Mental maps and travel behaviour: meanings and models

In this paper, the “mental map” concept is positioned with regard to individual travel behaviour to start with. Based on Ogden and Richards’ triangle of meaning (The meaning of meaning: a study of the influence of language upon thought and of the science of symbolism. International library of psychology, philosophy and scientific method. Routledge and Kegan Paul, London, 1966) distinct thoughts, referents and symbols originating from different scientific disciplines are identified and explained in order to clear up the notion’s fuzziness. Next, the use of this concept in two major areas of research relevant to travel demand modelling is indicated and discussed in detail: spatial cognition and decision-making. The relevance of these constructs to understand and model individual travel behaviour is explained and current research efforts to implement these concepts in travel demand models are addressed. Furthermore, these mental map notions are specified in two types of computational models, i.e. a Bayesian Inference Network (BIN) and a Fuzzy Cognitive Map (FCM). Both models are explained, and a numerical and a real-life example are provided. Both approaches yield a detailed quantitative representation of the mental map of decision-making problems in travel behaviour.     

The Potential of the Maximum Cross-Correlation Technique to Estimate Surface Currents From Thermal AVHRR Global Area Coverage Data

Having already shown its potential of deriving the vector fields representing the ocean-surface advection from sequential 1.1-km-resolution local area coverage (LAC) Advanced Very High Resolution Radiometer (AVHRR) images, the maximum cross-correlation (MCC) technique here is applied to four 4.4-km-resolution global area coverage (GAC) AVHRR images. The resulting three vector fields are compared to the vector fields obtained from the LAC imagery corresponding to the same satellite passages. To quantify the reduction in accuracy inevitable when applying the method to the lower resolution imagery, the LAC vector fields were assumed to be error free. The deviation of the GAC vectors from the LAC vectors is expressed as percentage errors of the signal variance of meridional u and zonal v velocity components, and they are 16%/30%, respectively, for the best case and 62%/117% and 92%/111% for the other two cases. These results indicate that, in its present state, the GAC data do not allow the MCC technique to extract reliable current-vector information from it     

Surface gravitational field and topography changes induced by the Earth’s fluid core motions

Using a Love number formalism, the elastic deformations of the mantle and the mass redistribution gravitational potential within the Earth induced by the fluid pressure acting at the core–mantle boundary (CMB) are computed. This pressure field changes at a decadal time scale and may be estimated from observations of the surface magnetic field and its secular variation. First, using a spherical harmonic expansion, the poloidal and toroidal part of the fluid velocity field at the CMB for the last 40 years is computed, under the hypothesis of tangential geostrophy. Then the associated geostrophic pressure, whose order of magnitude is about 1000 Pa, is computed. The surface topography induced by this pressure field is computed using Love numbers, and is a few millimetres. The mass redistribution gravitational potential induced by these deformations and, in particular, the zonal components of the related surface gravitational potential perturbation (J₂, J₃ and J₄ coefficients), are calculated. Overall perturbations for the J₂ coefficient of about 10^–10, for J₃ of about 10^–11 and for J₄ are found of about 0.3×10^–11. Finally, these theoretical results are compared with recent observations of the decadal variation of J₂ from satellite laser ranging. Results concerning J₂ can be described as follows: first, they are one order of magnitude too small to explain the observed decadal variation of J₂ and, second, they show a significant linear trend over the last 40 years, whose rate of decrease amounts to 7% of the observed value.     

Sunken wood habitat for thiotrophic symbiosis in mangrove swamps

Large organic falls to the benthic environment, such as dead wood or whale bones, harbour organisms relying on sulfide-oxidizing symbionts. Nothing is known however, concerning sulfide enrichment at the wood surface and its relation to wood colonization by sulfide-oxidizing symbiotic organisms.In this study we combined in situ hydrogen sulfide and pH measurements on sunken wood, with associated fauna microscopy analyses in a tropical mangrove swamp. This shallow environment is known to harbour thiotrophic symbioses and is also abundantly supplied with sunken wood. A significant sulfide enrichment at the wood surface was revealed. A 72 h sequence of measurements emphasized the wide fluctuation of sulfide levels (0.1–>100 μM) over time with both a tidal influence and rapid fluctuations. Protozoans observed on the wood surface were similar to Zoothamnium niveum and to vorticellids. Our SEM observations revealed their association with ectosymbiotic bacteria, which are likely to be sulfide-oxidizers. These results support the idea that sunken wood surfaces constitute an environment suitable for sulfide-oxidizing symbioses.     

