University of Connecticut

Events Calendar

MS Thesis Defense - Adam Chlus - NRE

Friday, April 24, 2015
11:00am – 12:00pm

Storrs Campus
Advanced Technology Laboratory (ATL) 109

"Monitoring Long-Term Forest Dynamics Using Very Dense Landsat Time Series"

The rapid pace at which the world’s forests are changing requires active monitoring and measuring of key characteristics indicative of forest health and functioning. However, plot level measurements are unable to provide the spatial and temporal coverage required to develop large scale, long-term records of forest characteristics due to high costs. This thesis describes two new methods for taking advantage of the wealth of data stored in the Landsat satellite image archive for detecting disturbances and estimating forest height over a period of 25 years in a mixed boreal forest in Quebec, Canada. Using an object based approach multi-seasonal spectral trajectories were created and used to detect abrupt changes in spectral values indicative of disturbance events. Forest height was estimated by relating average wintertime reflectance to LiDAR derived measures of forest height. Results indicate high accuracy for disturbance detection (92%) and strong correlation between wintertime near infrared reflectance and forest height (RMSE: 0.77 – 1.33 m; R-squared: 0.70- 0.90). This thesis demonstrates the value of an object based approach for analyses of dense time series of satellite imagery and highlights the importance of long-term Earth observing satellite missions for monitoring forest ecosystems.

Contact:

Daniel Civco

Graduate School - Theses and Dissertation Defense (primary), CAHNR Academic Programs, Center for Environmental Science and Engineering, CLEAR - Center for Land Use Education and Research, UConn Master Calendar

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