Filtros : "IEE" "Dias, Helen Cristina" Limpar

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  • Source: Journal of South American Earth Sciences. Unidade: IEE

    Assunto: DESLIZAMENTO DE TERRA

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    • ABNT

      DIAS, Helen Cristina e GROHMANN, Carlos Henrique. Standards for shallow landslide identification in Brazil: Spatial trends and inventory mapping. Journal of South American Earth Sciences, v. 135, p. art.104805/1-10, 2024Tradução . . Acesso em: 21 jul. 2024.
    • APA

      Dias, H. C., & Grohmann, C. H. (2024). Standards for shallow landslide identification in Brazil: Spatial trends and inventory mapping. Journal of South American Earth Sciences, 135, art.104805/1-10.
    • NLM

      Dias HC, Grohmann CH. Standards for shallow landslide identification in Brazil: Spatial trends and inventory mapping. Journal of South American Earth Sciences. 2024 ;135 art.104805/1-10.[citado 2024 jul. 21 ]
    • Vancouver

      Dias HC, Grohmann CH. Standards for shallow landslide identification in Brazil: Spatial trends and inventory mapping. Journal of South American Earth Sciences. 2024 ;135 art.104805/1-10.[citado 2024 jul. 21 ]
  • Source: Proceedings. Geomorphometry 2023. Conference titles: International Conference on Geomorphometry. Unidade: IEE

    Assunto: GEOMORFOMETRIA

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      GROHMANN, Carlos Henrique et al. RPA flight pattern and GCP influence on SfMMVS modeling of a stable landslide in SE Brazil. 2023, Anais.. [S.l.]: International Society for Geomorphometry, 2023. Disponível em: https://doi.org/10.5281/zenodo.7779223. Acesso em: 21 jul. 2024.
    • APA

      Grohmann, C. H., Garcia, G. P. B., Viana, C. D., Dias, H. C., & Coelho, R. D. (2023). RPA flight pattern and GCP influence on SfMMVS modeling of a stable landslide in SE Brazil. In Proceedings. Geomorphometry 2023. International Society for Geomorphometry. doi:10.5281/zenodo.7779223
    • NLM

      Grohmann CH, Garcia GPB, Viana CD, Dias HC, Coelho RD. RPA flight pattern and GCP influence on SfMMVS modeling of a stable landslide in SE Brazil [Internet]. Proceedings. Geomorphometry 2023. 2023 ;[citado 2024 jul. 21 ] Available from: https://doi.org/10.5281/zenodo.7779223
    • Vancouver

      Grohmann CH, Garcia GPB, Viana CD, Dias HC, Coelho RD. RPA flight pattern and GCP influence on SfMMVS modeling of a stable landslide in SE Brazil [Internet]. Proceedings. Geomorphometry 2023. 2023 ;[citado 2024 jul. 21 ] Available from: https://doi.org/10.5281/zenodo.7779223
  • Source: GI_Forum. Unidade: IEE

    Assunto: DESLIZAMENTO DE TERRA

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      DIAS, Helen Cristina et al. Application of Object-Based Image Analysis for Detecting and Differentiating between Shallow Landslides and Debris Flows. GI_Forum, v. 11, n. 1, p. 34-44, 2023Tradução . . Disponível em: https://austriaca.at/0xc1aa5576_0x003e555a.pdf. Acesso em: 21 jul. 2024.
    • APA

      Dias, H. C., Holbling, D., Dias, V. C., & Grohmann, C. H. (2023). Application of Object-Based Image Analysis for Detecting and Differentiating between Shallow Landslides and Debris Flows. GI_Forum, 11( 1), 34-44. Recuperado de https://austriaca.at/0xc1aa5576_0x003e555a.pdf
    • NLM

      Dias HC, Holbling D, Dias VC, Grohmann CH. Application of Object-Based Image Analysis for Detecting and Differentiating between Shallow Landslides and Debris Flows [Internet]. GI_Forum. 2023 ;11( 1): 34-44.[citado 2024 jul. 21 ] Available from: https://austriaca.at/0xc1aa5576_0x003e555a.pdf
    • Vancouver

      Dias HC, Holbling D, Dias VC, Grohmann CH. Application of Object-Based Image Analysis for Detecting and Differentiating between Shallow Landslides and Debris Flows [Internet]. GI_Forum. 2023 ;11( 1): 34-44.[citado 2024 jul. 21 ] Available from: https://austriaca.at/0xc1aa5576_0x003e555a.pdf
  • Source: Abstract EGU23. Conference titles: EGU General Assembly 2023. Unidade: IEE

