## 6 Conclusions
### Perspectives for Future Research
(2019)_ [PERSON] [PERSON]; [PERSON] [PERSON]; [PERSON]; [PERSON] Large-Scale Probabilistic Identification of Boreal Peatlands Using Google Earth Engine, Open-Access Satellite Data, and Machine Learning. _PLoS ONE_**2019**, _14_, e0218165. [CrossRef] [PubMed]
* _[PERSON] et al. (2021)_ [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON] An Integrated Geophysical and GIS Based Approach Improves Estimation of Peatland Carbon Stocks. _Geoderma_**2021**, _402_, 115176. [CrossRef]
* _[PERSON] et al. (2019)_ [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON]; et al. Characterizing Boreal Peatland Plant Composition and Species Diversity with Hyperspectral Remote Sensing. _Remote Sens._**2019**, _11_, 1685. [CrossRef]
* _[PERSON] et al. (2021)_ [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON] Modelling and Upscaling Ecosystem Respiration Using Thermal Cameras and UAVs: Application to a Peatland during and after a Hot Drought. _Agric. For. Meteorol._**2021**, _300_, 108330. [CrossRef]
* _[PERSON] et al. (2019)_ [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON] A UAV-Based Sensor System for Measuring Land Surface Albedo: Tested over a Boreal Peatland Ecosystem. _Drones_**2019**, \(3\), 27. [CrossRef]
* _[PERSON] et al. (2021)_ [PERSON]; [PERSON]; [PERSON] [PERSON]; [PERSON] [PERSON]; [PERSON] Predicting Catchment-Scale Methane Fluxes with Multi-Source Remote Sensing. _Landsc. Ecol._**2021**, _36_, 1177-1195. [CrossRef]
* _[PERSON] et al. (2017)_ [PERSON]; [PERSON]; [PERSON] Assessing the Value of UAV Photogrammetry for Characterizing Terrain in Complex Peatlands. _Remote Sens._**2017**, \(9\), 715. [CrossRef]
* _[PERSON] et al. (2019)_ [PERSON]; [PERSON] [PERSON]; [PERSON]; [PERSON] [PERSON]; [PERSON] [PERSON]; [PERSON] Delineating Northern Peatlands Using Sentinel-I Time Series and Terrain Indices from Local and Regional Digital Elevation Models. _Remote Sens. Environ._**2019**, _231_, 111252. [CrossRef]
* _[PERSON] et al. (2022)_ [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON]; et al. Towards a Monitoring Approach for Understanding permafrost Degradation and Linked Subsidence in Arctic Peatlands. _Remote Sens._**2022**, _14_, 444. [CrossRef]
* _[PERSON] et al. (2018)_ [PERSON]; [PERSON]; [PERSON]; [PERSON] Soil Moisture Monitoring in a Temperate Peatland Using Multi-Sensor Remote Sensing and Linear Mixed Effects. _Remote Sens._**2018**, _10_, 903. [CrossRef]
* _[PERSON] et al. (2017)_ [PERSON]; [PERSON]; [PERSON] Assessing Multitemporal Water-Level Changes with UAV-Based Photogrammetry. _Photogramm. Rec._**2017**, _32_, 424-442. [CrossRef]
* _[PERSON] et al. (2021)_ [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON]. Assessing the Reliability of Peatland GPP Measurements by Remote Sensing: From Plot to Landscape Scale. _Sci. Total Environ._**2021**, _766_, 142613. [CrossRef] [PubMed]  
**Disclaimer/Publisher's Note:** The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.