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thedivtagguy · May 11, 2023 · 78dd69f · 78dd69f
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diff --git a/.Rprofile b/.Rprofile
@@ -0,0 +1 @@
+source("renv/activate.R")
diff --git a/11-field-visits.rmd b/11-field-visits.rmd
@@ -57,7 +57,7 @@ After your site visit, there are a few things you should do to make sure you mak
 In Section \@ref(levels), I outlined how I separate my study in Ejipura into what I believed to be its constitutent parts. Suppose you have only four visits thatr you can do and you need to make the most of them, how would each one look like? Table \@ref(tab:four) offers some insight.
 
 | Site Visit \# | Activities                                               | Areas of Focus                                                                                                                                                                                                                                                                                                                                                                                                                                                                          |
-|-------------|-------------|----------------------------------------------|
+|---------------|----------------------------------------------------------|-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
 | 1             | Walk-through exploration, mapping, and photography       | Level 1 and 2: Analyze the overall characteristics of the neighborhood, including its geographic boundaries, land uses, and demographic patterns. Also examine the pedestrian landscape of the neighborhood, including the design and accessibility of sidewalks, crosswalks, and other public spaces.                                                                                                                                                                                  |
 | 2             | On-ground analysis, participatory exercises              | Level 3 and 4: Investigate the distribution and characteristics of residential units and blocks within the neighborhood, such as their size, age, occupancy rate, and more. Also examine how land in the neighborhood is used, including the types of businesses and institutions present, the prevalence of green spaces and public parks, and the location of major roads and highways. Conduct interviews with local residents to understand their perspectives on the neighborhood. |
 | 3             | Interviews, surveys, and community engagement activities | Level 5: Examine the availability and accessibility of key amenities and services in the neighborhood, including public transit, grocery stores, restaurants, schools, and healthcare facilities. Conduct more interviews in a different region to remove spatial bias.                                                                                                                                                                                                                 |

diff --git a/_book/The Walkability Wiki.pdf b/_book/The Walkability Wiki.pdf
diff --git a/_book/bookdown-demo.pdf b/_book/bookdown-demo.pdf
diff --git a/bridging-the-gap.bib b/bridging-the-gap.bib
@@ -429,6 +429,15 @@ @online{gopalkrishnanBengaluruSolutionsAre
   abstract = {Why air-conditioned railway stations are political}
 }
 
