TY - GEN
T1 - A semi-empirical model to estimate biophysical parameters in southern Mexico
AU - Constantino-Recillas, Daniel Enrique
AU - Monsiváis-Huertero, Alejandro
AU - Jiménez-Escalona, José Carlos
AU - Zempoaltecatl-Ramirez, Enrique
AU - Magagi, Ramata
AU - Goïta, Kalifa
N1 - Publisher Copyright:
© 2018 IEEE.
PY - 2018/10/31
Y1 - 2018/10/31
N2 - The monitoring of tropical ecosystems is complex due to the type of terrain and adverse weather conditions present during most of the year. This paper proposes the development and implementation of a methodology based on RADARSAT-2 images and a semi-empirical model to obtain surface parameters in a tropical forest. The model takes into consideration the sensor configuration, and vegetation and soil parameters to represent the behavior of the wave in the scene. To retrieve the surface parameters, the model is implemented in an optimization framework using all polarizations (HH, HV, VH and VV). Finally, as outputs of the optimization process, we obtain the trunk diameter (Dt), the crow height (hc), and the optical penetration depth (τ). By using τ, the vegetation water content (VWC) is estimated. The accuracy of this methodology is about 83% when compared to ground data.
AB - The monitoring of tropical ecosystems is complex due to the type of terrain and adverse weather conditions present during most of the year. This paper proposes the development and implementation of a methodology based on RADARSAT-2 images and a semi-empirical model to obtain surface parameters in a tropical forest. The model takes into consideration the sensor configuration, and vegetation and soil parameters to represent the behavior of the wave in the scene. To retrieve the surface parameters, the model is implemented in an optimization framework using all polarizations (HH, HV, VH and VV). Finally, as outputs of the optimization process, we obtain the trunk diameter (Dt), the crow height (hc), and the optical penetration depth (τ). By using τ, the vegetation water content (VWC) is estimated. The accuracy of this methodology is about 83% when compared to ground data.
KW - RADARSAT-2
KW - Semi-empirical model
KW - Surface parameters
KW - Tropical ecosystems
UR - http://www.scopus.com/inward/record.url?scp=85064177905&partnerID=8YFLogxK
U2 - 10.1109/IGARSS.2018.8518991
DO - 10.1109/IGARSS.2018.8518991
M3 - Contribución a la conferencia
AN - SCOPUS:85064177905
T3 - International Geoscience and Remote Sensing Symposium (IGARSS)
SP - 5344
EP - 5347
BT - 2018 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2018 - Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 38th Annual IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2018
Y2 - 22 July 2018 through 27 July 2018
ER -