This document outlines the connectivity methodology version 3.0 for measuring walking distances between random points within city boundaries. It describes key updates to the process, underlying principles, input preparation in ArcGIS and Excel, interim procedures for generating random points and selecting eligible points, calculating distances, potential issues and solutions, output results, and an evaluation of the methodology. The process generates 1000 random points for each city, selects 40 eligible points, measures walking distances between eligible points and square buffer points around them, and calculates the average distance as the connectivity score.

1. Connectivity Methodology
Ver. 3.0
NRDC Sustainable Cities Team
Presenter: TL
July 15,2015

2. Many thx to RND team!

3. Outline
• Key updates
• Principles
• Input preparation
• Interim procedure
• Output result
• Evaluation of the Methodology

4. Key Updates
• Powerful ArcGIS (licensed authorization!)
• Overcome some constrains posed by KMZ preparation
• Generate random points
• Select eligible points
• Batch: python code
• Update of Cityname.xlsx file
• Skipping of sheet Random_Points
• Important annotation: the unit of average altitude is kilometers

5. Principles
• The process will…
• generate 1000 random points for each city;
• Increasing capacity is feasible
• allow us to choose 40 eligible points to measure the walking distances;
• Identify if the interim points meet the standard (od distance = 500m)
• Discard the points that do not meet the requirement
• Go back to the bank test if a new eligible point meet the requirement
• get average walking distances from the final 40 points;
• The process need to be…
• strictly random in point selecting
• accurate in calculating the distance
• comparable across all cities
• efficient

6. Input Preparation
• Google Earth Pro:
• citynameRND.kmz (Many thanks to Ning, Xiao, Judy, Chenzi, Danlu)
• Same setting requirement: degree (decimal)
• Microsoft Excel:
• cityname.xlsx
• (Random_Points_Value), Eligible_Points, (Eligible_Points_Raw), Square_Points, Distance
• ESRI ArcGIS 10.X:
• Manually geoprocessing
• Python stand-alone processing
• (Windows environment is strongly recommended!)
• VPN and good network

7. Interim procedure: RP gen and EP selection
• In ArcGIS:
• KMZ to Layer
• Feature class to feature class
• (transforming boundary polylines into polygons)
• Generate random points: CITYNAME_RP.dbf
• (confined by boundary polygons)
• Selecting eligible points: CITYNAME_EP.dbf
• Detailed procedure: consulting to the python file
• In Excel:
• Copy and paste fields: Name, Latitude, Longitude
• From CITYNAME_RP.dbf to sheet Random_Points_Value
• From CITYNAME_EP.dbf to sheet Eligible_Points_Value (1 st round EP)

8. Interim Procedure: Square Points
• In workbook Square_Points of Nanchang.xlsx:
• Fill value of Nanchang’s average altitude in the cell following Average
Altitude;

9. Interim Procedure: Distance
• In workbook Distance of Nanchang.xlsx:
• Copy the cells in column C (Output);
• In GE Pro;
• Select “Search Google”;
• Paste the value in box to the left of
“Search” button;
• Make sure no space after the last character!
• Otherwise GE will recognize this syntax as an
error.
• Click on “Search” button;

10. Interim Procedure: Distance (Con’t)
• In GE Pro;
• Read the distance;
• In workbook Distance of
Nanchang.xlsx:
• Record the original value (unit:
meters) in corresponding cell in
column E;
• Do not worry about the weird
direction/distance you get now.

11. Interim Procedure: Distance (Con’t)
• Check for reasonableness
• If the trip origination and trip
destination are approximately
located at the point eligible
points…
• You are lucky!

12. Interim Procedure: Distance (Con’t)
• Check for reasonableness
• If the trip origination and trip
destination are not at the
intended places…
• (distance between origination and
destination <> 500m)
• Too long
• Too short
• Mark the corresponding cell in
column I as problematic
• E.g. “*od<>500”
• (need to specify the error type?)

13. Interim Procedure: Distance (Con’t)
• Complete all 160 (4 square points of each eligible point * 40 eligible
points) entries
• Good luck!
• Review the notes for problematic results;
• You have made marks for each pair of eligible point and square point;
• Look at column I;
• Check if the note belongs to a problematic eligible point
• If more than 3/4 (including 3/4) direction/distance results of the eligible point
are marked as problematic, we need 2nd round of eligible points selecting;
• Clear all four results of the problematic eligible point in column E

14. Interim Procedure: 2nd round Eligible Points
• In workbook Eligible_Points of Nanchang.xlsx:
• Mark all problematic eligible points
• Find the first backup eligible points…
• Directly from Nanchang_RP layer in GE
• Manually replace the number of the problematic eligible point in column A with the one of
backup eligible point;
• Use a point from the back up list generated in 1st round
• Use a point from the back up list generated by ArcGIS
• (time saving)
• Repeat the Interim procedure: Distance
• If the back up point is still problematic, continue the process of finding new back up
eligible point.
• Finish the process when no problematic eligible points show up.

15. Output Result
• Save Nanchang.xlsx.
• The results will keep in workbook Distance;

16. Output Result
• Copy column B, C, and D to Nanchang_EP.csv;
• Save Nanchang_EP.csv;
• No need to copy column A;
• Copy column C, D, and E to Nanchang_Square.csv;
• Save Nanchang_Square.csv;
• No need to copy the rest columns;
• Import Nanchang_EP.csv and Nanchang_Square.csv to Nanchang.kmz in GE
Pro;
• Same procedure of importing Nanchang_RP.csv;
• Use different colors;
• Be sure to save to My Places;
• Save as Nanchang_Square.kmz;

17. Evaluation
• The estimated time of finishing one city is 2-3 hours.
• The majority of the process could be documented.
• Use ArcGIS can help increase the randomness in selecting eligible points
• Strongly depend on the accuracy of boundary and RND boundary
• Batch processing allows for massive amount of cities to be measured
• Strictly randomness in RP and EP selecting process
• Overcome the inconsistency of different coordinate systems
• WGS-84 and GCJ-02 coordinate system
• Points are random, so the relative location between points and road network is of no
necessary importance in the process.

18. Evaluation
• In Interim Procedure: Distance, it would allow at ½ of the results to be
inaccurate, which generate inaccuracy.
• Tolerance level could be lower by only allowing no more than ½ result to be
problematic
• < 500m is calculated as 500m
• Hard to decide whether the distance between an od pair is 500m
• Usually not!
• How close?
• Both not accurate, but the distance seems to be 500m?

19. THX!