The Vehicle, Fall 1970

Vol. 13, No. 1 Table of Contents A Thought Written in a Locked RoomJudy Huntpage 1 The Eggshell MoonWilliam Probeckpage 2 PoemBarb Parkerpage 3 4/5, May, 1970J. Michael Sainpage 5 A TreeRichard Stickannpage 6 both or noneMichelle Hallpage 6 The TrainSteve Sestinapage 8 Attempted DiscoveryDonald R. Johnsonpage 16 Island of SmokeVerna L. Jonespage 18 AwakeRobert Bladepage 19 PoemMary Klinkerpage 19 In ChurchMuriel Poolpage 21 PoemBarb Parkerpage 21 PoemMichelle Hallpage 22 Pod\u27nerVerna L. Jonespage 23 Rain and Other ThingsCarol Staniecpage 24 PoemAnn Graffpage 24 Examination of StudentdomMelvin Zaloudekpage 26 Women\u27s LiberationTonya Mortonpage 27 Morning Reflections on the Evening NewsPrudence Herberpage 29 Art and Photography Credits Jim Diaspage 4 Mike Dorseypages 7, 20 David Griffithpages 8, 17, 25 Cover PhotographyMark McKinneyhttps://thekeep.eiu.edu/vehicle/1024/thumbnail.jp

Assessing the utility of geospatial technologies to investigate environmental change within lake systems

Over 50% of the world's population live within 3. km of rivers and lakes highlighting the on-going importance of freshwater resources to human health and societal well-being. Whilst covering c. 3.5% of the Earth's non-glaciated land mass, trends in the environmental quality of the world's standing waters (natural lakes and reservoirs) are poorly understood, at least in comparison with rivers, and so evaluation of their current condition and sensitivity to change are global priorities. Here it is argued that a geospatial approach harnessing existing global datasets, along with new generation remote sensing products, offers the basis to characterise trajectories of change in lake properties e.g., water quality, physical structure, hydrological regime and ecological behaviour. This approach furthermore provides the evidence base to understand the relative importance of climatic forcing and/or changing catchment processes, e.g. land cover and soil moisture data, which coupled with climate data provide the basis to model regional water balance and runoff estimates over time. Using examples derived primarily from the Danube Basin but also other parts of the World, we demonstrate the power of the approach and its utility to assess the sensitivity of lake systems to environmental change, and hence better manage these key resources in the future

An Enhanced Algorithm for Automatic Radiometric Harmonization of High-Resolution Optical Satellite Imagery Using Pseudoinvariant Features and Linear Regression

The growing number of available optical remote sensing data providing large spatial and temporal coverage enables the coherent and gapless observation of the earth’s surface on the scale of whole countries or continents. To produce datasets of that size, individual satellite scenes have to be stitched together forming so-called mosaics. Here the problem arises that the different images feature varying radiometric properties depending on the momentary acquisition conditions. The interpretation of optical remote sensing data is to a great extent based on the analysis of the spectral composition of an observed surface reflection. Therefore the normalization of all images included in a large image mosaic is necessary to ensure consistent results concerning the application of procedures to the whole dataset. In this work an algorithm is described which enables the automated spectral harmonization of satellite images to a reference scene. As the stable and satisfying functionality of the proposed algorithm was already put to operational use to process a high number of SPOT-4/-5, IRS LISS-III and Landsat-5 scenes in the frame of the European Environment Agency's Copernicus/GMES Initial Operations (GIO) High-Resolution Layer (HRL) mapping of the HRL Forest for 20 Western, Central and (South)Eastern European countries, it is further evaluated on its reliability concerning the application to newer Sentinel-2 multispectral imaging products. The results show that the algorithm is comparably efficient for the processing of satellite image data from sources other than the sensor configurations it was originally designed for

Europe’s Green Arteries—A Continental Dataset of Riparian Zones

Riparian zones represent ecotones between terrestrial and aquatic ecosystems and are of utmost importance to biodiversity and ecosystem functions. Modelling/mapping of these valuable and fragile areas is needed for improved ecosystem management, based on an accounting of changes and on monitoring of their functioning over time. In Europe, the main legislative driver behind this goal is the European Commission’s Biodiversity Strategy to 2020, on the one hand aiming at halting biodiversity loss, on the other hand enhancing ecosystem services by 2020, and restoring them as far as is feasible. A model, based on Earth Observation data, including Digital Elevation Models, hydrological, soil, land cover/land use data, and vegetation indices is employed in a multi-modular and stratified approach, based on fuzzy logic and object based image analysis, to delineate potential, observed and actual riparian zones. The approach is designed in an open modular way, allowing future modifications and repeatability. The results represent a first step of a future monitoring and assessment campaign for European riparian zones and their implications on biodiversity and on ecosystem functions and services. Considering the complexity and the enormous extent of the area, covering 39 European countries, including Turkey, the level of detail is unprecedented. Depending on the accounting modus, 0.95%–1.19% of the study area can be attributed as actual riparian area (considering Strahler’s stream orders 3–8, based on the Copernicus EU-Hydro dataset), corresponding to 55,558–69,128 km2. Similarly, depending on the accounting approach, the potential riparian zones cover an area about 3–5 times larger. Land cover/land use in detected riparian areas was mainly of semi-natural characteristics, while the potential riparian areas are predominately covered by agriculture, followed by semi-natural and urban areas