Geology topics

Beverly A. Friesen

Publications and source records attributed to Beverly A. Friesen.

10 recordsLinked to original sources

USGS2016

Latest Pleistocene and Holocene glacial events in the Colonia valley, Northern Patagonia Icefield, southern Chile

The Northern Patagonia Icefield (NPI) is the primary glaciated terrain worldwide at its latitude (46.5–47.5°S), and constraining its glacial history provides unique information for reconstructing Southern Hemisphere paleoclimate. The Colonia Glacier is the largest outlet glacier draining the eastern NPI. Ages were determined using dendrochronology, lichenometry, radiocarbon, cosmogenic 10 Be and optically stimulated luminescence. Dated moraines in the Colonia valley defined advances at 13.2 ± 0.95, 11.0 ± 0.47 and 4.96 ± 0.21 ka, with the last being the first constraint on the onset of Neoglaciation for the eastern NPI from a directly dated landform. Dating in the tributary Cachet valley, which contains an ice-dammed lake during periods of Colonia Glacier expansion, defined an advance at ca. 2.95 ± 0.21 ka, periods of advancement at 810 ± 49 cal a BP and 245 ± 13 cal a BP, and retreat during the intervening periods. Recent Colonia Glacier thinning, which began in the late 1800s, opened a lower-elevation outlet channel for Lago Cachet Dos in ca. 1960. Our data provide the most comprehensive set of Latest Pleistocene and Holocene ages for a single NPI outlet glacier and expand previously developed NPI glacial chronologies.

Colonia valley, Northern Patagonia Iceﬁeld↗

USGS2015

Use of satellite images to determine surface-water cover during the flood event of September 13, 2013, in Lyons and western Longmont, Colorado

The flooding that occurred in north-central Colorado in 2013 was some of the most destructive in the state’s history. Following a summer of drought and wildfires, a wet weather system stalled over the Front Range area from Fort Collins in the north to Colorado Springs in the south, including the cities of Lyons and Longmont. This weather system produced rainfall amounts that greatly exceeded historical highs. The Colorado Office of Emergency Management reported at least eight deaths. More than 11,000 people were evacuated from their homes, and the flooding caused an estimated $2 billion dollars in damages. On September 14, 2013, President Barack Obama issued a major disaster declaration for 15 Colorado counties affected by the severe weather and related damage. To support local, State, and Federal disaster response coordination efforts in Colorado, the U.S. Geological Survey (USGS) developed a geospatial product to identify surface-water cover from Lyons to western Longmont. This information was derived from September 13, 2013 WorldView-2 multispectral imagery at a spatial resolution of 3 meters (m). These data were orthocorrected and pan-sharpened. Three spectral indices (NDVI, NDWI, and NDTI) that were computed from this processed imagery were used to help determine the extent of the surface-water cover. The result was converted to a vector format. This surface-water cover dataset was created as a timely representation of post-flood ground conditions to support response efforts. This dataset and all processed imagery and derived products were uploaded to the USGS Hazards Data Distribution System (HDDS) website (http://hddsexplorer.usgs.gov/uplift/hdds/ ) for distribution to those responding to the flood event.

Colorado↗

USGS2015

Using satellite images to monitor glacial-lake outburst floods: Lago Cachet Dos drainage, Chile

