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Remote Sens. 2014, 6(9), 8310-8336; doi:10.3390/rs6098310

Building Change Detection from Historical Aerial Photographs Using Dense Image Matching and Object-Based Image Analysis

Institute of Geomatics Engineering, FHNW University of Applied Sciences and Arts Northwestern Switzerland, Gründenstrasse 40, 4132 Muttenz, Switzerland
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Received: 9 July 2014 / Revised: 22 August 2014 / Accepted: 25 August 2014 / Published: 2 September 2014
(This article belongs to the Special Issue Advances in Geographic Object-Based Image Analysis (GEOBIA))
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Abstract

A successful application of dense image matching algorithms to historical aerial photographs would offer a great potential for detailed reconstructions of historical landscapes in three dimensions, allowing for the efficient monitoring of various landscape changes over the last 50+ years. In this paper we propose the combination of image-based dense DSM (digital surface model) reconstruction from historical aerial imagery with object-based image analysis for the detection of individual buildings and the subsequent analysis of settlement change. Our proposed methodology is evaluated using historical greyscale and color aerial photographs and numerous reference data sets of Andermatt, a historical town and tourism destination in the Swiss Alps. In our paper, we first investigate the DSM generation performance of different sparse and dense image matching algorithms. They demonstrate the superiority of dense matching algorithms and of the resulting historical DSMs with root mean square error values of 1–1.5 GSD (ground sampling distance) and yield point densities comparable to those of recent airborne LiDAR DSMs. In the second part, we present an object-based building detection workflow mainly based on the historical DSMs and the historical imagery itself. Additional inputs are a current digital terrain model and a cadastral building database. For the case of densely matched DSMs, the evaluation yields building detection rates of 92% for grayscale and 94% for color imagery. View Full-Text
Keywords: OBIA; DSM; digital surface model; historic; aerial imagery; photogrammetry; image matching; building detection; time series OBIA; DSM; digital surface model; historic; aerial imagery; photogrammetry; image matching; building detection; time series
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This is an open access article distributed under the Creative Commons Attribution License (CC BY 3.0).

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MDPI and ACS Style

Nebiker, S.; Lack, N.; Deuber, M. Building Change Detection from Historical Aerial Photographs Using Dense Image Matching and Object-Based Image Analysis. Remote Sens. 2014, 6, 8310-8336.

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