Michele Torresani

1.2k total citations
28 papers, 577 citations indexed

About

Michele Torresani is a scholar working on Ecology, Ecological Modeling and Global and Planetary Change. According to data from OpenAlex, Michele Torresani has authored 28 papers receiving a total of 577 indexed citations (citations by other indexed papers that have themselves been cited), including 18 papers in Ecology, 13 papers in Ecological Modeling and 12 papers in Global and Planetary Change. Recurrent topics in Michele Torresani's work include Remote Sensing in Agriculture (15 papers), Species Distribution and Climate Change (13 papers) and Remote Sensing and LiDAR Applications (9 papers). Michele Torresani is often cited by papers focused on Remote Sensing in Agriculture (15 papers), Species Distribution and Climate Change (13 papers) and Remote Sensing and LiDAR Applications (9 papers). Michele Torresani collaborates with scholars based in Italy, Czechia and Germany. Michele Torresani's co-authors include Duccio Rocchini, Giustino Tonon, Marc Zebisch, Carlo Ricotta, Ruth Sonnenschein, Vítězslav Moudrý, Matteo Marcantonio, Michael Heym, Enrico Tomelleri and Marco Malavasi and has published in prestigious journals such as Remote Sensing of Environment, Scientific Reports and Agricultural and Forest Meteorology.

In The Last Decade

Michele Torresani

28 papers receiving 567 citations

Peers

Michele Torresani
Rafi Kent Israel
Peter J. Olsoy United States
David C. Marvin United States
Chris Toney United States
Matthew Colgan United States
Tanya G. Bailey Australia
Klara Dološ Germany
Klaus Ecker Switzerland
Ahmet Mert Türkiye
Edna Rödig Germany
Rafi Kent Israel
Michele Torresani
Citations per year, relative to Michele Torresani Michele Torresani (= 1×) peers Rafi Kent

Countries citing papers authored by Michele Torresani

Since Specialization
Citations

This map shows the geographic impact of Michele Torresani's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Michele Torresani with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Michele Torresani more than expected).

Fields of papers citing papers by Michele Torresani

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Michele Torresani. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Michele Torresani. The network helps show where Michele Torresani may publish in the future.

Co-authorship network of co-authors of Michele Torresani

This figure shows the co-authorship network connecting the top 25 collaborators of Michele Torresani. A scholar is included among the top collaborators of Michele Torresani based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Michele Torresani. Michele Torresani is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Geßner, Ursula, Christopher R. Hakkenberg, Stefanie Holzwarth, et al.. (2025). Characterizing local forest structural complexity based on multi-platform and -sensor derived indicators. Ecological Indicators. 170. 113085–113085. 2 indexed citations
2.
Torresani, Michele, et al.. (2025). Machine learning for biodiversity: UAV-based flower detection as an indirect proxy for bee abundance. Ecological Informatics. 91. 103346–103346. 1 indexed citations
3.
Liu, Xiao, Anette Eltner, Kateřina Gdulová, et al.. (2025). Towards 90 m resolution digital terrain model combining ICESat-2 and GEDI data: Balancing accuracy and sampling intensity. Science of Remote Sensing. 12. 100293–100293. 2 indexed citations
4.
Torresani, Michele, Christian Rossi, Marco Mina, et al.. (2025). Spectral heterogeneity from the spaceborne imaging spectrometer EnMAP reveals biodiversity patterns in forest ecosystems. International Journal of Applied Earth Observation and Geoinformation. 144. 104902–104902. 1 indexed citations
5.
Angiolini, Claudia, Giovanni Bacaro, Emanuele Fanfarillo, et al.. (2025). Fuzzy approaches provide improved spatial detection of coastal dune EU habitats. Ecological Informatics. 86. 103059–103059. 1 indexed citations
6.
Moudrý, Vítězslav, Lukáš Gábor, Suzanne Marselis, et al.. (2024). Comparison of three global canopy height maps and their applicability to biodiversity modeling: Accuracy issues revealed. Ecosphere. 15(10). 13 indexed citations
7.
Moudrý, Vítězslav, Jiří Prošek, Suzanne Marselis, et al.. (2024). How to Find Accurate Terrain and Canopy Height GEDI Footprints in Temperate Forests and Grasslands?. Earth and Space Science. 11(10). 6 indexed citations
8.
Torresani, Michele, Leonardo Montagnani, Duccio Rocchini, et al.. (2024). LiDAR insights on stand structure and topography in mountain forest wind extreme events: The Vaia case study. Agricultural and Forest Meteorology. 359. 110267–110267. 2 indexed citations
9.
Torresani, Michele, Duccio Rocchini, Hannes Feilhauer, et al.. (2024). Grassland vertical height heterogeneity predicts flower and bee diversity: an UAV photogrammetric approach. Scientific Reports. 14(1). 809–809. 11 indexed citations
10.
Rocchini, Duccio, Michele Torresani, & Carlo Ricotta. (2024). On the mathematical properties of spatial Rao’s Q to compute ecosystem heterogeneity. Theoretical Ecology. 17(3). 247–254. 7 indexed citations
11.
Rocchini, Duccio, Giles M. Foody, Simon Garnier, et al.. (2024). Under the mantra: ‘Make use of colorblind friendly graphs’. Environmetrics. 35(6). 2 indexed citations
12.
Moudrý, Vítězslav, Petr Keil, Lukáš Gábor, et al.. (2023). Scale mismatches between predictor and response variables in species distribution modelling: A review of practices for appropriate grain selection. Progress in Physical Geography Earth and Environment. 47(3). 467–482. 23 indexed citations
13.
Febbraro, Mirko Di, Luisa Conti, Jan Divíšek, et al.. (2023). The relationship between spectral and plant diversity: Disentangling the influence of metrics and habitat types at the landscape scale. Remote Sensing of Environment. 293. 113591–113591. 32 indexed citations
14.
Rocchini, Duccio, Jakub Nowosad, Giovanni Bacaro, et al.. (2023). Scientific maps should reach everyone: The cblindplot R package to let colour blind people visualise spatial patterns. Ecological Informatics. 76. 102045–102045. 5 indexed citations
15.
Torresani, Michele, et al.. (2023). LiDAR GEDI derived tree canopy height heterogeneity reveals patterns of biodiversity in forest ecosystems. Ecological Informatics. 76. 102082–102082. 49 indexed citations
16.
Torresani, Michele, David Kleijn, Harm Bartholomeus, et al.. (2023). A novel approach for surveying flowers as a proxy for bee pollinators using drone images. Ecological Indicators. 149. 110123–110123. 21 indexed citations
17.
Anderle, Matteo, Mattia Brambilla, Andreas Hilpold, et al.. (2023). Habitat heterogeneity promotes bird diversity in agricultural landscapes: Insights from remote sensing data. Basic and Applied Ecology. 70. 38–49. 35 indexed citations
18.
19.
Rocchini, Duccio, Michele Torresani, Carl Beierkuhnlein, et al.. (2022). Double down on remote sensing for biodiversity estimation: a biological mindset. Community Ecology. 23(3). 267–276. 17 indexed citations
20.
Torresani, Michele, Duccio Rocchini, Marc Zebisch, Ruth Sonnenschein, & Giustino Tonon. (2018). Testing the spectral variation hypothesis by using the RAO-Q index to estimate forest biodiversity: Effect of spatial resolution. View. 1183–1186. 13 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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