The U.S. Geological Survey (USGS) is monitoring and analyzing glacial-lake outburst floods (GLOFs) in the Colonia valley in the Patagonia region of southern Chile. A GLOF is a type of flood that occurs when water impounded by a glacier or a glacial moraine is released catastrophically. In the Colonia valley, GLOFs originating from Lago Cachet Dos, which is dammed by the Colonia Glacier, have recurred periodically since 2008. The water discharged during these GLOFs flows under or through the Colonia Glacier, into Lago Colonia and then the Río Colonia, and finally into the Río Baker—Chile's largest river in terms of volume of water. This report presents a GeoEye-1 image collected December 1, 2011 and a WorldView-2 image collected September 27, 2013. The 2011 image shows Lago Cachet Dos when the water level was near its maximum extent. The 2013 image shows the drained lake four days after a GLOF event. The images were used to delineate the differences in water surface area prior to, and immediately following, a GLOF event. The imagery shown here highlights the dramatic changes that typically occur during GLOFs from Lago Cachet Dos. The lake area decreased from 4.84 km 2 in 2011 (pre-GLOF) to only 0.30 km 2 in September 2013 (post-GLOF). The water surface lowered approximately 90 m between the pre- and post-GLOF satellite images, yielding a change in volume of approximately 217,000,000 m 3 ; this value is similar to previous estimates (about 200 million m 3 ) of the volume of flood water that flowed down the Río Colonia during some previous GLOFs. During 2008–2013, 14 GLOFs were released from Lago Cachet Dos and created environmental and safety concerns for downstream residents and to infrastructure. If GLOFs and the consequent headward erosion continue, the moraine that creates Lago Cachet Uno could be destabilized and breached, and the two lakes could merge. If the two lakes become connected, the volume of future GLOFs likely would be greater and thus cause longer and (or) more extensive flooding downstream. Additional GLOFs from Lago Cachet Dos are expected in the future, and continued environmental monitoring could provide an early warning system as well as scientific information that could increase our understanding of GLOFs and their consequences. GLOFs occur in glaciated areas around the world and remote sensing technologies can allow researchers to better understand—and potentially predict—future GLOF events.

Colonia valley, Lago Cachet Dos, Patagonia↗

USGS2015

Documenting 35 years of land cover change: Lago Cachet Dos drainage, Chile

The U.S. Geological Survey (USGS) Special Applications Science Center is monitoring temporal changes at the Colonia Glacier and Lago Cachet Dos, Northern Patagonia Icefield of southern Chile. This location is one of the newest international sites in the USGS Global Fiducial Program (GFP)—a program which provides systematic monitoring of dynamic and environmentally critical areas with high-resolution imagery (http://gfp.usgs.gov/). In 2008, Lago Cachet Dos began experiencing glacial lake outburst floods (GLOFs) during which the entire pool of water (about 200 million cubic meters) rapidly drains from the lake and flows south-southeast through the Colonia Glacier. These catastrophic events cause massive erosion of valley-fill deposits and consequent upstream expansion of Lago Cachet Dos towards Lago Cachet Uno. Panchromatic and multispectral images for 1979, 2007, and 2014 highlight the dramatic changes that have occurred at this site over a 35-year period. The lake was smallest in 1979, when the Colonia Glacier was at its maximum extent during the study period. Between 1979 and 2007, the glacier shrank causing an increase in the surface area of the lake. The size of the lake increased substantially, from 2.98 square kilometers (km 2 ) in 1979 to 4.41 km 2 in 2014, primarily due to erosion of valley-fill deposits upstream of its northern edge by the 15 GLOFs that occurred between April 2008 and February 2014. Ongoing studies of the Colonia Glacier and Lago Cachet Dos are focused on providing real-time monitoring of Lago Cachet Dos lake levels, understanding the history of advances and retreats of the Colonia Glacier, and determining the physical mechanisms and hazards associated with the GLOFs that come from Lago Cachet Dos.

Lago Cachet Dos↗

USGS2014

Use of satellite imagery to identify vegetation cover changes following the Waldo Canyon Fire event, Colorado, 2012-2013

