{"id":2769,"date":"2022-07-28T16:28:00","date_gmt":"2022-07-28T19:28:00","guid":{"rendered":"https:\/\/www.ufrgs.br\/ppgsr\/?page_id=2769"},"modified":"2025-12-27T17:57:26","modified_gmt":"2025-12-27T20:57:26","slug":"featured-scientific-articles","status":"publish","type":"page","link":"https:\/\/www.ufrgs.br\/ppgsr\/en\/publications\/featured-scientific-articles\/","title":{"rendered":"Featured scientific articles"},"content":{"rendered":"\n
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Articles published in international journals by faculty, students and recent graduates of PPGSR\/UFRGS:<\/strong><\/p>\n\n\n\n

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2025 (under construction)<\/h2>\n\n\n\n
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VARNIER, MACLEIDI; WEBER, ELISEU JOS\u00c9. “Evaluating the Accuracy of Land-Use Change Models for Predicting Vegetation Loss Across Brazilian Biomes” Land<\/em> 14, no. 3: 560. – 2025: https:\/\/doi.org\/10.3390\/land14030560<\/a><\/p>\n\n\n\n

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2024<\/h2>\n\n\n\n

FONTANA, DENISE CYBIS; RADIN, BERNADETE ; OLIVEIRA, GUILHERME ARI FERREIRA DE ; BELFANTE JUNIOR, VLAMIR ; BREMM, CAROLINA . Annual and daily pattern of soil temperature in an integrated crop-livestock system in the south of Brazil. Agrometeoros<\/em>,<\/strong> v. 32, p. e027624-2024, 2024.DOI: http:\/\/dx.doi.org\/10.31062\/agrom.v32.e027624<\/a><\/p>\n\n\n\n

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DE OLIVEIRA, Allan de Oliveira; SARMENTO, Eliana Casco; DOS SANTOS, Roberta Roxilene; HASENACK, Heinrich; WEBER, Eliseu Jos\u00e9; ROSA, Maria Luiza Correa da Camara. Vector cartographic database of geological data of the Coastal Province of the State of Rio Grande do Sul, Brazil. Latin American Data in Science<\/em>, [S. l.], v. 4, n. 1, p. 2\u201310, 2024. DOI: https:\/\/doi.org\/10.53805\/lads.v4i1.68<\/a><\/p>\n\n\n\n

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ANDRADE, HUGO NUNES; NUNES, ANDR\u00c9 BECKER; TEIXEIRA, MATEUS SILVA; QUADRO, M\u00c1RIO FRANCISCO LEAL DE; AVILA, VILSON DIAS DE; OLIVEIRA, FABR\u00cdCIO SANGUINETTI CRUZ DE; ALVES, RITA DE C\u00c1SSIA MARQUES. Composite Analysis of Explosive Cyclones in the Southern Atlantic Ocean. International Journal of Climatology<\/em>, 2024. DOI: https:\/\/doi.org\/10.1002\/joc.8737<\/a>.<\/p>\n\n\n\n

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GIANUCA, KAHUAM; SILVA, TATIANA ; ASMUS, MILTON . Ecosystem-based spatial modeling: Assessing the supply of hydrological services in a watershed in Southern Brazil. ECOLOGICAL MODELLING<\/em>, v. 492, p. 110723, 2024. DOI: https:\/\/doi.org\/10.1016\/j.ecolmodel.2024.110723<\/p>\n\n\n\n

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FONTOURA, GLAUBER DA; FREITAS, LUIS ANTONIO DE; SILVA, TATIANA; POSSANTTI, IPOR\u00c3. Equivalent biodiversity area: A novel metric for No Net Loss success in Brazil\u2019s changing biomes. Journal of Environmental Management<\/em>, v. 355, p. 120540, mar. 2024. DOI:https:\/\/doi.org\/10.1016\/j.jenvman.2024.120540<\/a><\/p>\n\n\n\n

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BERRA, ELIAS FERNANDO; FONTANA, DENISE CYBIS; YIN, FENG; BREUNIG, FABIO MARCELO. Harmonized Landsat and Sentinel-2 Data with Google Earth Engine. <\/strong>Remote Sensing<\/em>, v. 16, n. 15, p. 2695, 2024. DOI: https:\/\/doi.org\/10.3390\/rs16152695.<\/a><\/p>\n\n\n\n

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QUEVEDO, RENATA PACHECO; MACIEL, DANIEL ANDRADE; REIS, MARIANE SOUZA; RENN\u00d3, CAMILO DALELES; DUTRA, LUCIANO VIEIRA; ANDRADES-FILHO, CL\u00d3DIS DE OLIVEIRA; VEL\u00c1STEGUI-MONTOYA, ANDR\u00c9S; ZHANG, TINGYU; K\u00d6RTING, THALES SEHN; ANDERSON, LIANA OIGHENSTEIN. Land use and land cover changes without invalid transitions: A case study in a landslide-affected area. Remote Sensing Applications: Society and Environment<\/em>, v. 36, p. 101314, nov. 2024.DOI: https:\/\/doi.org\/10.1016\/j.rsase.2024.101314<\/a><\/p>\n\n\n\n

