# Remote Sensing and Machine Learning Tools to Support
## Abbreviations
[CrossRef]
* (134) [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON] A Novel Landsat-Based Automated Mapping of Marsh Wetland in the Headwaters of the Brahmapurta, Ganges and Indus Rivers, Southwestern Tibetan Plateau. _Int. J. Appl. Earth Obs. Geoinf._**2021**, _103_, 102481. [CrossRef]
* (135) [PERSON]; [PERSON]; [PERSON] [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON] Monthly Estimation of the Surface Water Extent in France at a 10-m Resolution Using Sentinel-2 Data. _Remote Sens. Environ._**2020**, _244_, 111803. [CrossRef]
* (136) [PERSON]; [PERSON]; [PERSON] Deep Learning. _Nature_**2015**, _521_, 436-444. [CrossRef] [PubMed]
* (137) [PERSON]; [PERSON]; [PERSON]; [PERSON] Application of Convolutional Neural Network in Classification of High Resolution Agricultural Remote Sensing Images. _ISPRS -Intl. Arch. Photogramm. Remote Sens. Spat. Inf. Sci._**2017**, _42W7_, 989-992. [CrossRef]
* (138) [PERSON]; [PERSON]; [PERSON]; [PERSON] Deep Learning Using Physically-Informed Input Data for Wetland Identification. _Environ. Model. Softw._**2020**, _126_, 104665. [CrossRef]
* (139) [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON] Bagging and Boosting Ensemble Classifiers for Classification of Multispectral, Hyperspectral and PolSAR Data: A Comparative Evaluation. _Remote Sens._**2021**, _13_, 4405. [CrossRef]
* (140) [PERSON]; [PERSON] Deep Forest: Towards An Alternative to Deep Neural Networks. In Proceedings of the 2017 International Joint Conference on Artificial Intelligence, Melbourne, Australia, 19-25 August 2017; pp. 3553-3559. * (141) [PERSON]; [PERSON] An SVM Ensemble Approach Combining Spectral, Structural, and Semantic Features for the Classification of High-Resolution Remotely Sensed Imagery. _IEEE Trans. Geosci. Remote Sens._**2013**, _51_, 257-272. [CrossRef]
* (142) [PERSON]; [PERSON] Meta-Analysis of Deep Neural Networks in Remote Sensing: A Comparative Study of Mono-Temporal Classification to Support Vector Machines. _ISPRS J. Photogramm. Remote Sens._**2019**, _152_, 192-210. [CrossRef]
* (143) [PERSON]; [PERSON]; [PERSON]; [PERSON] [PERSON] Support Vector Reduction in SVM Algorithm for Abrupt Change Detection in Remote Sensing. _IEEE Geosci. Remote Sens. Lett._**2009**, \(6\), 606-610. [CrossRef]
* (144) [PERSON]; [PERSON]; [PERSON]; [PERSON] Wetland Landscape Spatio-Temporal Degradation Dynamics Using the New Google Earth Engine Cloud-Based Platform: Opportunities for Non-Specialists in Remote Sensing. _Trans. ASABE_**2016**, _59_, 1333-1344. * (145) [PERSON] [PERSON]; [PERSON] [PERSON]; [PERSON] [PERSON]; [PERSON] [PERSON]; [PERSON] [PERSON]; [PERSON]; [PERSON]; [PERSON] Multitemporal Optical and Radar Metrics for Wetland Mapping at National Level in Albania. _Heliyon_**2020**, \(6\), e04496. [CrossRef]
* (146) [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON] [PERSON]; [PERSON] Assessing Nebraska Playa Wetland Inmutation Status during 1985-2015 Using Landsat Data and Google Earth Engine. _Environ. Monit. Assess._**2016**, _188_, 654. [CrossRef]
* (147) [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON] Leveraging Google Earth Engine User Interface for Semiautomated Wetland Classification in the Great Lakes Basin at 10 m With Optical and Radar Geospatial Datasets. _IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens._**2020**, _13_, 6008-6018. [CrossRef]* _Farda (2017)_ _Farda, N.M. Multi-Temporal Land Use Mapping of Coastal Wetlands Area Using Machine Learning in Google Earth Engine. IOP Conf. Ser. Earth Environ. Sci._**2017**_, 98_, 012042. [CrossRef]
* _[PERSON] _et al._ (2020)_ _[PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON] Mapping Coastal Wetlands of the Bohai Rim at a Spatial Resolution of 10 m Using Multiple Open-Access Satellite Data and Terrain Indices. Remote Sens._**2020**, _12_, 4114. [CrossRef]
* _[PERSON] _et al._ (2018)_ _[PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON] A Remote Sensing-Based Model of Tidal Marsh Aboveground Carbon Stocks for the Conterminous United States.