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Due to its nearly 1.5 million ha extension and the aimed fine mapping resolution, classical vegetation mapping was not suitable method to prepare the habitat map of Duna-Tisza köze region (Hungary). We developed a novel mapping method. By this method the actual status of more than 12,000 patches of semi-natural vegetation was recorded, documented previously as grasslands, wetlands, open forests and grasslands with scattered trees and shrubs in the middle of the 1980s. A digital layer of 272,387 ha at 1 : 25,000 resolution was created as the background of the analysis. Vegetation type was classified at 46,930 points in the mapping area. The collaboration of 59 colleagues resulted in the development of the digital geographical database of the study area (D-TMap GIS Point database). One-third of the data relies on field data, while the other two-thirds on satellite interpretation. Landscape pattern and the accuracy of the statistical data of the habitats, generated from the point database, are improved by the polygonised version of the point database (D-TMap GIS Polygon database). In this paper we show how the GIS Point database was generated, and summarise the ecological content, availability, and limitation of the derived point and polygon based actual habitat maps. Analysis of the database and the landscape scale pattern of the habitats are discussed in a further paper.
Abstract
Patterns of migration among disciplines and specialties are examined using data from a large survey of U. S. Ph. D. s in a broad range of fields. Mappings of scholarly fields are derived from the migration patterns and these mappings are largely consistent with results from previous studies using citation flows and other measures of field similarities. Migration patterns suggest that there are two boundaries dividing the fields in this analysis, and that hierarchical relations among disciplines are weak or absent. In contrast, specialties within a discipline are more likely to exhibit structural hierarchies.
The role of remote sensing is well known and can be successfully applied as an initial step in surface geologic exploration. The aim of this study, by means of Landsat TM 7 image interpretation, is to assist photogeologic map compiling, which will serve as a core document for an upcoming field mapping exercise. The mathematical background and the wide variety of math-method possibilities offered by a satellite image interpretation software were used for this purpose. In this way the requested preliminary photogeologic map was compiled, based on the spectral properties of the surface geologic formations. Fortunately the areas of interest were in a desert area (Central Libya), so there was no limitation by vegetation coverage to hinder the application of spectral properties to geologic formations. After the geocoding of the images the display of different compositions of the Landsat TM 7 registration channels was begun. Contrast enhancement and histogram fitting were applied, and further operations to highlight some hidden properties of the original dataset were performed. Thus, some filters from the set offered by the software, some edge enhancement and finally the two types of classification (unsupervised and supervised), were applied.
