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Dr. Alby Duarte Rocha

Dr. Alby Duarte Rocha
Dr. Alby Duarte Rocha
Lupe

Research Assistant

Phone: +49 (0)30 / 314 – 24 95 3

Email: a.duarterocha(at)tu-berlin.de

Room: EB 203b

Personal Data
Date and place of birth:
1976 (São Paulo, São Paulo, Brazil)
Employment and academic vita
Since 2020
Post-doctoral Research Assistant
Technische Universität Berlin
Institute of Landscape Architecture and Environmental Planning, Department of Geoinformation Processing for Landscape and Environmental Planning
2014-2019
PhD - Remote Sensing University of Twente, Netherlands International Institute for Geo-Information Science and Earth Observation (ITC). Department of Natural Resources
2005-2019
Project Manager Observatory of Indicators of Sustainability (ORBIS) Curitiba | Paraná | Brazil
2005-2007
Master in Geodesy - Remote Sensing Federal University of Paraná (UFPR) Department of Geodesy | Brazil
2003-2005
Lecturer Federal University of Paraná - UFPR Department of Statistics | Curitiba | Brazil
2000-2003
Consultant
Werkema Associate Consultants
Belo Horizonte | Brazil
1996-2000
Statistician Curitiba Research and Urban Planning Institute (IPPUC) Curitiba | Brazil
1994-1998
Bachelor in Statistics Federal University of Paraná (UFPR) Department of Statistics | Brazil
Degrees
1998
Bachelor, Federal University of Paraná (UFPR), Brazil
2007
Master, Federal University of Paraná (UFPR), Brazil
2019
Doctorate, University of Twente, The Netherlands

 

 

Research Topics

  • Biophysical and biochemical plant trait predictive models using hyperspectral data.
  • Assessment of Spatiotemporal Models, Machine Learning Algorithms and Radiative Transfer Models to predict/retrieval (quantitative) vegetation parameters with Remote Sensing.
  • Modelling Evapotranspiration in urban landscapes with the support of remote sensing.

 

Articles

2019
Rocha, A.D.; Groen, T.A.; Skidmore, A.K., 2019. Spatially-explicit modelling with support of hyperspectral data can improve prediction of plant traits. Remote Sensing of Environment, Doi: 10.1016/j.rse.2019.05.019, (111200).

2018
Rocha, A., Groen, T., Skidmore, A., Darvishzadeh, R. and Willemen, L., 2018. Machine Learning Using Hyperspectral Data Inaccurately Predicts Plant Traits Under Spatial Dependency. Remote sensing, 10(8), p.1263. Doi:10.1016/j.isprsjprs.2017.09.012

2017
Rocha, A.D., Groen, T.A., Skidmore, A.K., Darvishzadeh, R. and Willemen, L., 2017. The Naïve Overfitting Index Selection (NOIS): A new method to optimize model complexity for hyperspectral data. ISPRS Journal of Photogrammetry and Remote Sensing, 133, pp.61-74. Doi:10.3390/rs10081263

2012
AFB Antunes, A Duarte, 2012. Characterization of the growth of urban areas by means of QUICKBIRD images through object-oriented segmentation. Proceedings of the 4th GEOBIA, Rio de Janeiro, Brazil, 191.

2011
Rocha, A.D. and Antunes, A.F.F.B., 2011. O desafio de caracterizar objetos relevantes ao planejamento urbano a partir de imagens de satélite de alta resolução. Revista Brasileira de Cartografia, (64 ESP. 1).

2008
Rocha, Alby Duarte, and Alzir Felippe Buffara Antunes, 2008. Caracterização de áreas de expansão urbana como subsídio ao planejamento urbano por meio de técnicas de segmentação orientada a objetos de imagens Quickbird. Boletim de Ciências Geodésicas 14.3.

2000
Rocha, A. D., Okabe, I., Martins, M. E. A., Machado, P. H. B., & Mello, T. C. D. (2000). Qualidade de vida, ponto de partida ou resultado final?. Ciência & saúde coletiva, 5, 63-81.

Other Publications

2019
Duarte Rocha, A., 2019. Tuning a statistical trade-off between spectral and spatial domains to predict plant traits with hyperspectral remote sensing. University of Twente, Faculty of Geo-Information Science and Earth Observation (ITC). Enschede, The Netherlands, Doi:10.3990/1.9789036548625.

2007
Duarte Rocha, A., 2007. Caracterização de áreas de expansão urbana como subsídio ao planejamento urbano por meio de técnicas de segmentação orientada a objetos de imagens Quickbird. Universidade Federal do Paraná, Setor de Ciencias da Terra, Programa de Pós-Graduação em Ciencias Geodésicas. Curitiba.

 

 

 

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