for e-thesis: update all 21 comparison application figures

sampoves · Oct 16, 2020 · 8d4c8a2 · 8d4c8a2 · sampoves · Oct 16, 2020
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diff --git a/content/appendices.tex b/content/appendices.tex
@@ -207,23 +207,23 @@ \section{}
 \begin{sidewaysfigure}
     \section{}
     \centering
-    \includegraphics[trim={0.9cm 0.3cm 0.25cm 0.3cm},clip,width=\textwidth]{images/compare_traveltimes_mapfill-msc_r_pct_fromzip-00520_11-10-2020.png}
+    \includegraphics[trim={0.9cm 0.3cm 0.25cm 0.3cm},clip,width=\textwidth]{images/compare_traveltimes_mapfill-msc_r_pct_fromzip-00520_15-10-2020.png}
     \caption[Parking process proportion from Itä-Pasila, rush hour traffic]{The parking process proportion in the total travel chain, in rush hour traffic, starting from 00520 Itä-Pasila. SFP stands for \textit{searching for parking}, \code{parktime}, and WTD \textit{walking to destination}, \code{walktime}. These are the components of the parking process in the \textit{door-to-door approach}.}%
     \label{fig:compare_msc_r_pct_00520}%
 \end{sidewaysfigure}
 
 \begin{sidewaysfigure}
     \section{}
     \centering
-    \includegraphics[trim={0.9cm 0.3cm 0.25cm 0.3cm},clip,width=\textwidth]{images/compare_traveltimes_mapfill-msc_m_pct_fromzip-00520_11-10-2020.png}
+    \includegraphics[trim={0.9cm 0.3cm 0.25cm 0.3cm},clip,width=\textwidth]{images/compare_traveltimes_mapfill-msc_m_pct_fromzip-00520_15-10-2020.png}
     \caption[Parking process proportion from Itä-Pasila, midday traffic]{The parking process proportion in the total travel chain, in midday traffic, starting from 00520 Itä-Pasila.}%
     \label{fig:compare_msc_m_pct_00520}%
 \end{sidewaysfigure}
 
 \begin{sidewaysfigure}
     \section{}
     \centering
-    \includegraphics[trim={0.9cm 0.3cm 0.25cm 0.3cm},clip,width=\textwidth]{images/compare_traveltimes_mapfill-msc_all_pct_fromzip-00520_11-10-2020.png}
+    \includegraphics[trim={0.9cm 0.3cm 0.25cm 0.3cm},clip,width=\textwidth]{images/compare_traveltimes_mapfill-msc_all_pct_fromzip-00520_15-10-2020.png}
     \caption[Parking process proportion from Itä-Pasila, all temporal values]{The parking process proportion in the total travel chain, using all temporal values, starting from 00520 Itä-Pasila.}%
     \label{fig:compare_msc_all_pct_00520}%
 \end{sidewaysfigure}
@@ -232,23 +232,23 @@ \section{}
 \begin{sidewaysfigure}
     \section{}
     \centering
-    \includegraphics[trim={0.9cm 0.3cm 0.25cm 0.3cm},clip,width=\textwidth]{images/compare_traveltimes_mapfill-msc_r_pct_fromzip-02650_11-10-2020.png}
+    \includegraphics[trim={0.9cm 0.3cm 0.25cm 0.3cm},clip,width=\textwidth]{images/compare_traveltimes_mapfill-msc_r_pct_fromzip-02650_16-10-2020.png}
     \caption[Parking process proportion from Pohjois-Leppävaara, rush hour traffic]{The parking process proportion in the total travel chain, in rush hour traffic, starting from 02650 Pohjois-Leppävaara. SFP stands for \textit{searching for parking}, \code{parktime}, and WTD \textit{walking to destination}, \code{walktime}. These are the components of the parking process in the \textit{door-to-door approach}.}%
     \label{fig:compare_msc_r_pct_02650}%
 \end{sidewaysfigure}
 