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PRATES HALLAL, G.; DE ALMEIDA ESPINOZA, J. M.; VEETTIL, B. K.; PORCHER, C. C.; OLIVEIRA RIGHI DA SILVA, M.; BEATRIZ ALVES ROLIM, S. Mapping heavy mineral deposits on the coast of the state of Rio Grande do Sul (Brazil) using orbital and proximal remote sensing. PLoS ONE<\/em>, v. 19, n. 9, p. e0309043, 2024. DOI: https:\/\/doi.org\/10.1371\/journal.pone.0309043.<\/a><\/p>\n\n\n\n

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CANO, DEYVIS; CACCIUTTOLO, CARLOS; HALLER, ANDREAS; ROSARIO, CIZA; GUERRA, JUAN CARLOS; OLIVEIRA, GUILHERME GARCIA DE. Spatio-temporal tendencies of urban land surface temperature on the Andean piedmont under climate change: A case study of Metropolitan Lima, Peru (1986\u20132024). Remote Sensing Applications<\/em>: Society and Environment, v. 36, p. 101378, nov. 2024. DOI: https:\/\/doi.org\/10.1016\/j.rsase.2024.101378<\/a><\/p>\n\n\n\n

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RODIGHERI, GRAZIELI; FONTANA, DENISE CYBIS; LUZ, LUANA BECKER DA; DALMAGO, GENEI ANTONIO; SCHIRMBECK, LUCIMARA WOLFARTH; SCHIRMBECK, JULIANO; GOUV\u00caA, JORGE ALBERTO DE; CUNHA, GILBERTO ROCCA DA. TVDI-based water stress coefficient to estimate net primary productivity in soybean areas. Ecological Modelling<\/em>, v. 490, p. 110636, abr. 2024. DOI: https:\/\/doi.org\/10.1016\/j.ecolmodel.2024.110636<\/a><\/p>\n\n\n\n

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FERNANDES, RODRIGO; FERREIRA, ANTONIO; NASCIMENTO, VICTOR; FREITAS, MARCOS; OMETTO, JEAN. Urban Heat Island Assessment in the Northeastern State Capitals in Brazil Using Sentinel-3 SLSTR Satellite Data. Sustainability<\/em>, v. 16, n. 11, p. 4764, 2024. DOI: https:\/\/doi.org\/10.3390\/su16114764.<\/a><\/p>\n\n\n\n

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2023<\/h2>\n\n\n\n
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SALES, V. F.; ZANOTTA, D. C.; MARQUES JR., A.; RACOLTE, G.; MULLER, M.; CAZARIN, C. L. An adaptive spectral index for carbonate rocks using OLI Landsat-8 imagery. Geocarto International<\/em>, v. 38, n. 1, 2023. DOI: https:\/\/doi.org\/10.1080\/10106049.2023.2179671<\/a><\/p>\n\n\n\n

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ZANOTTA, DANIEL C.; MARQUES JUNIOR, ADEMIR; MOTTA, JO\u00c3O GABRIEL; SALES, VIN\u00cdCIUS; GUIMAR\u00c3ES, TAIN\u00c1 T.; KUPSSINSKU, LUCAS S.; RACOLTE, GRACIELA; BORDIN, FABIANE; CAZARIN, CAROLINE L.; GONZAGA JR., LUIZ; VERONEZ, MAUR\u00cdCIO R. An assisted multi-frame approach for super-resolution in hyperspectral images of rock samples. Computers & Geosciences<\/em>, v. 181, p. 105456, dez. 2023. DOI: https:\/\/doi.org\/10.1016\/j.cageo.2023.105456<\/a><\/p>\n\n\n\n

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MENDON\u00c7A, LUIS FELIPE FERREIRA DE; FETTER-FILHO, ANT\u00d4NIO FERNANDO HARTER; ANDRADE, MAURO MICHELENA; OLIVEIRA, FABR\u00cdCIO SANGUINETTI CRUZ DE; LINDEMANN, DOUGLAS DA SILVA; FREITAS, ROSE ANE PEREIRA DE; REIS, RAFAEL AFONSO DO NASCIMENTO; LENTINI, CARLOS ALESSANDRE DOMINGOS; PARISE, CLAUDIA KLOSE; SANTOS, DANIEL CAETANO. Analysis of a coastal-trapped wave generated by the 2016 extra-tropical cyclonic system in the Southern Brazilian continental shelf with COAWST modeling system. Journal of Geophysical Research: Oceans<\/em>, 2024. DOI: https:\/\/doi.org\/10.1016\/j.jsames.2023.104522<\/a><\/p>\n\n\n\n