The Waldo Canyon Fire of 2012 was one of the most destructive wildfire events in Colorado history. The fire burned a total of 18,247 acres, claimed 2 lives, and destroyed 347 homes. The Waldo Canyon Fire continues to pose challenges to nearby communities. In a preliminary emergency assessment conducted in 2012, the U.S. Geological Survey (USGS) concluded that drainage basins within and near the area affected by the Waldo Canyon Fire pose a risk for future debris flow events. Rainfall over burned, formerly vegetated surfaces resulted in multiple flood and debris flow events that affected the cities of Colorado Springs and Manitou Springs in 2013. One fatality resulted from a mudslide near Manitou Springs in August 2013. Federal, State, and local governments continue to monitor these hazards and other post-fire effects, along with the region’s ecological recovery. At the request of the Colorado Springs Office of Emergency Management, the USGS Special Applications Science Center developed a geospatial product to identify vegetation cover changes following the 2012 Waldo Canyon Fire event. Vegetation cover was derived from July 2012 WorldView-2 and September 2013 QuickBird multispectral imagery at a spatial resolution of two meters. The 2012 image was collected after the fire had reached its maximum extent. Per-pixel increases and decreases in vegetation cover were identified by measuring spectral changes that occurred between the 2012 and 2013 image dates. A Normalized Difference Vegetation Index (NDVI), and Green-Near Infrared Index (GRNIR) were computed from each image. These spectral indices are commonly used to characterize vegetation cover and health condition, due to their sensitivity to detect foliar chlorophyll content. Vector polygons identifying surface-cover feature boundaries were derived from the 2013 imagery using image segmentation software. This geographic software groups similar image pixels into vector objects based upon their spatial and spectral characteristics. The vector dataset was then populated with the per-pixel spectral change information to provide an estimated percentage of vegetation increase or decrease of pixels within each polygon. Information collected during a field visit to the Waldo Canyon burn scar in September 2013 was used to help validate this assessment (see photographs 1-3). The numbers on the satellite images correspond to the location of the photographs. For display purposes, the polygons shown on the map represent areas where significant decrease or increase in vegetation cover occurred. Only polygons that held a 70 percent or greater cover change are shown on this map (a GIS dataset with complete information is available upon request). A significant increase in vegetation cover was found in the burned area. This increase is likely due to the growth of grasses and other herbaceous vegetation. Minimal vegetation cover decrease was detected at this threshold. This product is meant to provide a broad survey of post-fire vegetation trends within the Waldo Canyon burned area to Federal, State, and local officials. It is not designed to quantify species-level vegetation change at this time.

Colorado↗

USGS2013

Satellite images of the September 2013 flood event in Lyons, Colorado

The U.S. Geological Survey (USGS) Special Applications Science Center (SASC) produced an image base map showing high-resolution remotely sensed data over Lyons, Colorado—a city that was severely affected by the flood event that occurred throughout much of the Colorado Front Range in September of 2013. The 0.5-meter WorldView-2 data products were created from imagery collected by DigitalGlobe on September 13 and September 24, 2013, during and following the flood event. The images shown on this map were created to support flood response efforts, specifically for use in determining damage assessment and mitigation decisions. The raw, unprocessed imagery were orthorectified and pan-sharpened to enhance mapping accuracy and spatial resolution, and reproduced onto a cartographic base map. These maps are intended to provide a snapshot representation of post-flood ground conditions, which may be useful to decisionmakers and the general public. The SASC also provided data processing and analysis support for other Colorado flood-affected areas by creating cartographic products, geo-corrected electro-optical and radar image mosaics, and GIS water cover files for use by the Colorado National Guard, the National Park Service, the U.S. Forest Service, and the flood response community. All products for this International Charter event were uploaded to the USGS Hazards Data Distribution System (HDDS) website (http://hdds.usgs.gov/hdds2/) for distribution.

