# Remote Sensing and Machine Learning Tools to Support
## Abbreviations
ISPRS J. Photogramm. Remote Sens._**2018**, _139_, 255-271. [CrossRef]
* _[PERSON] _et al._ (2021)_ _[PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON] A Classification of Tidal Flat Wetland Vegetation Combining Phenological Features with Google Earth Engine. Remote Sens. **2021**, _13_, 443. [CrossRef]
* _[PERSON] _et al._ (2021)_ _[PERSON]; [PERSON]; [PERSON] A Fused Radar-Optical Approach for Mapping Wetlands and Deepwaters of the Mid-Atlantic and Gulf Coast Regions of the United States. Remote Sens. **2021**, _13_, 2495. [CrossRef]
* _[PERSON] _et al._ (2019)_ _[PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON] Canadian Wetland Inventory Using Google Earth Engine: The First Map and Preliminary Results. Remote Sens. **2019**, _11_, 842. [CrossRef]
* _[PERSON] _et al._ (2021)_ _[PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON] Tracking Historical Wetland Changes in the China Side of the Amur River Basin Based on Landsat Imagery and Training Samples Migration. Remote Sens. **2021**, _13_, 2161. [CrossRef]
* _[PERSON] _et al._ (2021)_ _[PERSON]; [PERSON]; [PERSON] [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON] Wetland Change Analysis in Alberta, Canada Using Four Decades of Landsat Imagery. IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens. **2021**, _14_, 10314-10335. [CrossRef]
* _[PERSON] _et al._ (2019)_ _[PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON] [PERSON] A Generalized Supervised Classification Scheme to Produce Provincial Wetland Inventory Maps: An Application of Google Earth Engine for Big Geo Data Processing. Big Earth Data**2019**, \(3\), 378-394. [CrossRef]
* _[PERSON] _et al._ (2021)_ _[PERSON]; [PERSON]; [PERSON]; [PERSON] A Training Sample Migration Method for Wetland Mapping and Monitoring Using Sentinel Data in Google Earth Engine. Remote Sens. **2021**, _13_, 4169. [CrossRef]
* _[PERSON] _et al._ (2019)_ _[PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON] Mapping Wetland Dynamics With SAR-Based Change Detection in the Cloud. IEEE Geosci. Remote Sens. Lett. **2019**, _16_, 1536-1539. [CrossRef]
* _[PERSON] et al._ (2021)_ _[PERSON]; [PERSON]; [PERSON]; [PERSON] Mapping the Vegetation Distribution and Dynamics of a Wetland Using Adaptive-Stacking and Google Earth Engine Based on Multi-Source Remote Sensing Data. Int. J. Appl. Earth Obs. Geeinf. **2021**, _102_, 102453. [CrossRef]
* _[PERSON] _et al._ (2020)_ _[PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON] [PERSON] Big Data for a Big Country: The First Generation of Canadian Wetland Inventory Map at a Spatial Resolution of 10-m Using Sentinel-1 and Sentinel-2 Data on the Google Earth Engine Cloud Computing Platform. Can. J. Remote Sens. **2020**, _46_, 15-33. [CrossRef]
* _[PERSON] _et al._ (2021)_ _[PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON] Using Time Series Optical and SAR Data to Assess the Impact of Historical Wetland Change on Current Wetland in Zhenlai County, Jilin Province, China. Remote Sens. **2021**, _13_, 4514. [CrossRef]
* _[PERSON] _et al._ (2021)_ _[PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON] [PERSON]; [PERSON]; et al. Evaluation of the Landsat-Based Canadian Wetland Inventory Map Using Multiple Sources: Challenges of Large-Scale Wetland Classification Using Remote Sensing. IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens. **2021**, _14_, 32-52. [CrossRef]
* _[PERSON] _et al._ (2020)_ _[PERSON]; [PERSON] Salt Marsh Monitoring along the Mid-Atlantic Coast by Google Earth Engine Enabled Time Series. PLoS ONE**2020**, _15_, e0229605. [CrossRef]
* _[PERSON] _et al._ (2020)_ _[PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON] Wetland Mapping With Multitemporal Sentinel Radar Remote Sensing In The Southeast Region Of Brazil. In Proceedings of the 2020 IEEE Latin American GRSS & ISPRS Remote Sensing Conference (LAGIRS), Santiago, Chile, 21-26 March 2020; pp. 669-674.