DANIELE TORREGGIANI

Full professor, PhD

University of Bologna

Italy

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Daniele Torreggiani is a Full Professor at the University of Bologna, Italy. His research areas encompass deep learning applications in agricultural practices, climate change adaptation strategies, and sustainable urban planning. Recent publications highlight his work on crop mapping using Sentinel-2 data, evaluating green roof management in Mediterranean climates, and applying machine learning techniques for building energy needs and dairy cow heat stress responses.

Articles (9)

Year:

2025

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2025

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2025

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2024

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2023

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2023

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2022

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2022

Year:

2020

Collaborators (6)

Mattia Trenta

University of Bologna

ITALY

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Juanjo Galan

Associate Professor

Universitat Politècnica de València

SPAIN

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Bas Pedroli

Associate Professor

Wageningen University & Research

NETHERLANDS

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Alberto Barbaresi

Senior assistant professor (fixed-term)

University of Bologna

ITALY

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Marco Bovo

University of Bologna

ITALY

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Stefano Benni

Associate Professor

University of Bologna

ITALY

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DANIELE TORREGGIANI

Research Interests

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Articles (9)

Green Roof Management in Mediterranean Climates: Evaluating the Performance of Native Herbaceous Plant Species and Green Manure to Increase Sustainability

Deep Learning Applications for Crop Mapping Using Multi-Temporal Sentinel-2 Data and Red-Edge Vegetation Indices: Integrating Convolutional and Recurrent Neural Networks

Assessing feature extraction, selection, and classification combinations for crop mapping using Sentinel-2 time series: A case study in northern Italy

DAIRY CHAOS: Data driven Approach Identifying daiRY Cows affected by HeAt lOad Stress

Landscape adaptation to climate change: Local networks, social learning and co-creation processes for adaptive planning

Exploring the land-use urban heat island nexus under climate change conditions using machine learning approach: A spatio-temporal analysis of remotely sensed data

Effects of LED supplemental lighting on the growth and metabolomic profile of Taxus baccata cultivated in a smart greenhouse

Application of Machine Learning Models for Fast and Accurate Predictions of Building Energy Need

A generalised additive model to characterise dairy cows’ responses to heat stress

Collaborators (6)

Mattia Trenta

Juanjo Galan

Bas Pedroli

Alberto Barbaresi

Marco Bovo

Stefano Benni

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