乾安地区盐碱地显热通量的测量

文中给出了用大孔径闪烁仪在 2 0 0 0年生长季观测到的盐碱地区显热通量的主要结果 ,并初步计算了当地的水热平衡状况。结果表明 :乾安盐碱地区显热通量占净辐射量的百分比在干旱、非生长季达到 6 5 % ,在多雨、植被生长季仅为 11% ;显热通量因降水而明显降低 ,幅度与降水强度有关 ,反映了当地的气候和土壤特征。文中还把LAS的测量结果与传统的梯度法作了比较 ,结果基本一致。     

Landsat-8 vs. Sentinel-2: examining the added value of sentinel-2’s red-edge bands to land-use and land-cover mapping in Burkina Faso

The availability of freely available moderate-to-high spatial resolution (10–30 m) satellite imagery received a major boost with the recent launch of the Sentinel-2 sensor by the European Space Agency. Together with Landsat, these sensors provide the scientific community with a wide range of spatial, spectral, and temporal properties. This study compared and explored the synergistic use of Landsat-8 and Sentinel-2 data in mapping land use and land cover (LULC) in rural Burkina Faso. Specifically, contribution of the red-edge bands of Sentinel-2 in improving LULC mapping was examined. Three machine-learning algorithms – random forest, stochastic gradient boosting, and support vector machines – were employed to classify different data configurations. Classification of all Sentinel-2 bands as well as Sentinel-2 bands common to Landsat-8 produced an overall accuracy, that is 5% and 4% better than Landsat-8. The combination of Landsat-8 and Sentinel-2 red-edge bands resulted in a 4% accuracy improvement over that of Landsat-8. It was found that classification of the Sentinel-2 red-edge bands alone produced better and comparable results to Landsat-8 and the other Sentinel-2 bands, respectively. Results of this study demonstrate the added value of the Sentinel-2 red-edge bands and encourage multi-sensoral approaches to LULC mapping in West Africa.     

基于梯度提升算法的岩性识别方法

传统的岩性识别方法如岩屑录井、钻井取心及测井资料解释等技术,对录井质量的依赖程度较高,识别精度与效率低,泛化能力差。随着计算机技术的迅速发展,将测井资料与计算机技术相结合开展岩性研究已成为岩性识别的有效手段。本文提出了一种基于梯度提升算法XGBoost和LightGBM的岩性识别方法。以苏里格气田苏东41-33区块下碳酸盐岩储层为例进行测试验证,采用该方法结合测井资料中的声波时差、自然伽马、光电吸收截面指数、密度、深侧向电阻率和补偿中子等6种参数进行岩性识别,并与KNN （K近邻分类器）、朴素贝叶斯和支持向量机等传统算法进行对比,结果表明,3种传统算法的岩性识别准确率分别为78.45%、74.43%和78.72%,基于梯度提升算法XGBoost和LightGBM的识别准确率分别达到了98.90%和98.72%,远高于传统算法。     

A real-time, event-triggered storm surge forecasting system for the state of North Carolina

A new real-time, event-triggered storm surge prediction system has been developed for the State of North Carolina to assist emergency managers, policy-makers and other government officials with evacuation planning, decision-making and resource deployment during tropical storm landfall and flood inundation events. The North Carolina Forecast System (NCFS) was designed and built to provide a rapid response assessment of hurricane threat, accomplished by driving a high-resolution, two-dimensional, depth-integrated version of the ADCIRC (Advanced Circulation) coastal ocean model with winds from a synthetic asymmetric gradient wind vortex. These parametric winds, calculated at exact finite-element mesh node locations and directly coupled to the ocean model at every time step, are generated from National Hurricane Center (NHC) forecast advisories the moment they are inserted into the real-time weather data stream, maximizing the number of hours of forecast utility. Tidal harmonic constituents are prescribed at the open water boundaries and applied as tidal potentials in the interior of the ocean model domain. A directional surface roughness parameterization that modulates the wind speed at a given location based on the types of land cover encountered upwind, a forest canopy sheltering effect, and a spatially varying distribution of Manning’s–n friction coefficient used for computing the bottom/channel bed friction are also included in the storm surge model. Comparisons of the simulated wind speeds and phases against their real meteorological counterparts, of model elevations against actual sea surface elevations measured by NOAA tide gauges along the NC coast, and of simulated depth-averaged current velocities against Acoustic Doppler Current Profiler (ADCP) data, indicate that this new system produces remarkably realistic predictions of winds and storm surge.     

