基于智能公交卡数据的出行行为的时空间分析及规划启示——以布里斯班为例

智能公交卡作为越来越普遍的城市公共交通付费方式产生了大量详细的出行数据。这种大数据的出现为出行行为研究特别在时空间方面带来新的机会和挑战。以布里斯班为例,展示了一种地理可视化方法——条件流量图及其在分析智能公交卡数据方面的应用。对该数据进行可视化后,揭示了基于巴士公交的出行在一个城市尺度下相对精细的时空间分布和特征,以及在不同因素(包括快速巴士公交道、乘客组群和天气)作用下的变化。这些发现对建立城市公交系统更有针对性地规划和运营以更好满足乘客出行需求有一定的启示作用。同时,未来研究需要进一步完善和补充智能公交卡数据,并发展更成熟的分析方法。

林西地区强对流天气过程时空间特征分析及其对农业的影响

文章利用内蒙古自治区林西县X波段单偏振多普勒雷达资料对林西地区强对流天气发展演变的时空间特征进行总结分析,并对农业的影响进行了阐述。结果表明:林西地区强对流天气过程集中于6—8月份,其中7月份强对流过程较其他月份明显偏多,强对流天气过程活动的时空间分布特征与林西地区降水量的时空间分布特征存在明显的相关关系;全天内强对流活动主要发生时段为中午前后,傍晚至入夜前强对流活动较显著;林西地区强对流天气活动主要移动路径为1纵3横,主要移动方向为西北—东南方向,在路径交汇处有3个关键区。利用强对流天气活动的时空间分布特征,可有效针对林西地区夏季强对流天气的短时、临近预报、灾害天气预警以及人影防范强对流天气工作作出指导。

基于社交媒体签到数据的城市居民暴雨洪涝响应时空分析

暴雨洪涝等小型地域性气候灾害给城市韧性带来挑战。以南京暴雨洪涝为例,通过挖掘新浪微博签到数据,构建公众感知指数和公众情绪指数,分析居民对暴雨洪涝响应的时空格局。在时间维度上,居民对暴雨洪涝的响应主要集中在暴雨洪涝期,并随灾害的严重程度而变化;在暴雨洪涝期内,居民在社交媒体上对暴雨洪涝的响应集中在早、晚高峰。在空间维度上,居民对暴雨洪涝的响应集中在主城区和3个新市区;重要交通基础枢纽地区和低海拔、经历快速城市化的新市区的居民对暴雨洪涝担忧程度更高。时空分析表明,暴雨洪涝对居民的交通出行影响最明显。基于时空间分析,最后从硬件和软件设施上为提升暴雨洪涝的城市韧性提供相关政策建议。

空间时频分布中的信号分类

空间时频分布可被用于信号盲分离和来波到达角的高分辨率估计等领域,在空间时频分布矩阵中选择合适的时频点是基于空间时频分布的阵列信号处理算法的关键。分析了空间时频分布矩阵的结构特征,通过无约束最优化方法在时频平面上搜索单一信号项的时频点,然后使用改进的最邻近法对时频点按来波类型进行分类,可以区分具有不同时频特征的方向相近的多个信号。

基于多分辨率动态模态分解的电磁信号时频-能量分析

针对电磁信号时-频-空间-能量分析不兼容的问题,提出一种基于分解时空域电磁辐射信号的数据驱动方法来分析复杂电磁环境。首先,使用多分辨率动态模态分解方法将复杂电磁信号以不同的分辨率分离为不同时空尺度的模态分量。然后,利用时频分布对各模态瞬时频率和能量特征进行采集。这种动态的分解分析方式能快速侦测电路和电子系统的多方面电磁环境状态,具有不需要先验数据训练,不受时频分辨率限制,可以实时分析和降低数据维数等优点,且提取的动态模式及其频谱分别在空间域和时域具有明确的物理意义。仿真实验显示,重组信号和原信号的平均误差在-18 dB以下,证明了所提方法的可行性和优势。

