Detection of illegal building using geodetic data gathering
Author
Matrka, Lukas
Term
4. term
Publication year
2018
Submitted on
2018-11-21
Pages
107
Abstract
Dette speciale undersøger, hvordan ulovligt byggeri kan opdages ved at sammenholde matriklens oplysninger med en opdateret repræsentation af virkeligheden indsamlet ved geodetisk opmåling. I den indledende del kortlægges problemfeltet, herunder definitioner og den slovakiske kontekst for ulovlige bygninger samt opbygningen af matrikel og matrikelkort. Forskellige datakilder og metoder vurderes (bl.a. terrestrisk opmåling, satellit- og ortofoto samt LiDAR), hvorefter LiDAR identificeres som den mest relevante til det eksperimentelle arbejde. Den praktiske del omfatter behandling af LiDAR-punktskyer (støjfiltrering, klassifikation af jord- og bygningspunkter, højdeberegning), afgrænsning af bygningers konturer til bygningspolygoner, forberedelse af det vektoriserede matrikelkort samt harmonisering af koordinatsystemer. Herefter sammenlignes bygningspolygoner fra opmålingen og matriklen for at finde afvigelser; disse analyseres som mulige indikatorer på ulovlige bygninger, hvorefter der foretages en faglig evaluering af forløbet. Arbejdet leverer en systematisk proces til registrering og analyse af afvigelser mellem registreret og faktisk bebyggelse; konkrete resultater og præstationsmål omtales i den fulde afhandling, men fremgår ikke af dette uddrag.
This thesis explores how illegal buildings can be detected by comparing cadastral records with an up-to-date representation of reality captured through geodetic surveying. The introductory part situates the issue, including definitions and the Slovak context of illegal construction, and outlines the structure of the cadastre and the cadastral map. Multiple data sources and methods are reviewed (e.g., ground surveys, satellite and orthophoto imagery, and LiDAR), with LiDAR identified as the most suitable for the experimental work. The practical workflow processes LiDAR point clouds (noise filtering, ground and building classification, height computation), delineates building footprints as polygons, prepares the vector cadastral map, and harmonizes coordinate systems. Building polygons derived from the survey are then compared with those in the cadastre to identify discrepancies; these outliers are analyzed as potential indicators of illegal construction and the overall approach is evaluated. The outcome is a systematic process for detecting and assessing mismatches between recorded and actual buildings; specific quantitative results and performance figures are discussed in the full thesis but are not included in this excerpt.
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