Main Page/Research

MSB Issues

issue	priority	who	resolution?	resolved?
timestamps on MyExperience do not match SMS	high	Phil	"fuzzy" time matching will fix	R code fixes
timestamps should be in a consistent or explicit time zone	high	??
duplicate timestamps on certain records	high	Phil	delete duplicates	perl script fixes
GPS data: full set of measurements	medium (assuming these can be extracted from current data)	Jonathan
wget copies index.html files	high	Jonathan	use wget --reject=html,htm
GPS data munged, see part_02	medium (unless this pattern repeats itself)	??
need codes for LEDs on MSB	medium/high (for troubleshooting when subjects will go out)	Carl	Blinking red - no communication w/ gps module Solid red - communication ok, no lock Green - Fully locked Cyan - Partial (2D) lock Blue - Dead reckoning	see codes (left)
MyExperience Analyzer command line interface	low	Jon F
some data sets do not get parsed, see pmh04.2 This dir seems to contain 8 blocks of data (large files) separated by a series of small files (293 or 0 kB). The output is very limited for part_05 and part_08, and part_06 could not be classified.	high	Jonathan	When the MSB runs out of power, the last file causes the entire session not to parse. In order to avoid this, rename files that are not the standard size to *.uwar.junk or anything other than *.uwar.	Yes

Overall Strategy

Based on discussion with Miles, 2008-09-23

1. Define and explicate a new data-driven construct for conceptualizing movement in urban environments.
   1. Three typologies of movement:
      1. Dwell

         XY-aggregated locations at which a substantial amount of "non-moving" time is spent; may include short, punctuated bouts of "moving" points

      2. Trip

         linear collections of "moving" points, may contain short, punctuated bouts of "non-moving" points

      3. Stop

         XY-aggregated locations of "non-moving" points within trips

   How have others attempted to define & measure this or a similar typology?

   What does this new paradigm have to offer?

   What data set would be necessary to investigate the use of this paradigm?

   What hypotheses could be tested using this construct?

2. Explicate methodology for obtaining & processing data set
3. Hypotehsis testing for hypotheses made in step 1
4. 4D data frame
   1. XY (Cartesian)
   2. Z (elevation)
   3. time
   4. attribute(s) of points

   Display a cloud of XYZt data with unique value classification of an attribute

   "Collapse" one of the dimensions by viewing data cube endwise

   Look for patterns across subjects, dwell, or trip types.

Research Questions

• What are the built environment characteristics of areas of maximum utilization distribution?
• What are the differences in built environment characteristics of areas of maximum UD stratified by activity type?
• What are the BE characteristics of the proximate area for bouts of different types of PA?
• What is the relationship between PA and distance between home and work?
• What is the relationship between PA and the size of home range?
• What is the relationship between the size of home range and distance between home and work?
• What is the difference, if any, of diversity of environments in areas/locations of different PA?
• What are the BE characteristics of trips that differ by:
  • Transportation mode
  • Trip duration
  • Trip distance

Census data

Importing ZCTA census data