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FONTANA, A. G., NASCIMENTO, V. F., OMETTO, J. P., & DO AMARAL, F. H. F. (2023). Analysis of past and future urban growth on a regional scale using remote sensing and machine learning. Frontiers in Remote Sensing<\/em>, 4, 1123254. DOI: https:\/\/doi.org\/10.3389\/frsen.2023.1123254<\/a><\/p>\n\n\n\n

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SFREDDO, G. A., SILVA, T. S., & BARBOZA, E. G. (2023). Assessment of local coastal vulnerability based on a global model: A case study in Jaguaruna, southern Brazil. Regional Studies in Marine Science<\/em>, 61, 102824. DOI: https:\/\/doi.org\/10.1016\/j.rsma.2023.102824<\/a><\/p>\n\n\n\n

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SILVEIRA, LEONARD N. DA; NASCIMENTO, V\u00cdCTOR FERNANDEZ; CASAGRANDE, FERNANDA; SOUZA, SERGIO FLOR\u00caNCIO DE; OMETTO, JEAN PIERRE HENRY BALBAUD. Assessment of soil loss susceptibility in geodetic landmarks for the past and future climate change scenarios. Journal of South American Earth Sciences<\/em>, v. 130, p. 104551, out. 2023. DOI: https:\/\/doi.org\/10.1016\/j.jsames.2023.104551<\/a><\/p>\n\n\n\n

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ALMEIDA JUNIOR, V. H. DE, & GEREMIA-NIEVINSKI, F. (2023). Computation of specular reflections on a sphere: Assessment and validation of algorithms based on special boundary cases. Computers & Geosciences<\/em>, 176, 105357. DOI: https:\/\/doi.org\/10.1016\/j.cageo.2023.105357<\/a><\/p>\n\n\n\n

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Thalia Nikolaidou , Marcelo Santos , Simon Williams , et al. Development and validation of comprehensive closed formulas for atmospheric delay and altimetry correction in ground-based GNSS-R. <\/strong>TechRxiv<\/em>. November 01, 2022. DOI: 10.36227\/techrxiv.14345153.v4<\/a><\/p>\n\n\n\n

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KORB, C. C., GUASSELLI, L. A., BELLOLI, T. F., & CUNHA, C. S. (2023). Din\u00e2mica espa\u00e7o-temporal de pulsos de inunda\u00e7\u00f5es nas \u00c1reas \u00damidas do Parque Nacional da Lagoa do Peixe, sul do Brasil. Investigaciones Geogr\u00e1ficas<\/em>.DOI: https:\/\/doi.org\/10.5354\/0719-5370.2023.71701<\/a><\/p>\n\n\n\n

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JESUS, J. B. DE, KUPLICH, T. M., BARRETO, \u00cd. D. DE C., & GAMA, D. C. (2023). Dual polarimetric decomposition in Sentinel-1 images to estimate aboveground biomass of arboreal caatinga. Remote Sensing<\/em>, 15(15), 4187. DOI:  https:\/\/doi.org\/10.3390\/rs15154187<\/a><\/p>\n\n\n\n

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Loureiro, A. I., Bressane, A., Nascimento, V. F., & Negri, R. G. (2023). Enhancing landfill monitoring and assessment: A proposal combining GIS-based analytic hierarchy processes and fuzzy artificial intelligence. Knowledge<\/em>, 3(4), 610-625. DOI: https:\/\/doi.org\/10.3390\/knowledge3040038<\/a><\/p>\n\n\n\n

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DE JESUS, J.B., KUPLICH, T.M., DE C. BARRETO, \u00cd.D. et al. Estimation of aboveground biomass of arboreal species in the semi-arid region of Brazil using SAR (synthetic aperture radar) images. J. Arid Land<\/em> 15, 695\u2013709 (2023). DOI: https:\/\/doi.org\/10.1007\/s40333-023-0017-4<\/a><\/p>\n\n\n\n

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Herrmann PB, Nascimento VF, Freitas MWDd and Ometto JP (2023) Fire in highland grasslands in the Atlantic Forest Biome, a burned areas time series analysis and its correlation with the legislation. Front. Remote Sens<\/em>. 4:1099430. DOI: https:\/\/doi.org\/10.3389\/frsen.2023.1099430<\/a><\/p>\n\n\n\n

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FERNANDES, R.; NASCIMENTO, V.; FREITAS, M.; OMETTO, J. Local Climate Zones to Identify Surface Urban Heat Islands: A Systematic Review. Remote Sens<\/em>. 2023, 15, 884.DOI: https:\/\/doi.org\/10.3390\/rs15040884<\/a><\/p>\n\n\n\n

