Dr. Sousa obtained his BSc. degree in Forest Engineering in 2011. During his undergraduate studies, he worked as an analyst on a governmental project for mapping the native flora and reforested areas of Minas Gerais state in Brazil. This experience was the stepping stone to his MSc. in Forest Engineering and Management with emphasis in Remote Sensing of Forest Resources, obtained in 2013. During his MSc, he joined Dr. Olaf Niemann's research group at University of Victoria (UVic), British Columbia in 2012/2013 as a visiting researcher. In 2013, Dr. Sousa was admitted into the Forest Ecosystems & Society doctoral program at Oregon State University. During his Ph.D, he worked with stress related changes in the light use efficiency of the Amazonian rainforests using space-borne multi-angle remote sensing data.
Dr. Celio Sousa' research focus on using cloud-computing and multi-temporal/ multi-sensor data for characterizing and quantifying land cover extent and change in tropical regions and its biophysical and socioeconomic impacts.
In partnership with Conservation International, Dr. Sousa is providing decision support tools for African countries who have committed themselves to incorporating ecosystem service accounting into national decision making through the Gaborone Declaration for Sustainability in Africa. Along with Conservation International, Dr. Sousa's goal is to developed repeatable methodologies to map ecosystem extent, meet international standards for ecosystem accounting, and satisfy the requirements of a broad range of nation specific decision support needs.
Dr. Sousa is currently supported through the NASA Earth Science Division’s Partnerships Program which seeks to build commercial and NGO relationships that amplify our understanding of the Earth as an integrated system and enable societal benefits.
Thesis: Analise do Comportamento Espectral de Areas em Regeneracao Natural no Bioma Cerrado [Analysis of the Spectral Behavior of Areas under Natural Regeneration in the Cerrado Biome, Brazil]
Thesis: Evaluating Segmentation and Classification Approaches using RapidEye Data for Vegetation Mapping in Minas Gerais, Brazil
Dissertation: Remote Sensing of Photosynthetic Light-Use Efficiency of Amazonian Rainforests
FINESST Earth Science Carbon Cycle and Ecosystem (CC&E) Panel Review May 2-3, 2019.
Campbell, A. D., T. Fatoyinbo, S. P. Charles, et al. L. L. Bourgeau-Chavez, J. Goes, H. Gomes, M. Halabisky, J. Holmquist, S. Lohrenz, C. Mitchell, L. M. Moskal, B. Poulter, H. Qiu, C. H. Resende De Sousa, M. Sayers, M. Simard, A. J. Stewart, D. Singh, C. Trettin, J. Wu, X. Zhang, and D. Lagomasino. 2022. "A review of carbon monitoring in wet carbon systems using remote sensing." Environmental Research Letters, 17 (2): 025009 [10.1088/1748-9326/ac4d4d]
de Sousa, C., L. Fatoyinbo, C. Neigh, et al. F. Boucka, V. Angoue, and T. Larsen. 2020. "Cloud-computing and machine learning in support of country-level land cover and ecosystem extent mapping in Liberia and Gabon." PLOS ONE, 15 (1): e0227438 [10.1371/journal.pone.0227438]
Dr. Sousa obtained his BSc. degree in Forest Engineering in 2011. During his undergraduate studies, he worked as an analyst on a governmental project for mapping the native flora and reforested areas of Minas Gerais state in Brazil. This experience was the stepping stone to his MSc. in Forest Engineering and Management with emphasis in Remote Sensing of Forest Resources, obtained in 2013. During his MSc, he joined Dr. Olaf Niemann's research group at University of Victoria (UVic), British Columbia in 2012/2013 as a visiting researcher. In 2013, Dr. Sousa was admitted into the Forest Ecosystems & Society doctoral program at Oregon State University. During his Ph.D, he worked with stress related changes in the light use efficiency of the Amazonian rainforests using space-borne multi-angle remote sensing data.
Campbell, A. D., T. Fatoyinbo, S. P. Charles, et al. L. L. Bourgeau-Chavez, J. Goes, H. Gomes, M. Halabisky, J. Holmquist, S. Lohrenz, C. Mitchell, L. M. Moskal, B. Poulter, H. Qiu, C. H. Resende De Sousa, M. Sayers, M. Simard, A. J. Stewart, D. Singh, C. Trettin, J. Wu, X. Zhang, and D. Lagomasino. 2022. "A review of carbon monitoring in wet carbon systems using remote sensing." Environmental Research Letters 17 (2): 025009 [10.1088/1748-9326/ac4d4d]
de Sousa, C., L. Fatoyinbo, C. Neigh, et al. F. Boucka, V. Angoue, and T. Larsen. 2020. "Cloud-computing and machine learning in support of country-level land cover and ecosystem extent mapping in Liberia and Gabon." PLOS ONE 15 (1): e0227438 [10.1371/journal.pone.0227438]