Canopy height map in Italy - 2004-2024

This is the data used or generated in the paper, "Annual canopy height mapping in Italy from Landsat and multi-source LiDAR for disturbance and recovery monitoring".

Authors

Yang Su a, b, c, Nikola Besic d, Xianglin Zhang c, Yidi Xu b, Saverio Francini e, Giovanni D'Amico f, Gherardo Chirici g, h, Martin Schwartz b, Ibrahim Fayad b, Sarah Brood b, Agnes Pellissier-tanon b, Ke Yu b, Haotian Chen i, c, Songchao Chen j, Alexandre d'Aspremont a, Philippe Ciais b

Affiliations

a CNRS & Département d'Informatique, École Normale Supérieure – PSL, 45 Rue d'Ulm, 75005 Paris, France

b Laboratoire des Sciences du Climat et de l’Environnement, CEA CNRS UVSQ Orme des Merisiers, 91190 Gif-sur-Yvette, France

c Université Paris-Saclay, AgroParisTech, INRAE, UMR ECOSYS, 91120 Palaiseau, France

d IGN, ENSG, Laboratoire d'inventaire forestier (LIF), 54000 Nancy, France

e Department of Science and Technology of Agriculture and Environment (DISTAL), University of Bologna, 40126 Bologna, Italy

f Department of Agriculture, Food, Environment and Forestry, Università degli Studi di Firenze, Via San Bonaventura, 13, 50145 Firenze, Italy

g Fondazione per il Futuro delle Città, Florence, Italy

h CNR Istituto dei Sistemi Complessi, Sesto Fiorentino (Florence), Italy

i Institute of Crop Sciences, Chinese Academy of Agricultural Sciences / Key Laboratory of Crop Physiology and Ecology, Ministry of Agriculture and Rural Affairs of China, Beijing 100081, China

j College of Environmental and Resource Sciences, Zhejiang University, 310058 Hangzhou, China

Corresponding Author

Yang Su

[e-mail]

[phone]

École normale supérieure - PSL

To use the data, please cite this study, and in case of difficulties when using the model and data, please contact the corresponding author for further details and possible assistance

Funding

Artificial Intelligence for forest monitoring from space – AI4Forests

Agence Nationale de la Recherche

Find out more...