Wednesday, August 14, 2019
Exhibit Hall, Kentucky International Convention Center
Mahsa Khodaee, Geography, Indiana university Bloomington, Bloomington, IN, Taehee Hwang, Department of Geography, Indiana University, Bloomington, IN, Jihyun Kim, Yonsei University, Sarah Thompson, Colorado State University and Steve Norman, Eastern Forest Environmental Threat Assessment Center, US Forest Service Southern Research Station, Asheville, NC
Background/Question/Methods: Hemlock Woolly Adelgid (
Adelges tsugae Annand, HWA) is a non-native pest that causes widespread foliar damage and potentially irreversible tree mortality in eastern (
Tsuga Canadensis L.) and Carolina (
Tsuaga caroliniana Engelm.) hemlocks throughout eastern United States. To better understand the implications of hemlock declines in biogeochemical cycles in forest landscapes, it is important to map the hemlock morbidity distribution and its recovery patterns in space and time. Recently, several change detection techniques using multi-temporal satellite images have been widely used for land use and land cover changes; however, there are few studies in application of forest infestation monitoring covering from pre-infestation to full recovery stages. In this study, our objective is to use all available Landsat satellite images to investigate the performance of NDVI and Tasseled Cap Transformation (TCT) indices in capturing spatial and temporal patterns of HWA-induced hemlock mortality and following deciduous forest regenerations in southern Appalachians.
Results/Conclusions: For each Landsat pixel, the time series of these indices were fitted using a time series analyses which can separate inter-annual (low frequency) disturbance patterns from seasonal phenology (high frequency) signals. We estimated the long-term infestation and following recovery patterns in space and time based on the residuals between predicted and observed values of the model, further validated with individual hemlock tree location identified from aerial photos. Specifically, we estimated (1) timing of HWA infestation and forest recovery, and (2) severity of HWA infestation. Our results suggested that the greenness-brightness ratio and NDVI time series performed more accurate in capturing disturbance timing and severity. These two indices not only can detect the forest disturbance timing, but also the long-term recovery patterns in previously hemlock dominated forests by deciduous trees.
