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运用LANDSAT ETM+和ASTER数据进行岩性分类 总被引:5,自引:0,他引:5
本文评价了运用ASTER和LANDSAT ETM+数据进行岩性制图的性能。分别利用ASTER数据不同波段区图像及其组合,以及ETM+数据进行岩性分类,并探讨了将ASTER和ETM+数据叠加在一起进行了岩性分类; 利用现有地质图对所有分类结果进行了定量评价。结果表明,ASTER数据不同波段的岩性识别能力不同,并且较ETM+数据能更准确地识别岩性。更重要的是,把ASTER与ETM+数据结合在一起进行岩性分类,可获得比用任一数据单独分类更高的分类精度,表明二者的光谱特征具有一定的互补性。 相似文献
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To investigate the stratification of hydrolytic enzyme activities and importance of subsurface layers in depolymerization of detritus biopolymers,nine hydrolytic enzyme activities involved in the cycling of carbon,phosphorus,nitrogen and sulphur were measured in various sediment layers and their extracts at Kylaniemi in Lake Saimaa in southern Finland and in Lake Ahvenjarvi in northern Finland. The results show that for each lake all nine hydrolytic enzyme activities were higher in all sediment layers than in comparable sediment extracts indicating that the major part of enzymes was bound to the sediment particles in all layers in both lakes.Carbohydratase,P-cellobiosidase,activities did not show any gradient with sediment depth at Kylaniemi in Lake Saimaa indicating that there was rapid turnover of carbohydrates in the entire sediment column.The activities of acetate esterase,butyrate esterase,phosphomonoesterase,aminopeptidase,N-acetyl glucosaminidase,sulphatase andβ-glucosidase in the deepest layers were 19-53%of those in the surface sediment indicating that depolymerization of biopolymers involved in the cycling of carbon,nitrogen,phosphorus and sulphur was substantial in subsurface sediment. 相似文献
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