Building a model-based personalised recommendation approach for tourist attractions from geotagged social media data

When travelling, people are accustomed to taking and uploading photos on social media websites, which has led to the accumulation of huge numbers of geotagged photos. Combined with multisource information (e.g. weather, transportation, or textual information), these geotagged photos could help us in constructing user preference profiles at a high level of detail. Therefore, using these geotagged photos, we built a personalised recommendation system to provide attraction recommendations that match a user's preferences. Specifically, we retrieved a geotagged photo collection from the public API for Flickr (Flickr.com) and fetched a large amount of other contextual information to rebuild a user's travel history. We then created a model-based recommendation method with a two-stage architecture that consists of candidate generation (the matching process) and candidate ranking. In the matching process, we used a support vector machine model that was modified for multiclass classification to generate the candidate list. In addition, we used a gradient boosting regression tree to score each candidate and rerank the list. Finally, we evaluated our recommendation results with respect to accuracy and ranking ability. Compared with widely used memory-based methods, our proposed method performs significantly better in the cold-start situation and when mining ‘long-tail’ data.     

Interpretation of Gravity Anomalies with the Normalized Full Gradient (NFG) Method and an Example

The Normalized Full Gradient (NFG) method which was put forward about 50 years ago has been used for downward continuation of gravity potential data, especially in the former Union of Soviet Socialist Republics. This method nullifies perturbations due to the passage of mass depth during downward continuation. The method depends on the downwards analytical continuation of normalized full gradient values of gravity data. Analytical continuation discriminates certain structural anomalies which cannot be distinguished in the observed gravity field. This method has been used in various petroleum and tectonic studies. The Trapeze method was used for the determination of Fourier coefficients during the application of this method. No other techniques for calculating these coefficients have been used. However, the Filon method was used for the determination of Fourier coefficients during the application of the NFG method in this work. This method, rather than the Trapeze method, should be preferred for indicating abnormal mass resources at the lower harmonics. In this study, the NFG method using the Filon method has been applied the first time to theoretical models of gravity profiles as example field at the Hasankale-Horasan petroleum exploration province where successful results were achieved. Hydrocarbon presence was shown on the NFG sections by the application of NFG downward continuation operations on theoretical models. Important signs of hydrocarbon structure on the NFG section for field and model data at low harmonics are obtained more effectively using this method.     

Gradient theory of nucleation in polar fluids

Gradient theory (GT), a form of density functional theory (DFT), was applied to water, methanol, and ethanol using the cubic perturbed hard body (CPHB) equation of state (EOS). Compared to the standard form of classical nucleation theory (CNT), the GT results for water showed an improved temperature dependence, but the supersaturation dependence was slightly poorer. GT and several forms of CNT were also found to be in good agreement with a single high T molecular dynamics rate for TIP4P water. The rates predicted by GT for methanol and ethanol were improved by several orders of magnitude compared to CNT, but no improvement in the predicted temperature dependence of the rates was found.     

Hybridization of the probability perturbation method with gradient information

Geostatistically based history-matching methods make it possible to devise history-matching strategies that will honor geologic knowledge about the reservoir. However, the performance of these methods is known to be impeded by slow convergence rates resulting from the stochastic nature of the algorithm. It is the purpose of this paper to introduce a method that integrates qualitative gradient information into the probability perturbation method to improve convergence. The potential of the proposed method is demonstrated on a synthetic history-matching example. The results indicate that inclusion of qualitative gradient information improves the performance of the probability perturbation method.     

Interpretation and modelling of regional gravity data of the Aveiro Basin (Northwest Portugal)

The gravity map of the Aveiro Basin, North West Portugal was produced in 2000/2001 and some limited two dimensional (2D) interpretation was carried out. It is intended in this article to advance the interpretation and modelling of the original Aveiro basin gravity data. Thus, the data were processed and the horizontal gradient, the second vertical derivative and downward continued field computed. The corresponding maps have been processed and a new interpretation of the basin tectonic features has been proposed. This is compared with the previous geological and tectonic information obtained from former surveys and local boreholes. As the next step a more detailed modelling of the Aveiro Basin took place. Bearing the interpretation of the basin tectonic features in mind, several north–south and east–west gravity profiles were established and modelled. The proposed models were presented and discussed. As a result, a comprehensive mass distribution model for the basin was proposed. Finally, comparison was made between the new gravity model and the previously published tectonic features map. This modelling is particularly useful for groundwater protection, exploration and exploitation and also for the dimensioning of drilling operations. Bearing in mind the geomorphology of the basin the gravity method is a very economical tool for the investigation of basin structures.     

Detecting multi-scale urban growth patterns and processes in the Algarve region (Southern Portugal)

The importance of urban growth processes and their spatial characteristics has led to a growing interest in monitoring these phenomena. Spatial metrics are widely employed for this purpose, appearing in an increasing number of studies where they are used to characterise growth patterns and their evolution over time. This paper presents an analysis of urban growth patterns using spatial metrics in the Algarve (southern Portugal), an area of considerable urban dynamics associated with tourism. Two datasets were used (CORINE 1:100,000 maps and COS 1:25,000 maps) and two time periods (1990 and 2006–2007) in order to compare the different urban land use patterns detected and their evolution over time. The results show differences in urban land use patterns and associated processes at each scale, with stable land use patterns predominating at the 1:100,000 scale whereas the 1:25,000 scale showed a move towards more dispersed patterns. These results have enabled an assessment of the principal differences in urban growth patterns observed at both scales, and the implications for planning these entail.