David W. Leverington

Glacial Lake Agassiz: A 5000 yr history of change and its relationship to the δ18O record of Greenland

Lake Agassiz was the largest lake in North America during the last period of deglaciation; the lake extended over a total of 1.5 × 10 6 km 2 before it drained at ca. 7.7 14 C ka (8.4 cal. [calendar] ka). New computer reconstructions—controlled by beaches, isostatic rebound data, the margin of the Laurentide Ice Sheet, outlet elevations, and a digital elevation model (DEM) of modern topographic data—show how variable the size and depth of this lake were during its 4000 14 C yr (5000 cal. yr) history. Abrupt reductions in lake level, ranging from 8 to 110 m, occurred on at least 18 occasions when new outlets were opened, reducing the extent of the lake and sending large outbursts of water to the oceans. Three of the largest outbursts correlate closely in time with the start of large δ 18 O excursions in the isotopic records of the Greenland ice cap, suggesting that those freshwaters may have had an impact on thermohaline circulation and, in turn, on climate.

Changes in the Bathymetry and Volume of Glacial Lake Agassiz Between 11,000 and 9300 14C yr B.P.

Computer reconstructions of the bathymetry of the lake were used to quantify variations in the size and form of Lake Agassiz during its final two phases (the Nipigon and Ojibway phases), between about 9200 and 7700 14C yr B.P. (ca. 10,300–8400 cal yr B.P.). New bathymetric models for four Nipigon Phase stages (corresponding to the McCauleyville, Hillsboro, Burnside, and The Pas strandlines) indicate that Lake Agassiz ranged between about 19,200 and 4600 km3 in volume and 254,000 and 151,000 km2 in areal extent at those times. A bathymetric model of the last (Ponton) stage of the lake, corresponding to the period in which Lake Agassiz was combined with glacial Lake Ojbway to the east, shows that Lake Agassiz– Ojibway was about 163,000 km3 in volume and 841,000 km2 in areal extent prior to the final release of lake waters into the Tyrrell Sea. During the Nipigon Phase, a number of catastrophic releases of water from Lake Agassiz occurred as more northerly (lower) outlets were made available by the retreating southern margin of the Laurentide Ice Sheet; we estimate that each of the four newly investigated Nipigon Phase releases involved water volumes of between 1600 and 2300 km3. The final release of Lake Agassiz waters into the Tyrrell Sea at about 7700 14C yr B.P. is estimated to have been about 163,000 km3 in volume. C

A GIS method for reconstruction of late quaternary landscapes from isobase data and modern topography

Digital reconstructions of late Quaternary landscapes can be produced using a geographic information system (GIS) method that subtracts interpolated isobase values from modern elevations and bathymetry. The principal utility of the GIS method for reconstructing late Quaternary landscapes is in the relative ease and rapidity with which high-resolution, quantitative, and georeferenced databases of paleo-topography can be generated. These databases can be used for many purposes, including the generation of paleo-topographic maps, the estimation of the areas and volumes of individual water bodies and landforms, and the approximation of paleo-shoreline positions. GIS-based estimates of the dimensions of water bodies and landforms can be used to help constrain hydrological and climatic models of the late Quaternary.

An igneous origin for features of a candidate crater-lake system in western Memnonia, Mars

The association of channels, inner terraces, and delta-like features with Martian impact craters has previously been interpreted as evidence in favor of the past existence of crater lakes on Mars. However, examination of a candidate crater-lake system in western Memnonia suggests instead that its features may have formed through igneous processes involving the flow and ponding of lava. Accumulations of material in craters and other topographic lows throughout much of the study region have characteristics consistent with those of volcanic deposits, and terraces found along the inner flanks of some of these craters are interpreted as having formed through drainage or subsidence of volcanic materials. Channels previously identified as inlets and outlets of the crater-lake system are interpreted instead as volcanic rilles. These results challenge previous interpretations of terrace and channel features in the study region and suggest that candidate crater lakes located elsewhere should be reexamined.

