A1 Refereed original research article in a scientific journal
Dating flowering cycles of Amazonian bamboo-dominated forests by supervised Landsat time series segmentation
Authors: Jasper Van Doninck, Jan Westerholm, Kalle Ruokolainen, Hanna Tuomisto, Risto Kalliola
Publisher: Elsevier
Publication year: 2020
Journal: International Journal of Applied Earth Observation and Geoinformation
Journal name in source: INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION
Journal acronym: INT J APPL EARTH OBS
Article number: ARTN 102196
Volume: 93
Number of pages: 11
ISSN: 1569-8432
DOI: https://doi.org/10.1016/j.jag.2020.102196
Self-archived copy’s web address: https://research.utu.fi/converis/portal/detail/Publication/51115570
Bamboo-dominated forests are unusual and interesting because their structure and biomass fluctuate in decades-long cycles corresponding to the flowering and mortality rhythm of the bamboo. In southwestern Amazonia, these forests have been estimated to occupy an area of approximately 160 000 km(2), and a single reproductively synchronized patch can cover up to thousands of square kilometers. Accurate mapping of these forests is challenging, however: the forests are spatially heterogeneous, with bamboo densities varying widely among adjacent sites; much of the area is inaccessible, so field verification of bamboo presence is difficult to obtain and georeferenced records of past flowering events virtually non-existent; and detectability of the bamboo by remote sensing varies considerably during its life cycle. In this study, we develop a supervised time series segmentation approach that allows us to identify both the presence of bamboo forests and the years in which the bamboo flowering and subsequent mortality have occurred. We then apply the method to the entire Landsat TM/ETM+ archive from 1984 to the end of 2018 and validate the classification by visual interpretation of very high resolution imagery. Collecting accurate ground reference data of bamboo presence and bamboo mortality timing is notably difficult in these forests, and we therefore developed a methodology that takes advantage of imperfect reference data obtained from the Landsat time series itself. Our results show that bamboo forests can be differentiated from non-bamboo forests using any of the infrared bands, but band 5 produces the highest classification accuracy. Interestingly, there appears to be a temporal difference in the spectral responses of the three infrared bands to bamboo flowering and mortality: near infrared (band 4) reflectance reacts to the event earlier than shortwave infrared (bands 5 and 7) reflectance. The long Landsat TM/ETM+ archive allows our methodology to detect some areas with two mortality events, with a theoretical maximum interval of 29 years. Analysis of these pixels with repeated mortality confirms that the life cycles of the local bamboo species (Guadua sarcocarpa and G. weberbauerii) last typically 28 years.
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