Li, Nan, Lopez-Sanchez, Juan M., Fu, Haiqiang, Zhu, Jianjun, Han, Wentao, Xie, Qinghua, Hu, Jun, Xie, Yanzhou
Rice Crop Height Inversion from TanDEM-X PolInSAR Data Using the RVoG Model Combined with the Logistic Growth Equation
Li N, Lopez-Sanchez JM, Fu H, Zhu J, Han W, Xie Q, Hu J, Xie Y. Rice Crop Height Inversion from TanDEM-X PolInSAR Data Using the RVoG Model Combined with the Logistic Growth Equation. Remote Sensing. 2022; 14(20):5109. https://doi.org/10.3390/rs14205109
URI: http://hdl.handle.net/10045/129070
DOI: 10.3390/rs14205109
ISSN: 2072-4292
Abstract: 
The random volume over ground (RVoG) model has been widely used in the field of vegetation height retrieval based on polarimetric interferometric synthetic aperture radar (PolInSAR) data. However, to date, its application in a time-series framework has not been considered. In this study, the logistic growth equation was introduced into the PolInSAR method for the first time to assist in estimating crop height, and an improved inversion scheme for the corresponding RVoG model parameters combined with the logistic growth equation was proposed. This retrieval scheme was tested using a time series of single-pass HH-VV bistatic TanDEM-X data and reference data obtained over rice fields. The effectiveness of the time-series RVoG model based on the logistic growth equation and the convenience of using equation parameters to evaluate vegetation growth status were analyzed at three test plots. The results show that the improved method can effectively monitor the height variation of crops throughout the whole growth cycle and the rice height estimation achieved an accuracy better than when single dates were considered. This proved that the proposed method can reduce the dependence on interferometric sensitivity and can achieve the goal of monitoring the whole process of rice height evolution with only a few PolInSAR observations.
Keywords:PolInSAR, Dynamic monitoring, Logistic growth equation, RVoG, Rice crop height
MDPI
info:eu-repo/semantics/article