Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies
if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the
same subfield and year (this is the minimum needed to enter the top 1%, not the average
within it), or reaches the top citation threshold in at least one of its specific research
topics.
A small-baseline approach for investigating deformations on full-resolution differential SAR interferograms
2004815 citationsRiccardo Lanari, Oscar Mora et al.IEEE Transactions on Geoscience and Remote Sensingprofile →
Peers — A (Enhanced Table)
Peers by citation overlap · career bar shows stage (early→late)
cites ·
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Countries citing papers authored by Michele Manunta
Since
Specialization
Citations
This map shows the geographic impact of Michele Manunta'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 Michele Manunta with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Michele Manunta more than expected).
This network shows the impact of papers produced by Michele Manunta. 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 Michele Manunta. The network helps show where Michele Manunta may publish in the future.
Co-authorship network of co-authors of Michele Manunta
This figure shows the co-authorship network connecting the top 25 collaborators of Michele Manunta.
A scholar is included among the top collaborators of Michele Manunta 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 Michele Manunta. Michele Manunta is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Bonano, Manuela, et al.. (2019). A large scale exploitation of high resolution satellite SAR data to analyze surface deformation in urban areas through the parallel full resolution SBAS-DInSAR approach. EGU General Assembly Conference Abstracts. 17496.1 indexed citations
7.
Manzo, M., Riccardo Lanari, Giuseppe Solaro, et al.. (2019). Ground deformation analysis of the Italian Peninsula through space-borne SAR interferometry and geophysical modelling: the IREA-CNR/MiSE-DGS-UNMIG agreement. EGU General Assembly Conference Abstracts. 14863.1 indexed citations
8.
Manunta, Michele. (2019). The satellite component of the EPOS infrastructure: Thematic Core Service Satellite Data. EGU General Assembly Conference Abstracts. 16052.1 indexed citations
Manunta, Michele, Francesco Casu, Claudio De Luca, et al.. (2017). The Geohazards Exploitation Platform: an advanced cloud-based environment for the Earth Science community. elib (German Aerospace Center). 14911.3 indexed citations
11.
Bonano, Manuela, Chandrakanta Ojha, P. Berardino, et al.. (2017). A new implementation of full resolution SBAS-DInSAR processing chain for the effective monitoring of structures and infrastructures. EGUGA. 17809.1 indexed citations
Zinno, Ivana, Manuela Bonano, Francesco Casu, et al.. (2016). Sentinel-1 DInSAR processing chain within Geohazard Exploitation Platform. EGU General Assembly Conference Abstracts.2 indexed citations
14.
Casu, Francesco, Claudio De Luca, Stefano Elefante, et al.. (2015). New perspectives and advanced approaches on effectively processing Big InSAR data: from long term ERS archives to new Sentinel-1 massive data flow. EGU General Assembly Conference Abstracts. 7802.4 indexed citations
15.
Zhao, Qing, Antonio Pepe, Wei Gao, et al.. (2014). Derivation of Ground Settlement Spatiotemporal Characteristics of Reclaimed Area in Nanhui New City, Shanghai, China, from Time-Series in InSAR Interpretation. ESASP. 724. 39.1 indexed citations
16.
Casu, Francesco, Stefano Elefante, Pasquale Imperatore, et al.. (2013). DInSAR time series generation within a cloud computing environment: from ERS to Sentinel-1 scenario. EGUGA.1 indexed citations
17.
Ardizzone, Francesca, Fabiana Calò, Raffaele Castaldo, et al.. (2012). Temporal and Spatial Analysis of Landslides Through the SBAS-DInSAR Approach: the Ivancich, Assisi, test case. EGU General Assembly Conference Abstracts. 4319.1 indexed citations
18.
Pepe, Antonio, et al.. (2012). New Improvements Of The EMCF Phase Unwrapping Algorithm For Surface Deformation Analysis At Full Spatial Resolution Scale. ESASP. 697. 19.1 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.