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. Resul...
Forests contain a majority of the aboveground carbon (C) found in ecosystems, and understanding biom...
Improving our ability to track and monitor changes on Earth’s surface will inevitably enhance our ab...
Landsat time series (LTS) and associated change detection algorithms are useful for monitoring the e...
Over the last century Canadian boreal forests have warmed by 2-3° C, causing growing seasons to leng...
Investigating the temporal and spatial pattern of landscape disturbances is an important requirement...
Forests are the largest aboveground sink for atmospheric carbon (C), and understanding how they chan...
The research applied new methods that integrated remote sensing and other spatial data bases to answ...
The primary goal of this research was to improve monitoring of temperate forest change using remote ...
The world's forest ecosystems are in a state of permanent flux at a variety of spatial and temp...
Recent studies have used satellite-derived normalized difference vegetation index (NDVI) time series...
Across boreal forests and resource rich areas, human-induced change is rapidly occurring at various ...
Forest ecosystems have recently received worldwide attention due to their biological diversity and t...
Forest ecosystems are being altered by climate change, invasive species, and additional stressors. O...
Forests contain a majority of the aboveground carbon (C) found in ecosystems, and understanding biom...
University of Minnesota Ph.D. dissertation. April 2010. Major: Computer Science. Advisor: Prof. Vipi...
Forests contain a majority of the aboveground carbon (C) found in ecosystems, and understanding biom...
Improving our ability to track and monitor changes on Earth’s surface will inevitably enhance our ab...
Landsat time series (LTS) and associated change detection algorithms are useful for monitoring the e...
Over the last century Canadian boreal forests have warmed by 2-3° C, causing growing seasons to leng...
Investigating the temporal and spatial pattern of landscape disturbances is an important requirement...
Forests are the largest aboveground sink for atmospheric carbon (C), and understanding how they chan...
The research applied new methods that integrated remote sensing and other spatial data bases to answ...
The primary goal of this research was to improve monitoring of temperate forest change using remote ...
The world's forest ecosystems are in a state of permanent flux at a variety of spatial and temp...
Recent studies have used satellite-derived normalized difference vegetation index (NDVI) time series...
Across boreal forests and resource rich areas, human-induced change is rapidly occurring at various ...
Forest ecosystems have recently received worldwide attention due to their biological diversity and t...
Forest ecosystems are being altered by climate change, invasive species, and additional stressors. O...
Forests contain a majority of the aboveground carbon (C) found in ecosystems, and understanding biom...
University of Minnesota Ph.D. dissertation. April 2010. Major: Computer Science. Advisor: Prof. Vipi...
Forests contain a majority of the aboveground carbon (C) found in ecosystems, and understanding biom...
Improving our ability to track and monitor changes on Earth’s surface will inevitably enhance our ab...
Landsat time series (LTS) and associated change detection algorithms are useful for monitoring the e...