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thedivtagguy committed Apr 26, 2023
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2 changes: 1 addition & 1 deletion 02-structure.Rmd
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Expand Up @@ -41,7 +41,7 @@ This book is a valuable resource for a wide range of professionals, academics, a

This book isn't a dry, technical manual. It's full of real-life case studies and practical techniques that can be used to make cities more walkable. So whether you're a professional or just someone who loves taking a stroll, this book is for you.

## Content Design
## How to Read This Book

```{=html}
<style>
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# Recommended Software & Tools
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# (PART) Overview of Methods {.unnumbered}

# Walkability

## Walkability Metrics

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7 changes: 7 additions & 0 deletions 05-types-of-analysis.Rmd
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# Types of Analysis

## Qualitative Analysis

## Quantitative Analysis

## Introducing additional dimensions to walkability
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24 changes: 24 additions & 0 deletions 08-site-selection.Rmd
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# (PART) Quantitative Assessment Guides {-}

# Site Selection Stratgies

## Defining your criteria

## Secondary research

### Census Data

### Population Data

### GIS sources

### Exisiing audits

## Space Syntax Analysis

### Defining the measures

### Using deptmapX

### Deriving insights from SSA

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9 changes: 9 additions & 0 deletions 09-physical-environment.Rmd
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# Assessment of Physical Environment

## Measuring Blocks Sizes

## Measuring Connectedness

## Measuring Integration

## Measuring Urban Structure
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5 changes: 5 additions & 0 deletions 10-infrastructure.Rmd
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# Assessment of Infrastructure

## Sourcing data from OpenStreetMaps

## Visualizing pedestrian sheds
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Expand Up @@ -68,6 +68,12 @@ Such characteristics should be **always** be considered alongside other variable

## Spatial

The built environment, through the design of streets and connectivity between them, can also reflect the extent of segregation in an area [@vlachouSuccessionalSegregationGerani2015]. It is possible to map the spatial properties of your study area through spatial syntax analysis (SSA), a quantative method to understand the configuration of a built environment and reveal how it is used [@dettlaffSpaceSyntaxAnalysis]
The built environment, through the design of streets and the connectivity between them, can also reflect the extent of segregation in an area [@vlachouSuccessionalSegregationGerani2015]. This isn't to say that the design is intentionally exclusionary, but the inherent properties of the space may contribute to the exclusion of certain groups. The environment can influence the politics that govern it. Therefore, to fully understand how specific groups may be excluded, we need to consider the background and social context surrounding it [@winnerArtifactsHavePolitics1980].

![](images/AngularStepDistance.png){width="650"}
It is possible to map the spatial properties of your study area through **spatial syntax analysis (SSA)**, a quantitative method to understand the configuration of a built environment and reveal how it is potentially used by pedestrians and motorists [@dettlaffSpaceSyntaxAnalysis]. The methodology is highly technical and includes many parameters we can analyse for our area, but we need to concern ourselves with only one metric; **angular step depth**.

In simple terms, **angular step depth** measures how near or *accessible* areas within the street network are. Well-connected streets with high intersection density allow you to walk from one place to another in lesser time. While this may seem obvious, as the farther you go, the less accessible an area is, the benefit of this analysis is evident when we analyse an area like Ejipura:

![](images/AngularStepDistance-01.png){width="600"}

Here, because of the design of the network, the National Games Village is just as inaccessible for people living in the blue region as the southern tip of the ward, despite being adjacent to each other. The reduced accessibility, whether by design or not, makes the two areas spatially segregated. This understanding, layered with observations on the built environment (\@ref(social)) and through secondary research methods, can provide a valuable starting point for identifying general levels of segregation within an area.
9 changes: 9 additions & 0 deletions 11-comfort.Rmd
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# Assessment of Comfort

## Mapping Green Cover

## Mapping Heat Exposure

## Mapping Artificial Shade

## Mapping Flood Risk
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# (PART) Qualitative Assessment Guides {-}

# Field Visits

## Things to keep in mind

## Suggested tools

## Observation notes

## Participatory Activities

### Semi-structured interviews

### Mapping acitvities

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# Street Audits

## Street comfort mapping

## Observations on built environment

## Tailoring your metrics

## Google Street View Audits
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# Deriving Insights

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# (PART) Visualizing Results

# Visualizing Results from Analysis

## Showcasing Your Study Site

## Interpreting and Presenting Results

## Designing in QGIS: A Crash Course
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# (PART) Conclusion {-}

# Finishing up

## Key takeaways

## Way forward
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# (APPENDIX) Appendix {-}

# Appendix A: Interviews

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# Cognitive Mapping
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# Assessment of Access

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# Data Sources
22 changes: 4 additions & 18 deletions _output.yml
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# config:
# toc:
# collapse: section
#
#
# bookdown::gitbook:
# css: style.css
#
# config:
# toc:
# collapse: section
# before: |
# <li><a href="./">Mastering Shiny</a></li>
# edit: https://github.com/thedivtagguy/walkability-wiki/edit/main/%s
# download: []
# sharing:
# facebook: no
# twitter: yes
# github: yes
# all: []


bookdown::pdf_book:
includes:
in_header: preamble.tex
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latex_engine: xelatex
citation_package: biblatex
template: null
pandoc_args: --top-level-division=chapter
toc_depth: 3
fig_width: 3
toc_unnumbered: no
toc_appendix: yes
quote_footer: ["\\VA{", "}{}"]
pandoc_args: ["-V", "papersize=a4paper"]
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