 \begin{sidewaysfigure}
     \section{}
     \centering
-    \includegraphics[trim={0.9cm 0.3cm 0.25cm 0.3cm},clip,width=\textwidth]{images/compare_traveltimes_mapfill-msc_m_pct_fromzip-02650_11-10-2020.png}
+    \includegraphics[trim={0.9cm 0.3cm 0.25cm 0.3cm},clip,width=\textwidth]{images/compare_traveltimes_mapfill-msc_m_pct_fromzip-02650_16-10-2020.png}
     \caption[Parking process proportion from Pohjois-Leppävaara, midday traffic]{The parking process proportion in the total travel chain, in midday traffic, starting from 02650 Pohjois-Leppävaara.}%
     \label{fig:compare_msc_m_pct_02650}%
 \end{sidewaysfigure}
 
 \begin{sidewaysfigure}
     \section{}
     \centering
-    \includegraphics[trim={0.9cm 0.3cm 0.25cm 0.3cm},clip,width=\textwidth]{images/compare_traveltimes_mapfill-msc_all_pct_fromzip-02650_11-10-2020.png}
+    \includegraphics[trim={0.9cm 0.3cm 0.25cm 0.3cm},clip,width=\textwidth]{images/compare_traveltimes_mapfill-msc_all_pct_fromzip-02650_16-10-2020.png}
     \caption[Parking process proportion from Pohjois-Leppävaara, all temporal values]{The parking process proportion in the total travel chain, using all temporal values, starting from 02650 Pohjois-Leppävaara.}%
     \label{fig:compare_msc_all_pct_02650}%
 \end{sidewaysfigure}
@@ -257,23 +257,23 @@ \section{}
 \begin{sidewaysfigure}
     \section{}
     \centering
-    \includegraphics[trim={0.9cm 0.3cm 0.25cm 0.3cm},clip,width=\textwidth]{images/compare_traveltimes_mapfill-msc_r_pct_fromzip-00430_11-10-2020.png}
+    \includegraphics[trim={0.9cm 0.3cm 0.25cm 0.3cm},clip,width=\textwidth]{images/compare_traveltimes_mapfill-msc_r_pct_fromzip-00430_16-10-2020.png}
     \caption[Parking process proportion from Maununneva, rush hour traffic]{The parking process proportion in the total travel chain, in rush hour traffic, starting from 00430 Maununneva. SFP stands for \textit{searching for parking}, \code{parktime}, and WTD \textit{walking to destination}, \code{walktime}. These are the components of the parking process in the \textit{door-to-door approach}.}%
     \label{fig:compare_msc_r_pct_00430}%
 \end{sidewaysfigure}
 
 \begin{sidewaysfigure}
     \section{}
     \centering
-    \includegraphics[trim={0.9cm 0.3cm 0.25cm 0.3cm},clip,width=\textwidth]{images/compare_traveltimes_mapfill-msc_m_pct_fromzip-00430_11-10-2020.png}
+    \includegraphics[trim={0.9cm 0.3cm 0.25cm 0.3cm},clip,width=\textwidth]{images/compare_traveltimes_mapfill-msc_m_pct_fromzip-00430_16-10-2020.png}
     \caption[Parking process proportion from Maununneva, midday traffic]{The parking process proportion in the total travel chain, in midday traffic, starting from 00430 Maununneva.}%
     \label{fig:compare_msc_m_pct_00430}%
 \end{sidewaysfigure}
 
