Successional stages and their evolution in tropical forests using multi-temporal photogrammetric surface models and superpixels
Autor(a) principal: | |
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Data de Publicação: | 2018 |
Outros Autores: | , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Institucional da UNESP |
Texto Completo: | http://dx.doi.org/10.1016/j.isprsjprs.2018.11.002 http://hdl.handle.net/11449/188345 |
Resumo: | Airborne photogrammetric image archives offer interesting possibilities for multi-temporal analyses of environmental evolution. The objective of this investigation was to develop a technique for classifying forest successional stages and performing multi-temporal analyses of the tree canopy based on tree height variances calculated from digital surface models (DSMs) created from photogrammetric imagery. Furthermore, our objective was to evaluate the usability of the technique in assessing the evolution of successional stages in a tropical forest. The local variance calculation in 3D space resulted in an image that was subdivided with a segmentation technique to generate small areas called superpixels. These superpixels, which use the local mean variance as an attribute, are assessed via cluster analysis to evaluate statistical similarity and define successional stage classes. The same superpixel shapes were located in georeferenced historical datasets to enable multi-temporal analysis. The cluster analysis of temporal superpixels enabled the spatiotemporal classification of forest canopy evolution. The technique was used to assess a tropical forest remnant in Brazil. Dense DSMs were generated with stereo-photogrammetric techniques using optical images (both film and digital images) from which height variances were computed. A cluster analysis of superpixels was performed to classify the forest canopy into four successional stages, which were consistent with Brazilian classification rules. The multi-temporal analysis identified six classes of forest cover evolution. Field data were collected in forest plots to validate the generated forest canopy classifications. The results showed that the proposed approach was feasible for forest cover classification and for identifying changes in the vertical forest structure and cover over time using only optical images. |
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Successional stages and their evolution in tropical forests using multi-temporal photogrammetric surface models and superpixelsDSMForest classificationForest successionSegmentationTemporal superpixelAirborne photogrammetric image archives offer interesting possibilities for multi-temporal analyses of environmental evolution. The objective of this investigation was to develop a technique for classifying forest successional stages and performing multi-temporal analyses of the tree canopy based on tree height variances calculated from digital surface models (DSMs) created from photogrammetric imagery. Furthermore, our objective was to evaluate the usability of the technique in assessing the evolution of successional stages in a tropical forest. The local variance calculation in 3D space resulted in an image that was subdivided with a segmentation technique to generate small areas called superpixels. These superpixels, which use the local mean variance as an attribute, are assessed via cluster analysis to evaluate statistical similarity and define successional stage classes. The same superpixel shapes were located in georeferenced historical datasets to enable multi-temporal analysis. The cluster analysis of temporal superpixels enabled the spatiotemporal classification of forest canopy evolution. The technique was used to assess a tropical forest remnant in Brazil. Dense DSMs were generated with stereo-photogrammetric techniques using optical images (both film and digital images) from which height variances were computed. A cluster analysis of superpixels was performed to classify the forest canopy into four successional stages, which were consistent with Brazilian classification rules. The multi-temporal analysis identified six classes of forest cover evolution. Field data were collected in forest plots to validate the generated forest canopy classifications. The results showed that the proposed approach was feasible for forest cover classification and for identifying changes in the vertical forest structure and cover over time using only optical images.Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)Academy of FinlandConselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)Department of Cartography UNESP – São Paulo State University, Rua Roberto Simonsen 305Department of Geography UNESP – São Paulo State University, Rua Roberto Simonsen 305Department of Remote Sensing and Photogrammetry Finnish Geospatial Research Institute FGI National Land Survey of FinlandDepartment of Cartography UNESP – São Paulo State University, Rua Roberto Simonsen 305Department of Geography UNESP – São Paulo State University, Rua Roberto Simonsen 305FAPESP: 2013/50426-4FAPESP: 2014/05033-7Academy of Finland: 273806CNPq: 305111/2010-8Universidade Estadual Paulista (Unesp)National Land Survey of FinlandBerveglieri, Adilson [UNESP]Imai, Nilton N. [UNESP]Tommaselli, Antonio M.G. [UNESP]Casagrande, Baltazar [UNESP]Honkavaara, Eija2019-10-06T16:05:02Z2019-10-06T16:05:02Z2018-12-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/article548-558http://dx.doi.org/10.1016/j.isprsjprs.2018.11.002ISPRS Journal of Photogrammetry and Remote Sensing, v. 146, p. 548-558.0924-2716http://hdl.handle.net/11449/18834510.1016/j.isprsjprs.2018.11.0022-s2.0-85056388797Scopusreponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPengISPRS Journal of Photogrammetry and Remote Sensinginfo:eu-repo/semantics/openAccess2021-10-22T21:15:49Zoai:repositorio.unesp.br:11449/188345Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462021-10-22T21:15:49Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false |