    Assunto: GEOMORFOMETRIA

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      DIAS, Helen Cristina e HOLBLING, Daniel e GROHMANN, Carlos Henrique. An object-based approach for semi-automated shallow landslide mapping: suitability and comparison in Itaóca (SP) and Nova Friburgo (RJ), southeastern Brazil. 2023, Anais.. Viena: Instituto de Energia e Ambiente, Universidade de São Paulo, 2023. Disponível em: https://doi.org/10.5194/egusphere-egu23-158. Acesso em: 21 jul. 2024.
    • APA

      Dias, H. C., Holbling, D., & Grohmann, C. H. (2023). An object-based approach for semi-automated shallow landslide mapping: suitability and comparison in Itaóca (SP) and Nova Friburgo (RJ), southeastern Brazil. In Abstract EGU23. Viena: Instituto de Energia e Ambiente, Universidade de São Paulo. doi:10.5194/egusphere-egu23-158
    • NLM

      Dias HC, Holbling D, Grohmann CH. An object-based approach for semi-automated shallow landslide mapping: suitability and comparison in Itaóca (SP) and Nova Friburgo (RJ), southeastern Brazil [Internet]. Abstract EGU23. 2023 ;[citado 2024 jul. 21 ] Available from: https://doi.org/10.5194/egusphere-egu23-158
    • Vancouver

      Dias HC, Holbling D, Grohmann CH. An object-based approach for semi-automated shallow landslide mapping: suitability and comparison in Itaóca (SP) and Nova Friburgo (RJ), southeastern Brazil [Internet]. Abstract EGU23. 2023 ;[citado 2024 jul. 21 ] Available from: https://doi.org/10.5194/egusphere-egu23-158
  • Source: Abstract EGU23. Conference titles: EGU General Assembly 2023. Unidade: IEE

    Assunto: GEOMORFOMETRIA

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      DIAS, Vivian Cristina e DIAS, Helen Cristina e GROHMANN, Carlos Henrique. Distinction between watersheds prone to debris flow, debris flood, and flood using morphometry in Serra do Mar, Brazil (São Paulo State North shore). 2023, Anais.. Viena: Instituto de Energia e Ambiente, Universidade de São Paulo, 2023. Disponível em: https://doi.org/10.5194/egusphere-egu23-1052. Acesso em: 21 jul. 2024.
    • APA

      Dias, V. C., Dias, H. C., & Grohmann, C. H. (2023). Distinction between watersheds prone to debris flow, debris flood, and flood using morphometry in Serra do Mar, Brazil (São Paulo State North shore). In Abstract EGU23. Viena: Instituto de Energia e Ambiente, Universidade de São Paulo. doi:10.5194/egusphere-egu23-1052
    • NLM

      Dias VC, Dias HC, Grohmann CH. Distinction between watersheds prone to debris flow, debris flood, and flood using morphometry in Serra do Mar, Brazil (São Paulo State North shore) [Internet]. Abstract EGU23. 2023 ;[citado 2024 jul. 21 ] Available from: https://doi.org/10.5194/egusphere-egu23-1052
    • Vancouver

      Dias VC, Dias HC, Grohmann CH. Distinction between watersheds prone to debris flow, debris flood, and flood using morphometry in Serra do Mar, Brazil (São Paulo State North shore) [Internet]. Abstract EGU23. 2023 ;[citado 2024 jul. 21 ] Available from: https://doi.org/10.5194/egusphere-egu23-1052
  • Source: Remote Sensing. Unidade: IEE

    Assunto: SENSORIAMENTO REMOTO

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    • ABNT

      DIAS, Helen Cristina e HOLBLING, Daniel e GROHMANN, Carlos Henrique. Rainfall-Induced Shallow Landslide Recognition and Transferability Using Object-Based Image Analysis in Brazil. Remote Sensing, v. 15, n. 21, p. art.5137/1-16, 2023Tradução . . Disponível em: https://doi.org/10.3390/rs15215137. Acesso em: 21 jul. 2024.
    • APA

      Dias, H. C., Holbling, D., & Grohmann, C. H. (2023). Rainfall-Induced Shallow Landslide Recognition and Transferability Using Object-Based Image Analysis in Brazil. Remote Sensing, 15(21), art.5137/1-16. Recuperado de https://doi.org/10.3390/rs15215137
    • NLM