Colorado↗

USGS2013

A new map of standardized terrestrial ecosystems of Africa

Terrestrial ecosystems and vegetation of Africa were classified and mapped as part of a larger effort and global protocol (GEOSS – the Global Earth Observation System of Systems), which includes an activity to map terrestrial ecosystems of the earth in a standardized, robust, and practical manner, and at the finest possible spatial resolution. To model the potential distribution of ecosystems, new continental datasets for several key physical environment datalayers (including coastline, landforms, surficial lithology, and bioclimates) were developed at spatial and classification resolutions finer than existing similar datalayers. A hierarchical vegetation classification was developed by African ecosystem scientists and vegetation geographers, who also provided sample locations of the newly classified vegetation units. The vegetation types and ecosystems were then mapped across the continent using a classification and regression tree (CART) inductive model, which predicted the potential distribution of vegetation types from a suite of biophysical environmental attributes including bioclimate region, biogeographic region, surficial lithology, landform, elevation and land cover. Multi-scale ecosystems were classified and mapped in an increasingly detailed hierarchical framework using vegetation-based concepts of class, subclass, formation, division, and macrogroup levels. The finest vegetation units (macrogroups) classified and mapped in this effort are defined using diagnostic plant species and diagnostic growth forms that reflect biogeographic differences in composition and sub-continental to regional differences in mesoclimate, geology, substrates, hydrology, and disturbance regimes (FGDC, 2008). The macrogroups are regarded as meso-scale (100s to 10,000s of hectares) ecosystems. A total of 126 macrogroup types were mapped, each with multiple, repeating occurrences on the landscape. The modeling effort was implemented at a base spatial resolution of 90 m. In addition to creating several rich, new continent-wide biophysical datalayers describing African vegetation and ecosystems, our intention was to explore feasible approaches to rapidly moving this type of standardized, continent-wide, ecosystem classification and mapping effort forward.

African Geographical Review↗

USGS2010

Landsat Thematic Mapper Image Mosaic of Colorado

The U.S. Geological Survey (USGS) Rocky Mountain Geographic Science Center (RMGSC) produced a seamless, cloud-minimized remotely-sensed image spanning the State of Colorado. Multiple orthorectified Landsat 5 Thematic Mapper (TM) scenes collected during 2006-2008 were spectrally normalized via reflectance transformation and linear regression based upon pseudo-invariant features (PIFS) following the removal of clouds. Individual Landsat scenes were then mosaicked to form a six-band image composite spanning the visible to shortwave infrared spectrum. This image mosaic, presented here, will also be used to create a conifer health classification for Colorado in Scientific Investigations Map 3103. An archive of past and current Landsat imagery exists and is available to the scientific community (http://glovis.usgs.gov/), but significant pre-processing was required to produce a statewide mosaic from this information. Much of the data contained perennial cloud cover that complicated analysis and classification efforts. Existing Landsat mosaic products, typically three band image composites, did not include the full suite of multispectral information necessary to produce this assessment, and were derived using data collected in 2001 or earlier. A six-band image mosaic covering Colorado was produced. This mosaic includes blue (band 1), green (band 2), red (band 3), near infrared (band 4), and shortwave infrared information (bands 5 and 7). The image composite shown here displays three of the Landsat bands (7, 4, and 2), which are sensitive to the shortwave infrared, near infrared, and green ranges of the electromagnetic spectrum. Vegetation appears green in this image, while water looks black, and unforested areas appear pink. The lines that may be visible in the on-screen version of the PDF are an artifact of the export methods used to create this file. The file should be viewed at 150 percent zoom or greater for optimum viewing.

