Moving Toward L‐Band NASA‐ISRO SAR Mission (NISAR) Dense Time Series: Multipolarization Object‐Based Classification of Wetlands Using Two Machine Learning Algorithms

Moving Toward L‐Band NASA‐ISRO SAR Mission (NISAR) Dense Time Series: Multipolarization Object‐Based Classification of Wetlands Using Two Machine Learning Algorithms

Abstract Given the key role wetlands play in climate regulation and shoreline stabilization, identifying their spatial distribution is essential for the management, restoration, and protection of these invaluable ecosystems. The increasing availability of high spatial and temporal resolution optical...

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Bibliographic Details
Main Authors: Sarina Adeli, Bahram Salehi, Masoud Mahdianpari, Lindi J. Quackenbush, Bruce Chapman
Format: article
Language:EN
Published: American Geophysical Union (AGU) 2021
Subjects:
NISAR
machine learning
random forest
SVM
classification
wetland mapping
Astronomy
QB1-991
Geology
QE1-996.5
Online Access:https://doaj.org/article/5b9df8647fad4a7dbf69ab567c1d105f
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https://doaj.org/article/5b9df8647fad4a7dbf69ab567c1d105f

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