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Phenological Monitoring of Irrigated Sugarcane Using Google Earth Engine, Time Series, and TIMESAT in the Brazilian Semi-Arid

Authors :
Diego Rosyur Castro Manrique
Pabrício Marcos Oliveira Lopes
Cristina Rodrigues Nascimento
Eberson Pessoa Ribeiro
Anderson Santos da Silva
Source :
AgriEngineering, Vol 6, Iss 4, Pp 3799-3822 (2024)
Publication Year :
2024
Publisher :
MDPI AG, 2024.

Abstract

Monitoring sugarcane phenology is essential since the globalized market requires reliable information on the quantity of raw materials for the industrial production of sugar and alcohol. In this context, the general objective of this study was to evaluate the phenological seasonality of the sugarcane varieties SP 79-1011 and VAP 90-212 observed from the NDVI time series over 19 years (2001–2020) from global databases. In addition, this research had the following specific objectives: (i) to estimate phenological parameters (Start of Season (SOS), End of Season (EOS), Length of Season (LOS), and Peak of Season (POS)) using TIMESAT software in version 3.3 applied to the NDVI time series over 19 years; (ii) to characterize the land use and land cover obtained from the MapBiomas project; (iii) to analyze rainfall variability; and (iv) to validate the sugarcane harvest date (SP 79-1011). This study was carried out in sugarcane growing areas in Juazeiro, Bahia, Brazil. The results showed that the NDVI time series did not follow the rainfall in the region. The sugarcane areas advanced over the savanna formation (Caatinga), reducing them to remnants along the irrigation channels. The comparison of the observed harvest dates of the SP 79-1011 variety to the values estimated with the TIMESAT software showed an excellent fit of 0.99. The mean absolute error in estimating the sugarcane harvest date was approximately ten days, with a performance index of 0.99 and a correlation coefficient of 0.99, significant at a 5% confidence level. The TIMESAT software was able to estimate the phenological parameters of sugarcane using MODIS sensor images processed on the Google Earth Engine platform during the evaluated period (2001 to 2020).

Details

Language :
English
ISSN :
26247402
Volume :
6
Issue :
4
Database :
Directory of Open Access Journals
Journal :
AgriEngineering
Publication Type :
Academic Journal
Accession number :
edsdoj.5c3c670cfb114e95ba7dd7efd08c98bf
Document Type :
article
Full Text :
https://doi.org/10.3390/agriengineering6040217