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BECERRA-ROND\u00d3N, ADRIANA, DUCATI, JORGE, & HAAG, RAFAEL. (2023). Partial COVID-19 lockdown effect in atmospheric pollutants and indirect impact in UV radiation in Rio Grande do Sul, Brazil. Atm\u00f3sfera<\/em>, 36(1), 143-154. Epub 07 de noviembre de 2022.DOI: https:\/\/doi.org\/10.20937\/atm.53027<\/a><\/p>\n\n\n\n

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ROLIM, S. B. A., VEETTIL, B. K., VIEIRO, A. P., KESSLER, A. B., & GONZATTI, C. (2023). Remote sensing for mapping algal blooms in freshwater lakes: A review. Environmental Science and Pollution Research International<\/em>, 30(8), 19602-19616. DOI: https:\/\/doi.org\/10.1007\/s11356-023-25230-2<\/a><\/p>\n\n\n\n

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ROCHA, N. S. DA, VEETTIL, B. K., WARD, R. D., COSTI, J., & ROLIM, S. B. A. (2023). Remote sensing of grasslands in the South American Pampas (scientometrics analysis). Land Degradation & Development<\/em>. DOI: https:\/\/doi.org\/10.1002\/ldr.4658<\/a><\/p>\n\n\n\n

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Herrmann, P. B., Nascimento, V. F., Casagrande, F., Freitas, M. W. D., & Klug, A. C. (2023). Spatial modeling of fire in the Atlantic forest considering future climate change scenarios in Rio Grande do Sul state \u2013 Brazil. Journal of South American Earth Sciences<\/em>, 131, 104614. DOI: https:\/\/doi.org\/10.1016\/j.jsames.2023.104614<\/a><\/p>\n\n\n\n

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Kappes, B. B.; Kuplich. T. M.; Silva, T. S.; Weber, E. J. (2023). Using multilayer perceptron and similarity\u2010weighted machine learning algorithms to reconstruct the past: A case study of the agricultural expansion on grasslands in the Uruguayan savannas. Integrated Environmental Assessment and Management<\/em>, v. 00, p. 1-16, 2023. DOI: https:\/\/doi.org\/10.1002\/ieam.4852<\/a><\/p>\n\n\n\n

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Lima, B. D., C\u00e1ssia Marques Alves, R., Oliveira, G. G., & Paim, B. L. (2023). The performance of artificial neural networks for modeling daily concentrations of particulate matter from meteorological data. Environmental Monitoring and Assessment<\/em>, 195(11), 1305. DOI: https:\/\/doi.org\/10.1007\/s10661-023-11911-5<\/a><\/p>\n\n\n\n

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Geremia-Nievinski, F. (2023). Low-Cost Ground-Based GNSS Reflectometry. In: Sideris, M.G. (eds) Encyclopedia of Geodesy<\/em>. Encyclopedia of Earth Sciences Series. Springer, Cham. DOI: https:\/\/doi.org\/10.1007\/978-3-319-02370-0_175-1<\/a><\/p>\n\n\n\n

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Hofmann, G. S., Silva, R. C., Weber, E. J., Barbosa, A. A., Oliveira, L. F. B., Alves, R. J. V., Hasenack, H., Schossler, V., Aquino, F. E., Cardoso, M. F. (2023). Changes in atmospheric circulation and evapotranspiration are reducing rainfall in the Brazilian Cerrado. Scientific Reports<\/em>, 13, 11236. DOI: https:\/\/doi.org\/10.1038\/s41598-023-38174-x<\/a><\/p>\n\n\n\n

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2022<\/h2>\n\n\n\n
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Karegar, M. A., Kusche, J., Geremia-Nievinski, F., & Larson, K. M. (2022). Raspberry Pi Reflector (RPR): A low-cost water-level monitoring system based on GNSS Interferometric Reflectometry. Water Resources Research<\/em>, 58, e2021WR031713. DOI: https:\/\/doi.org\/10.1029\/2021WR031713<\/a><\/p>\n\n\n\n

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Baeza, S., V\u00e9lez-Martin, E., […], Schirmbeck, J., […], Weber, E. J., […]. (2022). Two decades of land cover mapping in the R\u00edo de la Plata grassland region: The MapBiomas Pampa initiative. Remote Sensing Applications: Society and Environment<\/em>, 28, 100834 (November 2022). DOI: https:\/\/doi.org\/10.1016\/j.rsase.2022.100834<\/a><\/p>\n\n\n\n

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Gameiro, S., Oliveira, G. G., Guasselli, L. A. (2022). The influence of sampling on landslide susceptibility mapping using artificial neural networks. Geocarto International<\/em>, 37, 1-25 (6 November 2022). DOI: https:\/\/doi.org\/10.1080\/10106049.2022.2144475<\/a><\/p>\n\n\n\n