Image smoothing of multispectral imagery based on the HNN and geo-statistics

A new method for image down-scaling using geostatistical interpolation or smoothing based on the Hopfi eld Neural Network (HNN) and zero semivariance value is introduced. The method utilises the smoothing effect of the semivariogram matching process to produce the smoothened sub-pixel multispectral (MS) image with smaller RMSEs in comparison with the bilinear interpolation. In fact, the zero semivariograms increase the spatial correlation between the adjacent sub-pixels of the superresolution image. Containing higher spatial correlation, the resulting super-resolution MS image has smaller RMSEs compared with the original coarse image.     

“一带一路”区域可持续发展生态环境遥感监测

2013年9月和10月,习近平主席在出访中亚和东南亚国家期间,先后提出了共建"丝绸之路经济带"和"21世纪海上丝绸之路"(简称"一带一路")的重大倡议。要全面保护"一带一路"区域生态环境,实现2030年可持续发展目标,是一个具有挑战性的问题。遥感技术对生态环境监测与评价发挥着十分重要的作用。本研究利用多尺度、多源遥感数据,对2015年"一带一路"区域的生态环境状况进行监测和分析,旨在提供可持续发展目标生态环境遥感监测的本底。本文选取了几个重要的生态环境方面开展监测与分析,主要包括宏观生态系统结构和植被状况、太阳能资源分布、水资源平衡、主要生态环境限制因素对经济走廊建设的影响、主要城市生态环境质量等。监测区域覆盖亚洲、非洲、欧洲和大洋洲的陆上区域。研究结果为生态环境评价与保护提供了有效的决策依据,有助于"一带一路"建设积极推进。     

Objectives of fisheries management: case studies from the UK, France, Spain and Denmark

The main objectives of fisheries management are generally similar throughout the world. These are often stated in policy documents such as the Common Fisheries Policy and the Magnuson–Stevens Fishery Conservation and Management Act. However, at the local level often the key objectives of management are more detailed, characterised by both the overriding management structure and the status and type of fishery concerned. In this paper, we consider case study fisheries from the UK, France, Spain and Denmark to compare some of the various types of fisheries and fisheries management systems that exist in the European Union. From this, we define the key objectives for each management system.     

Multi-Conjugate Adaptive Optics with laser guide stars: performance in the infrared and visible

The assumption of the Gaussianity of primordial perturbations plays an important role in modern cosmology. The most direct test of this hypothesis consists of testing the Gaussianity of cosmic microwave background (CMB) maps. Counting the pixels with the temperatures in given ranges and thus estimating the one-point probability function of the field is the simplest of all the tests. Other usually more complex tests of Gaussianity generally use a great deal of the information already contained in the probability function. However, the most interesting outcome of such a test would be the signal of non-Gaussianity independent of the probability function. It is shown that the independent information has purely morphological character i.e. it depends on the geometry and topology of the level contours only. As an example we discuss in detail the quadratic model   v = u + α ( u ²-1)  ( u is a Gaussian field with   u¯ =0  and  〈 u ²〉=1  , α is a parameter) that may arise in slow-roll or two-field inflation models. We show that in the limit of small amplitude α the full information about the non-Gaussianity is contained in the probability function. If other tests are performed on this model they simply recycle the same information. A simple procedure allowing us to assess the sensitivity of any statistics to the morphological information is suggested. We provide an analytic estimate of the statistical limit for detecting the quadratic non-Gaussianity α _c as a function of the map size in the ideal situation when the scale of the field is resolved. This estimate is in a good agreement with the results of the Monte Carlo simulations of 256² and 1024² maps. The effect of resolution on the detection quadratic non-Gaussianity is also briefly discussed.     

Identifying influence areas with connectivity analysis – application to the local perturbation of heterogeneity distribution for history matching

Numerical representations of a target reservoir can help to assess the potential of different development plans. To be as predictive as possible, these representations or models must reproduce the data (static, dynamic) collected on the field. However, constraining reservoir models to dynamic data – the history-matching process – can be very time consuming. Many uncertain parameters need to be taken into account, such as the spatial distribution of petrophysical properties. This distribution is mostly unknown and usually represented by millions of values populating the reservoir grid. Dedicated parameterization techniques make it possible to investigate many spatial distributions from a small number of parameters. The efficiency of the matching process can be improved from the perturbation of specific regions of the reservoir. Distinct approaches can be considered to define such regions. For instance, one can refer to streamlines. The leading idea is to identify areas that influence the production behavior where the data are poorly reproduced. Here, we propose alternative methods based on connectivity analysis to easily provide approximate influence areas for any fluid-flow simulation. The reservoir is viewed as a set of nodes connected by weighted links that characterize the distance between two nodes. The path between nodes (or grid blocks) with the lowest cumulative weight yields an approximate flow path used to define influence areas. The potential of the approach is demonstrated on the basis of 2D synthetic cases for the joint integration of production and 4D saturation data, considering several formulations for the weights attributed to the links.