Pittsburgh -- Atlantic

Shows also part of Delaware.

Pittsburgh -- Atlantic

Shows also part of Delaware.

Memoirs, maps, &c., issued by the Geological Survey of the United Kingdom and the Museum of Practical Geology.

At head of title: List F.

Map of New Jersey and Pennsylvania exhibiting the post offices, post roads, canals, rail roads, &c.

Scale ca. 1:650,000.

The spatial analysis and speciation of uranium and thorium series radionuclides in the soil of the Cronamuck Valley, County Donegal, Ireland

This thesis details the findings of a study into the spatial distribution and speciation of 238U, 226Ra and 228Ra in the soils of the Cronamuck valley, County Donegal . The region lies on the north-eastern edge of the Barnesmore granite and has been the subject of uranium prospecting efforts in the past. The results of the project provide information on the practicability of geostatistical techniques as a means of estimating the spatial distribution of natural radionuclides and provide insight into the behaviour of these nuclides and their modes of occurrence and enrichment in an upland bog environment. The results of the geostatistical survey conducted on the area indicate that the primary control over the levels of the studied nuclides in the soil of the valley is the underlying geology. Isopleth maps of nuclide levels in the valley indicate a predominance of elevated nuclide levels in the samples drawn from the granite region, statistical analysis of the data indicating that levels of the nuclides in samples drawn from the granite are greater than levels drawn from the non-granite region by up to a factor of 4.6 for 238U and 4.9 for 226Ra. Redistribution of the nuclides occurs via drainage systems within the valley, this process being responsible for transport of nuclides away from the granite region resulting in enrichment of nuclides in soils not underlain by the granite. Distribution of the nuclides within the valley is erratic, the effect of drainage f lows on the nuclides resulting in localized enriched areas within the valley. Speciation of the nuclides within one of the enriched areas encountered in the study indicates that enrichment is as a result of saturation of the soil with drainage water containing trace amounts of radionuclides. 238U is primarily held within the labile fractions (exchangeable cat ions + easily oxidisable organics + amorphous iron oxides ) of the soil , 226Ra being associated with the non- labile fractions, most probably the resistant organic material. 228Ra displays a significant occurrence in both the labile and non- labile fractions. The ability of the soil to retain uranium appears to be affected largely by the redox status of the soil, samples drawn from oxidizing environments tending to have little or no uranium in the easily oxidisable and amorphous iron oxide fractions. This loss of uranium from oxidised soil samples is responsible for the elevated 226Ra /238U disequilibrium encountered in the enriched areas of the valley. Analysis of the data indicates that samples displaying elevated 226Ra/238U ratios also exhibit elevated 228Ra/238U ratios indicating a loss of uranium from the samples as opposed to an enrichment of 226Ra.

Mexico

[drawn by Erwin Raisz].

England

[drawn by Erwin Raisz].

From Lubeck to Milan

[drawn by Erwin Raisz].

From Black Sea thru Turkey to Cyprus

[drawn by Erwin] Raisz.

Australia

Shows cities, geology and topography, agricultural products and mineral resources.

Santiago -- Buenos Aires

[drawn by Erwin Raisz].

China N-S

[drawn by Erwin Raisz].

Geologic and water-supply reports and maps : Pennsylvania-New Jersey.

Mode of access: Internet.

Disaggregation of polygons of surficial geology and soil maps using spatial modelling and legacy data

Examples from the Murray-Darling basin in Australia are used to illustrate different methods of disaggregation of reconnaissance-scale maps. One approach for disaggregation revolves around the de-convolution of the soil-landscape paradigm elaborated during a soil survey. The descriptions of soil ma units and block diagrams in a soil survey report detail soil-landscape relationships or soil toposequences that can be used to disaggregate map units into component landscape elements. Toposequences can be visualised on a computer by combining soil maps with digital elevation data. Expert knowledge or statistics can be used to implement the disaggregation. Use of a restructuring element and k-means clustering are illustrated. Another approach to disaggregation uses training areas to develop rules to extrapolate detailed mapping into other, larger areas where detailed mapping is unavailable. A two-level decision tree example is presented. At one level, the decision tree method is used to capture mapping rules from the training area; at another level, it is used to define the domain over which those rules can be extrapolated. (C) 2001 Elsevier Science B.V. All rights reserved.

Comparison between detailed digital and conventional soil maps of an area with complex geology

Since different pedologists will draw different soil maps of a same area, it is important to compare the differences between mapping by specialists and mapping techniques, as for example currently intensively discussed Digital Soil Mapping. Four detailed soil maps (scale 1:10.000) of a 182-ha sugarcane farm in the county of Rafard, São Paulo State, Brazil, were compared. The area has a large variation of soil formation factors. The maps were drawn independently by four soil scientists and compared with a fifth map obtained by a digital soil mapping technique. All pedologists were given the same set of information. As many field expeditions and soil pits as required by each surveyor were provided to define the mapping units (MUs). For the Digital Soil Map (DSM), spectral data were extracted from Landsat 5 Thematic Mapper (TM) imagery as well as six terrain attributes from the topographic map of the area. These data were summarized by principal component analysis to generate the map designs of groups through Fuzzy K-means clustering. Field observations were made to identify the soils in the MUs and classify them according to the Brazilian Soil Classification System (BSCS). To compare the conventional and digital (DSM) soil maps, they were crossed pairwise to generate confusion matrices that were mapped. The categorical analysis at each classification level of the BSCS showed that the agreement between the maps decreased towards the lower levels of classification and the great influence of the surveyor on both the mapping and definition of MUs in the soil map. The average correspondence between the conventional and DSM maps was similar. Therefore, the method used to obtain the DSM yielded similar results to those obtained by the conventional technique, while providing additional information about the landscape of each soil, useful for applications in future surveys of similar areas.