Dynamic Corn yield predictions using Machine Learning on Multi-Source Data for Agri-Food 4.0
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publications
TURF-BOX: an active lighting multispectral imaging system with led VIS-NIR sources for monitoring of vegetated surfaces
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
Evaluating Biostimulants Via High-Throughput Field Phenotyping: Biophysical Traits Retrieval Through PROSAIL Inversion
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
Moisture content estimation and senescence phenotyping of novel Miscanthus hybrids combining UAV-based remote sensing and machine learning
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
UAV Remote Sensing for High-Throughput Phenotyping and for Yield Prediction of Miscanthus by Machine Learning Techniques
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
Impact of Training Set Size and Lead Time on Early Tomato Crop Mapping Accuracy
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
RTM Inversion through Predictive Equations for Multi-Crop LAI Retrieval Using Sentinel-2 Images
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
Comparison of PROSAIL Model Inversion Methods for Estimating Leaf Chlorophyll Content and LAI Using UAV Imagery for Hemp Phenotyping
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
Dynamic Maize Yield Predictions Using Machine Learning on Multi-Source Data
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
talks
Talk 1 on Relevant Topic in Your Field
Published:
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Conference Proceeding talk 3 on Relevant Topic in Your Field
Published:
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teaching
Agricoltura di precisione
course, Centro di formazione Dinamica, 2019
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Tecnico per il monitoraggio e la gestione del territorio e dell’ambiente
IFTS course, Centro di Formazione Vittorio Tadini, 2020
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Tecnico per il monitoraggio e la gestione sostenibile delle risorse idriche
IFTS course, Centro di Formazione Vittorio Tadini, 2021
This is a description of a teaching experience. You can use markdown like any other post.