Filip Sabo

874 total citations
30 papers, 560 citations indexed

About

Filip Sabo is a scholar working on Ecology, Media Technology and Global and Planetary Change. According to data from OpenAlex, Filip Sabo has authored 30 papers receiving a total of 560 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Ecology, 8 papers in Media Technology and 6 papers in Global and Planetary Change. Recurrent topics in Filip Sabo's work include Remote Sensing in Agriculture (8 papers), Remote-Sensing Image Classification (8 papers) and Geographic Information Systems Studies (4 papers). Filip Sabo is often cited by papers focused on Remote Sensing in Agriculture (8 papers), Remote-Sensing Image Classification (8 papers) and Geographic Information Systems Studies (4 papers). Filip Sabo collaborates with scholars based in Italy, Serbia and Netherlands. Filip Sabo's co-authors include Thomas Kemper, Christina Corbane, Panagiotis Politis, Martino Pesaresi, Vasileios Syrris, Pierre Soille, Aneta J. Florczyk, Michele Melchiorri, Sérgio Freire and Marcello Schiavina and has published in prestigious journals such as SHILAP Revista de lepidopterología, International Journal of Remote Sensing and Environmental Monitoring and Assessment.

In The Last Decade

Filip Sabo

29 papers receiving 535 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Filip Sabo Italy 11 319 140 125 89 85 30 560
Panagiotis Politis Italy 10 345 1.1× 146 1.0× 98 0.8× 93 1.0× 73 0.9× 28 561
Xiaoran Huang China 12 382 1.2× 114 0.8× 175 1.4× 158 1.8× 63 0.7× 36 686
Pesaresi Martino Germany 10 358 1.1× 92 0.7× 75 0.6× 71 0.8× 61 0.7× 29 555
Neema Simon Sumari Tanzania 10 407 1.3× 85 0.6× 91 0.7× 96 1.1× 68 0.8× 20 605
Basudeb Bhatta India 9 470 1.5× 118 0.8× 105 0.8× 178 2.0× 75 0.9× 13 643
Matina Halkia Italy 7 317 1.0× 92 0.7× 72 0.6× 108 1.2× 128 1.5× 8 468
Narumasa Tsutsumida Japan 13 302 0.9× 111 0.8× 184 1.5× 65 0.7× 54 0.6× 48 545
Mo Su China 9 299 0.9× 72 0.5× 125 1.0× 70 0.8× 36 0.4× 16 466
Lakshmi N. Kantakumar India 9 427 1.3× 110 0.8× 128 1.0× 126 1.4× 54 0.6× 10 553
Ferri Stefano Italy 10 531 1.7× 161 1.1× 124 1.0× 156 1.8× 187 2.2× 24 768

Countries citing papers authored by Filip Sabo

Since Specialization
Citations

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

Fields of papers citing papers by Filip Sabo

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Filip Sabo

This figure shows the co-authorship network connecting the top 25 collaborators of Filip Sabo. A scholar is included among the top collaborators of Filip Sabo 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 Filip Sabo. Filip Sabo 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.
Todri‐Sanial, Aida, et al.. (2024). Computing with oscillators from theoretical underpinnings to applications and demonstrators. PubMed. 1(1). 14–14. 8 indexed citations
2.
Sabo, Filip & Aida Todri‐Sanial. (2024). ClassONN: Classification with Oscillatory Neural Networks Using the Kuramoto Model. 1–2. 1 indexed citations
3.
Horst, Folkert, Filip Sabo, Valeria Bragaglia, et al.. (2024). Implementation of FitzHugh-Nagumo Neurons using Nanoscale VO2 Devices. TU/e Research Portal. 729–732. 1 indexed citations
4.
Sabo, Filip, Michele Meroni, François Waldner, & Felix Rembold. (2023). Is deeper always better? Evaluating deep learning models for yield forecasting with small data. Environmental Monitoring and Assessment. 195(10). 1153–1153. 17 indexed citations
5.
Corbane, Christina, Soushi Kato, Koki Iwao, et al.. (2020). Leveraging ALOS-2 PALSAR-2 for Mapping Built-Up Areas and Assessing Their Vertical Component. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. 13. 6473–6483. 2 indexed citations
6.
Corbane, Christina, Panagiotis Politis, Pieter Kempeneers, et al.. (2020). A global cloud free pixel- based image composite from Sentinel-2 data. SHILAP Revista de lepidopterología. 31. 105737–105737. 50 indexed citations
7.
Corbane, Christina, Martino Pesaresi, Thomas Kemper, et al.. (2019). Automated global delineation of human settlements from 40 years of Landsat satellite data archives. Big Earth Data. 3(2). 140–169. 114 indexed citations
8.
Florczyk, Aneta J., Michele Melchiorri, Julian Zeidler, et al.. (2019). The Generalised Settlement Area: mapping the Earth surface in the vicinity of built-up areas. International Journal of Digital Earth. 13(1). 45–60. 20 indexed citations
9.
Corbane, Christina, Filip Sabo, Vasileios Syrris, et al.. (2019). Application of the Symbolic Machine Learning to Copernicus VHR Imagery: The European Settlement Map. IEEE Geoscience and Remote Sensing Letters. 17(7). 1153–1157. 8 indexed citations
10.
Sabo, Filip, et al.. (2019). The European Settlement Map 2019 release. Joint Research Centre (European Commission). 1 indexed citations
11.
Melchiorri, Michele, Marcello Schiavina, Pesaresi Martino, et al.. (2019). Description of the GHS Urban Centre Database 2015. Joint Research Centre (European Commission). 64 indexed citations
12.
Corbane, Christina, Marcello Schiavina, Martino Pesaresi, et al.. (2019). GHS-UCDB R2019A - GHS Urban Centre Database 2015, multitemporal and multidimensional attributes. 15 indexed citations
13.
Sabo, Filip, Christina Corbane, Aneta J. Florczyk, et al.. (2018). Comparison of built‐up area maps produced within the global human settlement framework. Transactions in GIS. 22(6). 1406–1436. 19 indexed citations
14.
Corbane, Christina, Martino Pesaresi, Panagiotis Politis, et al.. (2017). Big earth data analytics on Sentinel-1 and Landsat imagery in support to global human settlements mapping. Big Earth Data. 1(1-2). 118–144. 92 indexed citations
15.
Stefano, Ferri, et al.. (2017). The European Settlement Map 2017 Release; Methodology and output of the European Settlement Map (ESM2p5m). Joint Research Centre (European Commission). 9 indexed citations
16.
Martino, Pesaresi, Panagiotis Politis, Vasileios Syrris, et al.. (2017). MASS PROCESSING OF SENTINEL-1 AND LANDSAT DATA FOR MAPPING HUMAN SETTLEMENTS AT GLOBAL LEVEL. Joint Research Centre (European Commission). 2 indexed citations
17.
Corbane, Christina, Guido Lemoine, Martino Pesaresi, et al.. (2017). Enhanced automatic detection of human settlements using Sentinel-1 interferometric coherence. International Journal of Remote Sensing. 39(3). 842–853. 28 indexed citations
18.
Jovanović, Dušan, et al.. (2016). Impact analysis of pansharpening Landsat ETM+, Landsat OLI, WorldView-2, and Ikonos images on vegetation indices. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 9688. 968814–968814. 8 indexed citations
19.
Jovanović, Dušan, et al.. (2015). Open Satellite Data for the area of Serbia. International Conference on Information Society. 127–132.
20.
Govedarica, Miro, Dušan Jovanović, & Filip Sabo. (2015). Corn yield estimation in Serbia using MODIS 13Q1 product. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 9535. 95351D–95351D. 4 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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