Mapping deciduous forests by using time series of filtered MODIS NDVI and neural networks
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| Format: | Artículo científico |
| Sprache: | en |
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Universidade Federal de Lavras
2010
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| _version_ | 1876485865797058560 |
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| author | Thomaz Chaves de Andrade Oliveira |
| author_facet | Thomaz Chaves de Andrade Oliveira |
| contents | Mapping deciduous forests by using time series of filtered MODIS NDVI and neural networks Thomaz Chaves de Andrade Oliveira Luis Marcelo Tavares de Carvalho Luciano Teixeira de Oliveira Adriana Zanella Martinhago Fausto Weimar Acerbi Júnior Mariana Peres de Lima Agrociencias Fourier time series Remote sensing signal processing wavelets analysis Multi-temporal images are now of standard use in remote sensing of vegetation during monitoring and classification. Temporal vegetation signatures (i. e., vegetation indices as functions of time) generated, poses many challenges, primarily due to signal to noise-related issues. This study investigates which methods generate the most appropriate smoothed curves of vegetation signatures on MODIS NDVI time series. The filtering techniques compared were the HANTS algorithm which is based on Fourier analyses and Wavelet temporal algorithm which uses the wavelet analysis to generate the smoothed curves. The study was conducted in four different regions of the Minas Gerais State. The smoothed data were used as input data vectors for vegetation classification by means of artificial neural networks for comparison purpose. A comparison of the results was ultimately discussed in this work showing encouraging results and similarity between the two filtering techniques used. 2010 artículo científico 0104-7760 https://www.redalyc.org/articulo.oa?id=74421665002 en http://www.redalyc.org/revista.oa?id=744 CERNE application/pdf Universidade Federal de Lavras CERNE (Brasil) Num.2 Vol.16 |
| format | Artículo científico |
| id | redalyc_74421665002 |
| institution | Redalyc |
| language | en |
| publishDate | 2010 |
| publisher | Universidade Federal de Lavras |
| spellingShingle | Mapping deciduous forests by using time series of filtered MODIS NDVI and neural networks Thomaz Chaves de Andrade Oliveira Agrociencias Fourier time series Remote sensing signal processing wavelets analysis Mapping deciduous forests by using time series of filtered MODIS NDVI and neural networks Thomaz Chaves de Andrade Oliveira Luis Marcelo Tavares de Carvalho Luciano Teixeira de Oliveira Adriana Zanella Martinhago Fausto Weimar Acerbi Júnior Mariana Peres de Lima Agrociencias Fourier time series Remote sensing signal processing wavelets analysis Multi-temporal images are now of standard use in remote sensing of vegetation during monitoring and classification. Temporal vegetation signatures (i. e., vegetation indices as functions of time) generated, poses many challenges, primarily due to signal to noise-related issues. This study investigates which methods generate the most appropriate smoothed curves of vegetation signatures on MODIS NDVI time series. The filtering techniques compared were the HANTS algorithm which is based on Fourier analyses and Wavelet temporal algorithm which uses the wavelet analysis to generate the smoothed curves. The study was conducted in four different regions of the Minas Gerais State. The smoothed data were used as input data vectors for vegetation classification by means of artificial neural networks for comparison purpose. A comparison of the results was ultimately discussed in this work showing encouraging results and similarity between the two filtering techniques used. 2010 artículo científico 0104-7760 https://www.redalyc.org/articulo.oa?id=74421665002 en http://www.redalyc.org/revista.oa?id=744 CERNE application/pdf Universidade Federal de Lavras CERNE (Brasil) Num.2 Vol.16 |
| title | Mapping deciduous forests by using time series of filtered MODIS NDVI and neural networks |
| topic | Agrociencias Fourier time series Remote sensing signal processing wavelets analysis |
| url | https://www.redalyc.org/articulo.oa?id=74421665002 |