Verification and recalibration of HY-2A microwave radiometer brightness temperature

HY-2A is the first one of the Chinese HY-2 ocean satellite series carrying a microwave radiometer(RM)to measure sea surface temperature,sea surface wind speed,atmospheric water vapor,cloud liquid water content,and rain rate.We verified the RM level 1B brightness temperature(T B)to retrieve environmental parameters.In the verification,TB that simulated using the ocean-atmosphere radiative transfer model(RTM)was used as a reference.The total bias and total standard deviation(SD)of the RM level 1B TB,with reference to the RTM simulation,ranged-20.6-4.38 K and 0.7-2.93 K,respectively.We found that both the total bias and the total SD depend on the frequency and polarization,although the values for ascending and descending passes are different.In addition,substantial seasonal variation of the bias was found at all channels.The verification results indicate the RM has some problems regarding calibration,e.g.,correction of antenna spillover and antenna physical emission,especially for the 18.7-GHz channel.Based on error analyses,a statistical recalibration algorithm was designed and recalibration was performed for the RM level 1B TB.Validation of the recalibrated TB indicated that the quality of the recalibrated RM level 1B TB was improved significantly.The bias of the recalibrated T B at all channels was reduced to<0.4 K,seasonal variation was almost eradicated,and SD was diminished(i.e.,the SD of the 18.7-GHz channel was reduced by more than 0.5K).     

New photometric investigation of the low-mass-ratio contact binary star V1853 Orionis

Four-color charge-coupled device(CCD) light curves in the B, V, Rc and I c bands of the totaleclipsing binary system V1853 Orionis(V1853 Ori) are presented. By comparing our light curves with those published by previous investigators, it is determined that the O'Connell effect on the light curves has disappeared. By analyzing those multi-color light curves with the Wilson-Devinney code(W-D code),it is discovered that V1853 Ori is an A-type intermediate-contact binary with a degree of contact factor of f = 33.3%(3.7%) and a mass ratio of q = 0.1896(0.0013). Combining our 10 newly determined times of light minima together with others published in the literature, the period changes of the system are investigated. We found that the general trend of the observed minus calculated(O-C) curve shows a downward parabolic variation that corresponds to a long-term decrease in the orbital period with a rate of d P/dt =-1.96(0.46)×10^-7 d yr^-1. The long-term period decrease could be explained by mass transfer from the more-massive component to the less-massive one. By combining our photometric solutions with data from Gaia DR_2, absolute parameters were derived as M_1 = 1.20 M⊙, M_2 = 0.23 M⊙, R_1 = 1.36 R⊙and R_2 = 0.66 R⊙. The long-term period decrease and intermediate-contact configuration suggest that V1853 Ori will evolve into a high fill-out overcontact binary.     

Analysis of Spatio-temporal Land Surface Temperature and Normalized Difference Vegetation Index Changes in the Andassa Watershed,Blue Nile Basin,Ethiopia

Analysis of the nexus between vegetation dynamics and climatic parameters like surface temperature is essential in environmental and ecological studies and for monitoring of the natural resources. This study explored the spatio-temporal distribution of land surface temperature (LST) and Normalized Difference Vegetation Index (NDVI) and the relationship between them in the Andassa watershed from 1986 to 2016 periods using Landsat data. Monthly average air temperature data of three meteorological sites were used for validating the results. The findings of the study showed that the LST of the Andassa watershed has increased during the study periods. Overall, average LST has been rising with an increasing rate of 0.081°C per year. Other results of this study also showed that there has been a dynamic change in vegetation cover of the watershed in all seasons. There was also a negative correlation between LST and NDVI in all the studied years. From this study we can understand that there has been degradation of vegetation and intensification of LST from 1986 to 2016.     

Wave tank and bench-top control testing of a wave energy converter

An increasing number of experiments are being conducted to study the design and performance of wave energy converters. Often in these tests, a real-time realization of prospective control algorithms is applied in order to assess and optimize energy absorption as well as other factors. This paper details the design and execution of an experiment for evaluating the capability of a model-scale WEC to execute basic control algorithms. Model-scale hardware, system, and experimental design are considered, with a focus on providing an experimental setup capable of meeting the dynamic requirements of a control system. To more efficiently execute such tests, a dry bench testing method is proposed and utilized to allow for controller tuning and to give an initial assessment of controller performance; this is followed by wave tank testing. The trends from the dry bench test and wave tank test results show good agreement with theory and confirm the ability of a relatively simple feedback controller to substantially improve energy absorption. Additionally, the dry bench testing approach is shown to be an effective and efficient means of designing and testing both controllers and actuator systems for wave energy converters.     

Obtaining the distribution of quiescent periods directly from the power spectral densities of Sea waves

There is a growing practical interest in the ability to increase the sea states at which marine operations can be safely undertaken by exploiting the quiescent periods that are well known to exist under a wide range of sea conditions. While the actual prediction of quiescent periods at sea for the control of operations is a deterministic process, the long term planning of future maritime tasks that rely on these quiescent periods is a statistical process involving the anticipated quiescence properties of the forecasted sea conditions in the geographical region of interest. It is in principle possible to obtain such data in tabular form either large scale simulation or from field data. However, such simulations are computationally intensive and libraries of appropriate field data are not common. Thus, it is clearly attractive to develop techniques that exploit standard wave spectral models for describing the quiescence statistics directly from such spectra. The present study focuses upon such techniques and is a first step towards the production of a computationally low-cost quiescence prediction tool and compares its efficacy against simulations. Two significant properties emerge for a large class of wave spectral models that encompasses the ubiquitous Neumann and Pierson Moskowitz or Bretschneider forms. Firstly, the auto-correlation function of the wave profile that are required to produce the quiescence property can be obtained analytically in terms of standard special functions. This considerably reduces the computational cost making desktop computer-based planning tools a reality. Secondly, for each class of these parametric spectra, the probability of a given number of consecutive wave heights (normalised to the significant wave heights) less than some critical value is in fact independent of absolute wave height. Thus, for a broad class of practically interesting wave spectra all that is required to obtain the statistical distribution of the quiescent periods is simple rescaling.     

