Multi-temporal analysis of radiometric changes in satellite images of forest edges to infer selective-logging areas in the Amazon forest - Graça, Paulo Maurício Lima Alencastro de; Maldonado, Francisco Dario; Santos, João Roberto dos; Keizer, Edwin Willem Hermanus (Acta Amazonica, 2015)
Radiometric changes observed in multi-temporal optical satellite images have an important role in efforts to characterize selective-logging areas. The aim of this study was to analyze the multi-temporal behavior of spectral-mixture responses in satellite images in simulated selective-logging areas in the Amazon forest, considering red/near-infrared spectral relationships. Forest edges were used to infer the selective-logging infrastructure using differently oriented edges in the transition between forest and deforested areas in satellite images. TM/Landsat-5 images acquired at three dates with different solar-illumination geometries were used in this analysis. The method assumed that the radiometric responses between forest with selective-logging effects and forest edges in contact with recent clear-cuts are related. The spatial frequency attributes of red/near infrared bands for edge areas were analyzed. Analysis of dispersion diagrams showed two groups of pixels that represent selective-logging areas. The attributes for size and radiometric distance representing these two groups were related to solar-elevation angle. The results suggest that detection of timber exploitation areas is limited because of the complexity of the selective-logging radiometric response. Thus, the accuracy of detecting selective logging can be influenced by the solar-elevation angle at the time of image acquisition. We conclude that images with lower solar-elevation angles are less reliable for delineation of selecting logging.
Análise multitemporal das mudanças radiométricas em imagens de satélite de bordas de floresta para inferir áreas de corte seletivo na floresta Amazônica
Keywords: Timber Exploitation; Deforestation; Remote Sensing; Forest Monitoring; Exploração Madeireira; Desmatamento; Sensoriamento remoto; Monitoramento Florestal