150 resultados para Xinjiang


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Thematic Mapper (TM) and Enhanced Thematic Mapper (ETM)+ data have been successfully employed in the field of mineral exploration to identify key minerals over arid and semi-arid terrains. However, redundant vegetation and cloud may seriously interfere with the discrimination of the minerals with diagnostic features. Therefore, in this study, we use masking technique to eliminate the negative influence of vegetation and cloud and Crosta technique to identify the diagnostic features of hydroxyl-minerals, carbonate-minerals and iron oxides. Then the anomalies were endowed with special colours and overlapped with the remote-sensing and geochemical data, overlaying images as remote-sensing anomalies. The mineral exploration work was carried through by synthetic analysis of the remote-sensing images, geochemical data and structures. Finally, areas with high correlation between the occurrence of hydrothermal alteration and presence of main faults and geochemical anomalies were considered as mineral exploration targets worthy of further detailed exploration programmes.

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An analysis of historical Corona images, Landsat images, recent radar and Google Earth® images was conducted to determine land use and land cover changes of oases settlements and surrounding rangelands at the fringe of the Altay Mountains from 1964 to 2008. For the Landsat datasets supervised classification methods were used to test the suitability of the Maximum Likelihood Classifier with subsequent smoothing and the Sequential Maximum A Posteriori Classifier (SMAPC). The results show a trend typical for the steppe and desert regions of northern China. From 1964 to 2008 farmland strongly increased (+ 61%), while the area of grassland and forest in the floodplains decreased (- 43%). The urban areas increased threefold and 400 ha of former agricultural land were abandoned. Farmland apparently affected by soil salinity decreased in size from 1990 (1180 ha) to 2008 (630 ha). The vegetated areas of the surrounding rangelands decreased, mainly as a result of overgrazing and drought events.The SMAPC with subsequent post processing revealed the highest classification accuracy. However, the specific landscape characteristics of mountain oasis systems required labour intensive post processing. Further research is needed to test the use of ancillary information for an automated classification of the examined landscape features.