Published in Remote Sensing MDPI, 2022
Recommended citation: Croci M, Impollonia G, Meroni M, Amaducci S. Dynamic Maize Yield Predictions Using Machine Learning on Multi-Source Data. Remote Sensing. 2023; 15(1):100. https://doi.org/10.3390/rs15010100
Published in Remote Sensing MDPI, 2022
Recommended citation: Impollonia, G.; Croci, M.; Blandinières, H.; Marcone, A.; Amaducci, S. Comparison of PROSAIL Model Inversion Methods for Estimating Leaf Chlorophyll Content and LAI Using UAV Imagery for Hemp Phenotyping. Remote Sens. 2022, 14, 5801. https://doi.org/10.3390/rs14225801
Published in Agronomy MDPI, 2022
Recommended citation: Croci, M.; Impollonia, G.; Marcone, A.; Antonucci, G.; Letterio, T.; Colauzzi, M.; Vignudelli, M.; Ventura, F.; Anconelli, S.; Amaducci, S. RTM Inversion through Predictive Equations for Multi-Crop LAI Retrieval Using Sentinel-2 Images. Agronomy 2022, 12, 2835. https://doi.org/10.3390/agronomy12112835
Published in Remote Sensing MDPI, 2022
Recommended citation: Croci, M.; Impollonia, G.; Blandinières, H.; Colauzzi, M.; Amaducci, S. Impact of Training Set Size and Lead Time on Early Tomato Crop Mapping Accuracy. Remote Sens. 2022, 14, 4540. https://doi.org/10.3390/rs14184540
Published in Remote Sensing MDPI, 2022
Recommended citation: Impollonia, G.; Croci, M.; Ferrarini, A.; Brook, J.; Martani, E.; Blandinières, H.; Marcone, A.; Awty-Carroll, D.; Ashman, C.; Kam, J.; Kiesel, A.; Trindade, L.M.; Boschetti, M.; Clifton-Brown, J.; Amaducci, S. UAV Remote Sensing for High-Throughput Phenotyping and for Yield Prediction of Miscanthus by Machine Learning Techniques. Remote Sens. 2022, 14, 2927. https://doi.org/10.3390/rs14122927
Published in GCB Bioenergy, 2022
Recommended citation: Impollonia, G., Croci, M., Martani, E., Ferrarini, A., Kam, J., Trindade, L. M., Clifton-Brown, J., & Amaducci, S. (2022). Moisture content estimation and senescence phenotyping of novel Miscanthus hybrids combining UAV-based remote sensing and machine learning. GCB Bioenergy, 14, 639– 656. https://doi.org/10.1111/gcbb.12930
Published in Smart Agricultural Technology, 2022
Recommended citation: Antonucci, G., Impollonia, G., Croci, M., Potenza, E., Marcone, A., & Amaducci, S. (2022). Evaluating Biostimulants Via High-Throughput Field Phenotyping: Biophysical Traits Retrieval Through PROSAIL Inversion. Smart Agricultural Technology, 100067. https://doi.org/10.1016/j.atech.2022.100067
Published in Acta Horticulturae, 2021
Recommended citation: Motisi, A., Impollonia, G., Minacapilli, M., Orlando, S., & Sarno, M. (2021). TURF-BOX: an active lighting multispectral imaging system with led VIS-NIR sources for monitoring of vegetated surfaces. In Acta Horticulturae (Issue 1314, pp. 383–390). International Society for Horticultural Science (ISHS). https://doi.org/10.17660/actahortic.2021.1314.48