中心城区绿道智能选线规划研究——以宿迁为例

【目的】当前在绿道系统规划分析中较少应用自下而上的人本分析视角和时空间行为分析方法,缺乏对居民在绿道中行为方式的研究,在方法上对于机器学习的应用仍然处于探索阶段。【方法】以经典设计理论作为支撑,选取宿迁市中心城区作为案例地,整合手机信令数据、居民活动数据、街景数据等多源数据,借助人工智能、LSTM神经网络、时空行为分析等量化分析方法,分析居民真实出行的时空特征,提出绿道智能选线分析框架。【结果】结合LSTM神经网络、类A*算法等构建的轨迹模拟模型可有效开展绿道选线评估,模拟居民真实出行行为,提取潜在绿道网络。【结论】构建了中心城区绿道智能选线方法,将居民真实活动轨迹融入空间要素分析中,融合居民出行行为特征与街道环境要素,通过量化评估方法为绿道选线规划和建设提供指导。

城市交通消散期事故高峰现象及成因

学界对于交通事故高峰出现在交通高峰期还是之后的消散期存在争论,以惠州市中心城区为例,对城市交通事故进行研究,判别交通消散期事故高峰现象的存在性。以交通事故空间点数据为研究对象,使用核心密度估算法,分析交通事故的结构性特征和时空分布特征,并针对三个交通消散期研究其事故的具体特征及其成因。研究表明:惠州市中心城区交通消散期存在事故高峰现象,主要发生在上午和下午;机动车在交通事故中占主导地位;临近商业设施的交通消散期事故高峰现象最为明显;支路事故在晚间交通消散期后段出现了事故高峰;从上午到晚上,交通事故黑点从交通相关设施转移到商业设施。交通消散期事故高峰现象的形成与居民集中在交通消散期的非通勤交通行为、特定路段的小时交通量高峰出现在交通消散期,以及交通消散期内松懈的交通管制和驾驶行为等有一定的关系。

Prediction and Analysis of O_3 based on the ARIMA Model

The research conducted prediction on changes of atmosphere pollution during July 9, 2014-July 22, 2014 with SPSS based on monitored data of O3 in 13 successive weeks from 6 sites in Baoding City and demonstrated prediction effect of ARIMA model is good by Ljung-Box Q-test and R2, and the model can be used for prediction on future atmosphere pollutant changes.

PC-based artif icial neural network inversion for airborne time-domain electromagnetic data

Traditionally, airborne time-domain electromagnetic （ATEM） data are inverted to derive the earth model by iteration. However, the data are often highly correlated among channels and consequently cause ill-posed and over-determined problems in the inversion. The correlation complicates the mapping relation between the ATEM data and the earth parameters and thus increases the inversion complexity. To obviate this, we adopt principal component analysis to transform ATEM data into orthogonal principal components （PCs） to reduce the correlations and the data dimensionality and simultaneously suppress the unrelated noise. In this paper, we use an artificial neural network （ANN） to approach the PCs mapping relation with the earth model parameters, avoiding the calculation of Jacobian derivatives. The PC-based ANN algorithm is applied to synthetic data for layered models compared with data-based ANN for airborne time-domain electromagnetic inversion. The results demonstrate the PC-based ANN advantages of simpler network structure, less training steps, and better inversion results over data-based ANN, especially for contaminated data. Furthermore, the PC-based ANN algorithm effectiveness is examined by the inversion of the pseudo 2D model and comparison with data-based ANN and Zhody＇s methods. The results indicate that PC-based ANN inversion can achieve a better agreement with the true model and also proved that PC-based ANN is feasible to invert large ATEM datasets.

基于空间时频分布的信号源数目估计

基于信号空间时频分布的到达角(DOA)估计算法利用Cohen类分布构造空间时频分布矩阵D_(xx)(t,f)代替传统的阵列协方差矩阵R_(xx),信源数目判断是阵列测向中的重要课题,在基于空间时频分布的DOA算法基础上,对阵列观测结果的空间时频分布矩阵进行模式识别,通过搜索来波在时频平面的信号项进行聚类,可以在信号源数目多于阵元数时判断来波数量。

