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

17 citations as recorded by crossref.

1. Estimating Aboveground Forest Biomass Using Radar Methods I. Babiy et al. 10.1134/S1995425522050031
2. Modelling above ground biomass of Indian mangrove forest using dual-pol SAR data B. Vaghela et al. 10.1016/j.rsase.2020.100457
3. Estimation, Spatiotemporal Dynamics, and Driving Factors of Grassland Biomass Carbon Storage Based on Machine Learning Methods: A Case Study of the Hulunbuir Grassland Q. Zhi et al. 10.3390/rs16193709
4. Mangrove Resource Mapping Using Remote Sensing in the Philippines: A Systematic Review and Meta-Analysis F. Pillodar et al. 10.3390/f14061080
5. Mapping mangrove above ground carbon stock of benoa bay bali using sentinel-1 satellite imagery Z. Hidayah et al. 10.1088/1755-1315/1298/1/012013
6. Interpreting the Response of Forest Stock Volume with Dual Polarization SAR Images in Boreal Coniferous Planted Forest in the Non-Growing Season H. Zheng et al. 10.3390/f14091700
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
10. Improving the accuracy of mangrove forest mapping using sentinel image and developed classification algorithm based on machine learning A. Purwanto et al. 10.1080/14498596.2024.2337747
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
12. Phenology impact on mangrove area estimation pre- and post a cyclone in Fiji using Sentinel-1 imagery J. Cameron et al. 10.1007/s11852-022-00918-8
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
17. Modelling biophysical parameters of Indian Sundarbans mangroves using fully polarimetric L-band Synthetic Aperture Radar data and ground observations T. Kumar et al. 10.1007/s11852-023-00994-4