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Please use this identifier to cite or link to this item: http://hdl.handle.net/10362/3308

Title: The contribution of multitemporal information from multispectral satellite images for automatic land cover classification at the national scale
Authors: Carrão, Hugo Miguel Saiote
Advisor: Caetano, Mario
Gonçalves, Paulo Alexandre Andrade
Keywords: Remote sensing
Time series
Multispectral images
Land cover
Separability analysis
Classification
Prediction
Reference data
Accuracy assessment
Detecção remota
Séries temporais
Imagens multi-espectrais
Ocupação do solo
Análise de separabilidade
Classificação
Predição
Dados de referência
Avaliação da exactidão.
Issue Date: 27-Jan-2010
Series/Report no.: Doutoramento em Gestão de Informação;D0007
Abstract: Imaging and sensing technologies are constantly evolving so that, now, the latest generations of satellites commonly provide with Earth’s surface snapshots at very short sampling periods (i.e. daily images). It is unquestionable that this tendency towards continuous time observation will broaden up the scope of remotely sensed activities. Inevitable also, such increasing amount of information will prompt methodological approaches that combine digital image processing techniques with time series analysis for the characterization of land cover distribution and monitoring of its dynamics on a frequent basis. Nonetheless, quantitative analyses that convey the proficiency of three-dimensional satellite images data sets (i.e. spatial, spectral and temporal) for the automatic mapping of land cover and land cover time evolution have not been thoroughly explored. In this dissertation, we investigate the usefulness of multispectral time series sets of medium spatial resolution satellite images for the regular land cover characterization at the national scale. This study is carried out on the territory of Continental Portugal and exploits satellite images acquired by the Moderate Resolution Imaging Spectroradiometer (MODIS) and MEdium Resolution Imaging Spectrometer (MERIS). In detail, we first focus on the analysis of the contribution of multitemporal information from multispectral satellite images for the automatic land cover classes’ discrimination. The outcomes show that multispectral information contributes more significantly than multitemporal information for the automatic classification of land cover types. In the sequence, we review some of the most important steps that constitute a standard protocol for the automatic land cover mapping from satellite images. Moreover, we delineate a methodological approach for the production and assessment of land cover maps from multitemporal satellite images that guides us in the production of a land cover map with high thematic accuracy for the study area. Finally, we develop a nonlinear harmonic model for fitting multispectral reflectances and vegetation indices time series from satellite images for numerous land cover classes. The simplified multitemporal information retrieved with the model proves adequate to describe the main land cover classes’ characteristics and to predict the time evolution of land cover classes’individuals.
Description: Thesis submitted to the Instituto Superior de Estatística e Gestão de Informação da Universidade Nova de Lisboa in partial fulfillment of the requirements for the Degree of Doctor of Philosophy in Information Management – Geographic Information Systems
URI: http://hdl.handle.net/10362/3308
Appears in Collections:ISEGI - Teses de Doutoramento

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