Geology topics

Michael D. Fleming

Publications and source records attributed to Michael D. Fleming.

13 recordsLinked to original sources

USGS2025

Mapping eelgrass (Zostera marina) cover and biomass at Izembek Lagoon, Alaska, using in-situ field data and Sentinel-2 satellite imagery

The U.S. Geological Survey and the U.S. Fish and Wildlife Service have developed a three-tiered strategy for monitoring eelgrass ( Zostera marina ) beds at Izembek Lagoon, Alaska, that targets different spatial and temporal scales. The broadest-scale monitoring (tier-1) uses satellite imagery about every 5 years to delineate the spatial extent of eelgrass beds throughout the lagoon. This report describes the most recent (mid-2020s) tier-1 eelgrass monitoring at Izembek Lagoon. The monitoring effort began by canvasing all satellite imagery collected during summer, under clear daytime skies and at low-tide, since the last tier-1 effort in 2006. Two eelgrass maps of Izembek Lagoon were generated by first creating maps of spectrally unique classes from two Sentinel-2 satellite images collected on July 1, 2016, and August 14, 2020, then attributing those spectral classes with information about eelgrass conditions based on field data. Specifically, maps depicting various eelgrass metrics, such as percentage of cover and modeled biomass, were generated using summaries of the ground data that spatially intersected each spectral class. Comparisons of the 2016 and 2020 Sentinel-2 maps showing eelgrass distributional extent, as well as a 2006 Landsat map, indicated that areas where eelgrass presence may have declined during 2006–20 were most prevalent in the central part of Izembek Lagoon. More recently, during 2016-20, areas of possible biomass decline were more prevalent in the southern part of the lagoon. Monitoring eelgrass conditions at Izembek Lagoon with satellite imagery and concurrent ground data allows conditions to be compared over time, but the influences of tide levels, growing season phenology, and spatiotemporal co-registration accuracy should be considered when designing and interpreting change detection analyses.

Alaska↗

USGS2024

Mapping eelgrass cover and biomass at Izembek Lagoon, Alaska, using in-situ field data and Sentinel-2 satellite imagery

Two eelgrass ( Zostera marina ) maps of Izembek Lagoon, Alaska, were generated by first creating maps of spectrally unique classes from each of two Sentinel-2 satellite images collected on July 1, 2016, and August 14, 2020, then attributing the spectral classes with information about eelgrass conditions based on field data. Maps depicting various eelgrass metrics, such as percent cover and modeled biomass, were generated using summaries of the ground data that spatially intersected each spectral class. Comparisons between the 2016 and 2020 Sentinel-2 maps of eelgrass distributional extent, as well as a 2006 Landsat map, indicated that areas where eelgrass presence may have declined between 2006 and 2020 were most prevalent in the central part Izembek Lagoon, while areas of possible biomass decline were more prevalent in the southern part between 2016 and 2020. Monitoring eelgrass conditions at Izembek Lagoon with satellite imagery and concurrent ground data provides capabilities for making comparisons over time, but the influences of tide levels, growing season phenology, and spatiotemporal co-registration accuracy should be considered when designing and interpreting change detection analyses.

Alaska↗

USGS2023

Rapid population decline in McKay's Bunting, an Alaskan endemic, highlights the species’ current status relative to international standards for vulnerable species

The McKay’s Bunting ( Plectrophenax hyperboreus ) is endemic to Alaska, breeds solely on the remote and uninhabited St. Matthew and Hall islands (332 km 2 ) in the central Bering Sea, and is designated as a species of high conservation concern due to its small population size and restricted range. A previous hypothesized population estimate (~2,800—6,000 individuals) was greatly increased (~31,200 individuals) after systematic surveys of the species’ entire breeding range in 2003, establishing McKay’s Bunting as one of the rarest passerines in North America. In 2018, we replicated the 2003 surveys and used density surface models to estimate breeding season densities, distributions, and population change over the intervening time period. Our results indicate that the McKay's Bunting population declined by 38% (95% CI: 27—48%) from ~31,560 to 19,481 individuals since 2003. Spatial model predictions showed no areas with an increase of birds on either St. Matthew or Hall islands but revealed declines across 13% (42 km 2 ) of St. Matthew Island. Declines disproportionately occurred both in marginal habitats with reduced rocky nesting substrate and in high-density hotspots along the coast of St. Matthew Island. The total area occupied by breeding adults decreased by 8%, and high-density hotspots shifted inland from the coast of St. Matthew Island to higher elevations on both islands, the latter potentially responses to exceptionally warm weather and reduced spring snow cover in 2018. Additionally, we observed low numbers of predators and interspecific competitors in 2018 suggesting these did not cause the decline. Our findings indicate that McKay’s Bunting meets international standards for elevating its conservation status from Least Concern to Endangered based on the International Union for Conservation of Nature Red List of Threatened Species ranking criteria. Additional population monitoring and studies to identify the causal mechanisms of the recent population decline of this rare species could assist future population assessments.

