Claudio Conese

1.2k total citations
30 papers, 975 citations indexed

About

Claudio Conese is a scholar working on Ecology, Media Technology and Atmospheric Science. According to data from OpenAlex, Claudio Conese has authored 30 papers receiving a total of 975 indexed citations (citations by other indexed papers that have themselves been cited), including 24 papers in Ecology, 15 papers in Media Technology and 11 papers in Atmospheric Science. Recurrent topics in Claudio Conese's work include Remote Sensing in Agriculture (24 papers), Remote-Sensing Image Classification (15 papers) and Remote Sensing and Land Use (10 papers). Claudio Conese is often cited by papers focused on Remote Sensing in Agriculture (24 papers), Remote-Sensing Image Classification (15 papers) and Remote Sensing and Land Use (10 papers). Claudio Conese collaborates with scholars based in Italy, Spain and United States. Claudio Conese's co-authors include Fabio Maselli, María Amparo Gilabert Navarro, Giampiero Maracchi, Fabio Roli, Lorenzo Bruzzone, Tiziana De Filippis, Lorenzo Bottai, V. Sacco, F. Miglietta and G. Zipoli and has published in prestigious journals such as Remote Sensing of Environment, IEEE Transactions on Geoscience and Remote Sensing and International Journal of Remote Sensing.

In The Last Decade

Claudio Conese

29 papers receiving 824 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Claudio Conese Italy 17 598 372 343 294 283 30 975
Y. E. Shimabukuro Brazil 17 764 1.3× 398 1.1× 529 1.5× 417 1.4× 219 0.8× 40 1.3k
D. A. Stow United States 11 538 0.9× 265 0.7× 403 1.2× 256 0.9× 248 0.9× 13 863
Kerry Halligan United States 8 466 0.8× 272 0.7× 422 1.2× 370 1.3× 185 0.7× 10 910
Katherine Fitzpatrick-Lins United States 5 415 0.7× 271 0.7× 337 1.0× 236 0.8× 199 0.7× 8 920
L.L.F. Janssen Netherlands 10 382 0.6× 199 0.5× 313 0.9× 302 1.0× 193 0.7× 24 820
Pat Scaramuzza United States 8 661 1.1× 238 0.6× 595 1.7× 324 1.1× 314 1.1× 15 1.2k
A. Dyk Canada 12 682 1.1× 298 0.8× 523 1.5× 442 1.5× 225 0.8× 44 1.2k
F. Abarca-Hernández Spain 5 396 0.7× 259 0.7× 258 0.8× 278 0.9× 157 0.6× 5 761
George H. Rosenfield United States 6 371 0.6× 254 0.7× 288 0.8× 223 0.8× 183 0.6× 11 870
Terry Arvidson United States 10 651 1.1× 288 0.8× 505 1.5× 318 1.1× 235 0.8× 13 1.1k

