DRONE DATA ATMOSPHERIC CORRECTION CONCEPT FOR MULTI- AND HYPERSPECTRAL IMAGERY – THE DROACOR MODEL

15 citations as recorded by crossref.

1. Gaussian processes retrieval of crop traits in Google Earth Engine based on Sentinel-2 top-of-atmosphere data J. Estévez et al.
2. Tradeoffs in the Spatial and Spectral Resolution of Airborne Hyperspectral Imaging Systems: A Crop Identification Case Study J. Jia et al.
3. Radiometric calibration of a large-array commodity CMOS multispectral camera for UAV-borne remote sensing X. Zhou et al.
4. Hyperspectral imaging systems for corrosion detection from remotely operated vehicles D. Thomas & M. Gündel
5. Comparison of deep and shallow one-class classifiers for detecting invasive Prosopis trees in Kenya from airborne hyperspectral data I. Vuorinne et al.
6. Species-specific machine learning models for UAV-based forest health monitoring: Revealing the importance of the BNDVI S. Ecke et al.
7. Forage Height and Above-Ground Biomass Estimation by Comparing UAV-Based Multispectral and RGB Imagery H. Wang et al.
8. High-throughput phenotyping to detect anthocyanins, chlorophylls, and carotenoids in red lettuce germplasm A. Clemente et al.
9. Machine Learning and Unmanned Aerial Vehicles in Water Quality Monitoring B. Acharya & M. Bhandari
10. Unoccupied aerial systems imagery for phenotyping in cotton, maize, soybean, and wheat breeding A. Herr et al.
11. Assessing grapevine water status in a variably irrigated vineyard with NIR/SWIR hyperspectral imaging from UAV E. Laroche-Pinel et al.
12. Calibration and Validation from Ground to Airborne and Satellite Level: Joint Application of Time-Synchronous Field Spectroscopy, Drone, Aircraft and Sentinel-2 Imaging P. Naethe et al.
13. Evaluation of the DROACOR Model for Atmospheric Correction of Drone Hyperspectral Data Y. Son
14. UAV-based deep learning for biodiversity monitoring: Advances, applications, and future directions S. Wang et al.
15. Limitations of a Multispectral UAV Sensor for Satellite Validation and Mapping Complex Vegetation B. Cottrell et al.