 \begin{sidewaysfigure}
     \section{}
     \centering
-    \includegraphics[trim={0.9cm 0.3cm 0.25cm 0.3cm},clip,width=\textwidth]{images/compare_traveltimes_mapfill-msc_all_pct_fromzip-00430_11-10-2020.png}
+    \includegraphics[trim={0.9cm 0.3cm 0.25cm 0.3cm},clip,width=\textwidth]{images/compare_traveltimes_mapfill-msc_all_pct_fromzip-00430_16-10-2020.png}
     \caption[Parking process proportion from Maununneva, all temporal values]{The parking process proportion in the total travel chain, using all temporal values, starting from 00430 Maununneva.}%
     \label{fig:compare_msc_all_pct_00430}%
 \end{sidewaysfigure}
@@ -282,23 +282,23 @@ \section{}
 \begin{sidewaysfigure}
     \section{}
     \centering
-    \includegraphics[trim={0.9cm 0.3cm 0.25cm 0.3cm},clip,width=\textwidth]{images/compare_traveltimes_mapfill-msc_r_pct_fromzip-01690_11-10-2020.png}
+    \includegraphics[trim={0.9cm 0.3cm 0.25cm 0.3cm},clip,width=\textwidth]{images/compare_traveltimes_mapfill-msc_r_pct_fromzip-01690_16-10-2020.png}
     \caption[Parking process proportion from Ylästö, rush hour traffic]{The parking process proportion in the total travel chain, in rush hour traffic, starting from 01690 Ylästö. SFP stands for \textit{searching for parking}, \code{parktime}, and WTD \textit{walking to destination}, \code{walktime}. These are the components of the parking process in the \textit{door-to-door approach}.}%
     \label{fig:compare_msc_r_pct_01690}%
 \end{sidewaysfigure}
 
 \begin{sidewaysfigure}
     \section{}
     \centering
-    \includegraphics[trim={0.9cm 0.3cm 0.25cm 0.3cm},clip,width=\textwidth]{images/compare_traveltimes_mapfill-msc_m_pct_fromzip-01690_11-10-2020.png}
+    \includegraphics[trim={0.9cm 0.3cm 0.25cm 0.3cm},clip,width=\textwidth]{images/compare_traveltimes_mapfill-msc_m_pct_fromzip-01690_16-10-2020.png}
     \caption[Parking process proportion from Ylästö, midday traffic]{The parking process proportion in the total travel chain, in midday traffic, starting from 01690 Ylästö.}%
     \label{fig:compare_msc_m_pct_01690}%
 \end{sidewaysfigure}
 
 \begin{sidewaysfigure}
     \section{}
     \centering
-    \includegraphics[trim={0.9cm 0.3cm 0.25cm 0.3cm},clip,width=\textwidth]{images/compare_traveltimes_mapfill-msc_all_pct_fromzip-01690_11-10-2020.png}
+    \includegraphics[trim={0.9cm 0.3cm 0.25cm 0.3cm},clip,width=\textwidth]{images/compare_traveltimes_mapfill-msc_all_pct_fromzip-01690_16-10-2020.png}
     \caption[Parking process proportion from Ylästö, all temporal values]{The parking process proportion in the total travel chain, using all temporal values, starting from 01690 Ylästö.}%
     \label{fig:compare_msc_all_pct_01690}%
 \end{sidewaysfigure}

diff --git a/content/c1_introduction.tex b/content/c1_introduction.tex
@@ -19,7 +19,7 @@ \section{Introduction}
 This thesis promotes research transparency and repeatability. All parts of this thesis are available online at GitHub (\textcolor{blue}{\url{https://github.com/sampoves/Masters-2020}} and \textcolor{blue}{\url{https://github.com/sampoves/thesis-data-analysis}}). This includes the entire thesis in LaTeX format, the parking survey programmed in JavaScript, instructions to set up the web server as used in this research survey, and the interactive survey data and analysis applications programmed in Python and R. Complete development histories of all components are included. In addition to the work proper, as a side product, a point based variant of the park survey (\textcolor{blue}{\url{https://github.com/sampoves/leaflet-map-survey-point}}) have been made available.
 
 \bigskip
-% Make sure this environment is not divided to two pages
+% Makes sure this environment is not divided to two pages
 \begin{samepage}
     \noindent
     The research questions for this thesis are:

diff --git a/content/c2_background.tex b/content/c2_background.tex
@@ -1,5 +1,5 @@
 \section{Background}
-\label{sec:c2-background} % labe to enable hyperref to this chapter
+\label{sec:c2-background} % label to enable hyperref to this chapter
 \subsection{Private cars as a mode of urban transport}
 \justify
 

diff --git a/content/c3_data.tex b/content/c3_data.tex
@@ -195,7 +195,7 @@ \subsection{Software}
 
 In addition to the aforementioned technologies, the flowcharts in this thesis were created with the web application \textit{diagrams.net}. Most of the map visualisations of this thesis were made using the geographic information system application QGIS version 3.12.2.
 
