P
Paolo Villa
Researcher at National Research Council
Publications - 55
Citations - 1770
Paolo Villa is an academic researcher from National Research Council. The author has contributed to research in topics: Macrophyte & Land cover. The author has an hindex of 19, co-authored 50 publications receiving 1271 citations. Previous affiliations of Paolo Villa include Istituto di Scienza e Tecnologie dell'Informazione & Polytechnic University of Milan.
Papers
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Journal ArticleDOI
Advanced methods of plant disease detection. A review
Federico Martinelli,Riccardo Scalenghe,Salvatore Davino,Stefano Panno,Giuseppe Scuderi,Paolo Ruisi,Paolo Villa,Daniela Stroppiana,Mirco Boschetti,Luiz Ricardo Goulart,Cristina E. Davis,Abhaya M. Dandekar +11 more
TL;DR: Modern methods based on nucleic acid and protein analysis are described, which represent unprecedented tools to render agriculture more sustainable and safe, avoiding expensive use of pesticides in crop protection.
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Measuring freshwater aquatic ecosystems: The need for a hyperspectral global mapping satellite mission
Erin L. Hestir,Erin L. Hestir,Vittorio E. Brando,Mariano Bresciani,Claudia Giardino,Erica Matta,Paolo Villa,Arnold G. Dekker +7 more
TL;DR: In this paper, the authors evaluate the suitability and gaps of a hyperspectral global mapping satellite mission for measuring freshwater ecosystems and demonstrate the need for such a mission, and evaluate their suitability through an examination of the measurement resolution issues impacting freshwater ecosystem measurements (spatial, temporal, spectral and radiometric).
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Application of Remote Sensing in Water Resource Management: The Case Study of Lake Trasimeno, Italy
TL;DR: In this paper, a large-swath MERIS and MODIS sensors were proposed for regular broad scale monitoring of water quality, having compared the retrieved chlorophyll-a (Chl-a) concentration, Secchi disk (SD) depth and surface water temperature with the 2005-2008 time-series of the in situ data.
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Postflood damage evaluation using Landsat TM and ETM+ data integrated with DEM
TL;DR: A straightforward technique based on the sequential use of the spectral-temporal principal component analysis, logical filtering, and image segmentation integrated with the digital elevation model was developed as a decisional support tool for the allocations of the resource destined for the flooded areas.
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Aquatic vegetation indices assessment through radiative transfer modeling and linear mixture simulation
TL;DR: Two new VIs specifically targeted at aquatic vegetation: NDAVI and WAVI are introduced and their performance in capturing information about aquatic vegetation features by comparison with pre-existing indices: NDVI, SAVI and EVI is assessed.