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| Format: | Artículo científico |
| Language: | en |
| Published: |
Universidade Federal de Uberlândia
2019
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| Online Access: | https://www.redalyc.org/articulo.oa?id=321363062032 https://www.redalyc.org/journal/3213/321363062032/ https://www.redalyc.org/journal/3213/321363062032/html/ https://www.redalyc.org/journal/3213/321363062032/321363062032.epub https://www.redalyc.org/journal/3213/321363062032/movil |
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| _version_ | 1866590741608792064 |
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| author | Cristiane Batista Salgado |
| author_facet | Cristiane Batista Salgado |
| contents | Cloud interference analysis in the classification of MODIS-NDVI temporal series in the Amazon region, municipality of Capixaba, Acre - Brazil Cristiane Batista Salgado Osmar Abílio de Carvalho Roberto Arnaldo Trancoso Gomes Renato Fontes Guimarães Geografía Social Amazon Cloud cover Time series This research aimed to analyze MODIS-NDVI time series classifications, with three different algorithms, seeking to identify the ideal amount of images for studies in environments with high cloudiness rates. The spatial cut used for the study was the municipality of Capixaba, located in the state of Acre in the Amazon region. For each NDVI image, a cloud mask was constructed. This mask allowed to organize the temporal cube by cloud coverage quantity. Thus, the impact of eliminating high cloud images for the series classification was tested. At each cut, the temporal cube was redone, evaluating results for a new set of bands. For the accuracy analysis, the Kappa coefficient was adopted. A total of 84 classifications were made. Three classification algorithms (Minimum Distance, Spectral Angle Mapper and Spectral Correlation Mapper) and 4 different interactions between classes and samples were tested. Over the period analyzed, approximately 80% of images showed cloud cover above 90%. The tests showed that the removal of the images with cloud increased the quality of the classification, and the best results were found in small cubes (10 to 35 images) and with low cloud cover (0 to ~ 6%). The Minimum Distance algorithm presented the lowest coefficient of variation, showing a lower sensitivity to the presence of clouds. 2019 artículo científico 0103-1570 https://www.redalyc.org/articulo.oa?id=321363062032 https://www.redalyc.org/journal/3213/321363062032/ https://www.redalyc.org/journal/3213/321363062032/html/ https://www.redalyc.org/journal/3213/321363062032/321363062032.epub https://www.redalyc.org/journal/3213/321363062032/movil 10.14393/SN-v31-2019-47062 en http://www.redalyc.org/revista.oa?id=3213 Sociedade & Natureza application/pdf Universidade Federal de Uberlândia Sociedade & Natureza (Brasil) Vol.31 |
| format | Artículo científico |
| id | redalyc_321363062032 |
| language | en |
| publishDate | 2019 |
| publisher | Universidade Federal de Uberlândia |
| spellingShingle | Cloud interference analysis in the classification of MODIS-NDVI temporal series in the Amazon region, municipality of Capixaba, Acre - Brazil Cristiane Batista Salgado Geografía Social Amazon Cloud cover Time series Cloud interference analysis in the classification of MODIS-NDVI temporal series in the Amazon region, municipality of Capixaba, Acre - Brazil Cristiane Batista Salgado Osmar Abílio de Carvalho Roberto Arnaldo Trancoso Gomes Renato Fontes Guimarães Geografía Social Amazon Cloud cover Time series This research aimed to analyze MODIS-NDVI time series classifications, with three different algorithms, seeking to identify the ideal amount of images for studies in environments with high cloudiness rates. The spatial cut used for the study was the municipality of Capixaba, located in the state of Acre in the Amazon region. For each NDVI image, a cloud mask was constructed. This mask allowed to organize the temporal cube by cloud coverage quantity. Thus, the impact of eliminating high cloud images for the series classification was tested. At each cut, the temporal cube was redone, evaluating results for a new set of bands. For the accuracy analysis, the Kappa coefficient was adopted. A total of 84 classifications were made. Three classification algorithms (Minimum Distance, Spectral Angle Mapper and Spectral Correlation Mapper) and 4 different interactions between classes and samples were tested. Over the period analyzed, approximately 80% of images showed cloud cover above 90%. The tests showed that the removal of the images with cloud increased the quality of the classification, and the best results were found in small cubes (10 to 35 images) and with low cloud cover (0 to ~ 6%). The Minimum Distance algorithm presented the lowest coefficient of variation, showing a lower sensitivity to the presence of clouds. 2019 artículo científico 0103-1570 https://www.redalyc.org/articulo.oa?id=321363062032 https://www.redalyc.org/journal/3213/321363062032/ https://www.redalyc.org/journal/3213/321363062032/html/ https://www.redalyc.org/journal/3213/321363062032/321363062032.epub https://www.redalyc.org/journal/3213/321363062032/movil 10.14393/SN-v31-2019-47062 en http://www.redalyc.org/revista.oa?id=3213 Sociedade & Natureza application/pdf Universidade Federal de Uberlândia Sociedade & Natureza (Brasil) Vol.31 |
| title | Cloud interference analysis in the classification of MODIS-NDVI temporal series in the Amazon region, municipality of Capixaba, Acre - Brazil |
| topic | Geografía Social Amazon Cloud cover Time series |
| url | https://www.redalyc.org/articulo.oa?id=321363062032 https://www.redalyc.org/journal/3213/321363062032/ https://www.redalyc.org/journal/3213/321363062032/html/ https://www.redalyc.org/journal/3213/321363062032/321363062032.epub https://www.redalyc.org/journal/3213/321363062032/movil |