Abstract
The complexity of permafrost dynamics and its critical impact on climate feedbacks warrant continued development of advanced high-latitude terrestrial ecosystem characterization and monitoring approaches. In this study, we explore the value of remote sensing and surface geophysical data for characterizing land surface and subsurface properties and their linkages in an Alaskan Coastal Plain ecosystem. We base our study on data collected at the end of the 2011 growing season in the Barrow Environmental Observatory, where a nested suite of measurements were collected within a polygon-dominated region including: surface ground penetrating radar, electromagnetic, and electrical resistance tomography data; thaw depth, soil temperature and moisture content, soil texture, soil carbon and nitrogen content, and major and trace cations. Previously-collected lidar data were also available for the study.
Analysis of the datasets, individually and in combination, revealed the utility of the methods for characterizing critical land-surface and subsurface properties and associated spatial zonation. Lidar analysis was performed to extract geomorphic metrics (such as slope, curvature, and directed distance of polygons), which potentially indicate drainage potential and permafrost deformation state. Cluster analysis of these lidar-obtained attributes suggested that the land surface can be grouped into three spatially coherent zones, each having a dominant geomorphic expression including: a high centered polygon zone, a low centered polygon zone and a transitional zone. Comparison of the geophysical attributes from radar, electrical resistance tomography, and electromagnetic data with point measurements suggests that the surface geophysical data can provide very high-resolution information about subsurface properties that affect ecosystem feedbacks to climate, such as thaw depth and moisture content. Cluster analysis suggested that the geophysical attributes also varied spatially in a systematic way, suggesting the presence of three laterally distinct subsurface zones. Analysis of zone-based subsurface point measurements suggests that the geophysically-defined zones have unique distributions of hydrological, thermal, and geochemical properties and that the subsurface (geophysically-based) and land-surface (lidar-based) zonation is consistent. Although the close linkage between land surface (polygonal geomorphology) and subsurface (active layer) variability revealed through our study is not surprising, to our knowledge this is the first study to document such relationships using high resolution and non-invasive approaches.
This study suggests the potential of using coincident lidar and surface geophysical measurements to quantify land surface and subsurface properties (respectively) and their linkages, which are likely to play a role in terrestrial ecosystem evolution and feedbacks to climate. These findings open the way for future research focused on using combined geophysical and remote sensing datasets to estimate subsurface and land-surface properties in high resolution and over large regions as is needed for process understanding and numerical model initialization in high latitude terrestrial ecosystems.
