Design of a spectral-spatial pattern recognition framework for risk assessments using landsat data

A case study in Chile

verfasst von
Andreas Christian Braun, Carolina Rojas, Cristian Echeverri, Franz Rottensteiner, Hans Peter Bähr, Joachim Niemeyer, Mauricio Aguayo Arias, Sergey Kosov, Stefan Hinz, Uwe Weidner
Abstract

For many ecological applications of remote sensing, traditional multispectral data with moderate spatial and spectral resolution have to be used. Typical examples are land-use change or deforestation assessments. The study sites are frequently too large and the timespan covered too long assumes the availability of modern datasets such as very high resolution or hyperspectral data. However, in traditional datasets such as Landsat data, separability of the relevant classes is limited. A promising approach is to describe the landscape context pixels that are integrated. For this purpose, multiscale context features are computed. Then, spectral-spatial classification is employed. However, such approaches require sophisticated processing techniques. This study exemplifies these issues by designing an entire framework for exploiting context features. The framework uses kernel-based classifiers which are unified by a multiple classifier system and further improved by conditional random fields. Accuracy on three scenarios is raised between 19.0%pts and 26.6%pts. Although the framework is designed, focusing an application in Chile, it is generally enough to be applied to similar scenarios.

Organisationseinheit(en)
Institut für Photogrammetrie und Geoinformation
Externe Organisation(en)
Karlsruher Institut für Technologie (KIT)
Universidad de Concepcion
Typ
Artikel
Journal
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Band
7
Seiten
917-928
Anzahl der Seiten
12
ISSN
1939-1404
Publikationsdatum
03.2014
Publikationsstatus
Veröffentlicht
Peer-reviewed
Ja
ASJC Scopus Sachgebiete
Computer in den Geowissenschaften, Atmosphärenwissenschaften
Ziele für nachhaltige Entwicklung
SDG 15 – Lebensraum Land
Elektronische Version(en)
https://doi.org/10.1109/JSTARS.2013.2293421 (Zugang: Geschlossen)