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dc.contributor.authorSulla-Menashe, Damienen_US
dc.date.accessioned2016-01-14T19:32:56Z
dc.date.available2016-01-14T19:32:56Z
dc.date.issued2015
dc.identifier.urihttps://hdl.handle.net/2144/14035
dc.description.abstractGlobal forests are experiencing a variety of stresses in response to climate change and human activities. The broad objective of this dissertation is to improve understanding of how temperate and boreal forests are changing by using remote sensing to develop new techniques for detecting change in forest ecosystems and to use these techniques to investigate patterns of change in North American forests. First, I developed and applied a temporal segmentation algorithm to an 11-year time series of MODIS data for a region in the Pacific Northwest of the USA. Through comparison with an existing forest disturbance map, I characterized how the severity and spatial scale of disturbances affect the ability of MODIS to detect these events. Results from these analyses showed that most disturbances occupying more than one-third of a MODIS pixel can be detected but that prior disturbance history and gridding artifacts complicate the signature of forest disturbance events in MODIS data. Second, I focused on boreal forests of Canada, where recent studies have used remote sensing to infer decreases in forest productivity. To investigate these trends, I collected 28 years of Landsat TM and ETM+ data for 11 sites spanning Canada's boreal forests. Using these data, I analyzed how sensor geometry and intra- and inter-sensor calibration influence detection of trends from Landsat time series. Results showed systematic patterns in Landsat time series that reflect sensor geometry and subtle issues related to inter-sensor calibration, including consistently higher red band reflectance values from TM data relative to ETM+ data. In the final chapter, I extended the analyses from my second chapter to explore patterns of change in Landsat time series at an expanded set of 46 sites. Trends in peak-summer values of vegetation indices from Landsat were summarized at the scale of MODIS pixels. Results showed that the magnitude and slope of observed trends reflect patterns in disturbance and land cover and that undisturbed forests in eastern sites showed subtle, but detectable, differences from patterns observed in western sites. Drier forests in western Canada show declining trends, while mostly increasing trends are observed for wetter eastern forests.en_US
dc.language.isoen_US
dc.rightsAttribution 4.0 Internationalen_US
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/
dc.subjectRemote sensingen_US
dc.subjectForestsen_US
dc.subjectClimate changeen_US
dc.subjectRemote sensingen_US
dc.subjectTime series analysisen_US
dc.titleUsing multi-resolution remote sensing to monitor disturbance and climate change impacts on Northern forestsen_US
dc.typeThesis/Dissertationen_US
dc.date.updated2015-11-18T17:09:31Z
etd.degree.nameDoctor of Philosophyen_US
etd.degree.leveldoctoralen_US
etd.degree.disciplineEarth & Environmenten_US
etd.degree.grantorBoston Universityen_US


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Attribution 4.0 International
Except where otherwise noted, this item's license is described as Attribution 4.0 International