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4. Multi-Temporal Satellite Imagery for Monitoring Productivity Trend in Mediterranean Coastal Forest Ecosystems: The Study Case of the State Natural Reserve 'Duna Feniglia' (Italy)

Author

Solano, Francesco, Praticò, Salvatore, Modica, Giuseppe, Quilghini, Giovanni, Piovesan, Gianluca, di Prisco, Marco, Series Editor, Chen, Sheng-Hong, Series Editor, Vayas, Ioannis, Series Editor, Kumar Shukla, Sanjay, Series Editor, Sharma, Anuj, Series Editor, Kumar, Nagesh, Series Editor, Wang, Chien Ming, Series Editor, Ferro, Vito, editor, Giordano, Giuseppe, editor, Orlando, Santo, editor, Vallone, Mariangela, editor, Cascone, Giovanni, editor, and Porto, Simona M. C., editor

Published
2023
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5. Historic Agricultural Landscape Characterization: First Attempt of Historic Landscape Characterization (HLC) to Costa Viola Terraced Landscape (Calabria, Italy)

Author

Praticò, Salvatore, Solano, Francesco, Di Fazio, Salvatore, Modica, Giuseppe, di Prisco, Marco, Series Editor, Chen, Sheng-Hong, Series Editor, Vayas, Ioannis, Series Editor, Kumar Shukla, Sanjay, Series Editor, Sharma, Anuj, Series Editor, Kumar, Nagesh, Series Editor, Wang, Chien Ming, Series Editor, Ferro, Vito, editor, Giordano, Giuseppe, editor, Orlando, Santo, editor, Vallone, Mariangela, editor, Cascone, Giovanni, editor, and Porto, Simona M. C., editor

Published
2023
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6. Multispectral UAV-Based Monitoring of Behavior of Different Wheat and Barley Varieties

Author

Messina, Gaetano, Badagliacca, Giuseppe, Praticò, Salvatore, Preiti, Giovanni, Monti, Michele, Modica, Giuseppe, di Prisco, Marco, Series Editor, Chen, Sheng-Hong, Series Editor, Vayas, Ioannis, Series Editor, Kumar Shukla, Sanjay, Series Editor, Sharma, Anuj, Series Editor, Kumar, Nagesh, Series Editor, Wang, Chien Ming, Series Editor, Ferro, Vito, editor, Giordano, Giuseppe, editor, Orlando, Santo, editor, Vallone, Mariangela, editor, Cascone, Giovanni, editor, and Porto, Simona M. C., editor

Published
2023
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7. Assessing Differences in Land Productivity Trends to Climatic Data in Arid and Semi-arid Zones: A Study Case in Northern Mozambique

Author

Solano, Francesco, Praticò, Salvatore, Ripa, Maria Nicolina, Modica, Giuseppe, di Prisco, Marco, Series Editor, Chen, Sheng-Hong, Series Editor, Vayas, Ioannis, Series Editor, Kumar Shukla, Sanjay, Series Editor, Sharma, Anuj, Series Editor, Kumar, Nagesh, Series Editor, Wang, Chien Ming, Series Editor, Ferro, Vito, editor, Giordano, Giuseppe, editor, Orlando, Santo, editor, Vallone, Mariangela, editor, Cascone, Giovanni, editor, and Porto, Simona M. C., editor

Published
2023
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8. An Unpiloted Aerial System (UAV) Light Detection and Ranging (LiDAR) Based Approach to Detect Canopy Forest Structure Parameters in Old-Growth Beech Forests: Preliminary Results

Author

Praticò, Salvatore, Solano, Francesco, Piovesan, Gianluca, Modica, Giuseppe, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Gervasi, Osvaldo, editor, Murgante, Beniamino, editor, Rocha, Ana Maria A. C., editor, Garau, Chiara, editor, Scorza, Francesco, editor, Karaca, Yeliz, editor, and Torre, Carmelo M., editor

Published
2023
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9. UAV LiDAR Survey for Forest Structure Metrics Estimation in Planning Scenario. A Case Study on a Laricio Pine Forest in the Sila Mountains (Southern Italy)

Author

De Luca, Giandomenico, Praticò, Salvatore, Messina, Gaetano, Borgogno-Mondino, Enrico, Modica, Giuseppe, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Gervasi, Osvaldo, editor, Murgante, Beniamino, editor, Rocha, Ana Maria A. C., editor, Garau, Chiara, editor, Scorza, Francesco, editor, Karaca, Yeliz, editor, and Torre, Carmelo M., editor

Published
2023
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10. Intra-network Analysis Based on Comparison Between Graph Theory Approach and Pathwalker

Author

Lumia, Giovanni, Cushman, Samuel, Praticò, Salvatore, Modica, Giuseppe, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Gervasi, Osvaldo, editor, Murgante, Beniamino, editor, Rocha, Ana Maria A. C., editor, Garau, Chiara, editor, Scorza, Francesco, editor, Karaca, Yeliz, editor, and Torre, Carmelo M., editor

Published
2023
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12. Preliminary Results in the Use of WorldView-3 for the Detection of Cork Oak (Quercus Suber L.): A Case in Calabria (Italy)