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Belloli, T. F., Guasselli, L. A., Kuplich, T. M., Ruiz, L. F. C., Arruda, D. C., Etchelar, C. B., Simioni, J. D. (2022). Estimation of aboveground biomass and carbon in palustrine wetland using bands and multispectral indices derived from optical satellite imageries PlanetScope and Sentinel-2A. Journal of Applied Remote Sensing<\/em>, 16(3), 034516 (4 August 2022). DOI: https:\/\/doi.org\/10.1117\/1.JRS.16.034516<\/a><\/p>\n\n\n\n

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Lucchese, L. V., Oliveira, G. G., Pedrollo, O. C. (2022). A hybrid Random Forests and Artificial Neural Networks Bagging Ensemble for Landslide Susceptibility Modelling. Geocarto International<\/em>, 37, 1-18 (3 August 2022). DOI: http:\/\/dx.doi.org\/10.1080\/10106049.2022.2109761<\/a><\/p>\n\n\n\n

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Hillebrand, F. L., Bremer, U. F., de Freitas, M. W. D., Costi, J., Mendes Junior, C. W., Arigony-Neto, J., & Sim\u00f5es, J. C. (2022). Spectral linear mixing model applied to data from passive microwave radiometers for sea ice mapping in the Antarctic Peninsula. Geocarto International<\/em>, 37, 3141-3166. DOI: https:\/\/doi.org\/10.1080\/10106049.2020.1856194<\/a><\/p>\n\n\n\n

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Martinez-Felix, C. A., Vazquez-Becerra, G. E., Geremia-Nievinski, F., Millan-Almaraz, J. R., Franco-Ochoa, C., Melgarejo-Morales, A., & Gaxiola-Camacho, J. R. (2022). Tidal measurements in the Gulf of Mexico: intercomparison of coastal tide gauge, insular GNSS reflectometry and SAR altimetry. GPS Solutions<\/em>, 26(1), 1-10. DOI: https:\/\/doi.org\/10.1007\/s10291-021-01207-x<\/a><\/p>\n\n\n\n

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Simioni, J. P. D., Guasselli, L. A., Belloli, T. F., & Ramos, R. A. (2022). Assessment of fire resilience in subtropical wetlands using high spatial resolution images. Environmental Monitoring and Assessment<\/em>, 194(6), 1-14. DOI: https:\/\/doi.org\/10.1007\/s10661-022-09985-8<\/a><\/p>\n\n\n\n

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Zhang, T., Quevedo, R. P., Wang, H., Fu, Q., Luo, D., Wang, T., \u2026 & Renno, C. D. (2022). Improved tree-based machine learning algorithms combining with bagging strategy for landslide susceptibility modeling. Arabian Journal of Geosciences<\/em>, 15(2), 1-19. DOI: https:\/\/doi.org\/10.1007\/s12517-022-09488-3<\/a><\/p>\n\n\n\n

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K\u00e4fer, P. S., da Rocha, N. S., Veeck, G. P., Diaz, L. R., da Costa, S. T. L., Kaiser, E. A., \u2026 & Rolim, S. B. A. (2022). Assessing uncertainties in estimating surface energy fluxes from remote sensing over natural grasslands in Brazil. Theoretical and Applied Climatology<\/em>, 148(1), 751-765. DOI: https:\/\/doi.org\/10.1007\/s00704-021-03869-6<\/a><\/p>\n\n\n\n

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de Jesus, J. B., de Oliveira, D. G., Ara\u00fajo, W. S., da Cruz, L. S., & Kuplich, T. M. (2022). Influence of anthropization on the floristic composition and phytosociology of the Caatinga susceptible to desertification in the state of Sergipe, Brazil. Tropical Ecology<\/em>, 1-11. DOI: https:\/\/doi.org\/10.1007\/s42965-021-00201-1<\/a><\/p>\n\n\n\n

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da Rosa, C. N., Pereira Filho, W., Bremer, U. F., Putzke, J., de Andrade, A. M., Kramer, G., \u2026 & de Jesus, J. B. (2022). Spectral behavior of vegetation in Harmony Point, Nelson Island, Antarctica. Biodiversity and Conservation<\/em>, 1-19. DOI: https:\/\/doi.org\/10.1007\/s10531-022-02408-7<\/a><\/p>\n\n\n\n

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Gameiro, S., Nascimento, V., Facco, D., Sfredo, G., & Ometto, J. (2022). Multitemporal Spatial Analysis of Land Use and Land Cover Changes in the Lower Jaguaribe Hydrographic Sub-Basin, Cear\u00e1, Northeast Brazil. Land<\/em>, 11(1), 103. DOI: https:\/\/doi.org\/10.3390\/land11010103<\/a><\/p>\n\n\n\n

