耦合GF-2遥感影像与街景影像的广州市城中村识别

及时准确地获取城中村的空间分布及其环境质量信息对于优化城市空间、改善人居环境具有重要意义。本文以广州市越秀区为例,提出了耦合GF-2高分遥感影像和百度街景影像的城中村识别方法。首先,从街景影像中提取越秀区的街道空间品质特征;其次,在对高分遥感影像预处理并进行多尺度分割的基础上计算光谱、形状、纹理、场景特征和建筑结构5类共计23个特征;最后,融合两种影像的特征用于构建随机森林分类器进行城中村识别。结果表明,基于高分影像和基于街景影像的城中村识别整体精度分别为94.5%和85.7%,Kappa系数分别为0.58和0.31,而两者融合后的分类精度和Kappa系数为96.1%和0.67;其中基于街景影像获取的度量街道空间品质的5个指标贡献了31.6%的特征重要性。鸟瞰视野高分影像和人本视角街景影像提供的信息综合互补,构建了更有区分度的特征空间,减少了城中村的错分现象。本文证实了高分影像和街景影像在特征尺度的融合提升了城中村识别精度。街景影像中的信息可以融入到高分遥感影像等数据源中,辅助进行城中村等非正规居住空间的识别。     

安徽省绩溪县上金山地区钨钼矿矿化类型及找矿前景分析

上金山钨钼矿位于安徽省绩溪县与旌德县交界地带,是扬子准地台南缘新发现的一处大型层控型矿床。南华系休宁组上段上部地层及燕山早期的花岗闪长岩是本矿床主要控矿因素,赋矿地层岩性为锰钙质砂岩—粉砂岩,该赋矿层位是皖南地区找矿新发现。该矿床已达大型规模,地质、物化探综合信息显示,上金山地区具进一步找矿前景,且在已控制的层控型矿床深部及外围,存在寻找斑岩型钨钼矿及石英脉型钨矿的良好条件,经进一步勘查,矿床资源量将显著增加。     

黔北务川—正安—道真地区下二叠统大竹园组和梁山组孢粉学研究

文中材料采自黔北务川—正安—道真地区下二叠统大竹园组和梁山组。大竹园组孢粉化石类型单调,保存较差;而梁山组孢粉化石丰富,保存良好。孢粉组合特征为:(1)大竹园组包含丰富的Calamospora和Florinites及少量Torispora verrucosa,Gulisporites,Alisporites,Hamiapollenites和Striatopodocarpites,这一孢粉组合主要出现在上石炭统至下二叠统。按照大竹园组层位和孢粉化石特征,其地质时代应为早二叠世Asselian期—Artinskian期(相当于紫松期—隆林期)。(2)梁山组中可建立孢粉组合Laevigatosporites vulgaris-Gulisporites-Florinites ovalis,共计发现孢粉化石34属49种,其中蕨类植物孢子含量为51.6％～56.1％,裸子植物花粉含量为43.9％～48.4％。与大竹园组沉积时期相比,这一时期植被极为繁盛。根据孢粉组合特征,梁山组地质时代可能为早二叠世隆林期,即Kungurian期。     

基于模糊综合评判和GIS技术的矿山地质环境影响评价

蒲白矿产资源集中开采区分布于渭北黑腰带地区的蒲城和白水县,煤炭、石灰岩、铝土矿和粘土等多种矿产的持续开发,产生了各类的矿山地质环境问题,其中煤矿采空区塌陷及裂缝最为突出。选取了地形相对高差、岩土体特征、开采方式、有效深厚比、采空区面积比、矿山地质灾害发育密度、地下水位、压占破坏土地资源等11个指标作为评价因子,构建了矿山地质环境影响评价指标体系。采用模糊综合评判法对研究区矿山地质环境影响进行评价,并结合GIS空间分析技术划分为矿山地质环境影响严重区12个,较严重区4个,较轻区2个。评价结果与实际调查情况较为相近,较客观的反映了采矿活动对矿山地质环境的影响,并结合区内实际提出了矿山地质环境恢复治理措施建议,为矿山地质环境保护与恢复治理提供了依据。     

鄂尔多斯盆地延川南区块目的煤层含气性分析

为计算鄂尔多斯盆地延川南区块煤层气资源量、甄选有利区带及确定先导性试验井组的部署,对全区探井的煤层含气性进行综合分析。结果显示:区块内煤层气含量为5.54~19.56m3/t;兰氏体积为13.59~33.78m3/t,兰氏压力为2.06~3.72MPa,含气饱和度为41.48%~92.19%;临储压力比为19.18%~84.28%。区块整体含气性显示较好,开发较为有利,其中以包括Y3、Y6等井在内的万宝山构造带为煤层气开发的最有利区带。     

测井曲线特征在贵州省兴达井田煤岩层对比中的应用

贵州兴达井田含煤9-17层,其中K1、K2、K3、K4四层煤较稳定,为主要可采煤层。依据钻孔资料,分析测井曲线形态与煤层顶底板以及上下标志层间的组合关系,对井田的煤岩层进行了对比。该井田K1煤层常分叉为K1上、K1下两个分层,其直接顶板高视电阻率异常,三叠系至K1煤层组间自上而下的缓坡状视电阻率曲线形态与自然伽马幅值相对较高的组合特征可作为二叠系含煤地层与三叠系地层划分依据;K2煤层位于龙潭组顶部,下距长兴组灰岩标志层10m左右,煤层本身高伽马异常;K3、K4煤层及其底板具较高的自然伽马特征。     

