Mapping of aggregated floodplain plant communities using image fusion of CASI and LiDAR data

Combined optical and laser altimeter data offer the potential to map and monitor plant communities based on their spectral and structural characteristics. A problem unresolved is, however, that narrowly defined plant communities, i.e. plant communities at a low hierarchical level of classification in the Braun-Blanquet system, often cannot be linked directly to remote sensing data for vegetation mapping. We studied whether and how a floristic dataset can be aggregated into a few major discrete, mappable classes without substantial loss of ecological meaning. Multi-source airborne data (CASI and LiDAR) and floristic field data were collected for a floodplain along the river Waal in the Netherlands. Mapping results based on floristic similarity alone did not achieve highest levels of accuracy. Ordination of floristic data showed that terrain elevation and soil moisture were the main underlying environmental drivers shaping the floodplain vegetation, but grouping of plant communities based on their position in the ordination space is not always obvious. Combined ordination-based grouping with floristic similarity clustering led to syntaxonomically relevant aggregated plant assemblages and yielded highest mapping accuracies.     

Optimizing support vector machine learning for semi-arid vegetation mapping by using clustering analysis

In remote sensing communities, support vector machine (SVM) learning has recently received increasing attention. SVM learning usually requires large memory and enormous amounts of computation time on large training sets. According to SVM algorithms, the SVM classification decision function is fully determined by support vectors, which compose a subset of the training sets. In this regard, a solution to optimize SVM learning is to efficiently reduce training sets. In this paper, a data reduction method based on agglomerative hierarchical clustering is proposed to obtain smaller training sets for SVM learning. Using a multiple angle remote sensing dataset of a semi-arid region, the effectiveness of the proposed method is evaluated by classification experiments with a series of reduced training sets. The experiments show that there is no loss of SVM accuracy when the original training set is reduced to 34% using the proposed approach. Maximum likelihood classification (MLC) also is applied on the reduced training sets. The results show that MLC can also maintain the classification accuracy. This implies that the most informative data instances can be retained by this approach.     

The impact of overfishing and El Niño on the condition factor and reproductive success of Peruvian hake, Merluccius gayi peruanus

In this study we examine physiological responses of Peruvian hake (Merluccius gayi peruanus) to changes in their population structure and physical environment during the period 1971–2004. In particular, we assess the relative investment of energy in growth and/or reproduction of small (20–35 cm) and large (35–50 cm) hake. We calculated the (i) condition (Fulton’s K), (ii) gonad and (iii) gut fullness indices for 42,761 female hakes sampled from commercial landings; these indices indicate fish somatic, reproductive and feeding condition, respectively. Using Generalized Additive Models we then examined potential relationships between these indices and sea surface temperature anomalies and date. Drastic energy exhaustion and a decrease in female hake fecundity were observed during El Niño events. The long-term trend showed a general increase in condition factor and a decrease in gonad index for large hake between 1971 and 2004. Small hake exhibited a different trend with an increase in reproductive activity, which was accompanied by an earlier maturation. We hypothesise that the observed low investment of energy in reproduction by large female hake might be related to the lack of large males, due to a sex-selective fishery and the impact of El Niño. We suggest that fishing diminished hake reproductive capacity, modified the sex ratio in favour of females and increased population vulnerability to environmental stress, in particular to the El Niño. The impact of multidecadal variability and predators like the squid, Dosidicus gigas, remain unresolved until longer time series become available.     

西湖凹陷油气成藏的主控因素

西湖凹陷位于东海大陆架边缘,地壳为相对软弱的过渡壳。西湖凹陷中新世末以前属于萎缩型盆地,上新世伴随冲绳海槽的形成才成为扩张性盆地。受构造控制盆地萎缩期沉积有以下3个特点：第一,整体表现为海退;第二,沉积范围逐次减小;第三,泥岩百分比越来越低,盖层条件越来越差。平湖组存在区域盖层,钻遇断块气藏;花港组存在局部盖层,背斜充满度高,断背斜充满度低,断块未成藏;新近系盖层条件更差,断背斜亦未能成藏。由此可见保存条件是西湖凹陷油气成藏的主控因素,保存条件好的领域是西湖凹陷下一步勘探的方向。     

提高机采水平的配套技术及应用

随着濮城油田的持续性高速开发,油田综合含水逐渐上升,油水井井况进一步恶化,作为油田生产主体的机械采油井躺井频繁、管杆泵使用寿命缩短。近几年中原油田采油二厂濮城油田年平均躺井数达560井次之多,导致机械采油井维护费用增加,管杆泵投入增大,严重制约着油田的生产和经营。通过加缓蚀剂在油管内壁形成保护油膜,起到润滑作用;应用特殊抽油杆防腐止磨;应用尼龙扶正器对抽油杆体扶正,避免了钢体与钢体的硬磨;应用旋转井口通过地面人力转动改变油管与抽油杆的偏磨面;配合合理生产参数;各种配套技术的合理应用,使濮城油田躺井减少,避免了频繁作业,增加长寿井,管杆泵投入节约了19.3%。     

港域波浪数学模型的改进与验证

通过物理模型对改进的港内波浪传播变形数学模型进行验证。该数学模型以推广的时变缓坡方程为控制方程,采用含松弛因子的ADI法求解,并对波浪反射和透射边界模拟方法进行改进。先通过物理模型试验确定斜向浪入射条件下抛石防波堤前的波浪反射系数,作为数学模型中部分反射边界模拟的依据。然后进行了一个典型港口内波浪折射、绕射和反射的模型试验,测量港内波浪分布。对比模型试验和数学模型计算的结果表明,数学模型可较好地模拟港内复杂地形和边界条件下规则波和不规则波的传播变形。     

SPOT影像光束法平差复共线性消除

CCD卫星影像空间后方交会时,存在系数矩阵列向量间的强相关的问题,用光束法平差同样存在这个问题,将光束法平差与线角元素分求法、广义岭估计、附有限制条件的平差结合,证实三种方法都可以克服平差时外元素和变率改正数震荡大的缺点,并且取得了合理的空间后方交会精度和地面点定位精度。     

Nonlinear random wave-induced drag force on a vegetation field

This paper provides a practical method by which the drag force on a vegetation field beneath nonlinear random waves can be estimated. This is achieved by using a simple drag formula together with an empirical drag coefficient given by Mendez et al. (Mendez, F.J., Losada, I.J., Losada, M.A., 1999. Hydrodynamics induced by wind waves in a vegetation field. J. Geophys. Res. 104 (C8), 18383–18396). Effects of nonlinear waves are included by using Stokes second order wave theory where the basic harmonic motion is assumed to be a stationary Gaussian narrow–band random process. An example of calculation is also presented.     

Study on General Performance of Jack-up Under Elevated Condition

Method of checking for jack-up elevated performance including leg structure strength, fixation system or jacking system bearing capacity, pre-load requirements, spud can bearing capacity and overturning stability is suggested in this paper. As an example, a jack-up with truss legs is analyzed by finite element analysis method. This paper may be helpful to the rig owners, operators and designers.     

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