TY - JOUR
T1 - Estimation of Rice Crop Height from X-and C-Band PolSAR by Metamodel-Based Optimization
AU - Yuzugullu, Onur
AU - Erten, Esra
AU - Hajnsek, Irena
N1 - Publisher Copyright:
© 2008-2012 IEEE.
PY - 2017/1
Y1 - 2017/1
N2 - Rice crops are important in global food economy and are monitored by precise agricultural methods, in which crop morphology in high spatial resolution becomes the point of interest. Synthetic aperture radar (SAR) technology is being used for such agricultural purposes. Using polarimetric SAR (PolSAR) data, plant morphology dependent electromagnetic scattering models can be used to approximate the backscattering behaviors of the crops. However, the inversion of such models for the morphology estimation is complex, ill-posed, and computationally expensive. Here, a metamodel-based probabilistic inversion algorithm is proposed to invert the morphology-based scattering model for the crop biophysical parameter mainly focusing on the crop height estimation. The accuracy of the proposed approach is tested with ground measured biophysical parameters on rice fields in two different bands (X and C) and several channel combinations. Results show that in C-band the combination of the HH and VV channels has the highest overall accuracy through the crop growth cycle. Finally, the proposed metamodel-based probabilistic biophysical parameter retrieval algorithm allows estimation of rice crop height using PolSAR data with high accuracy and low computation cost. This research provides a new perspective on the use of PolSAR data in modern precise agriculture studies.
AB - Rice crops are important in global food economy and are monitored by precise agricultural methods, in which crop morphology in high spatial resolution becomes the point of interest. Synthetic aperture radar (SAR) technology is being used for such agricultural purposes. Using polarimetric SAR (PolSAR) data, plant morphology dependent electromagnetic scattering models can be used to approximate the backscattering behaviors of the crops. However, the inversion of such models for the morphology estimation is complex, ill-posed, and computationally expensive. Here, a metamodel-based probabilistic inversion algorithm is proposed to invert the morphology-based scattering model for the crop biophysical parameter mainly focusing on the crop height estimation. The accuracy of the proposed approach is tested with ground measured biophysical parameters on rice fields in two different bands (X and C) and several channel combinations. Results show that in C-band the combination of the HH and VV channels has the highest overall accuracy through the crop growth cycle. Finally, the proposed metamodel-based probabilistic biophysical parameter retrieval algorithm allows estimation of rice crop height using PolSAR data with high accuracy and low computation cost. This research provides a new perspective on the use of PolSAR data in modern precise agriculture studies.
KW - Agriculture
KW - optimization methods
KW - polarimetry
KW - polynomial approximation
KW - synthetic aperture radar (SAR)
UR - http://www.scopus.com/inward/record.url?scp=84976511966&partnerID=8YFLogxK
U2 - 10.1109/JSTARS.2016.2575362
DO - 10.1109/JSTARS.2016.2575362
M3 - Article
AN - SCOPUS:84976511966
SN - 1939-1404
VL - 10
SP - 194
EP - 204
JO - IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
JF - IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
IS - 1
M1 - 7501808
ER -