Alaska↗

USGS2010

Comparing maps of mean monthly surface temperature and precipitation for Alaska and adjacent areas of Canada produced by two different methods

Maps of mean monthly surface temperature and precipitation for Alaska and adjacent areas of Canada, produced by Oregon State University's Spatial Climate Analysis Service (SCAS) and the Alaska Geospatial Data Clearinghouse (AGDC), were analyzed. Because both sets of maps are generally available and in use by the community, there is a need to document differences between the processes and input data sets used by the two groups to produce their respective set of maps and to identify similarities and differences between the two sets of maps and possible reasons for the differences. These differences do not affect the observed large-scale patterns of seasonal and annual variability. Alaska is divided into interior and coastal zones, with consistent but different variability, separated by a transition region. The transition region has high interannual variability but low long-term mean variability. Both data sets support the four major ecosystems and ecosystem transition zone identified in our earlier work. Differences between the two sets of maps do occur, however, on the regional scale; they reflect differences in physiographic domains and in the treatment of these domains by the two groups (AGDC, SCAS). These differences also provide guidance for an improved observational network for Alaska. On the basis of validation with independent in situ data, we conclude that the data set produced by SCAS provides the best spatial coverage of Alaskan long-term mean monthly surface temperature and precipitation currently available.

Alaska, British Columbia, Northwest Territories, Y↗

USGS2009

Characteristics of vegetation phenology over the Alaskan landscape using AVHRR time-series data

Advanced Very High Resolution Radiometer (AVHRR) satellite data were acquired and composited into twice-a-month periods from 1 May 1991 to 15 October 1991 in order to map vegetation characteristics of the Alaskan landscape. Unique spatial and temporal qualities of the AVHRR data provide information that leads to a better understanding of regional biophysical characteristics of vegetation communities and patterns. These data provided synoptic views of the landscape and depicted phenological diversity, temporal vegetation phenology (green-up, peak of green, and senescence), photosynthetic activity, and regional landscape patterns. Products generated from the data included a phenological class map, phenological composite maps (onset, peak, and duration), and photosynthetic activity maps (mean and maximum greenness). The time-series data provide opportunities to study phenological processes at small landscape scales over time periods of weeks, months, and years. Regional patterns identified on some of the maps are unique to specific areas; others correspond to biophysical or ecoregional boundaries. The data provide new insights to landscape processes, ecology, and landscape physiognomy that allow scientists to look at landscapes in ways that were previously difficult to achieve.

Alaska↗

USGS2005

The Circumpolar Arctic vegetation map

Question: What are the major vegetation units in the Arctic, what is their composition, and how are they distributed among major bioclimate subzones and countries? Location: The Arctic tundra region, north of the tree line. Methods: A photo-interpretive approach was used to delineate the vegetation onto an Advanced Very High Resolution Radiometer (AVHRR) base image. Mapping experts within nine Arctic regions prepared draft maps using geographic information technology (ArcInfo) of their portion of the Arctic, and these were later synthesized to make the final map. Area analysis of the map was done according to bioclimate subzones, and country. The integrated mapping procedures resulted in other maps of vegetation, topography, soils, landscapes, lake cover, substrate pH, and above-ground biomass. Results: The final map was published at 1:7 500 000 scale map. Within the Arctic (total area = 7.11 x 106 km 2), about 5.05 ?? 106 km2 is vegetated. The remainder is ice covered. The map legend generally portrays the zonal vegetation within each map polygon. About 26% of the vegetated area is erect shrublands, 18% peaty graminoid tundras, 13% mountain complexes, 12% barrens, 11% mineral graminoid tundras, 11% prostrate-shrub tundras, and 7% wetlands. Canada has by far the most terrain in the High Arctic mostly associated with abundant barren types and prostrate dwarf-shrub tundra, whereas Russia has the largest area in the Low Arctic, predominantly low-shrub tundra. Conclusions: The CAVM is the first vegetation map of an entire global biome at a comparable resolution. The consistent treatment of the vegetation across the circumpolar Arctic, abundant ancillary material, and digital database should promote the application to numerous land-use, and climate-change applications and will make updating the map relatively easy. ?? IAVS; Opulus Press.