Countries citing papers authored by Claudio Conese

Since Specialization
Citations

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

Fields of papers citing papers by Claudio Conese

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Claudio Conese

This figure shows the co-authorship network connecting the top 25 collaborators of Claudio Conese. A scholar is included among the top collaborators of Claudio Conese 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 Claudio Conese. Claudio Conese 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.
Rapi, B., et al.. (2007). INTEGRATED TECHNIQUES FOR VINEYARD VARIABILITY EVALUATION. Acta Horticulturae. 379–384. 1 indexed citations
2.
Conese, Claudio, et al.. (2006). Correlation between meteorological data and fire occurrence in a Mediterranean area (Tuscany Region). Forest Ecology and Management. 234. S63–S63. 3 indexed citations
3.
Conese, Claudio, et al.. (2005). BURNED LAND MAPPING FROM REMOTE SENSING IMAGERY. 1 indexed citations
4.
Maselli, Fabio, et al.. (2000). Classification of Mediterranean vegetation by TM and ancillary data for the evaluation of fire risk. International Journal of Remote Sensing. 21(17). 3303–3313. 33 indexed citations
5.
Bruzzone, Lorenzo, Claudio Conese, Fabio Maselli, & Fabio Roli. (1997). Multisource Classification of Complex Rural Areas by Statistical and Neural-Network Approaches. Photogrammetric Engineering & Remote Sensing. 63(5). 523–533. 72 indexed citations
6.
Maracchi, Giampiero, et al.. (1996). Assessment and Examination of Coastal Vegetation Deterioration by Means of Landsat TM Data. Journal of Coastal Research. 12(1). 103–111. 20 indexed citations
7.
Maselli, Fabio, et al.. (1996). Evaluation of forest fire risk by the analysis of environmental data and TM images. International Journal of Remote Sensing. 17(7). 1417–1423. 1 indexed citations
8.
Maselli, Fabio, et al.. (1996). Multi‐scale classification of remotely sensed data by the maximization of fuzzy membership grades. Remote Sensing Reviews. 13(3-4). 187–205. 3 indexed citations
9.
Conese, Claudio, et al.. (1996). Fuzzy classification of spatially degraded Thematic Mapper data for the estimation of sub-pixel components. International Journal of Remote Sensing. 17(3). 537–551. 50 indexed citations
10.
Maselli, Fabio, et al.. (1996). Eco-climatic classification of Tuscany through NOAA-AVHRR data. International Journal of Remote Sensing. 17(12). 2369–2384. 13 indexed citations
11.
Navarro, María Amparo Gilabert, Fabio Maselli, Claudio Conese, & Marco Bindi. (1995). Characterization of primary productivity levels of Niger by means of NOAA NDVI variations. Geocarto International. 10(4). 31–41. 10 indexed citations
12.
Maselli, Fabio, et al.. (1994). Use of probability entropy for the estimation and graphical representation of the accuracy of maximum likelihood classifications. ISPRS Journal of Photogrammetry and Remote Sensing. 49(2). 13–20. 74 indexed citations
13.
Conese, Claudio & Fabio Maselli. (1994). Evaluation of contextual, per‐pixel and mixed classification procedures applied to a sub‐tropical landscape. Remote Sensing Reviews. 9(3). 175–186. 5 indexed citations
14.
Navarro, María Amparo Gilabert, Claudio Conese, & Fabio Maselli. (1994). An atmospheric correction method for the automatic retrieval of surface reflectances from TM images. International Journal of Remote Sensing. 15(10). 2065–2086. 139 indexed citations
15.
Conese, Claudio. (1993). Topographic normalization of TM scenes through the use of an atmospheric correction method and digital terrain model. Photogrammetric Engineering & Remote Sensing. 59(12). 1745–1753. 73 indexed citations
16.
Conese, Claudio & Fabio Maselli. (1993). Selection of optimum bands from TM scenes through mutual information analysis. ISPRS Journal of Photogrammetry and Remote Sensing. 48(3). 2–11. 73 indexed citations
17.
Conese, Claudio & Fabio Maselli. (1992). Use of error matrices to improve area estimates with maximum likelihood classification procedures. Remote Sensing of Environment. 40(2). 113–124. 55 indexed citations
18.
Maselli, Fabio, et al.. (1992). Use of NOAA-AVHRR NDVI data for environmental monitoring and crop forecasting in the Sahel. Preliminary results. International Journal of Remote Sensing. 13(14). 2743–2749. 46 indexed citations
19.
Conese, Claudio & Fabio Maselli. (1991). Use of multitemporal information to improve classification performance of TM scenes in complex terrain. ISPRS Journal of Photogrammetry and Remote Sensing. 46(4). 187–197. 39 indexed citations
20.
Maselli, Fabio, et al.. (1990). Use of error probabilities to improve area estimates based on maximum likelihood classifications. Remote Sensing of Environment. 31(2). 155–160. 15 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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