\documentclass{article}

\usepackage[L7x,T1]{fontenc}
\usepackage[utf8]{inputenc}
\usepackage{csquotes}
\usepackage[english]{babel}
\usepackage[maxbibnames=99,style=authoryear]{biblatex}
\addbibresource{bib.bib}
\usepackage{hyperref}
\usepackage{caption}
\usepackage{subcaption}
\usepackage{gensymb}
\usepackage{varwidth}
\usepackage{tikz}
\usetikzlibrary{er,positioning}

\title{
    Cartografic Generalization of Lines \\
    (example of rivers) \\ \vspace{4mm}
}

\author{Motiejus Jakštys}

\date{\today}

\begin{document}
\maketitle

\newpage

\section{Abstract}
\label{sec:abstract}

Ready-to-use, open-source line generalization solutions emit poor cartographic
output. Therefore, if one is using open-source technology to create a
large-scale map, downscaled lines (e.g. rivers) will look poorly. This paper
explores line generalization algorithms and suggests one for an avid GIS
developer to implement. Once it is implemented and integrated to open-source
GIS solutions (e.g. QGIS), rivers on future large-scale maps will look
professionally downscaled.

\section{Introduction}
\label{sec:introduction}

Cartographic generalization is one of the key processes of creating large-scale
maps: how can one approximate object features, without losing its main
cartographic properties?

Linear generalization algorithms are well studied, tested and implemented.

There are two main approaches to generalize lines in a map: geometric and
cartographic.

\subsection{

\section{The Problem}
\label{sec:the_problem}

\section{My Idea}
\label{sec:my_idea}

\section{The Details}
\label{sec:the_details}

\section{Related Work}
\label{sec:related_work}

\section{Conclusions and Further Work}
\label{sec:conclusions_and_further_work}

\printbibliography

\end{document}