MULTI-TEMPORAL ANALYSIS OF LANDSCAPES AND URBAN AREAS
E. Nocerino, F. Menna, F. Remondino
3D Optical Metrology (3DOM) unit, Bruno Kessler Foundation (FBK), Trento, Italy
Web: http://3dom.fbk.eu
E-mail: <nocerino><fmenna><remondino>@fbk.eu
Commission IV, WG2
KEY WORDS: Multi-temporal, Land Use, Photogrammetry, Aerial Imagery, Orthorectification, Databases
ABSTRACT:
This article presents a 4D modelling approach that employs multi-temporal and historical aerial images to derive spatio-temporal
information for scenes and landscapes. Such imagery represent a unique data source, which combined with photo interpretation and
reality-based 3D reconstruction techniques, can offer a more complete modelling procedure because it adds the fourth dimension of
time to 3D geometrical representation and thus, allows urban planners, historians, and others to identify, describe, and analyse
changes in individual scenes and buildings as well as across landscapes. Particularly important to this approach are historical aerial
photos, which provide data about the past that can be collected, processed, and then integrated as a database. The proposed
methodology employs both historical (1945) and more recent (1973 and 2000s) aerial images from the Trentino region in North-
eastern Italy in order to create a multi-temporal database of information to assist researchers in many disciplines such as topographic
mapping, geology, geography, architecture, and archaeology as they work to reconstruct building phases and to understand landscape
transformations (Fig. 1).
year: 1945 year: 1973 year: 2005
Figure 1: Examples of multi-temporal aerial imagery used in the project to acquire spatio-temporal data and identify
anthropomorphic changes landscapes.
1. INTRODUCTION individual scenes and buildings as well as across landscapes.
Such data about change through time assist researchers as they
Since the advent of photography in the XIX century, the work to reconstruct changes in buildings and understand
possibility of acquiring images from the air has been recognised landscape transformations. For example, researchers have used
as an invaluable source of data, especially for military strategic multi-temporal imagery for many purposes like: (1)
planning. Prior to satellite imagery, aerial photographs were the investigation of land cover dynamics (Ratcliffe & Henebry,
primary source of information about the Earth's surface. Images 2004; Sandric et al., 2007), (2) detection of change detection in
from balloons, airplanes, helicopters, and even modern historic city centers (Patias et al., 2011), (3) creation of 4D
unmanned drones, are important sources of information for interactive presentations of heritage sites (El-Hakim et al.,
mapping purposes; however, these images offer many other 2008), (4) modelling of architectural changes (Stefani et al.,
potential uses that are typically not investigated once the map is 2011), (5) 4D city modelling (Schindler, 2010) and (6) urban
produced. In particular, historical aerial imagery are often analyses (Vizzari, 2011).
overlooked despite the fact that they store unique information The article presents a spatio-temporal modelling approach using
about the past, that is useful for many disciplines including the Trentino region (Italy) as a case study. The employed
topographic mapping, geology, geography, architecture and methodology makes use of both historical and more recent
archacology. In the era of digital photogrammetry, historical acrial images and orthophotos (Fig. 1) in order to acquire data
photos represent a unique resource that, together with photo to create a multi-temporal database of information. Rigorous
interpretation and reality-based 3D reconstruction techniques, photogrammetric measurement techniques for image
can offer a more complete modelling procedure, by adding the triangulation, Digital Surface Model (DSM) production and
fourth dimension of time to 3D geometrical representations. A orthoimage generation were applied to historical photos dating
spatio-temporal or 4D modelling approach allows researchers to back to the Second World War (WWII) in order to derive metric
identify, describe, and subsequently analyse changes in and geo-referenced information about past scenes. From these
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