The largest ice shelf in Antarctic, Ross Ice Shelf, was investigated over the years of 1988–2014. Near the basal stress boundary between the ice shelf and the West Antarctic ice sheet, ice velocity ranges from a few meters per year to several hundred meters per year in ice streams. Ice velocity increases as the ice moves seaward, reaching more than 1 km yr−1 in the central portions of the ice front. Most of the drainage from West Antarctica into the Ross Ice Shelf flows down two major ice streams, each of which discharges more than 20 km3 of ice each year.

A hydrophyte of high relevance, submerged aquatic vegetation (SAV) is of great importance to estuarine environments. SAV helps improve water quality, provides food and shelter for waterfowl, fish, and shellfish, as well as protects shorelines from erosion. In coastal bays most SAV was eliminated by disease in the 1930's. In the late 1960's and 1970's a dramatic decline of all SAV species was correlated with increasing nutrient and sediment inputs from development of surrounding watersheds (MDNP et. al 2004). Currently state programs work to protect and restore existing wetlands, however, increasing development and population pressure continue to degrade and destroy both tidal and non-tidal wetlands and hinder overall development of SAV growth. The focus of this research was to utilize spatial referencing software in the mapping of healthy submerged aquatic vegetation (SAV) habitats. In cooperation with the United States Fish and Wildlife Service (USFWS), and the National Oceanic and Atmospheric Administration (NOAA), students from Elizabeth City State University (ECSU) developed and applied Geographic Information Systems (GIS) skills to evaluate the distribution and abundance of SAV in North Carolina's estuarine environments. Utilizing ESRI ArcView, which includes ArcMap, ArcCatalog and ArcToolbox, and the applications of on-screen digitizing, an assessment of vegetation cover was made through the delineation of observable SAV beds in Core Sound, North Carolina. Aerial photography of the identified coastal water bodies was taken at 12,000 feet above mean terrain (AMT) scale 1:24,000. The georeferenced aerial photographs were assessed for obscurities and the SAV beds were digitized. Through the adoption of NOAA guidelines and criteria for benthic habitat mapping using aerial photography for image acquisition and analysis, students delineated SAV beds and developed a GIS spatial database relevant to desired results. This newly created database yielded products in the form of usable shapefiles of SAV polygonsι as well as attribute information with location information, area in hectares, and percent coverage of SAV.

This work focuses on automating the task of estimating Polar ice thickness from airborne radar data acquired over Greenland and Antarctica. This process involves the identification and accurate selection of the ice sheet's surface location and interface between the ice sheet and the underlying bedrock for each measurement. Identifying the surface and bedrock locations in the radar imagery enables the computation of ice sheet thickness, which is important for the study of ice sheets, their volume, and how they may contribute to global climate change. The time-consuming manual approach requires sparse hand-selection of surface and bedrock interfaces by several human experts, and interpolating between the selections to save time.

This paper focuses on automating the task of estimating Polar ice thickness from airborne radar data acquired over Greenland and Antarctica. This process involves the identification and accurate selection of the ice sheet's surface location and interface between the ice sheet and the underlying bedrock for each measurement. Identifying the surface and bedrock locations in the radar imagery enables the computation of ice sheet thickness, which is important for the study of ice sheets, their volume, and how they may contribute to global climate change. The time-consuming manual approach requires sparse hand-selection of surface and bedrock interfaces by several human experts, and interpolating between the selections to save time. Two primary methods have been studied in this paper, namely, edge-based and active contour. Results are evaluated and presented using the metrics of time requirements and accuracy. Automated ice thickness estimation results from 2006 and 2007 Greenland field campaigns illustrate that the edge-based approach offers faster processing (seconds compared to minutes), but suffers from a lack of continuity and smoothness aspects that active contours provide. The active contour approach is more accurate when compared to ground truth selections provided by human experts, and has proven to be more robust to image artifacts. It is shown that both techniques offer advantages which could be integrated to yield a more effective system.