Journal of Vegetation Science↗

USGS2002

Geographic patterns and dynamics of Alaskan climate interpolated from a sparse station record

Data from a sparse network of climate stations in Alaska were interpolated to provide 1-km resolution maps of mean monthly temperature and precipitation-variables that are required at high spatial resolution for input into regional models of ecological processes and resource management. The interpolation model is based on thin-plate smoothing splines, which uses the spatial data along with a digital elevation model to incorporate local topography. The model provides maps that are consistent with regional climatology and with patterns recognized by experienced weather forecasters. The broad patterns of Alaskan climate are well represented and include latitudinal and altitudinal trends in temperature and precipitation and gradients in continentality. Variations within these broad patterns reflect both the weakening and reduction in frequency of low-pressure centres in their eastward movement across southern Alaska during the summer, and the shift of the storm tracks into central and northern Alaska in late summer. Not surprisingly, apparent artifacts of the interpolated climate occur primarily in regions with few or no stations. The interpolation model did not accurately represent low-level winter temperature inversions that occur within large valleys and basins. Along with well-recognized climate patterns, the model captures local topographic effects that would not be depicted using standard interpolation techniques. This suggests that similar procedures could be used to generate high-resolution maps for other high-latitude regions with a sparse density of data.

Global Change Biology↗

USGS2002

Long-term climate patterns in Alaskan surface temperature and precipitation and their biological consequences

Mean monthly climate maps of Alaskan surface temperature and precipitation produced by the parameter-elevation regression on independent slopes model (PRISM) were analyzed. Alaska is divided into interior and coastal zones with consistent but different climatic variability separated by a transition region; it has maximum interannual variability but low long-term mean variability. Pacific decadal oscillation (PDO)- and El Nino Southern Oscillation (ENSO)-type events influence Alaska surface temperatures weakly (1-2/spl deg/C) statewide. PDO has a stronger influence than ENSO on precipitation but its influence is largely localized to coastal central Alaska. The strongest influence of Arctic oscillation (AO) occurs in northern and interior Alaskan precipitation. Four major ecosystems are defined. A major eco-transition zone occurs between the interior boreal forest and the coastal rainforest. Variability in insolation, surface temperature, precipitation, continentality, and seasonal changes in storm track direction explain the mapped ecosystems. Lack of westward expansion of the interior boreal forest into the western shrub tundra is influenced by the coastal marine boundary layer (enhanced cloud cover, reduced insolation, cooler surface and soil temperatures).

IEEE Transactions on Geoscience and Remote Sensing↗

USGS2001

El Niño and its impact on fire weather conditions in Alaska

Examining the relationship of El Niño to weather patterns in Alaska shows wide climate variances that depend on the teleconnection between the tropics and the northern latitudes. However, the weather patterns exhibited in Alaska during and just after moderate to strong El Niño episodes are generally consistent: above normal temperature and precipitation along the Alaskan coast, and above normal temperature and below normal precipitation in the interior, especially through the winter. The warm, dry conditions in the Alaskan interior increase summer wildfire potential. Statistics on the area burned since 1940 show that 15 out of 17 of the biggest fire years occurred during a moderate to strong El Niño episode. These 15 years account for nearly 63% of the total area burned over the last 58 years. Evidence points to increased dry thunderstorms and associated lightning activity during an El Niño episode; the percentage of total area burned by lightning caused fires during five episodes increased from a normal of less than 40% to a high of about 96%.

