Roof type determination from a sparse laser scanning point cloud

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11310%2F12%3A10130195" target="_blank" >RIV/00216208:11310/12:10130195 - isvavai.cz</a>

Výsledek na webu

<a href="http://web.natur.cuni.cz/gis/aucg/index.php?option=com_phocadownload&view=category&download=96:petr-hofman-marketa-potkova-roof-type-determination-from-a-sparse-laser-scanning-point-cloud-&id=14:issue-12012&Itemid=98" target="_blank" >http://web.natur.cuni.cz/gis/aucg/index.php?option=com_phocadownload&view=category&download=96:petr-hofman-marketa-potkova-roof-type-determination-from-a-sparse-laser-scanning-point-cloud-&id=14:issue-12012&Itemid=98</a>

DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

Roof type determination from a sparse laser scanning point cloud

Popis výsledku v původním jazyce

A method for determining a roof coverage type and a building height from a sparse laser scanning point cloud was introduced in Hofman (2008). This model driven approach utilizes 2D building outlines from the Digital Cadastral Map (DCM) and orthoimages inaddition to an airborne laser scanning point cloud. Its results were unsatisfactory, since the determination of roof types was not reliable. Thus, a practical application of this method was not possible. While searching possibilities for its improvement, it was discovered that derivation of roof edges from orthoimages was the weakest point in the workflow. A new model driven method is presented, which is suitable for buildings with a rectangular plot. Based on four predefined roof types, a subset of apoint cloud is divided into several groups corresponding to roof planes. The best fitting planes are found by means of least squares adjustment with an iterative exclusion of outliers. The most probable roof type is selected by an evaluat

Název v anglickém jazyce

Roof type determination from a sparse laser scanning point cloud

Popis výsledku anglicky

A method for determining a roof coverage type and a building height from a sparse laser scanning point cloud was introduced in Hofman (2008). This model driven approach utilizes 2D building outlines from the Digital Cadastral Map (DCM) and orthoimages inaddition to an airborne laser scanning point cloud. Its results were unsatisfactory, since the determination of roof types was not reliable. Thus, a practical application of this method was not possible. While searching possibilities for its improvement, it was discovered that derivation of roof edges from orthoimages was the weakest point in the workflow. A new model driven method is presented, which is suitable for buildings with a rectangular plot. Based on four predefined roof types, a subset of apoint cloud is divided into several groups corresponding to roof planes. The best fitting planes are found by means of least squares adjustment with an iterative exclusion of outliers. The most probable roof type is selected by an evaluat

Druh

J_x - Nezařazeno - Článek v odborném periodiku (Jimp, Jsc a Jost)

CEP obor

DE - Zemský magnetismus, geodesie, geografie

OECD FORD obor

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Projekt

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Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2012

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

Acta Universitatis Carolinae. Geographica

ISSN

0300-5402

e-ISSN

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Svazek periodika

47

Číslo periodika v rámci svazku

1

Stát vydavatele periodika

CZ - Česká republika

Počet stran výsledku

5

Strana od-do

35-39

Kód UT WoS článku

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EID výsledku v databázi Scopus

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