+@misc{GuideNearestNeighbour2019,
+  title = {A {{Guide}} to {{Nearest Neighbour Analysis}}},
+  date = {2019},
+  publisher = {{Royal Geographic Society}},
+  url = {https://www.rgs.org/CMSPages/GetFile.aspx?nodeguid=153c11d5-2420-4e25-a972-03c91a774292&lang=en-GB},
+  urldate = {2023-05-08},
+  file = {C\:\\Users\\ADMIN\\Zotero\\storage\\AQ5L5JH7\\GetFile.pdf}
+}
+
 @article{hansenHowAccessibilityShapes1959,
   title = {How {{Accessibility Shapes Land Use}}},
   author = {Hansen, Walter G.},
@@ -1235,28 +1244,3 @@ @article{yueUsingConvolutionalNeural2022
   abstract = {Built environment neighborhood characteristics are difficult to measure and assess on a large scale. Consequently, there is a lack of sufficient data that can help us investigate neighborhood characteristics as structural determinants of health on a national level. The objective of this study is to utilize publicly available Google Street View images as a data source for characterizing built environments and to examine the influence of built environments on chronic diseases and health behaviors in the United States. Data were collected by processing 164 million Google Street View images from November 2019 across the United States. Convolutional Neural Networks, a class of multi-layer deep neural networks, were used to extract features of the built environment. Validation analyses found accuracies of 82\% or higher across neighborhood characteristics. In regression analyses controlling for census tract sociodemographics, we find that single-lane roads (an indicator of lower urban development) were linked with chronic conditions and worse mental health. Walkability and urbanicity indicators such as crosswalks, sidewalks, and two or more cars were associated with better health, including reduction in depression, obesity, high blood pressure, and high cholesterol. Street signs and streetlights were also found to be associated with decreased chronic conditions. Chain link fence (physical disorder indicator) was generally associated with poorer mental health. Living in neighborhoods with a built environment that supports social interaction and physical activity can lead to positive health outcomes. Computer vision models using manually annotated Google Street View images as a training dataset were able to accurately identify neighborhood built environment characteristics. These methods increases the feasibility, scale, and efficiency of neighborhood studies on health.},
   keywords = {big data,built environment,computer vision,GIS,machine learning,structural determinants of health}
 }
-
-@misc{safeyelli2022,
-	title = {Streetlamps and Businesses surveyed and mapped on 21-04 and 20-04. Most data has been uploaded to @openstreetmap https://t.co/OdKQkZpW1m},
-	author = {Safe Yelli, },
-	year = {2022},
-	date = {2022},
-	url = {https://twitter.com/SafeYelli/status/1517395594452828160},
-	langid = {en}
-}
-
-@article{rundle2011,
-	title = {Using Google Street View to Audit Neighborhood Environments},
-	author = {Rundle, Andrew G. and Bader, Michael D.M. and Richards, Catherine A. and Neckerman, Kathryn M. and Teitler, Julien O.},
-	year = {2011},
-	month = {01},
-	date = {2011-01},
-	journal = {American journal of preventive medicine},
-	pages = {94--100},
-	volume = {40},
-	number = {1},
-	doi = {10.1016/j.amepre.2010.09.034},
-	url = {https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3031144/},
-	note = {PMID: 21146773
-PMCID: PMC3031144}
-}
diff --git a/latex/before_docbook.tex b/latex/before_docbook.tex
@@ -0,0 +1 @@
+\includepdf[pages={1-6}]{C:/Users/ADMIN/Downloads/cover-3_merged.pdf}
diff --git a/latex/tufte-book.cls b/latex/tufte-book.cls
@@ -0,0 +1,80 @@
+\NeedsTeXFormat{LaTeX2e}[1994/06/01]
+
+\ProvidesClass{tufte-book}[2009/12/11 v3.5.0 Tufte-book class]
+
+%%
+% Declare we're tufte-book
+\newcommand{\@tufte@class}{book}% the base LaTeX class (defaults to the article/handout style)
+\newcommand{\@tufte@pkgname}{tufte-book}% the name of the package (defaults to tufte-handout)
+
+%%
+% Load the common style elements
+\input{tufte-common.def}
+
+
+%%
+% Set up any book-specific stuff now
+
+%%
+% The front matter in Tufte's /Beautiful Evidence/ contains everything up
+% to the opening page of Chapter 1.  The running heads, when they appear,
+% contain only the (arabic) page number in the outside corner.
+%\newif\if@mainmatter \@mainmattertrue
+\renewcommand\frontmatter{%
+  \cleardoublepage%
+  \@mainmatterfalse%
+  \pagenumbering{arabic}%
+  %\pagestyle{plain}%
+  \fancyhf{}%
+  \ifthenelse{\boolean{@tufte@twoside}}%
+    {\fancyhead[LE,RO]{\thepage}}%
+    {\fancyhead[RE,RO]{\thepage}}%
+}
+
+
+%%
+% The main matter in Tufte's /Beautiful Evidence/ doesn't restart the page
+% numbering---it continues where it left off in the front matter.
+\renewcommand\mainmatter{%
+  \cleardoublepage%
+  \@mainmattertrue%
+  \fancyhf{}%
+  \ifthenelse{\boolean{@tufte@twoside}}%
+    {% two-side
+      \renewcommand{\chaptermark}[1]{\markboth{##1}{}}%
+      \fancyhead[LE]{\thepage\quad\smallcaps{\newlinetospace{\plaintitle}}}% book title
+      \fancyhead[RO]{\smallcaps{\newlinetospace{\leftmark}}\quad\thepage}% chapter title
+    }%
+    {% one-side
+      \fancyhead[RE,RO]{\smallcaps{\newlinetospace{\plaintitle}}\quad\thepage}% book title
+    }%
+}
+
+
+%%
+% The back matter contains appendices, indices, glossaries, endnotes,
+% biliographies, list of contributors, illustration credits, etc.
+\renewcommand\backmatter{%
+  \if@openright%
+    \cleardoublepage%
+  \else%
+    \clearpage%
+  \fi%
+  \@mainmatterfalse%
+}
+
+%%
+% Only show the chapter titles in the table of contents
+\setcounter{tocdepth}{0}
+
+%%
+% If there is a `tufte-book-local.sty' file, load it.
+
+\IfFileExists{tufte-book-local.tex}
+  {\input{tufte-book-local}
+   \TufteInfoNL{Loading tufte-book-local.tex}}
+  {}
+
+%%
+% End of file
+\endinput