Remote sensing data have been widely applied to extract minerals in geologic exploration, however, in areas covered by vegetation, extracted mineral information has mostly been small targets bearing little information. In this paper, we present a new method for mineral extraction aimed at solving the difficulty of mineral identification in vegetation covered areas. The method selected six sets of spectral difference coupling between soil and plant (SVSCD). These sets have the same vegetation spectra reflectance and a maximum different reflectance of soil and mineral spectra from Hyperion image based on spectral reflectance characteristics of measured spectra. The central wavelengths of the six, selected band pairs were 2314 and 701 nm, 1699 and 721 nm, 1336 and 742 nm, 2203 and 681 nm, 2183 and 671 nm, and 2072 and 548 nm. Each data set’s reflectance was used to calculate the difference value. After band difference calculation, vegetation information was suppressed and mineral abnormal information was enhanced compared to the scatter plot of original band. Six spectral difference couplings, after vegetation inhibition, were arranged in a new data set that requires two components that have the largest eigenvalue difference from principal component analysis (PCA). The spatial geometric structure features of PC1 and PC2 was used to identify altered minerals by spectral feature fitting (SFF). The collecting rocks from the 10 points that were selected in the concentration of mineral extraction were analyzed under a high-resolution microscope to identify metal minerals and nonmetallic minerals. Results indicated that the extracted minerals were well matched with the verified samples, especially with the sample 2, 4, 5 and 8. It demonstrated that the method can effectively detect altered minerals in vegetation covered area in Hyperion image. 相似文献
Considering the current disadvantages of present offshore wind turbine foundations, a novel anchor foundation with skirt and branches is proposed, called offshore umbrella suction anchor foundation (USAF). A series of experiments and numerical simulations were performed to explore the bearing capacity of the USAF under various kinds of loading modes. The bearing characteristics and the anchor–soil interactions are described in detail for horizontal static loading, horizontal cyclic loading, and an antidrawing (pullout) test in silty soil. In the static loading test, the load–deflection of the anchor under step loading was analyzed and the normalized curve of the load–deflection was obtained to determine the ultimate horizontal bearing capacity of the anchor under normal working conditions. Under horizontal cyclic loading, the relationship between the plastic cumulative deformation and cyclic number was determined. In addition, the responses of USAF were investigated for a low wave frequency and storm surges. In the drawing test, it was found that a “segmentation phenomenon” occurred during the test. Moreover, a method to identify the maximum antidrawing load of USAF was provided based on dynamic mechanics. The numerical results show that the use of anchor branches and skirt can enhance the bearing performance of USAF to a certain degree. However, the anchor branch has a slight positive influence on the bearing performance improvement. The USAF is not only similar to a stiff short pile, but a rotation occurs. The failure envelope under composite loading (V-M) was obtained and the changes associated with changes in the aspect ratio of the internal compartment were clarified. 相似文献
高光谱遥感影像具有光谱分辨率极高的特点,承载了大量可区分不同类型地物的诊断性光谱信息以及区分亚类相似地物之间细微差别的光谱信息,在目标探测领域具有独特的优势。与此同时,高光谱遥感影像也带来了数据维数高、邻近波段之间存在大量冗余信息的问题,高维度的数据结构往往使得高光谱影像异常目标类和背景类之间的可分性降低。为了缓解上述问题,本文提出了一种基于波段选择的协同表达高光谱异常探测算法。首先,使用最优聚类框架对高光谱波段进行选择,获得一组波段子集来表示原有的全部波段,使得高光谱影像异常目标类与背景类之间的可分性增强。然后使用协同表达对影像上的像元进行重建,由于异常目标类和背景类之间的可分性增强,对异常目标像元进行协同表达时将会得到更大的残差,异常目标像元的输出值增大,可以更好地实现异常目标和背景类的分离。本文使用了3组高光谱影像数据进行异常目标探测实验,实验结果表明,该方法与其他现有高光谱异常目标探测算法对比,曲线下面积AUC(Area Under Curve)值更高,可以更好地实现异常目标与背景分离,能够更有效地对高光谱影像进行异常目标探测。 相似文献
Atlantic salmon reared in recirculating aquaculture system (RAS) may lead to inappropriately high stocking density, because fish live in a limited space. Finding the suitable stocking density of Atlantic salmon reared in RAS is very important for RAS industry. In this paper, the influence of stocking density on growth and some stress related physiological factors were investigated to evaluate the effects of stocking density. The fish were reared for 220 days at five densities (A: 24 kg/m3; B: 21 kg/m3; C: 15 kg/m3; D: 9 kg/ m3 and E: 6 kg/m3 ). The results show that 30 kg/m3 might be the maximum density which RAS can afford in China. The stocking densities under 30 kg/m3 have no effect on mortality of Atlantic salmon reared in RAS. However, the specific growth rate (SGR), final weight and weight gain in the high density group were significantly lower than the lower density groups and middle density groups. Moreover, feed conversion rate (FCR) had a negative correlation with density. Plasma hormone T3 and GH showed significant decrease with the increase of the stocking density of the experiment. Furthermore, thyroid hormone (T3), GH (growth hormone) activities were decreased with stocking density increase. However, plasma cortisol, GOT (glutamic oxalacetic transaminase) and GPT (glutamic pyruvic transaminase) activities were increase with stocking density increase. And the stocking density has no effects on plasma lysozyme of Atlantic salmon reared in RAS. These investigations would also help devise efficient ways to rear adult Atlantic salmon in China and may, in a way, help spread salmon mariculture in China.
