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FORSAT: a 3D forest monitoring system for cover mapping and volumetric 3D change detection
Authors:Efstratios Stylianidis  Daniela Poli  Martin Hofer  Armin Gruen  Victor Sanchez Martin
Affiliation:1. School of Spatial Planning and Development, Aristotle University of Thessaloniki, Thessaloniki, Greece "ORCIDhttps://orcid.org/0000-0002-0188-5117;2. 4DiXplorer AG, Zurich, Switzerland;3. GeoVille Information Systems GmbH, Innsbruck, Austria;4. Chair of Information Architecture, ETH Zurich, Switzerland;5. Ingeniería Y Soluciones Informáticas S.L., Sevilla, Spain
Abstract:ABSTRACT

A 3D forest monitoring system, called FORSAT (a satellite very high resolution image processing platform for forest assessment), was developed for the extraction of 3D geometric forest information from very high resolution (VHR) satellite imagery and the automatic 3D change detection. FORSAT is composed of two complementary tasks: (1) the geometric and radiometric processing of satellite optical imagery and digital surface model (DSM) reconstruction by using a precise and robust image matching approach specially designed for VHR satellite imagery, (2) 3D surface comparison for change detection. It allows the users to import DSMs, align them using an advanced 3D surface matching approach and calculate the 3D differences and volume changes (together with precision values) between epochs. FORSAT is a single source and flexible forest information solution, allowing expert and non-expert remote sensing users to monitor forests in three and four (time) dimensions. The geometric resolution and thematic content of VHR optical imagery are sufficient for many forest information needs such as deforestation, clear-cut and fire severity mapping. The capacity and benefits of FORSAT, as a forest information system contributing to the sustainable forest management, have been tested and validated in case studies located in Austria, Switzerland and Spain.
Keywords:Deforestation  3D  VHR satellite imagery  orientation  image matching  DSM generation  co-registration  volumetric change detection  volume precision
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