基于支持向量机的京津冀城市群热环境时空形态模拟

城市群热环境作为区域生态重要组成部分,已成为近年来的研究热点。而如何选择针对城市群这种复杂地地貌特征的热环境量化工具一直是亟待解决的技术难点,基于此本研究提出了一种解决多样本、非线性、非平稳及高维函数拟合的计算方法,并建立了基于支持向量机(SVM)的京津冀城市群热环境曲面模型来揭示城市群热环境的时空形态变化。研究结果表明：① SVM模型在刻画多核心、多种土地利用类型城市群热环境的空间分布方面具有理论与实践可行性,能够根据热环境的整体空间布局通过高斯核函数进行局部优化差值,最大限度减少缺省值对模型拟合结果的影响。相比于对照方法可以模拟出更高精度的复杂地貌特征城市群热岛空间分布格局;② 在SVM模型曲面拟合的过程中,拟合精度和拟合时间是衡量拟合结果的重要指标,而原始影像的分辨率则是影响该指标的决定性因素;③ 2003-2013年区域内北京市与天津市的城市热岛效应变化最为明显,热岛面积分别增加7091 km²与4196 km²,空间上呈现出逐年接近连片发展趋势,热岛重心移动轨迹具有明显的时空分异性。北京城市热岛特征为东南部地区异速增长,西部地区缓慢增长;天津城市热岛特征为以城市中心为圆心向周围扩展。本研究进一步丰富了城市群热环境评测的定量方法,可以在实践上对城市群的城市规划、城市建设、环境保护和区域可持续发展等提供定量化、可视化的决策支持。     

Simulation of landscape spatial layout evolution in rural-urban fringe areas: a case study of Ganjingzi District

In recent years, the rapid expansion of urban spaces has accelerated the mutual evolution of landscape types. Analyzing and simulating spatio-temporal dynamic features of urban landscape can help to reveal its driving mechanisms and facilitate reasonable planning of urban land resources. The purpose of this study was to design a hybrid cellular automata model to simulate dynamic change in urban landscapes. The model consists of four parts: a geospatial partition, a Markov chain (MC), a multi-layer perceptron artificial neural network (MLP-ANN), and cellular automata (CA). This study employed multivariate land use data for the period 2000–2015 to conduct spatial clustering for the Ganjingzi District and to simulate landscape status evolution via a divisional composite cellular automaton model. During the period of 2000–2015, construction land and forest land areas in Ganjingzi District increased by 19.43% and 15.19%, respectively, whereas farmland, garden lands, and other land areas decreased by 43.42%, 52.14%, and 75.97%, respectively. Land use conversion potentials in different sub-regions show different characteristics in space. The overall land-change prediction accuracy for the subarea-composite model is 3% higher than that of the non-partitioned model, and misses are reduced by 3.1%. Therefore, by integrating geospatial zoning and the MLP-ANN hybrid method, the land type conversion rules of different zonings can be obtained, allowing for more effective simulations of future urban land use change. The hybrid cellular automata model developed here will provide a reference for urban planning and policy formulation.     

Estimation of crowd density from UAVs images based on corner detection procedures and clustering analysis

With rapid developments in platforms and sensors technology in terms of digital cameras and video recordings, crowd monitoring has taken a considerable attentions in many disciplines such as psychology, sociology, engineering, and computer vision. This is due to the fact that, monitoring of the crowd is necessary to enhance safety and controllable movements to minimize the risk particularly in highly crowded incidents (e.g. sports). One of the platforms that have been extensively employed in crowd monitoring is unmanned aerial vehicles (UAVs), because UAVs have the capability to acquiring fast, low costs, high-resolution and real-time images over crowd areas. In addition, geo-referenced images can also be provided through integration of on-board positioning sensors (e.g. GPS/IMU) with vision sensors (digital cameras and laser scanner). In this paper, a new testing procedure based on feature from accelerated segment test (FAST) algorithms is introduced to detect the crowd features from UAV images taken from different camera orientations and positions. The proposed test started with converting a circle of 16 pixels surrounding the center pixel into a vector and sorting it in ascending/descending order. A single pixel which takes the ranking number 9 (for FAST-9) or 12 (for FAST-12) was then compared with the center pixel. Accuracy assessment in terms of completeness and correctness was used to assess the performance of the new testing procedure before and after filtering the crowd features. The results show that the proposed algorithms are able to extract crowd features from different UAV images. Overall, the values of Completeness range from 55 to 70 % whereas the range of correctness values was 91 to 94 %.     

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.     

Grey relational analysis on the relation between marine environmental factors and oxidation-reduction potential

The effects of marine environmental factors-temperature(T),dissolved oxygen(DO),salinity(S) and pH-on the oxidation-reduction potential(ORP) of natural seawater were studied in laboratory.The results show an indistinct relationship between these four factors and the ORP,but they did impact the ORP.Common mathematical methods were not applicable for describing the relationship.Therefore,a grey relational analysis(GRA) method was developed.The degrees of correlation were calculated according to GRA and the va...