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155 results on '"CELESTI, MARCO"'

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1. Onboard Processing of Hyperspectral Imagery: Deep Learning Advancements, Methodologies, Challenges, and Emerging Trends

2. Multi-sensor spectral synergies for crop stress detection and monitoring in the optical domain: A review

10. Using Sentinel-2-Based Metrics to Characterize the Spatial Heterogeneity of FLEX Sun-Induced Chlorophyll Fluorescence on Sub-Pixel Scale

11. Using Sentinel-2-Based Metrics to Characterize the Spatial Heterogeneity of FLEX Sun-Induced Chlorophyll Fluorescence on Sub-Pixel Scale

12. Using Sentinel-2-Based Metrics to Characterize the Spatial Heterogeneity of FLEX Sun-Induced Chlorophyll Fluorescence on Sub-Pixel Scale

13. OLCI-A/B tandem phase: evaluation of FLuorescence EXplorer (FLEX)-like radiances and estimation of systematic differences between OLCI-A and OLCI-FLEX

15. i-φ-MaLe: a novel AI-phasor based method for a fast and accurate retrieval of multiple Solar-Induced Fluorescence metrics and biophysical parameters

17. Deep Learning for On-board Processing of Imaging Spectroscopy: A Survey

20. Toward an on-board AI proof of concept for CHIME a feasibility study

21. Multi-sensor spectral synergies for crop stress detection and monitoring in the optical domain: A review

22. Multi-sensor spectral synergies for crop stress detection and monitoring in the optical domain:A review

23. Multi-sensor spectral synergies for crop stress detection and monitoring in the optical domain: A review

24. Towards consistent assessments of in situ radiometric measurements for the validation of fluorescence satellite missions

25. OLCI-A/B tandem phase: evaluation of FLuorescence EXplorer (FLEX)-like radiances and estimation of systematic differences between OLCI-A and OLCI-FLEX.

26. OLCI A/B tandem phase: Evaluation of FLEX like radiances and estimation of systematic differences between OLCI-A and OLCI-FLEX.

27. Estimation of leaf nitrogen content and photosynthetic nitrogen use efficiency in wheat using sun-induced chlorophyll fluorescence at the leaf and canopy scales

28. Unmanned Aerial Systems (UAS)-Based Methods for Solar Induced Chlorophyll Fluorescence (SIF) Retrieval with Non-Imaging Spectrometers: State of the Art

29. Effects of varying solar-view geometry and canopy structure on solar-induced chlorophyll fluorescence and PRI

30. Unmanned Aerial Systems (UAS)-Based Methods for Solar Induced Chlorophyll Fluorescence (SIF) Retrieval with Non-Imaging Spectrometers: State of the Art

31. Dynamics of sun-induced chlorophyll fluorescence and reflectance to detect stress-induced variations in canopy photosynthesis

35. Dynamics of sun‐induced chlorophyll fluorescence and reflectance to detect stress‐induced variations in canopy photosynthesis

36. Exploring continuous time series of vegetation hyperspectral reflectance and solar-induced fluorescence through radiative transfer model inversion

39. SENSECO: Optical synergies for spatiotemporal sensing of scalable ecophysiological traits. (COST Action CA17134)

40. Multi-Scale Evaluation of Drone-Based Multispectral Surface Reflectance and Vegetation Indices in Operational Conditions

42. The High-Performance Airborne Imaging Spectrometer HyPlant-From Raw Images to Top-of-Canopy Reflectance and Fluorescence Products: Introduction of an Automatized Processing Chain

45. A spectral fitting algorithm to retrieve the fluorescence spectrum from canopy radiance

46. Hyplant-derived sun-induced fluorescence—a new opportunity to disentangle complex vegetation signals from diverse vegetation types

47. Sun-induced chlorophyll fluorescence III: benchmarking retrieval methods and sensor characteristics for proximal sensing

48. The high-performance airborne imaging spectrometer HyPlant—from raw images to top-of-canopy reflectance and fluorescence products: introduction of an automatized processing chain

49. Sun-Induced Chlorophyll Fluorescence III: Benchmarking Retrieval Methods and Sensor Characteristics for Proximal Sensing

50. Development of novel methods to evaluate vegetation status from multi-source remote sensing data

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