Spatially resolved spectroscopy of the E+A galaxies in the z= 0.32 cluster AC 114

We present spatially resolved intermediate-resolution spectroscopy of a sample of 12 E+A galaxies in the   z = 0.32  rich galaxy cluster AC 114, obtained with the FLAMES multi-integral field unit system on the Very Large Telescope (VLT) of the European Southern Observatory. Previous integrated spectroscopy of all these galaxies by Couch & Sharples had shown them to have strong Balmer line absorption and an absence of [O  ii ]λ3727 emission – the defining characteristics of the 'E+A' spectral signature, indicative of an abrupt halt to a recent episode of quite vigorous star formation. We have used our spectral data to determine the radial variation in the strength of Hδ absorption in these galaxies and hence map out the distribution of this recently formed stellar population. Such information provides important clues as to what physical event might have been responsible for this quite dramatic change in star formation activity in the recent past of these galaxies. We find a diversity of behaviour amongst these galaxies in terms of the radial variation in Hδ absorption: four galaxies show little Hδ absorption across their entire extent; it would appear they were misidentified as E+A galaxies in the earlier integrated spectroscopic studies. The remainder show strong Hδ absorption, with a gradient that is either negative (Hδ equivalent width decreasing with radius), flat or positive . By comparison with numerical simulations we suggest that the first of these different types of radial behaviour provides evidence for a merger/interaction origin, whereas the latter two types of behaviour are more consistent with the truncation of star formation in normal disc galaxies with the Hδ gradient becoming increasingly positive with time after truncation. It would seem therefore that more than one physical mechanism is responsible for E+A formation in the same environment.     

Trace-element composition and zoning in clinopyroxene- and amphibole-group minerals: Implications for element partitioning and evolution of carbonatites

The present work is a first comprehensive study of the trace-element composition and zoning in clinopyroxene- and amphibole-group minerals from carbonatites, incorporating samples from 14 localities worldwide (Afrikanda, Aley, Alnö, Blue River, Eden Lake, Huayangchuan, Murun, Oka, Ozernaya Varaka, Ozernyi, Paint Lake, Pinghe, Prairie Lake, Turiy Mys). The new electron-microprobe data presented here significantly extend the known compositional range of clinopyroxenes and amphiboles from carbonatites. These data confirm that calcic and sodic clinopyroxenes from carbonatites are not separated by a compositional gap, instead forming an arcuate trend from nearly pure diopside through intermediate aegirine–augite compositions confined to a limited range of CaFeSi₂O₆ contents (15–45 mol%) to aegirine with < 25 mol% of CaMgSi₂O₆ and a negligible proportion of CaFeSi₂O₆. A large set of LA-ICPMS data shows that the clinopyroxenes of different composition are characterized by relatively low levels of Cr, Co and Ni (≤ 40 ppm) and manifold variations in the concentration of trivalent lithophile and some incompatible elements (1–150 ppm Sc, 26–6870 ppm V, 5–550 ppm Sr, 90–2360 ppm Zr, and nil to 150 ppm REE), recorded in some cases within a single crystal. The relative contribution of clinopyroxenes to the whole-rock Rb, Nb, Ta, Th and U budget is negligible. The major-element compositional range of amphiboles spans from alkali- and Al-poor members (tremolite) to Na–Al-rich Mg- or, less commonly, Fe-dominant members (magnesiohastingsite, hastingsite and pargasite), to calcic–sodic, sodic and potassic–sodic compositions intermediate between magnesio-ferrikatophorite, richterite, magnesioriebeckite, ferri-nyböite and (potassic-)magnesio-arfvedsonite. In comparison with the clinopyroxenes, the amphiboles contain similar levels of tetravalent high-field-strength elements (Ti, Zr and Hf) and compatible transition elements (Cr, Co and Ni), but are capable of incorporating much higher concentrations of Sc and incompatible elements (up to 500 ppm Sc, 43 ppm Rb, 1470 ppm Sr, 1230 ppm Ba, 80 ppm Pb, 1070 ppm REE, 140 ppm Y, and 180 ppm Nb). In some carbonatites, amphiboles contribute as much as 25% of the Zr + Hf, 15% of the Sr and 35% of the Rb + Ba whole-rock budget. Both clinopyroxenes and amphiboles may also host a significant share (~ 10%) of the bulk heavy-REE content. Our trace-element data show that the partitioning of REE between clinopyroxene (and, in some samples, amphibole) and the melt is clearly bimodal and requires a revision of the existing models assuming single-site REE partitioning. Clinopyroxenes and amphiboles from carbonatites exhibit a diversity of zoning patterns that cannot be explained exclusively on the basis of crystal chemistry and relative compatibility of different trace-element in these minerals. Paragenetic analysis indicates that in most cases, the observed zoning patterns develop in response to removal of selected trace elements by phases co-precipitating with clinopyroxene and amphibole (especially magnetite, fluorapatite, phlogopite and pyrochlore). With the exception of magnesiohastingsite–richterite sample from Afrikanda, the invariability of trace-element ratios in the majority of zoned clinopyroxene and amphibole crystals implies that fluids are not involved in the development of zoning in these minerals. The implications of the new trace-element data for mineral exploration targeting REE, Nb and other types of carbonatite-hosted rare-metal mineralization are discussed.     