Author

Messina, Gaetano, Lumia, Giovanni, Praticò, Salvatore, Di Fazio, Salvatore, Modica, Giuseppe, Kacprzyk, Janusz, Series Editor, Gomide, Fernando, Advisory Editor, Kaynak, Okyay, Advisory Editor, Liu, Derong, Advisory Editor, Pedrycz, Witold, Advisory Editor, Polycarpou, Marios M., Advisory Editor, Rudas, Imre J., Advisory Editor, Wang, Jun, Advisory Editor, Calabrò, Francesco, editor, Della Spina, Lucia, editor, and Piñeira Mantiñán, María José, editor

Published
2022
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13. Virtual Reality Approach for Geoparks Fruition During SARS-Cov2 Pandemic Situation: Methodological Notes and First Results

Author

Praticò, Salvatore, Neves, Marco, Merlino, Angelo, Tripodi, Raimondo, Bonomo, Peppuccio, Barreira, Paulo, Modica, Giuseppe, Kacprzyk, Janusz, Series Editor, Gomide, Fernando, Advisory Editor, Kaynak, Okyay, Advisory Editor, Liu, Derong, Advisory Editor, Pedrycz, Witold, Advisory Editor, Polycarpou, Marios M., Advisory Editor, Rudas, Imre J., Advisory Editor, Wang, Jun, Advisory Editor, Calabrò, Francesco, editor, Della Spina, Lucia, editor, and Piñeira Mantiñán, María José, editor

Published
2022
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14. A Fragmentation-Based Analysis of Costa Viola (Southern Italy) Agricultural Terraces

Author

Praticò, Salvatore, Solano, Francesco, Di Fazio, Salvatore, Modica, Giuseppe, di Prisco, Marco, Series Editor, Chen, Sheng-Hong, Series Editor, Vayas, Ioannis, Series Editor, Kumar Shukla, Sanjay, Series Editor, Sharma, Anuj, Series Editor, Kumar, Nagesh, Series Editor, Wang, Chien Ming, Series Editor, La Rosa, Daniele, editor, and Privitera, Riccardo, editor

Published
2022
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17. Unmanned Aerial Vehicle (UAV) Derived Canopy Gaps in the Old-Growth Beech Forest of Mount Pollinello (Italy): Preliminary Results

Author

Solano, Francesco, Praticò, Salvatore, Piovesan, Gianluca, Modica, Giuseppe, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Woeginger, Gerhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Gervasi, Osvaldo, editor, Murgante, Beniamino, editor, Misra, Sanjay, editor, Garau, Chiara, editor, Blečić, Ivan, editor, Taniar, David, editor, Apduhan, Bernady O., editor, Rocha, Ana Maria A. C., editor, Tarantino, Eufemia, editor, and Torre, Carmelo Maria, editor

Published
2021
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18. Monitoring Onion Crops Using UAV Multispectral and Thermal Imagery: Preliminary Results

Author

Messina, Gaetano, Praticò, Salvatore, Siciliani, Biagio, Curcio, Antonio, Di Fazio, Salvatore, Modica, Giuseppe, di Prisco, Marco, Series Editor, Chen, Sheng-Hong, Series Editor, Vayas, Ioannis, Series Editor, Kumar Shukla, Sanjay, Series Editor, Sharma, Anuj, Series Editor, Kumar, Nagesh, Series Editor, Wang, Chien Ming, Series Editor, Coppola, Antonio, editor, Di Renzo, Giovanni Carlo, editor, Altieri, Giuseppe, editor, and D'Antonio, Paola, editor

Published
2020
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27. Multispectral Vegetation Indices and Machine Learning Approaches for Durum Wheat (Triticum durum Desf.) Yield Prediction across Different Varieties.

Author

Badagliacca, Giuseppe, Messina, Gaetano, Praticò, Salvatore, Lo Presti, Emilio, Preiti, Giovanni, Monti, Michele, and Modica, Giuseppe

Subjects
PEARSON correlation (Statistics), DURUM wheat, MACHINE learning, WHEAT, CROP yields, SUPPORT vector machines
Abstract

Durum wheat (Triticum durum Desf.) is one of the most widely cultivated cereal species in the Mediterranean basin, supporting pasta, bread and other typical food productions. Considering its importance for the nutrition of a large population and production of high economic value, its supply is of strategic significance. Therefore, an early and accurate crop yield estimation may be fundamental to planning the purchase, storage, and sale of this commodity on a large scale. Multispectral (MS) remote sensing (RS) of crops using unpiloted aerial vehicles (UAVs) is a powerful tool to assess crop status and productivity with a high spatial–temporal resolution and accuracy level. The object of this study was to monitor the behaviour of thirty different durum wheat varieties commonly cultivated in Italy, taking into account their spectral response to different vegetation indices (VIs) and assessing the reliability of this information to estimate their yields by Pearson's correlation and different machine learning (ML) approaches. VIs allowed us to separate the tested wheat varieties into different groups, especially when surveyed in April. Pearson's correlations between VIs and grain yield were good (R2 > 0.7) for a third of the varieties tested; the VIs that best correlated with grain yield were CVI, GNDVI, MTVI, MTVI2, NDRE, and SR RE. Implementing ML approaches with VIs data highlighted higher performance than Pearson's correlations, with the best results observed by random forest (RF) and support vector machine (SVM) models. [ABSTRACT FROM AUTHOR]

