Using multi-resolution remote sensing to monitor disturbance and climate change impacts on Northern forests

Global 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 f...

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Main Author: Sulla-Menashe, Damien
Language:en_US
Published: 2016
Subjects:
Online Access:https://hdl.handle.net/2144/14035
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spelling ndltd-bu.edu-oai-open.bu.edu-2144-140352021-10-22T17:01:29Z Using multi-resolution remote sensing to monitor disturbance and climate change impacts on Northern forests Sulla-Menashe, Damien Remote sensing Forests Climate change Remote sensing Time series analysis Global 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. 2016-01-14T19:32:56Z 2016-01-14T19:32:56Z 2015 2015-11-18T17:09:31Z Thesis/Dissertation https://hdl.handle.net/2144/14035 en_US Attribution 4.0 International http://creativecommons.org/licenses/by/4.0/
collection NDLTD
language en_US
sources NDLTD
topic Remote sensing
Forests
Climate change
Remote sensing
Time series analysis
spellingShingle Remote sensing
Forests
Climate change
Remote sensing
Time series analysis
Sulla-Menashe, Damien
Using multi-resolution remote sensing to monitor disturbance and climate change impacts on Northern forests
description Global 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.
author Sulla-Menashe, Damien
author_facet Sulla-Menashe, Damien
author_sort Sulla-Menashe, Damien
title Using multi-resolution remote sensing to monitor disturbance and climate change impacts on Northern forests
title_short Using multi-resolution remote sensing to monitor disturbance and climate change impacts on Northern forests
title_full Using multi-resolution remote sensing to monitor disturbance and climate change impacts on Northern forests
title_fullStr Using multi-resolution remote sensing to monitor disturbance and climate change impacts on Northern forests
title_full_unstemmed Using multi-resolution remote sensing to monitor disturbance and climate change impacts on Northern forests
title_sort using multi-resolution remote sensing to monitor disturbance and climate change impacts on northern forests
publishDate 2016
url https://hdl.handle.net/2144/14035
work_keys_str_mv AT sullamenashedamien usingmultiresolutionremotesensingtomonitordisturbanceandclimatechangeimpactsonnorthernforests
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