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RSS FeedsRemote Sensing, Vol. 13, Pages 4920: Sentinel-2 Time Series Analysis for Identification of Underutilized Land in Europe (Remote Sensing)

 
 

3 december 2021 21:59:17

 
Remote Sensing, Vol. 13, Pages 4920: Sentinel-2 Time Series Analysis for Identification of Underutilized Land in Europe (Remote Sensing)
 


Biomass and bioenergy play a central role in Europe’s Green Transition. Currently, biomass is representing half of the renewable energy sources used. While the role of renewables in the energy mix is undisputed, there have been many controversial discussions on the use of biomass for energy due to the “food versus fuel” debate. Using previously underutilized lands for bioenergy is one possibility to prevent this discussion. This study supports the attempts to increase biomass for bioenergy through the provision of improved methods to identify underutilized lands in Europe. We employ advanced analysis methods based on time series modelling using Sentinel-2 (S2) data from 2017 to 2019 in order to distinguish utilized from underutilized land in twelve study areas in different bio-geographical regions (BGR) across Europe. The calculated parameters of the computed model function combined with temporal statistics were used to train a random forest classifier (RF). The achieved overall accuracies (OA) per study area vary between 80.25 and 96.76%, with confidence intervals (CI) ranging between 1.77% and 6.28% at a 95% confidence level. All in all, nearly 500,000 ha of underutilized land potentially available for agricultural bioenergy production were identified in this study, with the greatest amount mapped in Eastern Europe.


 
45 viewsCategory: Geology, Physics
 
Remote Sensing, Vol. 13, Pages 4921: Hybrid Dense Network with Dual Attention for Hyperspectral Image Classification (Remote Sensing)
Remote Sensing, Vol. 13, Pages 4918: Change Detection for Heterogeneous Remote Sensing Images with Improved Training of Hierarchical Extreme Learning Machine (HELM) (Remote Sensing)
 
 
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