International Journal of Wildland Fire↗

USGS1997

Digital shaded-relief image of Alaska

One of the most spectacular physiographic images of the conterminous United States, and the first to have been produced digitally, is that by Thelin and Pike ( USGS I-2206, 1991 ). The image is remarkable for its crispness of detail and for the natural appearance of the artificial land surface. Our goal has been to produce a shaded-relief image of Alaska that has the same look and feel as the Thelin and Pike image. The Alaskan image could have been produced at the same scale as its lower 48 counterpart (1:3,500,000). But by insetting the Aleutian Islands into the Gulf of Alaska, we were able to print the Alaska map at a larger scale (1:2,500,000) and about the same physical size as the Thelin and Pike image. Benefits of the 1:2,500,000 scale are (1) greater resolution of topographic features and (2) ease of reference to the U.S. Geological Survey (USGS) (1987) Alaska Map E and the statewide geologic map (Beikman, 1980), which are both 1:2,500,000 scale. Manually drawn, shaded-relief images of Alaska's land surface have long been available (for example, Department of the Interior, 1909; Raisz, 1948). The topography depicted on these early maps is mainly schematic. Maps showing topographic contours were first available for the entire State in 1953 (USGS, 1:250,000) (J.H. Wittmann, USGS, written commun., 1996). The Alaska Map E was initially released in 1954 in both planimetric (revised in 1973 and 1987) and shaded-relief versions (revised in 1973, 1987, and 1996); topography depicted on the shaded-relief version is based on the 1:250,000-scale USGS topographic maps. Alaska Map E was later modified to include hypsometric tinting by Raven Maps and Images (1989, revised 1993) as copyrighted versions. Other shaded-relief images were produced for The National Geographic Magazine (LaGorce, 1956; 1:3,000,000) or drawn by Harrison (1970; 1:7,500,000) for The National Atlas of the United States. Recently, the State of Alaska digitally produced a shaded-relief image of Alaska at 1:2,500,000 scale (Alaska Department of Natural Resources, 1994), using the 1,000-m digital elevation data set referred to below. An important difference between our image and these previous ones is the method of reproduction: like the Thelin and Pike (1991) image, our image is a composite of halftone images that yields sharp resolution and preserves contrast. Indeed, the first impression of many viewers is that the Alaskan image and the Thelin and Pike image are composites of satellite-generated photographs rather than an artificial rendering of a digital elevation model. A shaded-relief image represents landforms in a natural fashion; that is, a viewer perceives the image as a rendering of reality. Thus a shaded-relief image is intrinsically appealing, especially in areas of spectacular relief. In addition, even subtle physiographic features that reflect geologic structures or the type of bedrock are visible. To our knowledge, some of these Alaskan features have not been depicted before and so the image should provide earth scientists with a new "look" at fundamental geologic features of Alaska.

Alaska↗

USGS1993

"Relative CIR": an image enhancement and visualization technique

Many techniques exist to spectrally and spatially enhance digital multispectral scanner data. One technique enhances an image while keeping the colors as they would appear in a color-infrared (CIR) image. This "relative CIR" technique generates an image that is both spectrally and spatially enhanced, while displaying a maximum range of colors. The technique enables an interpreter to visualize either spectral or land cover classes by their relative CIR characteristics. A relative CIR image is generated by developed spectral statistics for each class in the classifications and then, using a nonparametric approach for spectral enhancement, the means of the classes for each band are ranked. A 3 by 3 pixel smoothing filter is applied to the classification for spatial enhancement and the classes are mapped to the representative rank for each band. Practical applications of the technique include displaying an image classification product as a CIR image that was not derived directly from a spectral image, visualizing how a land cover classification would look as a CIR image, and displaying a spectral classification or intermediate product that will be used to label spectral classes.

Pecora 12 Symposium↗

USGS1988

An integrated approach for automated cover-type mapping of large inaccessible areas in Alaska

The lack of any detailed cover type maps in the state necessitated that a rapid and accurate approach to be employed to develop maps for 329 million acres of Alaska within a seven-year period. This goal has been addressed by using an integrated approach to computer-aided analysis which combines efficient use of field data with the only consistent statewide spatial data sets available: Landsat multispectral scanner data, digital elevation data derived from 1:250 000-scale maps, and 1:60 000-scale color-infrared aerial photographs.

Alaska↗

USGS1986

Repetitive digital NOAA-AVHRR data for Alaskan engineering and scientific applications

Selected digitally enhanced NOAA - Advanced Very High Resolution Radiometer (AVHRR) images taken by the NOAA 6, 7, 8 and 9 Polar Orbiting Satellites demonstrate the capability and application of repetitive low-resolution satellite data to Alaska's engineering and science community. Selected cloud-free visible and thermal infrared images are enhanced to depict distinct oceanographic and geologic processes along Alaska's west coast and adjacent seas. Included are the advance of the Bering Sea ice field, transport of Yukon River sediment into Norton Sound, and monitoring of plume trajectories from the Mount Augustine volcanic eruptions. Presented illustrations are representative of the 94 scenes in a cooperative USGS EROS/NOAA Alaskan AVHRR Digital Archive. This paper will discuss the cooperative efforts in establishing the first year data set and identifying Alaskan applications.

Alaska↗