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A novel coherence optimization algorithm for forest height inversion using single-baseline PolInSAR images
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Forest height is one of the influential information for the management of forest cover and is also one of the criteria to evaluate the growth of organisms in the forest ecosystem. This paper suggests a novel coherence optimization algorithm to increase the accuracy of forest height estimation using the L-band PolInSAR images. First, the ground phase and coherence line are determined based on the mean of the coherence set. Then, the proposed algorithm is developed by adding more forced conditions to determine the volume-only coefficient coherence optimization. Finally, the forest height and extinction coefficient can be extracted by comparing the volume-only optimal coherence coefficient with the values in the look-up table. The effectiveness of the proposed method was evaluated with PolInSAR simulated and spaceborne data. Experimental results show that the proposed method has improved the accuracy of estimated forest height by more than 0.9m compared with the forest height retrieval algorithm by Tayebe.
Academy of Military Science and Technology
Title: A novel coherence optimization algorithm for forest height inversion using single-baseline PolInSAR images
Description:
Forest height is one of the influential information for the management of forest cover and is also one of the criteria to evaluate the growth of organisms in the forest ecosystem.
This paper suggests a novel coherence optimization algorithm to increase the accuracy of forest height estimation using the L-band PolInSAR images.
First, the ground phase and coherence line are determined based on the mean of the coherence set.
Then, the proposed algorithm is developed by adding more forced conditions to determine the volume-only coefficient coherence optimization.
Finally, the forest height and extinction coefficient can be extracted by comparing the volume-only optimal coherence coefficient with the values in the look-up table.
The effectiveness of the proposed method was evaluated with PolInSAR simulated and spaceborne data.
Experimental results show that the proposed method has improved the accuracy of estimated forest height by more than 0.
9m compared with the forest height retrieval algorithm by Tayebe.
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