TY - JOUR
T1 - Understanding Sentinel-1 backscatter response to sugarcane yield variability and waterlogging
AU - den Besten, Nadja
AU - Steele Dunne, Susan
AU - Mahmud, Ashfak
AU - Jackson, Daniel
AU - Aouizerats, Benjamin
AU - de Jeu, Richard
AU - Burger, Rogier
AU - Houborg, Rasmus
AU - McGlinchey, Mark
AU - van der Zaag, Pieter
PY - 2023
Y1 - 2023
N2 - Sentinel-1 observes the whole globe every 12 days (6 days when both satellites were operational) and provides a wealth of data relevant to agriculture. Sugarcane cultivators could potentially benefit from these data by using them to assist operational and management practices. However, first, thorough understanding is needed of Sentinel-1 backscatter and its behavior over sugarcane canopies. In this study, we aimed to improve understanding of how Sentinel-1 backscatter responds to sugarcane yield variability and waterlogging. In order to do so we focused on an irrigated sugarcane plantation in Xinavane, Mozambique. In the analysis presented, we assessed different polarizations, their ratio, and benchmarked them against optical indices and passive microwave observations in different seasons. With the help of a large sugarcane yield dataset, we analyzed how backscatter relates to sucrose yield variability in different seasons. We found VV backscatter related to the stalk development, the most important reservoir for sucrose accumulation. In addition, in a season with reported waterlogging, optical and radar observations showed a delay in sugarcane crop development. Further analysis showed the presence of water underneath the canopy caused an increase in all polarizations and the cross ratio (CR). The results imply that Sentinel-1 backscatter contains information on both waterlogging under the canopy as well as sucrose development in the stalk. By isolating and quantifying the impact of waterlogging on backscatter, it will be possible to further quantify sucrose development with backscatter observations and identify waterlogging simultaneously.
AB - Sentinel-1 observes the whole globe every 12 days (6 days when both satellites were operational) and provides a wealth of data relevant to agriculture. Sugarcane cultivators could potentially benefit from these data by using them to assist operational and management practices. However, first, thorough understanding is needed of Sentinel-1 backscatter and its behavior over sugarcane canopies. In this study, we aimed to improve understanding of how Sentinel-1 backscatter responds to sugarcane yield variability and waterlogging. In order to do so we focused on an irrigated sugarcane plantation in Xinavane, Mozambique. In the analysis presented, we assessed different polarizations, their ratio, and benchmarked them against optical indices and passive microwave observations in different seasons. With the help of a large sugarcane yield dataset, we analyzed how backscatter relates to sucrose yield variability in different seasons. We found VV backscatter related to the stalk development, the most important reservoir for sucrose accumulation. In addition, in a season with reported waterlogging, optical and radar observations showed a delay in sugarcane crop development. Further analysis showed the presence of water underneath the canopy caused an increase in all polarizations and the cross ratio (CR). The results imply that Sentinel-1 backscatter contains information on both waterlogging under the canopy as well as sucrose development in the stalk. By isolating and quantifying the impact of waterlogging on backscatter, it will be possible to further quantify sucrose development with backscatter observations and identify waterlogging simultaneously.
KW - Agriculture
KW - Crop monitoring
KW - Sentinel-1
KW - Sucrose
KW - Sugarcane yield
KW - Synthetic Aperture Radar (SAR)
KW - Waterlogging
UR - http://www.scopus.com/inward/record.url?scp=85151023252&partnerID=8YFLogxK
U2 - 10.1016/j.rse.2023.113555
DO - 10.1016/j.rse.2023.113555
M3 - Article
AN - SCOPUS:85151023252
SN - 0034-4257
VL - 290
JO - Remote Sensing of Environment
JF - Remote Sensing of Environment
M1 - 113555
ER -