TY - GEN
T1 - Understanding the Backscattering from Sentinel-1 over a Growing Season of Corn in Central Mexico Using the Thexmex Datasets
AU - Constantino-Recillas, Daniel Enrique
AU - Arizmendi-Vasconcelos, Eduardo
AU - Monsivais-Huertero, Alejandro
AU - Jimenez-Escalona, Jose Carlos
AU - Torres-Gomez, Aura Citlalli
AU - De La Rosa-Montero, Ivan Edmundo
AU - Hernandez-Sanchez, Juan Carlos
AU - Villalobos-Martinez, Roberto Ivan
AU - Zempoaltecatl-Ramirez, Enrique
AU - Aparicio-Garcia, Ramon Sidonio
AU - Huerta-Batizv, Hector Ernesto
AU - Zambrano-Gallardo, Cira Francisca
AU - Sanchez-Villanueva, Carlos Rodolfo
AU - Arizmendi-Vasconcelos, Leonardo
AU - Sauce-Rangel, Victor Manuel
AU - Judge, Jasmeet
N1 - Publisher Copyright:
© 2020 IEEE.
PY - 2020/9/26
Y1 - 2020/9/26
N2 - The proper management of resources allows better yields from crops. Within the field of remote sensing, one of the sectors benefited is the agricultural sector because changes in biodiversity can be quantified through the observation and temporary evaluation of satellite images. For example, different studies have shown the potential of using information from the ESA Sentinel-1 satellite to monitor the growing crops. The backscatter observations obtained from Sentinel 1A and Sentinel 1B satellites showed greater sensitivity to the change in vegetation according to the correlation study, it is shown that the correlation between vegetation parameters and Sentinel-1 observations is greater than 0.8. The application of this methodology allows the understanding of the temporal variability over corn fields in the central zone of Mexico and allows seeing the potential of the Sentinel-1 constellation for the monitoring of natural resources. The application of this methodology allows the understanding of the temporal variability over corn fields in the central zone of Mexico and allows seeing the potential of the Sentinel-1 constellation for the monitoring of natural resources.
AB - The proper management of resources allows better yields from crops. Within the field of remote sensing, one of the sectors benefited is the agricultural sector because changes in biodiversity can be quantified through the observation and temporary evaluation of satellite images. For example, different studies have shown the potential of using information from the ESA Sentinel-1 satellite to monitor the growing crops. The backscatter observations obtained from Sentinel 1A and Sentinel 1B satellites showed greater sensitivity to the change in vegetation according to the correlation study, it is shown that the correlation between vegetation parameters and Sentinel-1 observations is greater than 0.8. The application of this methodology allows the understanding of the temporal variability over corn fields in the central zone of Mexico and allows seeing the potential of the Sentinel-1 constellation for the monitoring of natural resources. The application of this methodology allows the understanding of the temporal variability over corn fields in the central zone of Mexico and allows seeing the potential of the Sentinel-1 constellation for the monitoring of natural resources.
KW - Sentinel 1A
KW - Sentinel 1B
KW - corn fields
KW - monitoring
UR - http://www.scopus.com/inward/record.url?scp=85102011827&partnerID=8YFLogxK
U2 - 10.1109/IGARSS39084.2020.9323299
DO - 10.1109/IGARSS39084.2020.9323299
M3 - Contribución a la conferencia
AN - SCOPUS:85102011827
T3 - International Geoscience and Remote Sensing Symposium (IGARSS)
SP - 4526
EP - 4529
BT - 2020 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2020 - Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2020 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2020
Y2 - 26 September 2020 through 2 October 2020
ER -