Identifying drought events in sugarcane using drought indices derived from Modis sensor

Authors

  • Michelle Cristina Araujo Picoli Universidade Estadual de Campinas, Faculdade de Engenharia Agrícola, Caixa Postal 6011, CEP 13083-875 Campinas, SP.
  • Daniel Garbellini Duft Laboratório Nacional de Ciência e Tecnologia do Bioetanol, Caixa Postal 6192, CEP 13083-970 Campinas, SP.
  • Pedro Gerber Machado Universidade Estadual de Campinas, Faculdade de Engenharia Mecânica, Caixa Postal 6122, CEP 13083-970 Campinas, SP.

DOI:

https://doi.org/10.1590/S1678-3921.pab2017.v52.24449

Keywords:

Saccharum officinarum, drought stress, image processing, satellite imagery, SPEI, warning systems

Abstract

The objective of this work was to evaluate the potential of several spectral indices, calculated using moderate resolution imaging spectroradiometer (Modis) images, in identifying drought events in sugarcane (Saccharum officinarum) crops. Images of Terra and Aqua satellites were used to calculate the spectral indices, using visible (red), near infrared, and shortwave infrared bands, and eight indices were selected: NDVI, EVI2, GVMI, NDI6, NDI7, NDWI, SRWI, and MSI. The indices were calculated using images between October and April of the crop years 2007/08, 2008/09, 2009/10, and 2013/14. These indices were then correlated with the standardized precipitation-evapotranspiration index (SPEI), calculated for 1, 3, and 6 months. Four of them had significant correlations with SPEI: GVMI, MSI, NDI7, and NDWI. Spectral indices from Modis sensor on board the Aqua satellite (MYD) were more suited for drought detection, and March provided the most relevant indices for that purpose. Drought indices calculated from Modis sensor data are effective for detecting sugarcane drought events, besides being able to indicate seasonal fluctuations.

Downloads

Additional Files

Published

2017-12-18

How to Cite

Picoli, M. C. A., Duft, D. G., & Machado, P. G. (2017). Identifying drought events in sugarcane using drought indices derived from Modis sensor. Pesquisa Agropecuaria Brasileira, 52(11), 1063–1071. https://doi.org/10.1590/S1678-3921.pab2017.v52.24449

Issue

Section

REMOTE SENSING