      Dias HC, Holbling D, Grohmann CH. Rainfall-Induced Shallow Landslide Recognition and Transferability Using Object-Based Image Analysis in Brazil [Internet]. Remote Sensing. 2023 ; 15(21):art.5137/1-16.[citado 2024 jul. 21 ] Available from: https://doi.org/10.3390/rs15215137
    • Vancouver

      Dias HC, Holbling D, Grohmann CH. Rainfall-Induced Shallow Landslide Recognition and Transferability Using Object-Based Image Analysis in Brazil [Internet]. Remote Sensing. 2023 ; 15(21):art.5137/1-16.[citado 2024 jul. 21 ] Available from: https://doi.org/10.3390/rs15215137
  • Source: E3S Web of Conferences. Conference titles: International Conference on Debris Flow Hazard Mitigation (DFHM8). Unidade: IEE

    Assunto: DESLIZAMENTO DE TERRA

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      DIAS, Vivian Cristina e DIAS, Helen Cristina e GROHMANN, Carlos Henrique. Rainfall-induced debris flows and shallow landslides in Ribeira Valley, Brazil: main characteristics and inventory mapping. E3S Web of Conferences. Les Ulis: Instituto de Energia e Ambiente, Universidade de São Paulo. Disponível em: https://doi.org/10.1051/e3sconf/202341505003. Acesso em: 21 jul. 2024. , 2023
    • APA

      Dias, V. C., Dias, H. C., & Grohmann, C. H. (2023). Rainfall-induced debris flows and shallow landslides in Ribeira Valley, Brazil: main characteristics and inventory mapping. E3S Web of Conferences. Les Ulis: Instituto de Energia e Ambiente, Universidade de São Paulo. doi:doi.org/10.1051/e3sconf/202341505003
    • NLM

      Dias VC, Dias HC, Grohmann CH. Rainfall-induced debris flows and shallow landslides in Ribeira Valley, Brazil: main characteristics and inventory mapping [Internet]. E3S Web of Conferences. 2023 ; 415. p. art.5003/1-4[citado 2024 jul. 21 ] Available from: https://doi.org/10.1051/e3sconf/202341505003
    • Vancouver

      Dias VC, Dias HC, Grohmann CH. Rainfall-induced debris flows and shallow landslides in Ribeira Valley, Brazil: main characteristics and inventory mapping [Internet]. E3S Web of Conferences. 2023 ; 415. p. art.5003/1-4[citado 2024 jul. 21 ] Available from: https://doi.org/10.1051/e3sconf/202341505003
  • Source: Remote Sensing. Unidades: IEE, IGC

    Assunto: DESLIZAMENTO DE TERRA

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      SOARES, Lucas Pedrosa et al. Landslide Segmentation with Deep Learning: evaluating model generalization in rainfall-induced landslides in Brazil. Remote Sensing, v. 14, n. 9, p. e2237/1-17, 2022Tradução . . Disponível em: https://doi.org/10.3390/rs14092237. Acesso em: 21 jul. 2024.
    • APA

      Soares, L. P., Dias, H. C., Garcia, G. P. B., & Grohmann, C. H. (2022). Landslide Segmentation with Deep Learning: evaluating model generalization in rainfall-induced landslides in Brazil. Remote Sensing, 14( 9), e2237/1-17. doi:10.3390/rs14092237
    • NLM

      Soares LP, Dias HC, Garcia GPB, Grohmann CH. Landslide Segmentation with Deep Learning: evaluating model generalization in rainfall-induced landslides in Brazil [Internet]. Remote Sensing. 2022 ; 14( 9):e2237/1-17.[citado 2024 jul. 21 ] Available from: https://doi.org/10.3390/rs14092237
    • Vancouver

      Soares LP, Dias HC, Garcia GPB, Grohmann CH. Landslide Segmentation with Deep Learning: evaluating model generalization in rainfall-induced landslides in Brazil [Internet]. Remote Sensing. 2022 ; 14( 9):e2237/1-17.[citado 2024 jul. 21 ] Available from: https://doi.org/10.3390/rs14092237
  • Source: Brazilian Journal of Geology. Unidades: IEE, IGC

    Assunto: MUDANÇA CLIMÁTICA

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      DIAS, Helen Cristina et al. Landslide recognition using SVM, Random Forest, and Maximum Likelihood classifiers on high-resolution satellite images: A case study of Itaóca, southeastern Brazil. Brazilian Journal of Geology, v. 51, n. 4. p. e20200105/1-10, 2021Tradução . . Disponível em: https://www.scielo.br/j/bjgeo/a/Y6s5whm57BV9cgrMDWcJvgp/?format=pdf&lang=en. Acesso em: 21 jul. 2024.
    • APA

