Semi-automated building footprint extraction from orthophotos

Rheannon Brooks, Trisalyn Nelson, Krista Amolins, G. Brent Hall

Research output: Contribution to journalArticle

4 Scopus citations

Abstract

Here we describe and apply a semi-automated, object-based method for extracting vector-building footprint polygons from aerial photographs (orthophotos) within urban settings. The approach integrates the use of high resolution orthophotos and image segmentation software and is compared with methods using Light Detection and Ranging (LiDAR) as the source data input. LiDAR data gives the best results with less processing, but is not widely used by municipalities due to the expense. Results from semi-automated image segmentation of the orthophotos showed a high accuracy between extracted building segments and reference building footprints for two study sites, comparable to those achieved using LiDAR data. We recommend image acquisition during summer months with a resolution of 10 cm by 10 cm. When data acquisition budgets are limited, combining ancillary GIS on roads with a semi-automated and object-based segmentation approach is a best practice strategy for land cover feature extraction and change quantification.

Original languageEnglish (US)
Pages (from-to)231-244
Number of pages14
JournalGeomatica
Volume69
Issue number2
DOIs
StatePublished - Jun 1 2015
Externally publishedYes

ASJC Scopus subject areas

  • Geography, Planning and Development
  • Earth-Surface Processes

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