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Doline probability map using logistic regression and GIS technology in the central Ebro Basin (Spain) 总被引：3，自引：0，他引：3
In the surroundings of Zaragoza, karstification processes are especially intense in covered karst areas where fluvial terraces
lie directly on Tertiary evaporites. Since the beginning of Quaternary, these processes have lead to the development of collapse
and subsidence dolines with a wide range of sizes, which have significant economic impacts. To reduce economic impact and
increase safety, a regional analysis of this phenomenon is needed for spatial management. Therefore, a probability map of
dolines was developed using logistic regression and geographic information system (GIS) techniques. This paper covers the
selection of input data, manipulation of data using the GIS technology, and the use of logistic regression to generate a doline
probability map. The primary variable in the doline development in this area is geomorphology, represented by the location
of endorheic areas and different terrace levels. Secondary variables are the presence of irrigation and the water table gradient. 相似文献
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Zaragoza city is located in the central Ebro Basin, in the Iberian Peninsula. The fluvial terraces formed by the Ebro River
present a valuable resource of sand and gravel deposits. However, taking advantage of these available resources implies conflicts
with other land use interests like urban and industrial development as well as agricultural use, which has also traditionally
occupied the alluvial terraces. These deposits represent a substantial groundwater resource that should be preserved for future
generations. The development of spatial decision support systems (SDSS) has greatly assisted efforts for solving land-use
conflicts. These systems combine the benefits of geographic information systems (GIS) and decision support methodologies and
are therefore suitable to manage sustainable development of urban areas. In this contribution, an extraction suitability map
taking into consideration a variety of environmental criteria is created with the help of a SDSS. The method used is the analytical
hierarchy process which is integrated in ArcGIS. Areas most suitable to sand and gravel extraction are located in the high
terraces, and in those terraces covered by pediments where the thickness of resource is relatively high. These areas are far
from valuable natural areas, outside areas most vulnerable to groundwater contamination, and beneath soils with poor irrigation
characteristics. 相似文献
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黑龙江省多宝山斑岩型铜(钼)矿床成矿流体特征及演化 总被引：7，自引：4，他引：3
黑龙江省多宝山斑岩铜(钼)矿床位于小兴安岭西北部,是中亚-兴蒙造山带北东段最大的斑岩型铜(钼)矿床,矿体产于加里东期花岗闪长岩和中奥陶世多宝山组安山岩、凝灰岩中。铜矿化与绢英岩化关系密切,而钼矿化主要产于钾硅化带中。矿区内脉体广泛发育,从早到晚依次为:石英+钾长石脉、早阶段石英+辉钼矿脉、晚阶段石英+辉钼矿脉、石英+黄铜矿+黄铁矿脉、石英+黄铁矿脉和方解石+石英脉。脉石英中广泛发育流体包裹体,包括气液两相水溶液包裹体(W型)、纯气相包裹体(G型)、含CO2三相包裹体(C型)及含子矿物多相包裹体(S型)。石英+钾长石脉中仅发育气液两相包裹体,均一温度峰值﹥550℃、盐度为16.2%～18.1%NaCleqv;早阶段石英+辉钼矿脉中发育大量气液两相包裹体和含子矿物多相包裹体,并见少量含CO2三相包裹体,均一温度集中在350～450℃、盐度变化于1.1%～﹥65.3%NaCleqv;晚阶段石英+辉钼矿脉体发育大量含CO2三相包裹体和含子矿物多相包裹体,另有少量气液两相包裹体,均一温度集中在270～350℃、盐度为0.8%～42.4%NaCleqv;石英+黄铜矿+黄铁矿脉中发育丰富的气液两相包裹体,见少量含子矿物多相包裹体、含CO2三相包裹体和纯气相包裹体,均一温度峰值在230～330℃、盐度为0.8%～42.4%NaCleqv;石英+黄铁矿脉和方解石+石英脉中仅发育气液两相包裹体,均一温度变化于110～200℃、盐度为3.9%～8.4%NaCleqv。成矿流体在古深度4.1km左右,温度在230～450℃之间、压力在10～41MPa之间,发生了强烈的流体沸腾作用,大量CO2等气体从流体中释放出来,黄铜矿、斑铜矿和辉钼矿等巨量沉淀下来,形成了铜(钼)矿体。成矿流体总体上属H2O-CO2-NaCl体系,多期次的流体沸腾作用是该矿床的主要成矿机制。 相似文献
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SD-1型数字大地电磁测深仪是一种用途较广的地球物理勘探仪器,可用于研究地壳上地幔结构,普查石油、天然气田构造,寻找热田及监视地震前地壳电阻率随时间的变化。该仪器已于1982年8月通过国家鉴定。鉴定以后又在华南地区作了大地电磁测深工作。本文只是简述一下仪器的基本结构、几个主要的技术问题及鉴定前后用该仪器所 相似文献
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The Quaternary deposits of the Ebro Basin in the surroundings of Zaragoza (Spain) form an unconfined alluvial aquifer with
a high degree of permeability and low thickness of unsaturated materials. This fact causes a high degree of vulnerability
to contamination, which implies consequences for land-use decisions and the risk management of existing industrial facilities.
In addition, in the last decades the intense irrigation and the use of pesticides is threatening the quality of the groundwater
and as a consequence the amount of usable groundwater at a low cost. Thus, the development of groundwater vulnerability maps
has great importance in a regional planning process. Consequently, groundwater vulnerability maps have been developed following
a method proposed by the German State Geological Surveys. In this paper the methodology developed within ArcGIS and Gocad,
a two- and three-dimensional software, respectively, is presented. Although the results obtained within GIS (Geographical
Information System) are acceptable it is to say that the 3D-model improves considerably the final product. 相似文献
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ABSTRACTForest fires can change forest structure and composition, and low-density Airborne Laser Scanning (ALS) can be a valuable tool for evaluating post-fire vegetation response. The aim of this study is to analyze the structural diversity differences in Mediterranean Pinus halepensis Mill. forests affected by wildfires on different dates from 1986 to 2009. Several types of ALS metrics, such as the Light Detection and Ranging (LiDAR) Height Diversity Index (LHDI), the LiDAR Height Evenness Index (LHEI), and vertical and horizontal continuity of vegetation, as well as topographic metrics, were obtained in raster format from low point density data. In order to map burned and unburned areas, differentiate fire occurrence dates, and distinguish between old and more recent fires, a sample of pixels was previously selected to assess the existence of differences in forest structure using the Kruskal–Wallis test. Then, k-nearest neighbors algorithm (k-NN), support vector machine (SVM) and random forest (RF) classifiers were compared to select the most accurate technique. The results showed that, in more recent fires, around 70% of the laser returns came from grass and shrub layers, yielding low LHDI and LHEI values (0.37–0.65 and 0.28–0.46, respectively). In contrast, the areas burned more than 20 years ago had higher LHDI and LHEI values due to the growth of the shrub and tree strata. The classification of burned and unburned areas yielded an overall accuracy of 89.64% using the RF method. SVM was the best classifier for identifying the structural differences between fires occurring on different dates, with an overall accuracy of 68.79%. Furthermore, SVM yielded an overall accuracy of 75.49% for the classification between old and more recent fires. 相似文献
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