2024

• Ferreira, M. P., dos Santos, D. R., Ferrari, F., Coelho Filho, L. C. T., Martins, G. B., & Feitosa, R. Q. (2024). Improving urban tree species classification by deep-learning based fusion of digital aerial images and LiDAR. Urban Forestry & Urban Greening, 128240. 

• Ferreira, M. P., Martins, G. B., de Almeida, T. M. H., da Silva Ribeiro, R., da Veiga Júnior, V. F., Paz, I. D. S. R., ... & Kurtz, B. C. (2024). Estimating aboveground biomass of tropical urban forests with UAV-borne hyperspectral and LiDAR data.  Urban Forestry & Urban Greening, 128240. 

 2023

• Haneda, L.E., Brancalion, P.H., Molin, P.G., Ferreira, M.P., Silva, C.A., de Almeida, C.T., Resende, A.F., Santoro, G.B., Rosa, M., Guillemot, J. and Le Maire, G., 2023. Forest landscape restoration: Spectral behavior and diversity of tropical tree cover classes. Remote Sensing Applications: Society and Environment, 29, p.100882. 

• Lassalle, G., Ferreira, M.P., La Rosa, L.E.C., Scafutto, R.D.P.M. and de Souza Filho, C.R., 2023. Advances in multi-and hyperspectral remote sensing of mangrove species: A synthesis and study case on airborne and multisource spaceborne imagery. ISPRS Journal of Photogrammetry and Remote Sensing, 195, pp.298-312. 

• Ferrari, F., Ferreira, M.P., Almeida, C.A. and Feitosa, R.Q., 2023. Fusing Sentinel-1 and Sentinel-2 Images for Deforestation Detection in the Brazilian Amazon Under Diverse Cloud Conditions. IEEE Geoscience and Remote Sensing Letters, 20, pp.1-5. 

• Klauberg, C., Vogel, J., Dalagnol, R., Ferreira, M.P., Hamamura, C., Broadbent, E. and Silva, C.A., 2023. Post-Hurricane Damage Severity Classification at the Individual Tree Level Using Terrestrial Laser Scanning and Deep Learning. Remote Sensing, 15(4), p.1165. 

• de Paulo, M.C.M., Marques, H.A., Feitosa, R.Q. and Ferreira, M.P., 2023. New encoder–decoder convolutional LSTM neural network architectures for next-day global ionosphere maps forecast. GPS Solutions, 27(2), p.95. 

 2022

• Veras, H.F.P., Ferreira, M.P., da Cunha Neto, E.M., Figueiredo, E.O., Dalla Corte, A.P. and Sanquetta, C.R., 2022. Fusing multi-season UAS images with convolutional neural networks to map tree species in Amazonian forests. Ecological Informatics, p.101815. 

• Lassalle, G., Ferreira, M.P., La Rosa, L.E.C. and de Souza Filho, C.R., 2022. Deep learning-based individual tree crown delineation in mangrove forests using very-high-resolution satellite imagery. ISPRS Journal of Photogrammetry and Remote Sensing, 189, pp.220-235. 

• Leite, R.V., Silva, C.A., Broadbent, E.N., Do Amaral, C.H., Liesenberg, V., De Almeida, D.R.A., Mohan, M., Godinho, S., Cardil, A., Hamamura, C. and De Faria, B.L., ..., Ferreira, M.P., ..., Klauberg, C. 2022. Large scale multi-layer fuel load characterization in tropical savanna using GEDI spaceborne lidar data. Remote Sensing of Environment, 268, p.112764. 

 2021

• De Almeida, D.R.A., Broadbent, E.N., Ferreira, M.P., Meli, P., Zambrano, A.M.A., Gorgens, E.B., Resende, A.F., de Almeida, C.T., Do Amaral, C.H., Dalla Corte, A.P. and Silva, C.A., 2021. Monitoring restored tropical forest diversity and structure through UAV-borne hyperspectral and lidar fusion. Remote Sensing of Environment, 264, p.112582. 

• Ferreira, M.P., Lotte, R.G., D'Elia, F.V., Stamatopoulos, C., Kim, D.H. and Benjamin, A.R., 2021. Accurate mapping of Brazil nut trees (Bertholletia excelsa) in Amazonian forests using WorldView-3 satellite images and convolutional neural networks. Ecological Informatics, 63, p.101302.  

