TY - GEN
T1 - SPATIO-TEMPORAL ANALYSIS OF WATER SURFACE TEMPERATURE IN A RESERVOIR AND ITS RELATION WITH WATER QUALITY IN A CLIMATE CHANGE CONTEXT
AU - Ferral, A.
AU - German, A.
AU - Beltramone, G.
AU - Bonansea, M.
AU - Burgos Paci, M.
AU - Saunders de Carvalho, L.
AU - Shimoni, Michal
AU - Roque, M.
AU - Scavuzzo, M.
N1 - Publisher Copyright:
© 2021 IEEE.
PY - 2021
Y1 - 2021
N2 - Remote sensing community is making enormous efforts to implement early warning systems capable for following spatio-temporal patterns of water quality and climate change risk indicators, being Horizon 2030 EOXPOSURE project one of them. This work presents first results of surface temperature Landsat 8 Level 2 Collection 2 products analysis for a reservoir and compare them with field data measurements. A Root Mean Square Error (RMSE) of 1.7oC and a Mean Absolute Percentage Error (MAPE) of 7% were obtained for these products but validation curve resulted not confident at a 95% level. A semiempirical linear model with 94% accuracy, RMSE of 1.1oC and a MAPE of 5% is presented. It was successfully validated with a control group data set obtaining 94% accuracy. A Water Surface Temperature temporal series is shown for the 2013-2020 period and spatio temporal patterns are analyzed and discussed. Water surface temperature behavior in zones with algal bloom occurrence present greater significant values, up to 3oC, than those with clearer water, indicating that water emissitiviy must be revised for these cases.
AB - Remote sensing community is making enormous efforts to implement early warning systems capable for following spatio-temporal patterns of water quality and climate change risk indicators, being Horizon 2030 EOXPOSURE project one of them. This work presents first results of surface temperature Landsat 8 Level 2 Collection 2 products analysis for a reservoir and compare them with field data measurements. A Root Mean Square Error (RMSE) of 1.7oC and a Mean Absolute Percentage Error (MAPE) of 7% were obtained for these products but validation curve resulted not confident at a 95% level. A semiempirical linear model with 94% accuracy, RMSE of 1.1oC and a MAPE of 5% is presented. It was successfully validated with a control group data set obtaining 94% accuracy. A Water Surface Temperature temporal series is shown for the 2013-2020 period and spatio temporal patterns are analyzed and discussed. Water surface temperature behavior in zones with algal bloom occurrence present greater significant values, up to 3oC, than those with clearer water, indicating that water emissitiviy must be revised for these cases.
KW - Algal bloom
KW - Inland water
KW - Landsat 8
KW - Semiempirical modeling
KW - Validation
KW - Water surface temperature
UR - https://www.scopus.com/pages/publications/85124153411
U2 - 10.1109/IGARSS47720.2021.9553255
DO - 10.1109/IGARSS47720.2021.9553255
M3 - Conference contribution
AN - SCOPUS:85124153411
T3 - International Geoscience and Remote Sensing Symposium (IGARSS)
SP - 76
EP - 79
BT - IGARSS 2021 - 2021 IEEE International Geoscience and Remote Sensing Symposium, Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2021 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2021
Y2 - 12 July 2021 through 16 July 2021
ER -