Multi-level analysis of field synergy in the displacement mechanisms of heavy oil thermal recovery

One of the major problems of heavy oil thermal recovery is the inadequacy of understanding the multi-field coupling displacement mechanisms to improve the oil production and extraction ratio. From the perspective of “force” and “flow” in thermodynamics, oil displacement fields are divided into three groups: destination, driving and resistance potential fields. Based on the seepage law, the compositional structure of driving and resistance potential fields has been established by making use of non-equilibrium thermodynamics. In addition, coupling indexes among driving, resistance and a combination of both potential fields can be deduced. Then, the main process of multi-level analysis of oil displacement mechanism of field synergy in the process of heavy oil thermal recovery can be put forward. A practical multi-level case study of typical hot-water flooding displacement can provide useful information and guidance to enhance the displacement process.     

Evaluation of I-wall in New Orleans with back-calculated total stress soil parameters

This study back-calculated moduli and shear strength of soils in London Canal Ave., New Orleans, using full-scale load test data, and re-evaluated the behavior of the I-wall to explore how the existing levees and floodwalls may be reliably retrofitted and future levees and floodwalls may be designed. From the back-calculation, it turned out that the moduli of the field soils were mostly higher (1–12 times) than magnitudes appeared in Interagency Performance Evaluation Task Force (IPET). But the shear strength of a water-glazed Marsh layer in the gap turned out to be substantially lower (0.2–0.25 times) than the magnitude appeared in IPET. This much strength reduction was confirmed by field vane shear tests: tests with artificial water infiltration into the field vane hole presented immeasurably low disturbed strength and resulted in very high sensitivity that might contributed to the failure. This study also shows that the gap development and strength reduction in the water-glazed Marsh layer are two main causes of levee failure, which have been predicted in previous research. The stiffer-than-expected moduli of underlain layers did not affect the failure mechanism of the levee substantially because these underlain layers remained elastic. Therefore, retrofitting solutions should be the ones that may prevent the gap development and to reinforce the Marsh layer.     

A method for mineral prospectivity mapping integrating C4.5 decision tree,weights-of-evidence and m-branch smoothing techniques: a case study in the eastern Kunlun Mountains,China

In this study, a novel method that integrates C4.5 decision tree, weights-of-evidence and m-branch smoothing techniques was proposed for mineral prospectivity mapping. First, a weights-of-evidence model was used to rank the importance of each evidential map and determine the optimal buffer distance. Second, a classification technique that uses a C4.5 decision tree in data mining was used to construct a decision tree classifier for the grid dataset. Finally, an m-branch smoothing technique was used as a predictor, which transformed the decision tree into a probability evaluation tree. The method makes no conditional independence assumption and can be applied for class imbalanced datasets like those collected during mineral exploration for prospectivity mapping of an area. The traits of comprehensibility, accuracy and efficiency were derived from the C4.5 decision tree. In addition, a case study for iron prospectivity mapping was performed in the eastern Kunlun Mountains, China. Sixty-two Skarn iron deposits and eight evidential maps related to iron mineralization were studied. On the final map, areas of low, moderate and high potential for iron deposit occurrence covered areas of 71,491, 14,298, and 9,532 km², respectively. For the goodness-of-fit test, 91.94 % of the total 62 iron deposits were within a high-potential area, 8.06 % were within a moderate-potential area and 0 % were within a low-potential area. For ten-fold cross-validation, 82.26 % were within a high-potential area, 14.52 % were within a moderate-potential area and 3.22 % were within a low-potential area. To evaluate the predictive accuracy, Receiver Operating Characteristic (ROC) curves and Area Under ROC Curve (AUC) were employed. The accuracy of the goodness-of-fit test reached 97.07 %, and the accuracy of the ten-fold cross-validation was 95.10 %. The majority of the iron deposits were within high-potential and moderate-potential areas, which covered a small proportion of the study area.     

Microbiological degradation of phenol using two co-aggregating bacterial strains

Phenol biodegradation in an aerobic batch reactor was investigated using mixed two co-aggregating strains (Flavobacterium sp. and Acetobacter sp.). Response surface methodology by the Box–Behnken model was used to evaluate the optimal cell growth and phenol degradation conditions. The optimum temperature, pH value and inoculum size were found to be 33 °C, 6.06 and 13 %, respectively. In the conditions, phenol degradation rate and biomass were predicted to be 96.97 % and 410.78 mg/L within the range examined, respectively. Less toxic acetaldehyde, ethanol and acetic ether were identified as main intermediate products from the degraded samples using GC–MS. Substrate inhibition was calculated from experimental biomass growth and phenol degradation parameters using the Haldane equation. Kinetic parameters derived from nonlinear regression with correlation factors (R ²) were 0.9682 for phenol degradation and 0.9594 for biomass growth, respectively. The phenol concentration to avoid substrate inhibition was 278.17 mg/L.