stud/II/Referatas/mj-referatas.tex

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\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{
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Cartografic Generalization of Lines \\
(example of rivers) \\ \vspace{4mm}
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}
\author{Motiejus Jakštys}
\date{\today}
\begin{document}
\maketitle
\newpage
\section{Abstract}
\label{sec:abstract}
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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
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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.
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\section{Introduction}
\label{sec:introduction}
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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{
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\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}