SPATIAL DISTRIBUTION AND VARIATION TENDENCY OF DROUGHTS AND FLOODS IN HUNAN PROVINCE DURING THE PAST 36 YEARS

Using the 1970-2005 annual precipitation and evaporation data at 80 gauge stations across Hunan province,this work analyzes the spatial distribution and variation tendency of the local droughts and floods using linear regression,wavelet analysis,abrupt change,clusters,Empirical Orthogonal Function (EOF) and rotated EOF (REOF).Results show that there are four dry areas and three wet areas in Hunan.The whole province exhibits a moistening trend except some small areas in western,eastern and southern Hunan.The most prominent feature of annual precipitation is that the whole province basically displays a consistent variation tendency,as far as the dominant EOF mode is concerned.In addition,the spatial features of the other EOF modes include dry-wet differences,e.g.wet (or dry) in the north versus dry (or wet) in the south,wet (or dry) in the center and dry (or wet) in the surrounding areas.The distribution of the ratios of evaporation to precipitation exhibits both common features as well as spatial differences,which can be classified into four types:South Hunan,North Hunan,Northeast Hunan,and Central Hunan.There is an abrupt change from dry to wet patterns in the early 1990s.Generally,the drought-flood distribution presents variations of three periods.In the late 2000s,Hunan province will be in a period of drought,followed by a period of flood.

Differential Space Frequency Mapping Schemes and Norm Criterion

This paper proposed four types of differential modulation to map the unitary code into the orthogonal frequency division multiplexing(OFDM) signal. The time-varying channel model is established and the norm of detection metric is deduced. The norm is the inherent interference of the time-varying channel, so it can be used as criterion to evaluate the performance of the mapping schemes. The simulation results agree with the analytic conclusion.

Temporal Data Mining Using Genetic Algorithm and Neural Network——A Case Study of Air Pollutant Forecasts

This paper integrates genetic algorithm and neura l network techniques to build new temporal predicting analysis tools for geographic information system (GIS). These new GIS tools can be readily applied in a practical and appropriate manner in spatial and temp oral research to patch the gaps in GIS data mining and knowledge discovery functions. The specific achievement here is the integration of related artificial intellig ent technologies into GIS software to establish a conceptual spatial and temporal analysis framework. And, by using this framework to develop an artificial intelligent spatial and tempor al information analyst (ASIA) system which then is fully utilized in the existin g GIS package. This study of air pollutants forecasting provides a geographical practical case to prove the rationalization and justness of the conceptual tempo ral analysis framework.

Painlevé Integrability of Nonlinear Schrdinger Equations with both Space-and Time-Dependent Coefficients

We investigate the Painleve integrabiiity of nonautonomous nonlinear Schr6dinger （NLS） equations with both space-and time-dependent dispersion, nonlinearity, and external potentials. The Painleve analysis is carried out without using the Kruskal＇s simplification, which results in more generalized form of inhomogeneous equations. The obtained equations are shown to be reducible to the standard NLS equation by using a point transformation. We also construct the corresponding Lax pair and carry out its Kundu-type reduction to the standard Lax pair. Special cases of equations from choosing limited form of coefficients coincide with the equations from the previous Painleve analyses and/or become unknown new equations.

Remote sensing needs and capabilities in West Africa

The greatest advantage of remote sensing over conventional measurements lies in the opportunity to carry out detailed spatio-temporal analysis of land and ocean features on a very frequent basis. This paper analyses the contribution of satellite imagery to atmospheric, geophysical and ocean studies and management in West Africa since the early 1980s. The detailed application of data from optical sensors (e.g. Meteosat,NOAA/AVHRR, SPOT, Landsat TM, etc.) for weather prediction, hydrogeologicah landuse/cover and cartographic studies has been acknowledged. However, the use of microwave (e.g. SAR) and optical data for ocean monitoring and studies in the sub-region is still very limited. Even though sufficient remote sensing expertise and infrastructure is perceived in the region, no clearly defined networking or database exists.

Spatial Distribution of Archaeological Sites in Lakeshore of Chaohu Lake in China Based on GIS

There are about 19 Neolithic Age sites and 120 Shang-Zhou dynasties sites in the western lakeshore of Chaohu Lake,Anhui Province,China.Based on sites data,topographic data,drainage maps,administrative maps and SPOT5 remote sensing data,spatial analysis methods were introduced into the archaeology of Chaohu Lake Basin with Geographic Information System(GIS).The spatial analysis methods include:1) Point Density Analysis with density model to acquire the shift of the sites;2) Distance Analysis to reveal the spatial structure of the sites;3) 3D Analysis based on Digital Elevation Model to get micro-geomorphologic features of the sites;and 4) Buffer Analysis to discover the relationship between the sites and rivers.The results indicate that the archaeological sites spread from the western lakeshore of Chaohu Lake gradually to the northwest,later to the south,and then symmetrically spread.Controlled by productive forces and other factors,ancient people preferred to reside in those places near water,or in plain and fertile land,which resulted in linear and decentralized distribution of the sites,and presented such disciplines as river valley directivity,terrace directivity and soil directivity.This paper indicates that the distribution of archaeological sites was influenced earlier by natural elements and later by human elements in the study period.The research is important for the integration of GIS and archaeology.