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de Barros Franco, D. G., Steiner, M. T. A., Fernandes, R. P., & Nascimento, V. F. (2022). Modeling municipal solid waste disposal consortia on a regional scale for present and future scenarios. Socio-Economic Planning Sciences<\/em>, 101333. DOI: https:\/\/doi.org\/10.1016\/j.seps.2022.101333<\/a><\/p>\n\n\n\n

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Kupssinsk\u00fc, L. S., Guimar\u00e3es, T. T., Cardoso, M. D. B., Bachi, L., Zanotta, D., Estilon de Souza, I., \u2026 & Gonzaga Jr, L. (2022). Hyperspectral data as a proxy for porosity estimation of carbonate rocks. Australian Journal of Earth Sciences<\/em>, 1-15. DOI: https:\/\/doi.org\/10.1080\/08120099.2022.2046636<\/a><\/p>\n\n\n\n

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Racolte, G., Marques, A., Scalco, L., Tonietto, L., Zanotta, D. C., Cazarin, C. L., \u2026 & Veronez, M. R. (2022). Spherical K-means and Elbow method optimizations with Fisher statistics for 3D stochastic DFN from Virtual Outcrop Models. IEEE Access<\/em>, 10, 63723-63735. DOI: http:\/\/dx.doi.org\/10.1109\/ACCESS.2022.3182332<\/a><\/p>\n\n\n\n

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Marques, A., Racolte, G., Zanotta, D. C., Menezes, E., Cazarin, C. L., Gonzaga, L., & Veronez, M. R. (2022). Adaptive Segmentation for Discontinuity Detection on Karstified Carbonate Outcrop Images From UAV-SfM Acquisition and Detection Bias Analysis. IEEE Access<\/em>, 10, 20514-20526. DOI: http:\/\/dx.doi.org\/10.1109\/access.2022.3151897<\/a><\/p>\n\n\n\n

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2021<\/h2>\n\n\n\n
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Yamawaki, M. K., Geremia-Nievinski, F., & Monico, J. G. (2021). High-rate altimetry in SNR-based GNSS-R: Proof-of-concept of a synthetic vertical array. IEEE Geoscience and Remote Sensing Letters<\/em>, 19, 1-5. DOI: 10.1109\/LGRS.2021.3068091<\/a><\/p>\n\n\n\n

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Fagundes, M. A. R., Mendon\u00e7a-Tinti, I., Iescheck, A. L., Akos, D. M., & Geremia-Nievinski, F. (2021). An open-source low-cost sensor for SNR-based GNSS reflectometry: Design and long-term validation towards sea-level altimetry. GPS Solutions<\/em>, 25(2), 1-11. DOI: https:\/\/doi.org\/10.1007\/s10291-021-01087-1<\/a><\/p>\n\n\n\n

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Hillebrand, F. L., Bremer, U. F., de Freitas, M. W. D., Costi, J., Mendes J\u00fanior, C. W., Arigony-Neto, J., \u2026 & de Jesus, J. B. (2021). Statistical modeling of sea ice concentration in the northwest region of the Antarctic Peninsula. Environmental Monitoring and Assessment<\/em>, 193(2), 1-22. DOI: https:\/\/doi.org\/10.1007\/s10661-021-08843-3<\/a><\/p>\n\n\n\n

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Abrantes, T. C., Queiroz, A. R. S., Lucio, F. R., Mendes Junior, C. W., Kuplich, T. M., Bredemeier, C., & Merotto Junior, A. (2021). Assessing the effects of dicamba and 2, 4 Dichlorophenoxyacetic acid (2, 4D) on soybean through vegetation indices derived from Unmanned Aerial Vehicle (UAV) based RGB imagery. International Journal of Remote Sensing<\/em>, 42(7), 2740-2758. DOI: https:\/\/doi.org\/10.1080\/01431161.2020.1832283<\/a><\/p>\n\n\n\n

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Hillebrand, F. L., de Carvalho Barreto, I. D., Bremer, U. F., Arigony-Neto, J., J\u00fanior, C. W. M., Sim\u00f5es, J. C., \u2026 & de Jesus, J. B. (2021). Application of textural analysis to map the sea ice concentration with sentinel 1A in the western region of the Antarctic Peninsula. Polar Science<\/em>, 29, 100719. DOI: https:\/\/doi.org\/10.1016\/j.polar.2021.100719<\/a><\/p>\n\n\n\n

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Oliveira Andrades\u2013Filho, C., de F\u00e1tima Rossetti, D., & Bezerra, F. H. R. (2021). The unsteady post-rift stage of the South American passive margin based on the tectono-sedimentary evolution of the onshore Para\u00edba Basin, NE Brazil. Quaternary International<\/em>, 580, 100-119. DOI: https:\/\/doi.org\/10.1016\/j.quaint.2020.10.051<\/a><\/p>\n\n\n\n

