%0 Conference Proceedings
%4 sid.inpe.br/mtc-m18/2012/05.17.19.28
%2 sid.inpe.br/mtc-m18/2012/05.17.19.28.48
%@isbn 978-85-17-00059-1
%T Object-based change detection and classification improvement of time series analysis
%D 2012
%A Tiede, Dirk,
%A Wania, Annett,
%A Füreder, Petra,
%@electronicmailaddress dirk.tiede@sbg.ac.at
%@electronicmailaddress annett.wania@jrc.ec.europa.eu
%@electronicmailaddress petra.fuereder@sbg.ac.at
%E Feitosa, Raul Queiroz,
%E Costa, Gilson Alexandre Ostwald Pedro da,
%E Almeida, Cláudia Maria de,
%E Fonseca, Leila Maria Garcia,
%E Kux, Hermann Johann Heinrich,
%B International Conference on Geographic Object-Based Image Analysis, 4 (GEOBIA).
%C Rio de Janeiro
%8 May 7-9, 2012
%I Instituto Nacional de Pesquisas Espaciais (INPE)
%J São José dos Campos
%P 223-227
%S Proceedings
%1 Instituto Nacional de Pesquisas Espaciais (INPE)
%K post-classification change detection, OBIA, CNL, object comparison.
%X The paper presents a new approach for post-classification change detection. Classification results are integrated in an object-based hierarchical knowledge framework, compared and aggregated on a change detection layer. The approach is - dependent on the complexity of the input classifications - semi-automated and transferable. The change detection framework is illustrated by two different applications. The first application is a change detection analysis of land use / land cover classifications which aims at identifying changes in land use since the land reform in Zimbabwe. The second application analyses changes in built-up area to reflect the urban development of the city of Harare, Zimbabwe.
%9 Multitemporal Analysis
%@language en
%3 064.pdf