| Full text | |
| Author(s): |
Dias, Danielle
[1]
;
Dias, Ulisses
[2]
;
Menini, Nathalia
[1]
;
Lamparelli, Rubens
[3]
;
Le Maire, Guerric
[4]
;
Torres, Ricardo da S.
[5]
Total Authors: 6
|
| Affiliation: | [1] Univ Campinas UNICAMP, Inst Comp, BR-13083970 Campinas - Brazil
[2] Univ Campinas UNICAMP, Sch Technol, BR-13484350 Limeira - Brazil
[3] Univ Campinas UNICAMP, Nucleo Interdisciplinar Planejamento Energet, BR-13083970 Campinas - Brazil
[4] Univ Montpellier, Eco&Sols, CIRAD, INRA, IRD, Montpellier SupAgro, F-34000 Montpellier - France
[5] Norwegian Univ Sci & Technol NTNU, Dept ICT & Nat Sci, Alesund - Norway
Total Affiliations: 5
|
| Document type: | Journal article |
| Source: | IEEE Geoscience and Remote Sensing Letters; v. 17, n. 8, p. 1450-1454, AUG 2020. |
| Web of Science Citations: | 1 |
| Abstract | |
Pixelwise image classification based on time series profiles has been very effective in several applications. In this letter, we investigate recently proposed image-based time series encoding approaches {[}e.g., Gramian angular summation field/Gramian angular difference field (GASF/GADF) and Markov transition field (MTF)] to support the identification of eucalyptus regions in remote sensing images. We perform a comparative study concerning the combination of image-based representations suitable for encoding the most important time series patterns with the ability of state-of-the-art deep-learning-based approaches for characterizing image visual properties. The comparative study demonstrates that the evaluated image representations, combined with different deep learning feature extractors lead to highly effective classification results, which are superior to those of recently proposed methods for time-series-based eucalyptus plantation detection. (AU) | |
| FAPESP's process: | 14/50715-9 - Characterizing and predicting biomass production in sugarcane and eucalyptus plantations in Brazil |
| Grantee: | Rubens Augusto Camargo Lamparelli |
| Support Opportunities: | Research Grants - Research Partnership for Technological Innovation - PITE |
| FAPESP's process: | 17/20945-0 - Multi-user equipment approved in great 16/50250-1: local positioning system |
| Grantee: | Sergio Augusto Cunha |
| Support Opportunities: | Multi-user Equipment Program |
| FAPESP's process: | 16/50250-1 - The secret of playing football: Brazil versus the Netherlands |
| Grantee: | Sergio Augusto Cunha |
| Support Opportunities: | Research Projects - Thematic Grants |
| FAPESP's process: | 13/50155-0 - Combining new technologies to monitor phenology from leaves to ecosystems |
| Grantee: | Leonor Patricia Cerdeira Morellato |
| Support Opportunities: | Research Program on Global Climate Change - University-Industry Cooperative Research (PITE) |
| FAPESP's process: | 15/24494-8 - Communications and processing of big data in cloud and fog computing |
| Grantee: | Nelson Luis Saldanha da Fonseca |
| Support Opportunities: | Research Projects - Thematic Grants |
| FAPESP's process: | 14/12236-1 - AnImaLS: Annotation of Images in Large Scale: what can machines and specialists learn from interaction? |
| Grantee: | Alexandre Xavier Falcão |
| Support Opportunities: | Research Projects - Thematic Grants |