ADM Mass for Asymptotically de Sitter Space-Time

In this paper,an ADM mass formula for asymptotically de Sitter(dS) space-time is derived from theenergy-momentum tensor.We take the vacuum dS space as the background and investigate the ADM mass of the(d + 3)-dimensional sphere-symmetric space with a positive cosmological constant,and find that the ADM mass ofasymptotically dS space is based on the ADM mass of Schwarzschild field and the cosmological background brings somesmall mass contribution as well.

Space and Temporal Distribution Analysis of Interictal Spike in Epilepsy

Stereo-electroencephalography （SEEG） is the main investigation method for pre-surgical evaluation of patients suffering from drug-resistant partial epilepsy. SEEG signals reflect two types of paroxysmal activity： ictal activity and interictal activity or interictal spikes （IS）. The relationship between IS and ictal activity is an essential and recurrent question in epiletology. In this paper, we present a distributed and parallel architecture for space and temporal distribution analysis of IS, based on a distributed and collaborative methodology. The proposed approach exploits the SEEG data using vector analysis of the corresponding signals among multi-agents system. The objective is to present a new method to analyze and classify IS during wakefulness （W）, light sleep （LS） and deep sleep （DS） stages. Temporal and spatial relationships between IS and seizure onset zone are compared during wakefulness, light sleep and deep sleep. Results show that space and temporal distribution for real data are not random but correlated.

Spatiotemporal spectrum and momentum flux of the stratospheric gravity waves generated by a typhoon

The simulation results of Typhoon Matsa （2005） by using the Weather Research and Forecasting （WRF） model show that pro- nounced stratospheric gravity waves （GWs） are generated in the vicinity of the typhoon. Using the model output, we investi- gate the spatial structures and the temporal variations of the GWs through a three dimensional （3-d） spectral analysis, i.e. the spectrum with respect to two horizontal wavenumbers and frequency. We further derive the momentum flux carried by the GWs. Spectral investigation results show that the power spectral density （PSD） of the GWs exhibits a single-peaked spectrum, which consists primarily of a distinct spectrum at horizontal wavelength of -1000 km, time period of 12-18 h, and vertical wavelength of 7-9 kin. This spectrum is different from the spectra of GWs generated by deep convections disclosed by the previous researches. Both the PSD and momentum flux spectrum are prominent in positive kh portion, which is consistent with the fact that the GWs propagate in the upstream of mean flow. Large momentum flux is found to be associated with the GWs, and the net zonal momentum flux is 0.7845×10-3 Pa at 20 km height, which can account for -26% of the momentum flux that is required in driving the QBO phenomenon.

Spatio-temporal analysis and simulation on shallow rainfall-induced landslides in China using landslide susceptibility dynamics and rainfall I-D thresholds

An empirical simulation method to simulate the possible position of shallow rainfall-induced landslides in China has been developed.This study shows that such a simulation may be operated in real-time to highlight those areas that are highly prone to rainfall-induced landslides on the basis of the landslide susceptibility index and the rainfall intensity-duration(I-D) thresholds.First,the study on landslide susceptibility in China is introduced.The entire territory has been classified into five categories,among which high-susceptibility regions(Zone 4-'High' and 5-'Very high') account for 4.15%of the total extension of China.Second,rainfall is considered as an external triggering factor that may induce landslide initiation.Real-time satellite-based TMPA3B42 products may provide real rainfall spatial and temporal patterns,which may be used to derive rainfall duration time and intensity.By using a historical record of 60 significant past landslides,the rainfall I-D equation has been calibrated.The rainfall duration time that may trigger a landslide has resulted between 3 hours and 45 hours.The combination of these two aspects can be exploited to simulate the spatiotemporal distribution of rainfall-induced landslide hazards when rainfall events exceed the rainfall I-D thresholds,where the susceptibility category is 'high' or 'very high'.This study shows a useful tool to be part of a systematic landslide simulation methodology,potentially providing useful information for a theoretical basis and practical guide for landslide prediction and mitigation throughout China.