Juan Doblas

599 total citations
24 papers, 334 citations indexed

About

Juan Doblas is a scholar working on Ecology, Environmental Engineering and Global and Planetary Change. According to data from OpenAlex, Juan Doblas has authored 24 papers receiving a total of 334 indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Ecology, 9 papers in Environmental Engineering and 9 papers in Global and Planetary Change. Recurrent topics in Juan Doblas's work include Remote Sensing in Agriculture (12 papers), Remote Sensing and LiDAR Applications (9 papers) and Conservation, Biodiversity, and Resource Management (6 papers). Juan Doblas is often cited by papers focused on Remote Sensing in Agriculture (12 papers), Remote Sensing and LiDAR Applications (9 papers) and Conservation, Biodiversity, and Resource Management (6 papers). Juan Doblas collaborates with scholars based in Brazil, France and United States. Juan Doblas's co-authors include Luiz E. O. C. Aragão, Cláudio Almeida, Sidnei J. S. Sant’Anna, Yosio Edemir Shimabukuro, Y. E. Shimabukuro, Adriano Jerozolimski, Marisa Gesteira Fonseca, Stephan Schwartzman, Liana O. Anderson and Thais M. Rosan and has published in prestigious journals such as SHILAP Revista de lepidopterología, Philosophical Transactions of the Royal Society B Biological Sciences and Ecological Economics.

In The Last Decade

Juan Doblas

20 papers receiving 328 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Juan Doblas Brazil 8 183 141 91 47 33 24 334
Sá Nogueira Lisboa Mozambique 11 210 1.1× 112 0.8× 66 0.7× 81 1.7× 40 1.2× 26 388
Clément Bourgoin France 11 263 1.4× 205 1.5× 114 1.3× 49 1.0× 41 1.2× 24 514
João Victor Siqueira Brazil 4 240 1.3× 170 1.2× 81 0.9× 64 1.4× 24 0.7× 5 327
Him Lal Shrestha Nepal 8 235 1.3× 145 1.0× 68 0.7× 58 1.2× 16 0.5× 25 396
Landing Mané Norway 4 250 1.4× 195 1.4× 91 1.0× 32 0.7× 53 1.6× 8 363
Belay Manjur Gebru South Korea 9 236 1.3× 125 0.9× 44 0.5× 18 0.4× 33 1.0× 13 358
Myat Su Mon Japan 7 226 1.2× 176 1.2× 57 0.6× 40 0.9× 23 0.7× 8 328
F. Sedano United States 9 355 1.9× 166 1.2× 83 0.9× 42 0.9× 25 0.8× 12 511
Rutilio Castro-Miguel Mexico 4 228 1.2× 140 1.0× 27 0.3× 53 1.1× 16 0.5× 7 342
Salomé Misana Tanzania 12 258 1.4× 137 1.0× 61 0.7× 43 0.9× 40 1.2× 26 451

Countries citing papers authored by Juan Doblas

Since Specialization
Citations

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

Fields of papers citing papers by Juan Doblas

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Juan Doblas

This figure shows the co-authorship network connecting the top 25 collaborators of Juan Doblas. A scholar is included among the top collaborators of Juan Doblas 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 Juan Doblas. Juan Doblas 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.
Doblas, Juan, et al.. (2024). Gray Level Co-occurrence Matrix textural analysis for temporal mapping of sea ice in Sentinel-1A SAR images. Anais da Academia Brasileira de Ciências. 96(suppl 2). e20240554–e20240554.
2.
3.
Doblas, Juan, Stéphane Mermoz, Cláudio Almeida, et al.. (2024). DETER-RT: The new INPE-TropiSCO deforestation monitoring system in the Amazon biome. SHILAP Revista de lepidopterología. XLVIII-3-2024. 127–133. 2 indexed citations
4.
Toan, Thuy Le, Ludovic Villard, Juan Doblas, et al.. (2024). Tackling high biomass in tropical forests through the BIOMASS mission. SHILAP Revista de lepidopterología. XLVIII-3-2024. 287–293. 1 indexed citations
5.
Feitosa, Raul Queiroz, et al.. (2024). Deep network based approaches to mitigate seasonal effects in SAR images for deforestation monitoring. SHILAP Revista de lepidopterología. X-3-2024. 261–267.
6.
Mermoz, Stéphane, Juan Doblas, Milena Planells, et al.. (2024). Submonthly Assessment of Temperate Forest Clear-Cuts in Mainland France. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. 17. 13743–13764. 3 indexed citations
7.
Ferro-Famil, Laurent, et al.. (2024). Advanced Bayesian Method for Timely Small-Scale Forest Loss Detection in the Brazilian Amazon and Cerrado with Sentinel-1 Time-Series. SHILAP Revista de lepidopterología. XLVIII-3-2024. 43–49. 1 indexed citations
8.
Pessôa, Ana Carolina Moreira, Celso H. L. Silva, Juan Doblas, et al.. (2023). Protected areas are effective on curbing fires in the Amazon. Ecological Economics. 214. 107983–107983. 5 indexed citations
9.
Doblas, Juan, Stéphane Mermoz, Alexandre Bouvet, et al.. (2023). Inter-comparison of optical and SAR-based forest disturbance warning systems in the Amazon shows the potential of combined SAR-optical monitoring. International Journal of Remote Sensing. 44(1). 59–77. 13 indexed citations
10.
Doblas, Juan, et al.. (2022). DETER-R: An Operational Near-Real Time Tropical Forest Disturbance Warning System Based on Sentinel-1 Time Series Analysis. Remote Sensing. 14(15). 3658–3658. 31 indexed citations
11.
Doblas, Juan, et al.. (2022). Improving Deforestation Detection on Tropical Rainforests Using Sentinel-1 Data and Convolutional Neural Networks. Remote Sensing. 14(14). 3290–3290. 14 indexed citations
12.
Doblas, Juan, et al.. (2021). Assessment of Nonlocal Means Stochastic Distances Speckle Reduction for SAR Time Series. 52. 3265–3268. 3 indexed citations
13.
Silva, Celso H. L., Viola Heinrich, Igor S. Broggio, et al.. (2020). Benchmark maps of 33 years of secondary forest age for Brazil. Scientific Data. 7(1). 269–269. 80 indexed citations
14.
15.
Cassol, Henrique, et al.. (2020). Mapeamento da Vegetação do Cerrado – Uma Revisão das Iniciativas de Sensoriamento Remoto. SHILAP Revista de lepidopterología. 72. 1250–1274. 4 indexed citations
16.
Galvão, Lênio Soares, et al.. (2020). Dynamics of savanna clearing and land degradation in the newest agricultural frontier in Brazil. GIScience & Remote Sensing. 57(7). 965–984. 26 indexed citations
17.
18.
Junqueira, Rodrigo Gravina Prates, et al.. (2018). As Reservas Extrativistas da Terra do Meio: uma experiência de desenvolvimento alternativo para a Amazônia. Desenvolvimento e Meio Ambiente. 48. 3 indexed citations
19.
Schwartzman, Stephan, et al.. (2013). The natural and social history of the indigenous lands and protected areas corridor of the Xingu River basin. Philosophical Transactions of the Royal Society B Biological Sciences. 368(1624). 16 indexed citations
20.
Schwartzman, Stephan, et al.. (2013). The natural and social history of the indigenous lands and protected areas corridor of the Xingu River basin. Philosophical Transactions of the Royal Society B Biological Sciences. 368(1619). 20120164–20120164. 74 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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