Scientific Investigations Map↗

USGS2010

Conifer health classification for Colorado, 2008

Colorado has undergone substantial changes in forests due to urbanization, wildfires, insect-caused tree mortality, and other human and environmental factors. The U.S. Geological Survey Rocky Mountain Geographic Science Center evaluated and developed a methodology for applying remotely-sensed imagery for assessing conifer health in Colorado. Two classes were identified for the purposes of this study: healthy and unhealthy (for example, an area the size of a 30- x 30-m pixel with 20 percent or greater visibly dead trees was defined as ?unhealthy?). Medium-resolution Landsat 5 Thematic Mapper imagery were collected. The normalized, reflectance-converted, cloud-filled Landsat scenes were merged to form a statewide image mosaic, and a Normalized Difference Vegetation Index (NDVI) and Renormalized Difference Infrared Index (RDII) were derived. A supervised maximum likelihood classification was done using the Landsat multispectral bands, the NDVI, the RDII, and 30-m U.S. Geological Survey National Elevation Dataset (NED). The classification was constrained to pixels identified in the updated landcover dataset as coniferous or mixed coniferous/deciduous vegetation. The statewide results were merged with a separate health assessment of Grand County, Colo., produced in late 2008. Sampling and validation was done by collecting field data and high-resolution imagery. The 86 percent overall classification accuracy attained in this study suggests that the data and methods used successfully characterized conifer conditions within Colorado. Although forest conditions for Lodgepole Pine (Pinus contorta) are easily characterized, classification uncertainty exists between healthy/unhealthy Ponderosa Pine (Pinus ponderosa), Pi?on (Pinus edulis), and Juniper (Juniperus sp.) vegetation. Some underestimation of conifer mortality in Summit County is likely, where recent (2008) cloud-free imagery was unavailable. These classification uncertainties are primarily due to the spatial and temporal resolution of Landsat, and of the NLCD derived from this sensor. It is believed that high- to moderate-resolution multispectral imagery, coupled with field data, could significantly reduce the uncertainty rates. The USGS produced a four-county follow-up conifer health assessment using high-resolution RapidEye remotely sensed imagery and field data collected in 2009.

Scientific Investigations Map↗

USGS2009

Vegetation classification and distribution mapping report: Mesa Verde National Park

The classification and distribution mapping of the vegetation of Mesa Verde National Park (MEVE) and surrounding environment was achieved through a multi-agency effort between 2004 and 2007. The National Park Service’s Southern Colorado Plateau Network facilitated the team that conducted the work, which comprised the U.S. Geological Survey’s Southwest Biological Science Center, Fort Collins Research Center, and Rocky Mountain Geographic Science Center; Northern Arizona University; Prescott College; and NatureServe. The project team described 47 plant communities for MEVE, 34 of which were described from quantitative classification based on f eld-relevé data collected in 1993 and 2004. The team derived 13 additional plant communities from field observations during the photointerpretation phase of the project. The National Vegetation Classification Standard served as a framework for classifying these plant communities to the alliance and association level. Eleven of the 47 plant communities were classified as “park specials;” that is, plant communities with insufficient data to describe them as new alliances or associations. The project team also developed a spatial vegetation map database representing MEVE, with three different map-class schemas: base, group, and management map classes. The base map classes represent the fi nest level of spatial detail. Initial polygons were developed using Definiens Professional (at the time of our use, this software was called eCognition), assisted by interpretation of 1:12,000 true-color digital orthophoto quarter quadrangles (DOQQs). These polygons (base map classes) were labeled using manual photo interpretation of the DOQQs and 1:12,000 true-color aerial photography. Field visits verified interpretation concepts. The vegetation map database includes 46 base map classes, which consist of associations, alliances, and park specials classified with quantitative analysis, additional associations and park specials noted during photointerpretation, and non-vegetated land cover, such as infrastructure, land use, and geological land cover. The base map classes consist of 5,007 polygons in the project area. A field-based accuracy assessment of the base map classes showed overall accuracy to be 43.5%. Seven map classes comprise 89.1% of the park vegetated land cover. The group map classes represent aggregations of the base map classes, approximating the group level of the National Vegetation Classification Standard, version 2 (Federal Geographic Data Committee 2007), and reflecting physiognomy and floristics. Terrestrial ecological systems, as described by NatureServe (Comer et al. 2003), were used as the fi rst approximation of the group level. The project team identified 14 group map classes for this project. The overall accuracy of the group map classes was determined using the same accuracy assessment data as for the base map classes. The overall accuracy of the group representation of vegetation was 80.3%. In consultation with park staff , the team developed management map classes, consisting of park-defined groupings of base map classes intended to represent a balance between maintaining required accuracy and providing a focus on vegetation of particular interest or import to park managers. The 23 management map classes had an overall accuracy of 73.3%. While the main products of this project are the vegetation classification and the vegetation map database, a number of ancillary digital geographic information system and database products were also produced that can be used independently or to augment the main products. These products include shapefiles of the locations of field-collected data and relational databases of field-collected data.

Mesa Verde National Park↗