# Remote Sensing and Machine Learning Tools to Support
## Abbreviations
(2007) [PERSON]; [PERSON]; [PERSON]; [PERSON] Mapping and Classification of Peatland on the Isle of Lewis Using Landsat ETH+. _Scott. Geogr. J._**2007**, _123_, 173-192. [CrossRef]
* [PERSON] et al. (2021) [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON] Kernel Low-Rank Representation with Elastic Net for China Coastal Wetland Land Cover Classification Using GF-5 Hyperspectral Imagery. _ISPRS J. Photogramm. Remote Sens._**2021**, _171_, 238-252. [CrossRef]
* [PERSON] et al. (2021) [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON] Coastal Wetland Classification with GF-3 Polarimetric SAR Imagery by Using Object-Oriented Random Forest Algorithm. _Sensors_**2021**, _21_, 3395. [CrossRef]
* [PERSON] and [PERSON] (2008) [PERSON]; [PERSON] Using C-Band Synthetic Aperture Radar Data to Monitor Forested Wetland Hydrology in Maryland's Coastal Plain, USA. _IEEE Trans. Geosci. Remote Sens._**2008**, _46_, 535-546. [CrossRef]
* [PERSON] et al. (2011) [PERSON]; [PERSON]. Use of Multi-Sensor Data to Identify and Map Tropical Coastal Wetlands in the Amazon of Northern Brazil. _Wetlands_**2011**, _31_, 11-23. [CrossRef]* [PERSON] et al. (2017) [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON] Contributions of C-Band SAR Data and Polarimetric Decompositions to Subarctic Boreal Peatland Mapping. _IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens._**2017**, _10_, 1467-1482. [CrossRef]
* [PERSON] et al. (2017) [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON] [PERSON]; [PERSON] Moving to the RADARSAT Constellation Mission: Comparing Synthesized Compact Polarimetry and Dual Polarimetry Data with Fully Polarimetric RADARSAT-2 Data for Image Classification of Peatlands. _Remote Sens._**2017**, \(9\), 573. [CrossRef]
* [PERSON] et al. (2015) [PERSON]; [PERSON]; [PERSON] [PERSON]; [PERSON]; [PERSON] [PERSON] A Collection of SAR Methodologies for Monitoring Wetlands. _Remote Sens._**2015**, \(7\), 7615-7645. [CrossRef]
* [PERSON] et al. (2014) [PERSON] [PERSON]; [PERSON] [PERSON]; [PERSON]; [PERSON]; [PERSON] [PERSON] A Decision-Tree Classification for Low-Lying Complex Land Cover Types within the Zone of Discontinuous Permarfrost. _Remote Sens. Environ._**2014**, _143_, 73-84. [CrossRef]
* [PERSON] et al. (2022) [PERSON]; [PERSON]; [PERSON] Meta-Learning for Wetland Classification Using a Combination of Sentinel-1 and Sentinel-2 Imagery. _ISPRS Ann. Photogramm. Remote Sens. Spat. Inf. Sci._**2022**, _V-3-2022_, 47-52. [CrossRef]
* [PERSON] et al. (2022) [PERSON]; [PERSON] [PERSON]; [PERSON]; [PERSON]; [PERSON] WetNet: A Spatial-Temporal Ensemble Deep Learning Model for Wetland Classification Using Sentinel-1 and Sentinel-2. _IEEE Trans. Geosci. Remote Sens._**2022**, _60_, 1-14. [CrossRef]
* [PERSON] and [PERSON] (2013) [PERSON]; [PERSON] Wetland Mapping with LiDAR Derivatives, SAR Polarimetric Decompositions, and LiDAR-SAR Fusion Using a Random Forest Classifier. _Can. J. Remote Sens._**2013**, _39_, 290-307. [CrossRef]
* [PERSON] et al. (2015) [PERSON]; [PERSON]; [PERSON]; [PERSON] Use of Bi-Seasonal Landsat-8 Imagery for Mapping Marshall Plant Community Combinations at the Regional Scale. _Wetlands_**2015**, _35_, 1043-1054. [CrossRef]
* [PERSON] and [PERSON] (2018) [PERSON]; [PERSON] Monthly Analysis of Wetlands Dynamics Using Remote Sensing Data. _ISPRS Int. J. Geo-Inf._**2018**, \(7\), 411. [CrossRef]
* [PERSON] et al. (2021) [PERSON]; [PERSON]; [PERSON]; [PERSON] [PERSON]; [PERSON] [PERSON]; [PERSON] Fusing Multisource Data to Estimate the Effects of Urbanization, Sea Level Rise, and Hurricane Impacts on Long-Term Wetland Change Dynamics. _IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens._**2021**, _14_, 1768-1782. [CrossRef]
* [PERSON] and [PERSON] (2019) [PERSON]; [PERSON] The Integration of Multi-Source Remotely-Sensed Data in Support of the Classification of Wetlands. _Remote Sens._**2019**, _11_, 1537. [CrossRef]
* [PERSON] et al. (2015) [PERSON]; [PERSON]; [PERSON] Combined Use of LiDAR Data and Multispectral Earth Observation Imagery for Wetland Habitat Mapping. _Int. J. Appl. Earth Obs. Geinf._**2015**, _37_, 56-64.