Exploring uncertainty in remotely sensed data with parallel coordinate plots

The existence of uncertainty in classified remotely sensed data necessitates the application of enhanced techniques for identifying and visualizing the various degrees of uncertainty. This paper, therefore, applies the multidimensional graphical data analysis technique of parallel coordinate plots (PCP) to visualize the uncertainty in Landsat Thematic Mapper (TM) data classified by the Maximum Likelihood Classifier (MLC) and Fuzzy C-Means (FCM). The Landsat TM data are from the Yellow River Delta, Shandong Province, China. Image classification with MLC and FCM provides the probability vector and fuzzy membership vector of each pixel. Based on these vectors, the Shannon's entropy (S.E.) of each pixel is calculated. PCPs are then produced for each classification output. The PCP axes denote the posterior probability vector and fuzzy membership vector and two additional axes represent S.E. and the associated degree of uncertainty. The PCPs highlight the distribution of probability values of different land cover types for each pixel, and also reflect the status of pixels with different degrees of uncertainty. Brushing functionality is then added to PCP visualization in order to highlight selected pixels of interest. This not only reduces the visualization uncertainty, but also provides invaluable information on the positional and spectral characteristics of targeted pixels.     

The Creation of a National Agricultural Land Use Dataset: Combining Pycnophylactic Interpolation with Dasymetric Mapping Techniques

Agricultural Census data is summarised over spatially coarse reporting units for reasons of farm confidentiality. This is problematic for research at a local level. This article describes an approach combining dasymetric and volume preserving techniques to create a national land use dataset at 1 km² resolution. The results for an English county are compared with contemporaneous aggregated habitat data. The results show that the accurate estimates of local agricultural land use (Arable and Grass) patterns can be estimated when individual 1 km squares are combined into blocks of > 9 squares, thereby providing local estimates of agricultural land use. This in turn allows more detailed modelling of land uses related to specific livestock and cropping activities. The dataset created by this work has been subject to extensive external validation through its incorporation into a number of other national models: nitrate leaching (e.g. MAGPIE, NEAP‐N), waste, and pathogen modelling related to agricultural activity.     

Large area forest inventory using Landsat ETM+: A geostatistical approach

Large area forest inventory is important for understanding and managing forest resources and ecosystems. Remote sensing, the Global Positioning System (GPS), and geographic information systems (GIS) provide new opportunities for forest inventory. This paper develops a new systematic geostatistical approach for predicting forest parameters, using integrated Landsat 7 Enhanced Thematic Mapper Plus (ETM+) images, GPS, and GIS. Forest parameters, such as basal area, height, health conditions, biomass, or carbon, can be incorporated as a response variable, and the geostatistical approach can be used to predict parameter values for uninventoried points. Using basal area as the response and Landsat ETM+ images of pine stands in Georgia as auxiliary data, this approach includes univariate kriging (ordinary kriging and universal kriging) and multivariable kriging (co-kriging and regression kriging). The combination of bands 4, 3, and 2, as well as the combination of bands 5, 4, and 3, normalized difference vegetation index (NDVI), and principal components (PCs) were used in this study with co-kriging and regression kriging. Validation based on 200 randomly sampling points withheld field inventory was computed to evaluate the kriging performance and demonstrated that band combination 543 performed better than band combination 432, NDVI, and PCs. Regression kriging resulted in the smallest errors and the highest R-squared indicating the best geostatistical method for spatial predictions of pine basal area.