ESTIMATION OF MANGROVE FOREST ABOVEGROUND BIOMASS USING MULTISPECTRAL BANDS, VEGETATION INDICES AND BIOPHYSICAL VARIABLES DERIVED FROM OPTICAL SATELLITE IMAGERIES: RAPIDEYE, PLANETSCOPE AND SENTINEL-2

53 citations as recorded by crossref.

1. Gray mold and anthracnose disease detection on strawberry leaves using hyperspectral imaging B. Zhang et al. 10.1186/s13007-023-01123-w
2. Aboveground biomass estimation and mapping using Sentinel-2 data in a dry afromontane forest B. Tetemke et al. 10.1080/01431161.2024.2410958
3. Use of Remotely Sensed Data to Enhance Estimation of Aboveground Biomass for the Dry Afromontane Forest in South-Central Ethiopia H. Taddese et al. 10.3390/rs12203335
4. Identifying Spatial Variation of Carbon Stock in a Warm Temperate Forest in Central Japan Using Sentinel-2 and Digital Elevation Model Data H. Pei et al. 10.3390/rs15081997
5. Mapping the Above-Ground Biomass of Rhizophora apiculata plantation Forests Using PlanetScope Imagery in Thanh Phu Nature Reserve, Vietnam . Kieu Manh Huong et al. 10.1134/S1062359023601957
6. Application of a Multispectral UAS to Assess the Cover and Biomass of the Invasive Dune Species Carpobrotus edulis M. Meyer et al. 10.3390/rs15092411
7. Species-based aboveground mangrove carbon stock estimation using WorldView-2 image data M. Hidayatullah et al. 10.1016/j.rsase.2023.100959
8. Aboveground mangrove biomass estimation in Beibu Gulf using machine learning and UAV remote sensing Y. Tian et al. 10.1016/j.scitotenv.2021.146816
9. Sentinel-1 Data for Winter Wheat Phenology Monitoring and Mapping A. Nasrallah et al. 10.3390/rs11192228
10. Hyperspectral Imaging Combined with Deep Learning for the Early Detection of Strawberry Leaf Gray Mold Disease Y. Ou et al. 10.3390/agronomy14112694
11. Remote Sensing Approaches for Monitoring Mangrove Species, Structure, and Biomass: Opportunities and Challenges T. Pham et al. 10.3390/rs11030230
12. Strategies for detecting land-use change on the River Tea SCI ecological corridor via satellite images M. García-Ontiyuelo et al. 10.1016/j.scitotenv.2024.177507
13. Leveraging climate and remote sensing metrics for predicting forest carbon stock using Bayesian geostatistical modelling under a projected climate warming in Zimbabwe T. Chinembiri et al. 10.1016/j.gecadv.2024.100010
14. Predicting the future through observations of the past: Concretizing the role of Geosimulation for holistic geospatial knowledge I. Estacio et al. 10.1016/j.geomat.2024.100012
15. Estimating Aboveground Biomass of Two Different Forest Types in Myanmar from Sentinel-2 Data with Machine Learning and Geostatistical Algorithms P. Wai et al. 10.3390/rs14092146
16. A Comprehensive Comparison of Machine Learning and Feature Selection Methods for Maize Biomass Estimation Using Sentinel-1 SAR, Sentinel-2 Vegetation Indices, and Biophysical Variables C. Xu et al. 10.3390/rs14164083
17. Estimation of aboveground biomass and carbon in palustrine wetland using bands and multispectral indices derived from optical satellite imageries PlanetScope and Sentinel-2A T. Belloli et al. 10.1117/1.JRS.16.034516
18. Integrating Sentinel-1 and 2 with LiDAR data to estimate aboveground biomass of subtropical forests in northeast Guangdong, China L. Zhang et al. 10.1080/17538947.2023.2165180
19. The Utility of Sentinel-2 Spectral Data in Quantifying Above-Ground Carbon Stock in an Urban Reforested Landscape M. Mngadi et al. 10.3390/rs13214281
20. 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
21. Detection and Mapping of Cover Crops Using Sentinel-1 SAR Remote Sensing Data S. Najem et al. 10.1109/JSTARS.2023.3337989
22. Assessing above-ground biomass in reforested urban landscapes using machine learning and remotely sensed data C. Matiza et al. 10.1080/14498596.2024.2343764
23. Remote Monitoring of Crop Nitrogen Nutrition to Adjust Crop Models: A Review L. Silva et al. 10.3390/agriculture13040835
24. Estimation of the total dry aboveground biomass in the tropical forests of Congo Basin using optical, LiDAR, and radar data P. Migolet et al. 10.1080/15481603.2022.2026636
25. Application of nanosatellites PlanetScope data to monitor crop growth S. Kokhan et al. 10.1051/e3sconf/202017102014
26. Approaches, potential, and challenges in the use of remote sensing to study mangrove and other tropical wetland forests D. Chávez et al. 10.17129/botsci.3358
