Simone Pascucci

2.7k total citations
79 papers, 2.1k citations indexed

About

Simone Pascucci is a scholar working on Ecology, Environmental Engineering and Artificial Intelligence. According to data from OpenAlex, Simone Pascucci has authored 79 papers receiving a total of 2.1k indexed citations (citations by other indexed papers that have themselves been cited), including 46 papers in Ecology, 35 papers in Environmental Engineering and 20 papers in Artificial Intelligence. Recurrent topics in Simone Pascucci's work include Remote Sensing in Agriculture (43 papers), Soil Geostatistics and Mapping (25 papers) and Geochemistry and Geologic Mapping (20 papers). Simone Pascucci is often cited by papers focused on Remote Sensing in Agriculture (43 papers), Soil Geostatistics and Mapping (25 papers) and Geochemistry and Geologic Mapping (20 papers). Simone Pascucci collaborates with scholars based in Italy, China and United States. Simone Pascucci's co-authors include Stefano Pignatti, Raffaele Casa, Fabio Castaldi, Angelo Palombo, Federico Santini, Rosa Maria Cavalli, Wenjiang Huang, Giovanni Laneve, V. Cuomo and Lorenzo Fusilli and has published in prestigious journals such as SHILAP Revista de lepidopterología, PLoS ONE and Remote Sensing of Environment.

In The Last Decade

Simone Pascucci

77 papers receiving 2.1k citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Simone Pascucci Italy 25 1.0k 895 524 430 368 79 2.1k
A. Bannari Canada 18 1.6k 1.5× 994 1.1× 441 0.8× 260 0.6× 740 2.0× 61 2.4k
Lênio Soares Galvão Brazil 31 1.9k 1.8× 1.3k 1.5× 476 0.9× 460 1.1× 1.1k 3.0× 124 3.0k
Abduwasit Ghulam United States 24 844 0.8× 1.3k 1.4× 393 0.8× 745 1.7× 1.0k 2.8× 52 3.0k
Andreas Hueni Switzerland 23 1.3k 1.3× 766 0.9× 278 0.5× 376 0.9× 939 2.6× 84 2.2k
Michael L. Whiting United States 17 816 0.8× 841 0.9× 241 0.5× 345 0.8× 411 1.1× 31 1.5k
W. Dean Hively United States 30 1.3k 1.2× 1.1k 1.3× 455 0.9× 240 0.6× 544 1.5× 69 2.6k
Xinle Zhang China 23 850 0.8× 1.1k 1.2× 211 0.4× 574 1.3× 209 0.6× 93 1.7k
Fabio Castaldi Italy 26 1.0k 1.0× 1.4k 1.5× 297 0.6× 718 1.7× 213 0.6× 48 1.9k
Tim Malthus United Kingdom 28 1.7k 1.6× 887 1.0× 401 0.8× 148 0.3× 776 2.1× 98 2.9k
Michael Vohland Germany 27 747 0.7× 1.5k 1.7× 309 0.6× 753 1.8× 430 1.2× 72 2.4k