      Dias, H. C., Sandre, L. H., Satizábal Alarcón, D. A., Grohmann, C. H., & Quintanilha, J. A. (2021). Landslide recognition using SVM, Random Forest, and Maximum Likelihood classifiers on high-resolution satellite images: A case study of Itaóca, southeastern Brazil. Brazilian Journal of Geology, 51( 4. p. e20200105/1-10). Recuperado de https://www.scielo.br/j/bjgeo/a/Y6s5whm57BV9cgrMDWcJvgp/?format=pdf&lang=en
    • NLM

      Dias HC, Sandre LH, Satizábal Alarcón DA, Grohmann CH, Quintanilha JA. Landslide recognition using SVM, Random Forest, and Maximum Likelihood classifiers on high-resolution satellite images: A case study of Itaóca, southeastern Brazil [Internet]. Brazilian Journal of Geology. 2021 ; 51( 4. p. e20200105/1-10):[citado 2024 jul. 21 ] Available from: https://www.scielo.br/j/bjgeo/a/Y6s5whm57BV9cgrMDWcJvgp/?format=pdf&lang=en
    • Vancouver

      Dias HC, Sandre LH, Satizábal Alarcón DA, Grohmann CH, Quintanilha JA. Landslide recognition using SVM, Random Forest, and Maximum Likelihood classifiers on high-resolution satellite images: A case study of Itaóca, southeastern Brazil [Internet]. Brazilian Journal of Geology. 2021 ; 51( 4. p. e20200105/1-10):[citado 2024 jul. 21 ] Available from: https://www.scielo.br/j/bjgeo/a/Y6s5whm57BV9cgrMDWcJvgp/?format=pdf&lang=en
  • Source: Natural Hazards. Unidade: IEE

    Assunto: DESLIZAMENTO DE TERRA

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      DIAS, Helen Cristina et al. Statistical-based shallow landslide susceptibility assessment for a tropical environment: a case study in the southeastern Brazilian coast. Natural Hazards, v. 108, n. 1, p. 205-223, 2021Tradução . . Acesso em: 21 jul. 2024.
    • APA

      Dias, H. C., Gramani, M. F., Grohmann, C. H., Bateira, C., & Vieira, B. C. (2021). Statistical-based shallow landslide susceptibility assessment for a tropical environment: a case study in the southeastern Brazilian coast. Natural Hazards, 108( 1), 205-223.
    • NLM

      Dias HC, Gramani MF, Grohmann CH, Bateira C, Vieira BC. Statistical-based shallow landslide susceptibility assessment for a tropical environment: a case study in the southeastern Brazilian coast. Natural Hazards. 2021 ;108( 1): 205-223.[citado 2024 jul. 21 ]
    • Vancouver

      Dias HC, Gramani MF, Grohmann CH, Bateira C, Vieira BC. Statistical-based shallow landslide susceptibility assessment for a tropical environment: a case study in the southeastern Brazilian coast. Natural Hazards. 2021 ;108( 1): 205-223.[citado 2024 jul. 21 ]
  • Source: Geosciences. Unidade: IEE

    Assunto: DESLIZAMENTO DE TERRA

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      DIAS, Helen Cristina e HOLBLING, Daniel e GROHMANN, Carlos Henrique. Landslide Susceptibility Mapping in Brazil: a review. Geosciences, v. 11, n. 10, p. art.425/1-15, 2021Tradução . . Disponível em: https://doi.org/10.3390/geosciences11100425. Acesso em: 21 jul. 2024.
    • APA

      Dias, H. C., Holbling, D., & Grohmann, C. H. (2021). Landslide Susceptibility Mapping in Brazil: a review. Geosciences, 11( 10), art.425/1-15. doi:10.3390/geosciences11100425
    • NLM

      Dias HC, Holbling D, Grohmann CH. Landslide Susceptibility Mapping in Brazil: a review [Internet]. Geosciences. 2021 ; 11( 10): art.425/1-15.[citado 2024 jul. 21 ] Available from: https://doi.org/10.3390/geosciences11100425
    • Vancouver

      Dias HC, Holbling D, Grohmann CH. Landslide Susceptibility Mapping in Brazil: a review [Internet]. Geosciences. 2021 ; 11( 10): art.425/1-15.[citado 2024 jul. 21 ] Available from: https://doi.org/10.3390/geosciences11100425

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