Forest cover change analysis based on temporal gradients of the vertical structure and density

Autor: Adilson Berveglieri, Nilton N. Imai, Antonio M.G. Tommaselli, Rorai P. Martins-Neto, Gabriela Takahashi Miyoshi, Eija Honkavaara

Publikováno v: Ecological Indicators, Vol 126, Iss , Pp 107597- (2021)

Canopy height is an important attribute that allows characterizing the forest vertical structure and analyze changes in vegetation cover over time. The objective of this study is to develop an approach for a spatio-temporal analysis of the tropical f

Externí odkaz: https://doaj.org/article/f14e5eab73fb4d78856780efe424a111

A Novel Deep Learning Method to Identify Single Tree Species in UAV-Based Hyperspectral Images

Autor: Gabriela Takahashi Miyoshi, Mauro dos Santos Arruda, Lucas Prado Osco, José Marcato Junior, Diogo Nunes Gonçalves, Nilton Nobuhiro Imai, Antonio Maria Garcia Tommaselli, Eija Honkavaara, Wesley Nunes Gonçalves

Publikováno v: Remote Sensing, Vol 12, Iss 8, p 1294 (2020)

Deep neural networks are currently the focus of many remote sensing approaches related to forest management. Although they return satisfactory results in most tasks, some challenges related to hyperspectral data remain, like the curse of data dimensi

Externí odkaz: https://doaj.org/article/6706a4f68521453b853cc4666d6aecc0

Tree Species Classification in a Highly Diverse Subtropical Forest Integrating UAV-Based Photogrammetric Point Cloud and Hyperspectral Data

Autor: Camile Sothe, Michele Dalponte, Cláudia Maria de Almeida, Marcos Benedito Schimalski, Carla Luciane Lima, Veraldo Liesenberg, Gabriela Takahashi Miyoshi, Antonio Maria Garcia Tommaselli

Publikováno v: Remote Sensing, Vol 11, Iss 11, p 1338 (2019)

The use of remote sensing data for tree species classification in tropical forests is still a challenging task, due to their high floristic and spectral diversity. In this sense, novel sensors on board of unmanned aerial vehicle (UAV) platforms are a

Externí odkaz: https://doaj.org/article/68f3ce69afca434ab6bab326ba7cbb85

Comparative performance of convolutional neural network, weighted and conventional support vector machine and random forest for classifying tree species using hyperspectral and photogrammetric data

Autor: C. M. de Almeida, Jose David Bermudez Castro, Laura Elena Cué La Rosa, Carla Luciane Lima, Antonio Maria Garcia Tommaselli, Camile Sothe, Michele Dalponte, Raul Queiroz Feitosa, Marcos Benedito Schimalski, Gabriela Takahashi Miyoshi, Veraldo Liesenberg

Publikováno v: Scopus
Repositório Institucional da UNESP
Universidade Estadual Paulista (UNESP)
instacron:UNESP

Made available in DSpace on 2020-12-12T01:54:59Z (GMT). No. of bitstreams: 0 Previous issue date: 2020-04-02 Fundação de Amparo à Pesquisa e Inovação do Estado de Santa Catarina Conselho Nacional de Desenvolvimento Científico e Tecnológico (CN

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::2e975ac907abdcedf934584dd64f6e45
https://doi.org/10.1080/15481603.2020.1712102

Benchmarking Anchor-Based and Anchor-Free State-of-the-Art Deep Learning Methods for Individual Tree Detection in RGB High-Resolution Images

Autor: Jonathan de Andrade Silva, Gabriela Takahashi Miyoshi, Keiller Nogueira, José Marcato Junior, Wesley Nunes Gonçalves, P. A. P. Zamboni, Edson Takashi Matsubara

Publikováno v: Remote Sensing
Volume 13
Issue 13
Pages: 2482
Scopus
Repositório Institucional da UNESP
Universidade Estadual Paulista (UNESP)
instacron:UNESP
Remote Sensing, Vol 13, Iss 2482, p 2482 (2021)

Made available in DSpace on 2022-04-29T08:30:21Z (GMT). No. of bitstreams: 0 Previous issue date: 2021-07-01 Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::74c318d1fc5b89f2f16dd853a2f66e1c
http://dspace.stir.ac.uk/bitstream/1893/33010/1/remotesensing-13-02482.pdf