FUSION OF SENTINEL-2 AND PLANETSCOPE IMAGERY FOR VEGETATION DETECTION AND MONITORING

30 citations as recorded by crossref.

1. Mapping the Cerrado–Amazon Transition Using PlanetScope–Sentinel Data Fusion and a U-Net Deep Learning Framework C. Li et al.
2. Yield forecasting in maize: Performance and limits of unmanned aerial vehicle and PlanetScope remote sensing across multiple growth cycles P. Vigneault et al.
3. Soybean seed composition prediction from standing crops using PlanetScope satellite imagery and machine learning S. Sarkar et al.
4. Assessing the effectiveness of PlanetScope synthesized panchromatic bands for spatial enhancement of Sentinel-2 data G. Kaplan
5. Spatially predicting ecosystem service patterns in boreal drained peatlands forests using multisource satellite data K. Keränen et al.
6. Fusion of PlanetScope and Sentinel 2 in assessing foliar C:N ratio in a rangeland A. Arogoundade et al.
7. Early season irrigation detection and evapotranspiration modeling of winter vegetables based on Planet satellite using water and energy balance algorithm in lower Colorado basin R. Dhungel et al.
8. Trajectories of farming systems reshape land use/land cover dynamics in the agricultural zones of the Galapagos Islands F. Benitez et al.
9. Estimating and Monitoring Land Surface Phenology in Rangelands: A Review of Progress and Challenges T. Matongera et al.
10. A Fusion Approach for Water Area Classification Using Visible, Near Infrared and Synthetic Aperture Radar for South Asian Conditions S. Ahmad et al.
11. Significance of Planet SuperDove and refined Sentinel-2 imagery fusion for enhanced soil organic carbon prediction in croplands J. Mensah Biney et al.
12. Data-driven interpretability of urban tree species classification from deep learning models and Satellite Image Time Series C. Bressant et al.
13. Effects of Satellite Revisit Rate and Time-Series Smoothing Method on Throughout-Season Maize Yield Correlation Accuracy E. Myers et al.
14. Agricultural growth and land use land cover change in peri-urban India S. Patel et al.
15. Artificial Intelligence to Advance Earth Observation: A review of models, recent trends, and pathways forward D. Tuia et al.
16. Intercropping Classification From GF-1 and GF-2 Satellite Imagery Using a Rotation Forest Based on an SVM P. Liu & X. Chen
17. Spatial and Temporal Pasture Biomass Estimation Integrating Electronic Plate Meter, Planet CubeSats and Sentinel-2 Satellite Data J. Gargiulo et al.
18. Recognition of Areca Leaf Yellow Disease Based on PlanetScope Satellite Imagery J. Guo et al.
19. New Generation Hyperspectral Data From DESIS Compared to High Spatial Resolution PlanetScope Data for Crop Type Classification I. Aneece et al.
20. Cost-effectiveness of remote sensing technology for spruce budworm monitoring in Maine, USA A. Foster et al.
21. A robust and adaptive spatial-spectral fusion model for PlanetScope and Sentinel-2 imagery Y. Zhao & D. Liu
22. Generation of High-Resolution Time-Series NDVI Images for Monitoring Heterogeneous Crop Fields S. Kim et al.
23. Application of nanosatellites PlanetScope data to monitor crop growth S. Kokhan et al.
24. Comparison of PlanetScope and Sentinel-2 Spectral Channels and Their Alignment via Linear Regression for Enhanced Index Derivation C. Baldin & V. Casella
25. Crop Type and Land Cover Mapping in Northern Malawi Using the Integration of Sentinel-1, Sentinel-2, and PlanetScope Satellite Data D. Kpienbaareh et al.
26. Fusion of Sentinel-2 and PlanetScope time-series data into daily 3 m surface reflectance and wheat LAI monitoring Y. Sadeh et al.
27. Planetscope Nanosatellites Image Classification Using Machine Learning M. Anul Haq
28. Fine-Scale Phenology of Urban Trees From Satellite Image Time Series: Toward a Comprehensive Analysis of Influencing Factors C. Bressant et al.
29. Optimizing urban critical green space development using machine learning M. Ganjirad et al.
30. Leveraging Phenology to Assess Seasonal Variations of Plant Communities for Mapping Dynamic Ecosystems T. Surasinghe et al.