• Martins, G.B., La Rosa, L.E.C., Happ, P.N., Coelho Filho, L.C.T., Santos, C.J.F., Feitosa, R.Q. and Ferreira, M.P., 2021. Deep learning-based tree species mapping in a highly diverse tropical urban setting. Urban Forestry & Urban Greening, 64, p.127241. 

• Weihermann, J.D., Ferreira, M.P., de Castro, L.G., Ferreira, F.J.F. and Silva, A.M., 2021. Retrieving geological units with unsupervised clustering of gamma-ray spectrometry data. Journal of Applied Geophysics, 184, p.104225. 

 2020

• Ferreira, M.P., de Almeida, D.R.A., de Almeida Papa, D., Minervino, J.B.S., Veras, H.F.P., Formighieri, A., Santos, C.A.N., Ferreira, M.A.D., Figueiredo, E.O. and Ferreira, E.J.L., 2020. Individual tree detection and species classification of Amazonian palms using UAV images and deep learning. Forest Ecology and Management, 475, p.118397. 

• G. Braga, J.R., Peripato, V., Dalagnol, R., Ferreira, M.P., Tarabalka, Y., OC Aragão, L.E., F. de Campos Velho, H., Shiguemori, E.H. and Wagner, F.H., 2020. Tree crown delineation algorithm based on a convolutional neural network. Remote Sensing 12(8), p.1288. 

• de Almeida, D.R., Stark, S.C., Valbuena, R., Broadbent, E.N., Silva, T.S., de Resende, A.F., Ferreira, M.P., Cardil, A., Silva, C.A., Amazonas, N. and Zambrano, A.M., 2020. A new era in forest restoration monitoring. Restoration Ecology, 28(1), pp.8-11. 

 2019

• Ferreira, M.P., Wagner, F.H., Aragão, L.E., Shimabukuro, Y.E. and de Souza Filho, C.R., 2019. Tree species classification in tropical forests using visible to shortwave infrared WorldView-3 images and texture analysis. ISPRS journal of photogrammetry and remote sensing, 149, pp.119-131. 

• Wagner, F.H., Sanchez, A., Tarabalka, Y., Lotte, R.G., Ferreira, M.P., Aidar, M.P., Gloor, E., Phillips, O.L. and Aragao, L.E., 2019. Using the U‐net convolutional network to map forest types and disturbance in the Atlantic rainforest with very high resolution images. Remote Sensing in Ecology and Conservation, 5(4), pp.360-375. 

 2018

• Wagner, F.H., Ferreira, M.P., Sanchez, A., Hirye, M.C., Zortea, M., Gloor, E., Phillips, O.L., de Souza Filho, C.R., Shimabukuro, Y.E. and Aragão, L.E., 2018. Individual tree crown delineation in a highly diverse tropical forest using very high resolution satellite images. ISPRS journal of photogrammetry and remote sensing, 145, pp.362-377. 

• Zanotta, D.C., Zortea, M. and Ferreira, M.P., 2018. A supervised approach for simultaneous segmentation and classification of remote sensing images. ISPRS journal of photogrammetry and remote sensing, 142, pp.162-173. 

• Ferreira, M.P., Féret, J.B., Grau, E., Gastellu-Etchegorry, J.P., Do Amaral, C.H., Shimabukuro, Y.E. and de Souza Filho, C.R., 2018. Retrieving structural and chemical properties of individual tree crowns in a highly diverse tropical forest with 3D radiative transfer modeling and imaging spectroscopy. Remote Sensing of Environment, 211, pp.276-291. 

• Lacerda Silva, A., Salas Alves, D. and Ferreira, M.P. 2018. Landsat-Based land use change assessment in the Brazilian Atlantic forest: Forest transition and sugarcane expansion. Remote Sensing, 10(7), p.996. 

 2013-2016

• Ferreira, M.P., Zortea, M., Zanotta, D.C., Shimabukuro, Y.E. and de Souza Filho, C.R., 2016. Mapping tree species in tropical seasonal semi-deciduous forests with hyperspectral and multispectral data. Remote Sensing of Environment, 179, pp.66-78. 

• Ferreira, M.P., Alves, D.S. and Shimabukuro, Y.E., 2015. Forest dynamics and land-use transitions in the Brazilian Atlantic Forest: the case of sugarcane expansion. Regional Environmental Change, 15(2), pp.365-377. 

• Ferreira, M.P., Grondona, A.E., Rolim, S.B.A. and Shimabukuro, Y.E., 2013. Analyzing the spectral variability of tropical tree species using hyperspectral feature selection and leaf optical modeling. Journal of Applied Remote Sensing, 7(1), p.073502.