Published
2023
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29. Geomatics in Analysing the Evolution of Agricultural Terraced Landscapes

Author

Modica, Giuseppe, Praticò, Salvatore, Pollino, Maurizio, Di Fazio, Salvatore, Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Kobsa, Alfred, editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Terzopoulos, Demetri, editor, Tygar, Doug, editor, Weikum, Gerhard, editor, Murgante, Beniamino, editor, Misra, Sanjay, editor, Rocha, Ana Maria A. C., editor, Torre, Carmelo, editor, Rocha, Jorge Gustavo, editor, Falcão, Maria Irene, editor, Taniar, David, editor, Apduhan, Bernady O., editor, and Gervasi, Osvaldo, editor

Published
2014
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31. Analysis of the Spatiotemporal Urban Expansion of the Rome Coastline through GEE and RF Algorithm, Using Landsat Imagery.

Author

Lodato, Francesco, Colonna, Nicola, Pennazza, Giorgio, Praticò, Salvatore, Santonico, Marco, Vollero, Luca, and Pollino, Maurizio

Subjects
URBAN growth, LANDSAT satellites, REMOTE-sensing images, MULTISPECTRAL imaging, REMOTE sensing, COASTS, ARCHAEOLOGICAL geology
Abstract

This study analyzes, through remote sensing techniques and innovative clouding services, the recent land use dynamics in the North-Roman littoral zone, an area where the latest development has witnessed an important reconversion of purely rural areas to new residential and commercial services. The survey area includes five municipalities and encompasses important infrastructure, such as the "Leonardo Da Vinci" Airport and the harbor of Civitavecchia. The proximity to the metropolis, supported by an efficient network of connections, has modified the urban and peri-urban structure of these areas, which were formerly exclusively agricultural. Hereby, urban expansion has been quantified by classifying Landsat satellite images using the cloud computing platform "Google Earth Engine" (GEE). Landsat multispectral images from 1985 up to 2020 were used for the diachronic analysis, with a five-yearly interval. In order to achieve a high accuracy of the final result, work was carried out along the temporal dimension of the images, selecting specific time windows for the creation of datasets, which were adjusted by the information related to the NDVI index variation through time. This implementation showed interesting improvements in the model performance for each year, suggesting the importance of the NDVI standard deviation parameter. The results showed an increase in the overall accuracy, being from 90 to 97%, with improvements in distinguishing urban surfaces from impervious surfaces. The final results highlighted a significant increase in the study area of the "Urban" and "Woodland" classes over the 35-year time span that was considered, being 67.4 km2 and 70.4 km2, respectively. The accurate obtained results have allowed us to quantify and understand the landscape transformations in the area of interest, with particular reference to the dynamics of urban development. [ABSTRACT FROM AUTHOR]

Published
2023
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39. Machine Learning Classification of Mediterranean Forest Habitats in Google Earth Engine Based on Seasonal Sentinel-2 Time-Series and Input Image Composition Optimisation.

Author

Praticò, Salvatore, Solano, Francesco, Di Fazio, Salvatore, Modica, Giuseppe, and Millard, Koreen

Subjects
*CONSERVATION of natural resources, *MACHINE learning, *NATURE reserves, *SUPPORT vector machines, *MOUNTAIN forests
Abstract

The sustainable management of natural heritage is presently considered a global strategic issue. Owing to the ever-growing availability of free data and software, remote sensing (RS) techniques have been primarily used to map, analyse, and monitor natural resources for conservation purposes. The need to adopt multi-scale and multi-temporal approaches to detect different phenological aspects of different vegetation types and species has also emerged. The time-series composite image approach allows for capturing much of the spectral variability, but presents some criticalities (e.g., time-consuming research, downloading data, and the required storage space). To overcome these issues, the Google Earth engine (GEE) has been proposed, a free cloud-based computational platform that allows users to access and process remotely sensed data at petabyte scales. The application was tested in a natural protected area in Calabria (South Italy), which is particularly representative of the Mediterranean mountain forest environment. In the research, random forest (RF), support vector machine (SVM), and classification and regression tree (CART) algorithms were used to perform supervised pixel-based classification based on the use of Sentinel-2 images. A process to select the best input image (seasonal composition strategies, statistical operators, band composition, and derived vegetation indices (VIs) information) for classification was implemented. A set of accuracy indicators, including overall accuracy (OA) and multi-class F-score (Fm), were computed to assess the results of the different classifications. GEE proved to be a reliable and powerful tool for the classification process. The best results (OA = 0.88 and Fm = 0.88) were achieved using RF with the summer image composite, adding three VIs (NDVI, EVI, and NBR) to the Sentinel-2 bands. SVM and RF produced OAs of 0.83 and 0.80, respectively. [ABSTRACT FROM AUTHOR]

Published
2021
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