MODELLING ABOVE GROUND BIOMASS OF MANGROVE FOREST USING SENTINEL-1 IMAGERY

18 citations as recorded by crossref.

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7. LAND USE LAND COVER CHANGE MAPPING FROM SENTINEL 1B < 2A IMAGERY USING RANDOM FOREST ALGORITHM IN CÔTE D’IVOIRE C. Kouassi et al. 10.3846/gac.2024.18724
8. Potential of Sentinel-1 Data for Spatially and Temporally High-Resolution Detection of Drought Affected Forest Stands P. Kaiser et al. 10.3390/f13122148
9. Mapping Mangrove Above-Ground Carbon Using Multi-Source Remote Sensing Data and Machine Learning Approach in Loh Buaya, Komodo National Park, Indonesia S. Rijal et al. 10.3390/f14010094
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11. Generative Feature Extraction From Sentinel 1 and 2 Data for Prediction of Forest Aboveground Biomass in the Italian Alps P. Naik et al. 10.1109/JSTARS.2022.3179027
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13. Phenology Model of Oil Palm Plantation Based on Biophysical Parameter on Sentinel-1A Using Multiple Linear Regression (MLR) R. Hernawati et al. 10.1007/s12524-024-01973-4
14. Mangrove forest classification and aboveground biomass estimation using an atom search algorithm and adaptive neuro-fuzzy inference system M. Pham et al. 10.1371/journal.pone.0233110
15. Total Stem Biomass Estimation Using Sentinel-1 and -2 Data in a Dense Coniferous Forest of Complex Structure and Terrain N. Georgopoulos et al. 10.3390/f13122157
16. Evaluation of Aboveground Biomass in Mangrove Biosphere Reserves from 1993 to 2023 Under the Influence of Landscape Fragmentation T. Van Pham et al. 10.1007/s12524-024-02027-5
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18. UAV and satellite-based prediction of aboveground biomass in scots pine stands: a comparative analysis of regression and neural network approaches H. Aksoy & A. Günlü 10.1007/s12145-024-01657-0