be laid.  At a cost of $20,000 per mile this would equate into a cost of $828,600 for Time Warner.


Viewsheds Compared

September 27, 2008 2 comments

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.

Manual Viewshed

August 8, 2008 Leave a comment

Most viewsheds utilize digital terrain models (DTM) as the basis for what can and cannot be seen from any one location.  DTMs are usually synonymous with a digital elevation model (DEM) and show the bare earth of an area.  I have heard these viewsheds be described as “showing the best possible circumstances.” However, because the DTM does not take into account vegetation or man made structures the results can lead viewers to believe more is visible than reality.

If possible a digital surface model (DSM) should be used, which shows elevations on the top surfaces of buildings, vegetation, man made structures and any other object elevated above the bare earth. However, DSMs are usually collected with specialized equipment such as light ranging and detection (lidar) systems or interferometric synthetic aperture radar (IFSAR) systems.

If these options are not available to a user, manual viewsheds can be created by either going out to the field or by examining panoramic photos to see what is visible. This information is then saved to a GIS for later use. The purpose of the manual viewshed is to find the best locations to place potential sensors, collect the capabilities of existing sensors, verify the quality of viewsheds created otherwise and/or to validate conceptual models.

By using Google Street View I was able to create a manual viewshed. While viewing the panoramic view I switched back and forth between Google Earth and ArcGIS which utilized the 2008 NAIP imagery as a baselayer to assist in the digitization of the viewshed. Because Google Earth does not give dates of its imageryit is beneficial to view the location with multiple sources of imagery such as‘s bird’s eye view in case the panoramic imagery and the GIS base layers have significant differences.

Manual Viewshed of Overpass

Manual Viewshed

Google StreetView of viewshed

Google StreetView of viewshed

Aerial Photography with RC Planes

May 31, 2008 4 comments

EasyStarA few months ago I became intrigued with the concept of obtaining aerial photography utilizing RC planes for GIS applications. After reading the RC forums and different websites I purchased an EasyStar RC plane. I bought the ready to fly (RTF) kit, a couple of Pentax cameras w/cracked LCDs (I was going to replace the cracked LCDs later), an IR switch to trigger the shutter and an alarm in case I lost radio contact with the plane. I also picked up a couple of RC simulators, FS One and FMS.

Flying the plane was a lot harder than it looked and I started to have issues with my plane. The motor would cut out after a few minutes. I received some help from the people at the local RC airfield and we ruled out a number of issues, the problem was with either the engine or the speed control. Unfortunately I had spent most of my money getting the initial equipment and did not have any spare spending money to buy the needed replacement parts. Not mention school quickly overcame what little free time I had for the hobby.

However, this semester I am taking “Remote Sensing for the Geospatial Intelligence Professional” and I am toying with getting back into the hobby. Chris Anderson’s “DIY Drones” site has a few posts on how to upgrade the EasyStarto become a viable remote sensing platform. I also recently found a program that allows Canon cameras to take unlimited timed-interval picture series with only one shutter activation. I do not have a Canon but that seems like a better solution than using an IR switch to get three picture bursts.

For only a couple hundred dollars I can do this . . . now to convince the wife that this is a school expense.