A seq2seq-based forest height estimation for zero-baseline repeat-pass polinsar data

IGARSS 2023 - 2023 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM(2023)

Cited 0|Views9
No score
Abstract
This paper proposes a forest height estimation method based on Seq2Seq models for zero-baseline repeat-pass PolInSAR acquisitions. In zero-baseline configuration, the polarimetric coherence of RMoG model can be refined as a real function varying with ground to volume ratio (polarization) since the phase information is negligible. The primary decorrelation in this real polarimetric coherence is derived from the temporal changes, which has an intuitive connection with forest height and can be further used for forest height estimation. An initial attempt is to estimate the sequence of polarimetric coherence and ground to volume ratio directly from the PolInSAR data and then extract the forest height from the estimated sequence based on the nonlinear functions originating from the RMoG model. However, large discrepancies between the estimated and the model-based sequences make it hard to retrieve the forest height accurately. Thereby, a trained Seq2Seq model is used so that the characteristics of the output sequence can be easily recognized by the model for forest height estimation. Experiments are conducted on PolInSAR data simulated by PolSARproSim+ and results indicate that forest height can be effectively extracted from zero-baseline repeat-pass data with the proposed method.
More
Translated text
Key words
PolInSAR,temporal decorrelation,zero-baseline,repeat-pass,forest height,Seq2Seq model
AI Read Science
Must-Reading Tree
Example
Generate MRT to find the research sequence of this paper
Chat Paper
Summary is being generated by the instructions you defined