Sergio Ruggieri

459 total citations
34 papers, 344 citations indexed

About

Sergio Ruggieri is a scholar working on Environmental Engineering, Ecology and Plant Science. According to data from OpenAlex, Sergio Ruggieri has authored 34 papers receiving a total of 344 indexed citations (citations by other indexed papers that have themselves been cited), including 20 papers in Environmental Engineering, 16 papers in Ecology and 15 papers in Plant Science. Recurrent topics in Sergio Ruggieri's work include Remote Sensing in Agriculture (16 papers), Soil Moisture and Remote Sensing (11 papers) and Soil Geostatistics and Mapping (9 papers). Sergio Ruggieri is often cited by papers focused on Remote Sensing in Agriculture (16 papers), Soil Moisture and Remote Sensing (11 papers) and Soil Geostatistics and Mapping (9 papers). Sergio Ruggieri collaborates with scholars based in Italy, Spain and Belgium. Sergio Ruggieri's co-authors include Michele Rinaldi, Annamaria Castrignanò, Daniela De Benedetto, R. Tamborrino, Mariangela Diacono, Carmela Riefolo, Giuseppe Satalino, Pasquale Garofalo, Antonella Belmonte and Alessandro Vittorio Vonella and has published in prestigious journals such as SHILAP Revista de lepidopterología, The Science of The Total Environment and Geoderma.

In The Last Decade

Sergio Ruggieri

33 papers receiving 332 citations

Peers

Sergio Ruggieri

ECOLO

GPC

Benson Kipkemboi Kenduiywo Kenya

Jinbang Peng China

Ethan Shavers United States

Matteo G. Ziliani Saudi Arabia

Santhosh Seelan United States

Rolf Becker Germany

József Szatmári Hungary

Guomin Shao China

Laigang Wang China

Benson Kipkemboi Kenduiywo Kenya

Sergio Ruggieri

98 ×0.5

189 ×1.3

ECOLO

154 ×1.1

95 ×1.6

GPC

33 ×0.9

Citations per year, relative to Sergio Ruggieri Sergio Ruggieri (= 1×) peers Benson Kipkemboi Kenduiywo

Countries citing papers authored by Sergio Ruggieri

Since Specialization

Citations

This map shows the geographic impact of Sergio Ruggieri'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 Sergio Ruggieri with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Sergio Ruggieri more than expected).

Fields of papers citing papers by Sergio Ruggieri

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Sergio Ruggieri. 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 Sergio Ruggieri. The network helps show where Sergio Ruggieri may publish in the future.

Co-authorship network of co-authors of Sergio Ruggieri

This figure shows the co-authorship network connecting the top 25 collaborators of Sergio Ruggieri. A scholar is included among the top collaborators of Sergio Ruggieri 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 Sergio Ruggieri. Sergio Ruggieri is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

Ruggieri, Sergio, et al.. (2025). Robustness of Actual Evapotranspiration Predicted by Random Forest Model Integrating Remote Sensing and Meteorological Information: Case of Watermelon (Citrullus lanatus, (Thunb.) Matsum. & Nakai, 1916). Water. 17(3). 323–323. 6 indexed citations

Giannico, Vincenzo, et al.. (2025). Prediction of Winter Wheat Parameters with Planet SuperDove Imagery and Explainable Artificial Intelligence. Agronomy. 15(1). 241–241. 2 indexed citations

Satalino, Giuseppe, Anna Balenzano, Francesco Lovergine, et al.. (2024). Copernicus Sentinels For Tillage Change Detection. 1249–1252.