27. Preliminary investigation into the feasibility of combining satellite and GPS data to identify pasture growth and grazing S. Woodward et al. 10.33584/jnzg.2019.81.404
28. Estimating Aboveground Biomass in Dense Hyrcanian Forests by the Use of Sentinel-2 Data F. Moradi et al. 10.3390/f13010104
29. Advances in the estimations and applications of critical nitrogen dilution curve and nitrogen nutrition index of major cereal crops. A review X. Li et al. 10.1016/j.compag.2022.106998
30. Evaluating the saturation effect of vegetation indices in forests using 3D radiative transfer simulations and satellite observations S. Gao et al. 10.1016/j.rse.2023.113665
31. CO2Flux Model Assessment and Comparison between an Airborne Hyperspectral Sensor and Orbital Multispectral Imagery in Southern Amazonia J. Della-Silva et al. 10.3390/su14095458
32. Satellite image processing of the Buxus hyrcana Pojark dieback in the Northern Forests of Iran M. Ghavidel et al. 10.17221/56/2020-JFS
33. Estimation of Individual Tree Stem Biomass in an Uneven-Aged Structured Coniferous Forest Using Multispectral LiDAR Data N. Georgopoulos et al. 10.3390/rs13234827
34. Above ground biomass estimation in the upper Blue Nile basin forests, North-Western Ethiopia H. Kerebeh et al. 10.1186/s40068-024-00376-1
35. Development of a Rapid Mangrove Zonation Mapping Workflow Using Sentinel 2-Derived Indices and Biophysical Dataset A. Baloloy et al. 10.3389/frsen.2021.730238
36. 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
37. Mangrove Resource Mapping Using Remote Sensing in the Philippines: A Systematic Review and Meta-Analysis F. Pillodar et al. 10.3390/f14061080
38. Fusion of UAV-Acquired Visible Images and Multispectral Data by Applying Machine-Learning Methods in Crop Classification Z. Zheng et al. 10.3390/agronomy14112670
39. Mapping and Estimating Forest Stand Volume using Machine Learning Methods and Multi-Spectral Sentinel 2 Data N. Matso et al. 10.59324/ejtas.2024.2(2).55
40. Spatial patterns and driving factors of carbon stocks in mangrove forests on Hainan Island, China Y. Meng et al. 10.1111/geb.13549
41. Can biophysical parameters derived from Sentinel-2 space-borne sensor improve land cover characterisation in semi-arid regions? B. Mudereri et al. 10.1080/10106049.2019.1695956
42. Estimating mangrove above-ground biomass at Maowei Sea, Beibu Gulf of China using machine learning algorithm with Sentinel-1 and Sentinel-2 data Z. Huang et al. 10.1080/10106049.2022.2102226
43. Integration of satellite imagery and in situ soil moisture data for estimating irrigation water requirements S. Ihuoma et al. 10.1016/j.jag.2021.102396
44. Canopy defoliation by leaf-cutting ants in eucalyptus plantations inferred by unsupervised machine learning applied to remote sensing A. Santos et al. 10.1007/s11119-022-09919-x
45. Automated Machine Learning Driven Stacked Ensemble Modeling for Forest Aboveground Biomass Prediction Using Multitemporal Sentinel-2 Data P. Naik et al. 10.1109/JSTARS.2022.3232583
46. Carbon Stock Prediction in Managed Forest Ecosystems Using Bayesian and Frequentist Geostatistical Techniques and New Generation Remote Sensing Metrics T. Chinembiri et al. 10.3390/rs15061649
47. Linking Terrestrial LiDAR Scanner and Conventional Forest Structure Measurements with Multi-Modal Satellite Data K. Mulatu et al. 10.3390/f10030291
48. Cartographie du risque feu de forêt dans le Nord-est algérien : cas de la wilaya d’El Tarf A. Arfa et al. 10.4000/cybergeo.32304
49. Saf Kızılçam (Pinus brutia Ten.) Meşcerelerinde Aktif ve Pasif Uydu Görüntüleri Kullanılarak Topraküstü Biyokütlenin Tahmin Edilmesi (Anamur Orman İşletme Şefliği Örneği) İ. GÜVERÇİN & A. GÜNLÜ 10.24011/barofd.1261299
50. Assessing Forest Species Diversity in Ghana’s Tropical Forest Using PlanetScope Data E. Njomaba et al. 10.3390/rs16030463
51. Comparison of Multi-Temporal PlanetScope Data with Landsat 8 and Sentinel-2 Data for Estimating Airborne LiDAR Derived Canopy Height in Temperate Forests K. Shimizu et al. 10.3390/rs12111876
52. The use of remote sensing indices to understand flood‐recharged soil moisture impacts on trees in semi‐arid floodplains: A review E. Pedzisai et al. 10.1002/eco.2460
53. Estimation of above-ground biomass using machine learning approaches with InSAR and LiDAR data in tropical peat swamp forest of Brunei Darussalam E. Zadbagher et al. 10.3832/ifor4434-017