Successional stages and their evolution in tropical forests using multi-temporal photogrammetric surface models and superpixels

Autor(es)

Berveglieri, Adilson ^[1] ; Imai, Nilton N. ^[1] ; Tommaselli, Antonio M. G. ^[1] ; Casagrande, Baltazar ^[2] ; Honkavaara, Eija ^[3]

Afiliação do(s) autor(es)

^[1] UNESP Sao Paulo State Univ, Dept Cartog, Rua Roberto Simonsen 305, BR-19060900 Presidente Prudente - Brazil

^[2] UNESP Sao Paulo State Univ, Dept Geog, Rua Roberto Simonsen 305, BR-19060900 Presidente Prudente - Brazil

^[3] Natl Land Survey Finland, Finnish Geospatial Res Inst FGI, Dept Remote Sensing & Photogrammetry, Helsinki - Finland

• Tipo de documento: Artigo Científico
• Fonte: ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING; v. 146, p. 548-558, DEC 2018.
• Citações Web of Science: 2

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. (AU)

• Processo FAPESP: 13/50426-4 - Unmanned airborne vehicle-based 4D remote sensing for mapping Rain Forest biodiversity and its change in Brazil (UAV_4D_Bio)
• Beneficiário: Antonio Maria Garcia Tommaselli
• Modalidade de apoio: Auxílio à Pesquisa - Regular
• Processo FAPESP: 14/05033-7 - Orientação Integrada de Imagens Hiperespectrais Coletadas por VANT
• Beneficiário: Adilson Berveglieri
• Modalidade de apoio: Bolsas no Brasil - Pós-Doutorado