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Hofmann, G. S., Cardoso, M. F., Alves, R. J., Weber, E. J., Barbosa, A. A., de Toledo, P. M., \u2026 & de Oliveira, L. F. (2021). The Brazilian Cerrado is becoming hotter and drier. Global Change Biology<\/em>, 27(17), 4060-4073. DOI: https:\/\/doi.org\/10.1111\/gcb.15712<\/a><\/p>\n\n\n\n

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Souza, R., Pezzi, L., Swart, S., Oliveira, F., & Santini, M. (2021). Air-sea interactions over eddies in the brazil-malvinas confluence. Remote Sensing<\/em>, 13(7), 1335. DOI: https:\/\/doi.org\/10.3390\/rs13071335<\/a><\/p>\n\n\n\n

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Lucchese, L. V., de Oliveira, G. G., & Pedrollo, O. C. (2021). Investigation of the influence of nonoccurrence sampling on landslide susceptibility assessment using Artificial Neural Networks. Catena<\/em>, 198, 105067. DOI: https:\/\/doi.org\/10.1016\/j.catena.2020.105067<\/a><\/p>\n\n\n\n

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Lucchese, L. V., de Oliveira, G. G., & Pedrollo, O. C. (2021). Mamdani fuzzy inference systems and artificial neural networks for landslide susceptibility mapping. Natural Hazards<\/em>, 106(3), 2381-2405. DOI: https:\/\/doi.org\/10.1007\/s11069-021-04547-6<\/a><\/p>\n\n\n\n

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Gameiro, S., Riffel, E. S., de Oliveira, G. G., & Guasselli, L. A. (2021). Artificial neural networks applied to landslide susceptibility: The effect of sampling areas on model capacity for generalization and extrapolation. Applied Geography<\/em>, 137, 102598. DOI: https:\/\/doi.org\/10.1016\/j.apgeog.2021.102598<\/a><\/p>\n\n\n\n

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Pithan, P. A., Ducati, J. R., Garrido, L. R., Arruda, D. C., Thum, A. B., & Hoff, R. (2021). Spectral characterization of fungal diseases downy mildew, powdery mildew, black-foot and Petri disease on Vitis vinifera leaves. International Journal of Remote Sensing<\/em>, 42(15), 5680-5697. DOI: https:\/\/doi.org\/10.1080\/01431161.2021.1929542<\/a><\/p>\n\n\n\n

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Ruiz, L. F. C., Guasselli, L. A., Simioni, J. P. D., Belloli, T. F., & Fernandes, P. C. B. (2021). Object-based classification of vegetation species in a subtropical wetland using Sentinel-1 and Sentinel-2A images. Science of Remote Sensing<\/em>, 3, 100017. DOI: https:\/\/doi.org\/10.1016\/j.srs.2021.100017<\/a><\/p>\n\n\n\n

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Facco, D. S., Guasselli, L. A., Ruiz, L. F. C., Simioni, J. P. D., & Dick, D. G. (2021). Comparison of PBIA and GEOBIA classification methods in classifying turbidity in reservoirs. Geocarto International<\/em>, 1-22. DOI: https:\/\/doi.org\/10.1080\/10106049.2021.1899302<\/a><\/p>\n\n\n\n

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Fernandez Nascimento, V., Loureiro, A. I. S., Andrade, P. R., Guasselli, L. A., & Ometto, J. P. B. (2021). A worldwide meta-analysis review of restriction criteria for landfill siting using geographic information systems. Waste Management & Research<\/em>, 39(3), 409-426. DOI: https:\/\/doi.org\/10.1177\/0734242X20962834<\/a><\/p>\n\n\n\n

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Pezzi, L. P., de Souza, R. B., Santini, M. F., Miller, A. J., Carvalho, J. T., Parise, C. K., \u2026 & Rubert, J. (2021). Oceanic eddy-induced modifications to air\u2013sea heat and CO2 fluxes in the Brazil-Malvinas Confluence. Scientific Reports<\/em>, 11(1), 1-15. DOI: https:\/\/doi.org\/10.1038\/s41598-021-89985-9<\/a><\/p>\n\n\n\n

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da Rocha, N. S., Veettil, B. K., de Carvalho, C. M., K\u00e4fer, P. S., Diaz, L. R., Rolim, S. B. A., & Cruz, R. C. (2021). Potential impacts of air temperature rise in the hydric balance of Brazilian Pampa biome. Acta Geophysica<\/em>, 69(4), 1427-1445. DOI: https:\/\/doi.org\/10.1007\/s11600-021-00589-3<\/a><\/p>\n\n\n\n