dc.title.none.fl_str_mv |
Successional stages and their evolution in tropical forests using multi-temporal photogrammetric surface models and superpixels |
title |
Successional stages and their evolution in tropical forests using multi-temporal photogrammetric surface models and superpixels |
spellingShingle |
Successional stages and their evolution in tropical forests using multi-temporal photogrammetric surface models and superpixels Berveglieri, Adilson [UNESP] DSM Forest classification Forest succession Segmentation Temporal superpixel |
title_short |
Successional stages and their evolution in tropical forests using multi-temporal photogrammetric surface models and superpixels |
title_full |
Successional stages and their evolution in tropical forests using multi-temporal photogrammetric surface models and superpixels |
title_fullStr |
Successional stages and their evolution in tropical forests using multi-temporal photogrammetric surface models and superpixels |
title_full_unstemmed |
Successional stages and their evolution in tropical forests using multi-temporal photogrammetric surface models and superpixels |
title_sort |
Successional stages and their evolution in tropical forests using multi-temporal photogrammetric surface models and superpixels |
author |
Berveglieri, Adilson [UNESP] |
author_facet |
Berveglieri, Adilson [UNESP] Imai, Nilton N. [UNESP] Tommaselli, Antonio M.G. [UNESP] Casagrande, Baltazar [UNESP] Honkavaara, Eija |
author_role |
author |
author2 |
Imai, Nilton N. [UNESP] Tommaselli, Antonio M.G. [UNESP] Casagrande, Baltazar [UNESP] Honkavaara, Eija |
author2_role |
author author author author |
dc.contributor.none.fl_str_mv |
Universidade Estadual Paulista (Unesp) National Land Survey of Finland |
dc.contributor.author.fl_str_mv |
Berveglieri, Adilson [UNESP] Imai, Nilton N. [UNESP] Tommaselli, Antonio M.G. [UNESP] Casagrande, Baltazar [UNESP] Honkavaara, Eija |
dc.subject.por.fl_str_mv |
DSM Forest classification Forest succession Segmentation Temporal superpixel |
topic |
DSM Forest classification Forest succession Segmentation Temporal superpixel |
description |
Airborne photogrammetric image archives offer interesting possibilities for multi-temporal analyses of environmental evolution. The objective of this investigation was to develop a technique for classifying forest successional stages and performing multi-temporal analyses of the tree canopy based on tree height variances calculated from digital surface models (DSMs) created from photogrammetric imagery. Furthermore, our objective was to evaluate the usability of the technique in assessing the evolution of successional stages in a tropical forest. The local variance calculation in 3D space resulted in an image that was subdivided with a segmentation technique to generate small areas called superpixels. These superpixels, which use the local mean variance as an attribute, are assessed via cluster analysis to evaluate statistical similarity and define successional stage classes. The same superpixel shapes were located in georeferenced historical datasets to enable multi-temporal analysis. The cluster analysis of temporal superpixels enabled the spatiotemporal classification of forest canopy evolution. The technique was used to assess a tropical forest remnant in Brazil. Dense DSMs were generated with stereo-photogrammetric techniques using optical images (both film and digital images) from which height variances were computed. A cluster analysis of superpixels was performed to classify the forest canopy into four successional stages, which were consistent with Brazilian classification rules. The multi-temporal analysis identified six classes of forest cover evolution. Field data were collected in forest plots to validate the generated forest canopy classifications. The results showed that the proposed approach was feasible for forest cover classification and for identifying changes in the vertical forest structure and cover over time using only optical images. |
publishDate |
2018 |
dc.date.none.fl_str_mv |
2018-12-01 2019-10-06T16:05:02Z 2019-10-06T16:05:02Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://dx.doi.org/10.1016/j.isprsjprs.2018.11.002 ISPRS Journal of Photogrammetry and Remote Sensing, v. 146, p. 548-558. 0924-2716 http://hdl.handle.net/11449/188345 10.1016/j.isprsjprs.2018.11.002 2-s2.0-85056388797 |
url |
http://dx.doi.org/10.1016/j.isprsjprs.2018.11.002 http://hdl.handle.net/11449/188345 |
identifier_str_mv |
ISPRS Journal of Photogrammetry and Remote Sensing, v. 146, p. 548-558. 0924-2716 10.1016/j.isprsjprs.2018.11.002 2-s2.0-85056388797 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
ISPRS Journal of Photogrammetry and Remote Sensing |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
548-558 |
dc.source.none.fl_str_mv |
Scopus reponame:Repositório Institucional da UNESP instname:Universidade Estadual Paulista (UNESP) instacron:UNESP |
instname_str |
Universidade Estadual Paulista (UNESP) |
instacron_str |
UNESP |
institution |
UNESP |
reponame_str |
Repositório Institucional da UNESP |
collection |
Repositório Institucional da UNESP |
repository.name.fl_str_mv |
Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP) |
repository.mail.fl_str_mv |
|
_version_ |
1797789990840696832 |