UVM Theses and Dissertations
Format:
Print
Author:
White, Katharine M.
Dept./Program:
Natural Resources
Year:
2012
Degree:
MS
Abstract:
The timing of vegetation development, or phenology, is one of the most clearly observed terrestrial responses to changing climate. Current remote sensing studies of foliage emergence have been limited to coarse spatial or temporal resolution and often lack a direct link to field measurements. To address this gap, we compared multiple remote sensing methodologies to extensive field measurements in order to establish a robust method of quantifying phenology and a better understanding of what physiological characteristics the sensors are best able to detect. Five vegetation indices derived from Landsat 5 TM and 7 ETM data, five different mathematical fits to model a continuous temporal response, and a suite of index thresholds for "start of spring/season" assessments (SOS) were compared to field measurements of budburst stage, canopy transparency, and leaf area index.
Results indicated that a four parameter logistic model based on at least 5 spring coverages of the enhanced vegetation index (EVI) and a SOS threshold of 0.3 was most closely related to field metrics. Using this approach, we were able to match the field-measured date when plots first reached full leaf out to within 11 days (CV= 11.21). While better or more specific than prior studies, this indicates that landscape scale remote sensing efforts are useful to compare the seasonal change in canopy phenology and relative landscape differences in timing. However, estimates of spring to single day accuracy are not likely accurate across forest types. Of the various field metrics, the visual ranks of budburst stage were more closely related to vegetation indices (r= 0.9554) than photo metrics of canopy characteristics.
Results indicated that a four parameter logistic model based on at least 5 spring coverages of the enhanced vegetation index (EVI) and a SOS threshold of 0.3 was most closely related to field metrics. Using this approach, we were able to match the field-measured date when plots first reached full leaf out to within 11 days (CV= 11.21). While better or more specific than prior studies, this indicates that landscape scale remote sensing efforts are useful to compare the seasonal change in canopy phenology and relative landscape differences in timing. However, estimates of spring to single day accuracy are not likely accurate across forest types. Of the various field metrics, the visual ranks of budburst stage were more closely related to vegetation indices (r= 0.9554) than photo metrics of canopy characteristics.