Satalino, Giuseppe, Anna Balenzano, Francesco Lovergine, et al.. (2024). Earth Observation for the Early Forecast of Irrigation Needs. 4912–4915. 1 indexed citations

Rinaldi, Michele, Sergio Ruggieri, Giuseppe Satalino, et al.. (2024). A Crop Model for Large Scale and Early Irrigation Requirements Estimation. 3. 2807–2810. 1 indexed citations

Rana, Gianfranco, et al.. (2023). Decoupling factor, aerodynamic and canopy conductances of a hedgerow olive orchard under Mediterranean climate. Theoretical and Applied Climatology. 153(1-2). 349–365. 1 indexed citations

Ferrara, Rossana Monica, Pasquale Campi, Salvatore Camposeo, et al.. (2023). Water use of a super high-density olive orchard submitted to regulated deficit irrigation in Mediterranean environment over three contrasted years. Irrigation Science. 42(1). 57–73. 9 indexed citations

Ferrara, Rossana Monica, et al.. (2023). Transpiration by sap flow Thermal Dissipation Method: applicability to a hedgerow olive orchard. 37–46. 1 indexed citations

Mattia, Francesco, Anna Balenzano, Giuseppe Satalino, et al.. (2023). Earth Observation Retrieval and Classification Algorithms for Agriculture. 1428–1431. 2 indexed citations

10.

Castrignanò, Annamaria, Antonella Belmonte, I. Antelmi, et al.. (2020). A geostatistical fusion approach using UAV data for probabilistic estimation of Xylella fastidiosa subsp. pauca infection in olive trees. The Science of The Total Environment. 752. 141814–141814. 24 indexed citations

11.

Barca, Emanuele, Annamaria Castrignanò, Sergio Ruggieri, & Michele Rinaldi. (2019). A new supervised classifier exploiting spectral-spatial information in the Bayesian framework. International Journal of Applied Earth Observation and Geoinformation. 86. 101990–101990. 10 indexed citations

12.

Cartus, Oliver, U. Wegmüller, Giuseppe Satalino, et al.. (2019). Sensitivity of Sentinel-1 Interferometric Coherence to Crop Structure and Soil Moisture. IRIS Research product catalog (Sapienza University of Rome). 6219–6222. 3 indexed citations

13.

Riefolo, Carmela, Annamaria Castrignanò, Claudio Colombo, et al.. (2019). Investigation of soil surface organic and inorganic carbon contents in a low-intensity farming system using laboratory visible and near-infrared spectroscopy. Archives of Agronomy and Soil Science. 66(10). 1436–1448. 16 indexed citations

14.

Satalino, Giuseppe, Francesco Mattia, Anna Balenzano, et al.. (2018). Sentinel-1 & Sentinel-2 Data for Soil Tillage Change Detection. 6627–6630. 14 indexed citations

15.

Rinaldi, Michele, Annamaria Castrignanò, Daniela De Benedetto, et al.. (2014). Discrimination of tomato plants under different irrigation regimes: analysis of hyperspectral sensor data. Environmetrics. 26(2). 77–88. 16 indexed citations

16.

Malinverni, Eva Savina, Michele Rinaldi, & Sergio Ruggieri. (2012). AGRICULTURAL CROP CHANGE DETECTION BY MEANS OF HYBRID CLASSIFICATION AND HIGH RESOLUTION IMAGES. Università Politecnica delle Marche (Università Politecnica delle Marche). 4 indexed citations

17.

Mattia, Francesco, Giuseppe Satalino, Anna Balenzano, et al.. (2012). Time series of COSMO-SkyMed data for landcover classification and surface parameter retrieval over agricultural sites. Nova Science Publishers (Nova Science Publishers, Inc.). 5. 6511–6514. 9 indexed citations

18.

Benedetto, Daniela De, Annamaria Castrignanò, Michele Rinaldi, et al.. (2012). An approach for delineating homogeneous zones by using multi-sensor data. Geoderma. 199. 117–127. 52 indexed citations

19.

Manachini, Barbara, et al.. (2011). Preliminary selection of non-target Lepidoptera species for ecological risk assessment of Bt canola in Sicily. Nova Science Publishers (Nova Science Publishers, Inc.). 66. 59–63. 1 indexed citations

20.

Satalino, Giuseppe, Francesco Mattia, Sergio Ruggieri, & Michele Rinaldi. (2009). LAI estimation of agricultural crops from optical data at different spatial resolution. 112. IV–797. 2 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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