Countries citing papers authored by Simone Pascucci

Since Specialization
Citations

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

Fields of papers citing papers by Simone Pascucci

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Simone Pascucci

This figure shows the co-authorship network connecting the top 25 collaborators of Simone Pascucci. A scholar is included among the top collaborators of Simone Pascucci 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 Simone Pascucci. Simone Pascucci 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.
Pascucci, Simone, Maria Francesca Carfora, Raffaele Casa, et al.. (2024). Early-Season Crop Mapping by PRISMA Images Using Machine/Deep Learning Approaches: Italy and Iran Test Cases. Remote Sensing. 16(13). 2431–2431. 7 indexed citations
2.
Casa, Raffaele, Rocchina Guarini, Giovanni Laneve, et al.. (2024). Reduction of the Vegetation and Soil Moisture Effects to Improve Topsoil Properties Retrieval Accuracy from Prisma Images. IRIS Research product catalog (Sapienza University of Rome). 2243–2246. 2 indexed citations
3.
4.
Casa, Raffaele, Raimondo Bruno, Simone Pascucci, et al.. (2023). Topsoil Properties Estimation for Agriculture from Prisma: the Tehra Project. IRIS Research product catalog (Sapienza University of Rome). 3209–3212. 1 indexed citations
5.
6.
Satriani, Antonio, A. Loperte, & Simone Pascucci. (2021). The Cultivation of Industrial Hemp as Alternative Crop in a Less-Favoured Agricultural Area in Southern Italy: The Pignola Case Study. SHILAP Revista de lepidopterología. 1(3). 169–180. 14 indexed citations
7.
8.
Huang, Wenjiang, Weiping Kong, Simone Pascucci, et al.. (2019). A Comparison of Hybrid Machine Learning Algorithms for the Retrieval of Wheat Biophysical Variables from Sentinel-2. Remote Sensing. 11(5). 481–481. 109 indexed citations
9.
Lacava, Teodosio, Alice Madonia, Simone Pascucci, et al.. (2018). Evaluation of MODIS—Aqua Chlorophyll-a Algorithms in the Basilicata Ionian Coastal Waters. Remote Sensing. 10(7). 987–987. 16 indexed citations
10.
Pignatti, Stefano, Hao Yang, Guijun Yang, et al.. (2017). Sensitivity analysis of the Aquacrop and SAFYE crop models for the assessment of water limited winter wheat yield in regional scale applications. PLoS ONE. 12(11). e0187485–e0187485. 59 indexed citations
11.
Santini, Federico, Angelo Palombo, Rob J. Dekker, et al.. (2014). Advanced Anomalous Pixel Correction Algorithms for Hyperspectral Thermal Infrared Data: The TASI-600 Case Study. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. 7(6). 2393–2404. 8 indexed citations
12.
Pascucci, Simone, Raffaele Casa, Claudia Belviso, et al.. (2014). Estimation of soil organic carbon from airborne hyperspectral thermal infrared data: a case study. European Journal of Soil Science. 65(6). 865–875. 16 indexed citations
13.
Belviso, Claudia, E. Agostinelli, Sandra Belviso, et al.. (2014). Synthesis of magnetic zeolite at low temperature using a waste material mixture: Fly ash and red mud. Microporous and Mesoporous Materials. 202. 208–216. 83 indexed citations
14.
Pignatti, Stefano, Lorenzo Fusilli, Angelo Palombo, Federico Santini, & Simone Pascucci. (2013). Effectiveness of airborne multispectral thermal data for karst groundwater resources recognition in coastal areas. EGU General Assembly Conference Abstracts. 1 indexed citations
15.
Pascucci, Simone, Angelo Palombo, Nicola Pergola, et al.. (2013). Karst water resources detection through airborne thermal data: MIVIS and TASI-600 imagery. 49. 4550–4553. 2 indexed citations
16.
Casa, Raffaele, Fabio Castaldi, Simone Pascucci, & Stefano Pignatti. (2012). Potential of Hyperspectral Remote Sensing for Field Scale Soil Mapping and Precision Agriculture Applications. Italian Journal of Agronomy. 7(4). e43–e43. 11 indexed citations
17.
Bassani, Cristiana, Rosa Maria Cavalli, Angelo Palombo, et al.. (2009). Integration of airborne optical and thermal imagery for archaeological subsurface structures detection: the Arpi case study (Italy). EGU General Assembly Conference Abstracts. 7717. 2 indexed citations
18.
Cavalli, Rosa Maria, et al.. (2009). The natural areas of Rome Province detected by airborne remotely sensed data. Annals of Geophysics. 49(1). 2 indexed citations
19.
Cavalli, Rosa Maria, Lorenzo Fusilli, Simone Pascucci, Stefano Pignatti, & Federico Santini. (2008). Hyperspectral Sensor Data Capability for Retrieving Complex Urban Land Cover in Comparison with Multispectral Data: Venice City Case Study (Italy). Sensors. 8(5). 3299–3320. 50 indexed citations
20.
Dall’Oglio, G., et al.. (2003). COCHISE. Cosmological Observations at Concordia with High-sensitivity Instrument for Source Extraction. 2. 38. 1 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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