Geology topics

D.J. Selkowitz

Publications and source records attributed to D.J. Selkowitz.

4 recordsLinked to original sources

USGS2010

A comparison of multi-spectral, multi-angular, and multi-temporal remote sensing datasets for fractional shrub canopy mapping in Arctic Alaska

Shrub cover appears to be increasing across many areas of the Arctic tundra biome, and increasing shrub cover in the Arctic has the potential to significantly impact global carbon budgets and the global climate system. For most of the Arctic, however, there is no existing baseline inventory of shrub canopy cover, as existing maps of Arctic vegetation provide little information about the density of shrub cover at a moderate spatial resolution across the region. Remotely-sensed fractional shrub canopy maps can provide this necessary baseline inventory of shrub cover. In this study, we compare the accuracy of fractional shrub canopy (> 0.5 m tall) maps derived from multi-spectral, multi-angular, and multi-temporal datasets from Landsat imagery at 30 m spatial resolution, Moderate Resolution Imaging SpectroRadiometer (MODIS) imagery at 250 m and 500 m spatial resolution, and MultiAngle Imaging Spectroradiometer (MISR) imagery at 275 m spatial resolution for a 1067 km 2 study area in Arctic Alaska. The study area is centered at 69 °N, ranges in elevation from 130 to 770 m, is composed primarily of rolling topography with gentle slopes less than 10°, and is free of glaciers and perennial snow cover. Shrubs > 0.5 m in height cover 2.9% of the study area and are primarily confined to patches associated with specific landscape features. Reference fractional shrub canopy is determined from in situ shrub canopy measurements and a high spatial resolution IKONOS image swath. Regression tree models are constructed to estimate fractional canopy cover at 250 m using different combinations of input data from Landsat, MODIS, and MISR. Results indicate that multi-spectral data provide substantially more accurate estimates of fractional shrub canopy cover than multi-angular or multi-temporal data. Higher spatial resolution datasets also provide more accurate estimates of fractional shrub canopy cover (aggregated to moderate spatial resolutions) than lower spatial resolution datasets, an expected result for a study area where most shrub cover is concentrated in narrow patches associated with rivers, drainages, and slopes. Including the middle infrared bands available from Landsat and MODIS in the regression tree models (in addition to the four standard visible and near-infrared spectral bands) typically results in a slight boost in accuracy. Including the multi-angular red band data available from MISR in the regression tree models, however, typically boosts accuracy more substantially, resulting in moderate resolution fractional shrub canopy estimates approaching the accuracy of estimates derived from the much higher spatial resolution Landsat sensor. Given the poor availability of snow and cloud-free Landsat scenes in many areas of the Arctic and the promising results demonstrated here by the MISR sensor, MISR may be the best choice for large area fractional shrub canopy mapping in the Alaskan Arctic for the period 2000–2009.

Alaska↗

USGS2008

Radar imaging of winter seismic survey activity in the National Petroleum Reserve-Alaska

During the spring of 2006, Radarsat-1 synthetic aperture radar (SAR) imagery was acquired on a continual basis for the Teshekpuk Lake Special Area (TLSA), in the northeast portion of the National Petroleum Reserve, Alaska (NPR-A) in order to monitor lake ice melting processes. During data processing, it was discovered that the Radarsat-1 imagery detected features associated with winter seismic survey activity. Focused analysis of the image time series revealed various aspects of the exploration process such as the grid profile associated with the seismic line surveys as well as trails and campsites associated with the mobile survey crews. Due to the high temporal resolution of the dataset it was possible to track the progress of activities over a one month period. Spaceborne SAR imagery can provide information on the location of winter seismic activity and could be used as a monitoring tool for land and resource managers as increased petroleum-based activity occurs in the TLSA and NPR-A.

Polar Record↗

USGS2002

Interannual variations in snowpack in the Crown of the Continent Ecosystem

Ecosystem changes such as glacier recession and alpine treeline advance have been documented over the previous 150 years in the Rocky Mountains of northern Montana and southern British Columbia and Alberta, a region known as the Crown of the Continent Ecosystem (CCE). Such changes are controlled, at least partially, by variations in snowpack. The CCE consists primarily of public lands, the majority of which is undeveloped or wilderness. Consequently, this region is well suited for an examination of long-term snowpack variation and associated ecosystem change. Data from nine SNOTEL sites provide an indication of the daily accumulation and ablation of snowpack over the period 1977-2001, as well as the relationship between precipitation, temperature and snowpack. 1 April data from 21 snow courses indicated the extent of regional snowpack variation and trends over the period 1950-2001, and 1 May data from three snow courses in Glacier National Park allow this record to be extended back to 1922. SNOTEL data suggest CCE snowpacks are larger and more persistent than in most regions of the western USA, and that water year precipitation is the primary control on 1 April snow water equivalent (SWE). Snow course data indicate that variations in both 1 April and 1 May mean SWE are closely tied to the Pacific decadal oscillation, an El Nino-southern oscillation-like interdecadal pattern of Pacific Ocean climate variability. Despite relatively stable snowpacks and summer temperatures since 1922, the glaciers in Glacier National Park have receded steadily during this period, implying a significant climatic shift between their Little Ice Age glacial maxima (ca 1860) and 1922. Published in 2002 by John Wiley and Sons, Ltd.

Montana↗

USGS2002

Spatial and temporal snowpack variation in the crown of the continent ecosystem

Snowpack related ecosystem changes such as glacier recession and alpine treeline advance have been documented in the Crown of the Continent Ecosystem (CCE) over the course of the previous 150 years. Using data from the Natural Resource Conservation Service's SNOTEL sites and snow course surveys, we examined the spatial and temporal variation in snowpack in the region. SNOTEL data suggest CCE snowpacks are larger and more persistent than in most regions of the Western U.S., and that water year precipitation, rather than mean temperature, is the primary control on April 1 snow water equivalent (SWE). Snow course data indicate a statistically significant downward trend in mean April 1 SWE for the period 1950-2001 but no statistically significant trend in mean May 1 SWE for the longer period 1922-2001. Further analysis reveals that variations in both April 1 and May 1 mean SWE are closely tied to the Pacific Decadal Oscillation, an ENSO-like interdecadal pattern of Pacific Ocean climate variability. Despite no significant trend in mean May 1 SWE between 1922-2001, glaciers in Glacier National Park receded steadily during this period, implying changing climatic conditions crossed a threshold for glacier mass balance maintenace sometime between the Little Ice Age glacial maxima and 1922.

Conference Paper↗