-% Consider! Removing \raggedright and hyphenrules will enable nice even table cells. Could be worth it to look into
+% Removing \raggedright and hyphenrules will enable nice even table cells
 \begin{hyphenrules}{nohyphenation}
     \begin{table}[H]
         \centering
@@ -339,7 +339,7 @@ \subsubsection{Programming the parking survey}
 
 In the table \textit{visitors}, the following data was recorded: IP address (\code{ip}), the timestamp of the first visit of this IP address (\code{ts\_first}), the timestamp of the latest visit of this IP address (\code{ts\_latest}), and the count of visits (\code{count}). In this table, an IP address is only stored once. On the first visit of an IP address, the row for that IP address is created in the data table with \code{ts\_first} and \code{ts\_latest} being identical. On further visits of that IP address the original row is appended with updated information in the columns \code{ts\_latest} and \code{count} (table~\ref{tab:mysql_visitors_str}).
 
-% \scalebox to prevent table going too wide
+% \scalebox to prevent the table going too wide
 \begin{hyphenrules}{nohyphenation}
     \begin{table}[H]
         \centering
@@ -653,7 +653,7 @@ \subsection{Processing survey data}
     \end{table}
 \end{hyphenrules}
 
-% Some reading: https://www.spatialanalysisonline.com/HTML/index.html?classification_and_clustering.htm
+% Some reading about classification: https://www.spatialanalysisonline.com/HTML/index.html?classification_and_clustering.htm
 In the finalising section, \textit{records} was prepared for analysis and visualisation in R (figure~\ref{fig:gen_workflow}, section 5). The software library for plotting in R, \textit{ggplot2}, prefers data inputted in long format. To study characteristics of postal code areas in this research, it meant adding repetitive data columns in \textit{records}, where values for CORINE land cover 2018 artificial surfaces, YKR zone and subdivision remained unchanged for all rows in the same postal code area. For artificial surfaces, a custom Jenks natural breaks function with five classes were utilised to find the applicable Jenks breaks class for each postal code area. For \textit{YKR zones}, the most common urban structure type in percentage was selected for each postal code area. In addition, \textit{records} was inserted with municipality subdivision information (figure~\ref{fig:subdiv_placement}). This was achieved by collecting data from the web sites of the municipalities of the Helsinki Capital Region (\cite{Espoonkaupunki2020}, \cite{Helsinginkaupunkiymparistontoimiala2019}, \cite{Vantaankaupunki2019}). In these sources, each municipality broke the subdivisions down to city district level, from where it was possible to allot each postal code area with a subdivision. This was for the most part simplistic work, but in some cases the postal code areas and city districts did not align and author's own deliberation was used to help the placement. Some of the most glaring discrepancies between the postal code areas and subdivision boundaries occur in Espoo. In the case of Lippajärvi-Järvenperä, a postal code area north of Kauniainen, the subdivision Vanha-Espoo was chosen because Lippajärvi-Järvenperä as a whole does not fit into the characteristics of Suur-Leppävaara, and at the same time the city districts Lippajärvi and Järvenperä do not fit into the distinctive features of the subdivision Pohjois-Espoo. In the same spirit the postal code area Sepänkylä-Kuurinniitty south of Kauniainen lies troublingly in the area of four subdivisions of Espoo. In the end Vanha-Espoo was chosen as Sepänkylä-Kuurinniitty lies for the most part in its area. Similar complications occurred in Helsinki and Vantaa (the partial placement of Kirkonkylä-Veromäki and Ruskeasanta-Ilola in subdivision of Tikkurila) and using my best judgement, the classification shown in figure~\ref{fig:subdiv_placement} was used in the survey results analysis of this thesis.
 
 The source code for the data processing described in this chapter is available at GitHub (\textcolor{blue}{\url{https://github.com/sampoves/Msc-thesis-data-analysis}}).