Discrimination of sedimentary lithologies using Hyperion and Landsat Thematic Mapper data: a case study at Melville Island, Canadian High Arctic

The use of remote-sensing techniques in the discrimination of rock and soil classes in northern regions can support a diverse range of activities, such as environmental characterization, mineral exploration and the study of Quaternary paleoenvironments. Although images with low spectral resolution can commonly be used in the mapping of classes possessing distinct spectral properties, hyperspectral images offer greater potential for discrimination of materials characterized by more subtle reflectance properties. In an effort to better constrain the utility of broadband and hyperspectral datasets in high-latitude research, this study investigated the effectiveness of Landsat Thematic Mapper (TM) and EO-1 Hyperion data for discrimination of lithological classes at eastern Melville Island, Nunavut, Canada. TM data were classified using a standard neural-network algorithm, and both TM and Hyperion data were linearly unmixed using ground-truth spectra. TM classification results successfully discriminate between classes over much of the study area, although with incomplete separation between clastic and carbonate materials. TM unmixing results are poor, with useful class separation restricted to vegetation and red-weathered sandstone classes. Hyperion results effectively depict the fractional cover of end members, although the abundance images of several classes contain background abundance values that overestimate surface exposure in some areas. For the study area and surface classes involved, noisy hyperspectral data were found to be of greater utility than higher-fidelity broadband multispectral data in the generation of fractional abundance images for an inclusive set of surface-cover classes.

Satellite Remote Sensing of Permafrost and Seasonally Frozen Ground

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Landsat-TM-Based Discrimination of Lithological Units Associated with the Purtuniq Ophiolite, Quebec, Canada

In order to better constrain the utility of multispectral datasets in the characterization of surface materials, Landsat Thematic Mapper (TM) data were evaluated in the discrimination of geological classes in the Cape Smith Belt of Quebec, a greenstone belt that hosts Early Proterozoic units including those of the Purtuniq ophiolite. Ground-based measurements collected for the study area highlight the importance of chemical alteration in controlling the reflectance properties of key geological classes. The spatial distribution of exposed lithologies in the study area was determined through (1) image classification using a feedforward backpropagation neural network classifier; and (2) generation of fraction images for spectral end members using a linear unmixing algorithm and ground reflectance data. Despite some shortcomings, the database of surface cover generated by the neural network classifier is a useful representation of the spatial distribution of exposed geological materials in the study area, with an overall agreement with ground truth of 87.7%. In contrast, the fraction images generated through unmixing are poor representations of ground truth for several key lithological classes. These results underscore both the considerable utility and marked limitations of Landsat TM data in the mapping of igneous and metamorphic lithologies.

The volume and paleobathymetry of glacial Lake Agassiz

During the last retreat of the Laurentide Ice Sheet in North America, many proglacial lakes formed as continental drainage was impounded against the southern and western ice margin. Lake Agassiz was the largest of these lakes. The bathymetry of Lake Agassiz at the Herman and Upper Campbell beach levels – formed at about 11.5–11.0 ka and 9.9–9.5 ka, respectively – was computer modelled in this study by first collecting data for the isostatically-deformed paleowater planes of the two lake levels (derived from isobase lines constructed from beach elevations), and then subtracting these from the modern topography of the former lake floor. Pixels with dimensions of 1/30 × 1/30 of a degree were used in the model. Using these data, the area and volume of the lake were also calculated: at the Herman level these were ∼152 500 km2 and ∼13 100 km3 respectively; at the Upper Campbell level these were ∼350 400 km2 and ∼38 700 km3. Contour maps showing the paleobathymetry of both periods in the lakes history were also constructed. Determining the paleobathymetry and volume of Lake Agassiz is an important step in understanding the impact that the lake had on its surrounding environment and on the rivers, lakes, and oceans into which it flowed.

Discrimination of Geological End Members Using Hyperion Imagery: Preliminary Results, Big Bend National Park, Texas

Hyperion hyperspectral data are being tested as a means for generating databases of surface cover at Big Bend National Park, Texas. Preliminary unmixing results indicate a capacity for discrimination of general geological classes, but separation of several sedimentary end members has proven difficult due to shared weathering characteristics. Of special interest in this study is the utility of hyperspectral data in the mapping of fractional lithological compositions of widespread alluvial deposits.

On the use of consensus algorithms to address variability in the results of neural network classifications: preliminary tests involving two northern study areas

In past work it has been recognized that variations in parameters such as learning rate, momentum, and network architecture can influence the results in neural network classifications of satellite images. New tests suggest that variation in the results of neural network classifications, caused solely by differences in weight initializations, can also be substantial. This issue has the potential to limit the applicability of neural networks in remote sensing classifications. The negative effects of variation in neural network results can potentially be reduced or eliminated through application of consensus algorithms in which the outputs of multiple neural network classifications are combined. Research results presented here were based on training and test data with low sample sizes for many classes and, accordingly, the results must be interpreted with caution. Early results using majority-vote and evidential-reasoning consensus algorithms, however, suggest that near-optimum neural network classification accuracies can be achieved through application of these algorithms.