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Sobrino, J. A., Souza da Rocha, N., Skokovi\u0107, D., Su\u00e9len K\u00e4fer, P., L\u00f3pez-Urrea, R., Jim\u00e9nez-Mu\u00f1oz, J. C., & Alves Rolim, S. B. (2021). Evapotranspiration Estimation with the S-SEBI Method from Landsat 8 Data against Lysimeter Measurements at the Barrax Site, Spain. Remote Sensing<\/em>, 13(18), 3686. DOI: https:\/\/doi.org\/10.3390\/rs13183686<\/a><\/p>\n\n\n\n

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Diaz, L. R., Santos, D. C., K\u00e4fer, P. S., Iglesias, M. L., da Rocha, N. S., da Costa, S. T. L., \u2026 & Rolim, S. B. A. (2021). Reanalysis profile downscaling with WRF model and sensitivity to PBL parameterization schemes over a subtropical station. Journal of Atmospheric and Solar-Terrestrial Physics<\/em>, 222, 105724. DOI: https:\/\/doi.org\/10.1016\/j.jastp.2021.105724<\/a><\/p>\n\n\n\n

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Diaz, L. R., Santos, D. C., K\u00e4fer, P. S., Rocha, N. S. D., Costa, S. T. L. D., Kaiser, E. A., & Rolim, S. B. A. (2021). Land surface temperature retrieval using high-resolution vertical profiles simulated by wrf model. Atmosphere<\/em>, 12(11), 1436. DOI: https:\/\/doi.org\/10.3390\/atmos12111436<\/a><\/p>\n\n\n\n

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Diaz, L. R., Santos, D. C., K\u00e4fer, P. S., Rocha, N. S. D., Costa, S. T. L. D., Kaiser, E. A., & Rolim, S. B. A. (2021). Atmospheric Correction of Thermal Infrared Landsat Images Using High-Resolution Vertical Profiles Simulated by WRF Model. Environmental Sciences Proceedings<\/em>, 8(1), 27. DOI: https:\/\/doi.org\/10.3390\/ecas2021-10351<\/a><\/p>\n\n\n\n

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de Jesus, J. B., Kuplich, T. M., de Carvalho Barreto, \u00cd. D., da Rosa, C. N., & Hillebrand, F. L. (2021). Temporal and phenological profiles of open and dense Caatinga using remote sensing: response to precipitation and its irregularities. Journal of Forestry Research<\/em>, 32(3), 1067-1076. DOI: https:\/\/doi.org\/10.1007\/s11676-020-01145-3<\/a><\/p>\n\n\n\n

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Da Rosa, C. N., Pereira Filho, W., Bremer, U. F., De Andrade, A. M., Kramer, G., Hillebrand, F. L., & De Jesus, J. B. (2021). The limnology and spectral behaviour of a freshwater lake at Harmony Point, Nelson Island, Antarctica. Antarctic Science<\/em>, 33(5), 479-492. DOI: https:\/\/doi.org\/10.1017\/S0954102021000304<\/a><\/p>\n\n\n\n

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Morais, L., Nascimento, V., Sim\u00f5es, S., & Ometto, J. (2021). Regional Distance Routes Estimation for Municipal Solid Waste Disposal, Case Study S\u00e3o Paulo State, Brazil. Energies<\/em>, 14(13), 3964. DOI: https:\/\/doi.org\/10.3390\/en14133964<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"

Articles published in international journals by faculty, students and recent graduates of PPGSR\/UFRGS: 2025 (under construction) VARNIER, MACLEIDI; WEBER, ELISEU JOS\u00c9. “Evaluating the Accuracy of Land-Use Change Models for Predicting […]<\/p>\n","protected":false},"author":13,"featured_media":0,"parent":2556,"menu_order":1,"comment_status":"closed","ping_status":"closed","template":"","meta":{"footnotes":""},"class_list":["post-2769","page","type-page","status-publish","hentry"],"_links":{"self":[{"href":"https:\/\/www.ufrgs.br\/ppgsr\/wp-json\/wp\/v2\/pages\/2769","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.ufrgs.br\/ppgsr\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/www.ufrgs.br\/ppgsr\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/www.ufrgs.br\/ppgsr\/wp-json\/wp\/v2\/users\/13"}],"replies":[{"embeddable":true,"href":"https:\/\/www.ufrgs.br\/ppgsr\/wp-json\/wp\/v2\/comments?post=2769"}],"version-history":[{"count":11,"href":"https:\/\/www.ufrgs.br\/ppgsr\/wp-json\/wp\/v2\/pages\/2769\/revisions"}],"predecessor-version":[{"id":3724,"href":"https:\/\/www.ufrgs.br\/ppgsr\/wp-json\/wp\/v2\/pages\/2769\/revisions\/3724"}],"up":[{"embeddable":true,"href":"https:\/\/www.ufrgs.br\/ppgsr\/wp-json\/wp\/v2\/pages\/2556"}],"wp:attachment":[{"href":"https:\/\/www.ufrgs.br\/ppgsr\/wp-json\/wp\/v2\/media?parent=2769"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}