卫星时态信息可视化技术研究

时间问题是地理学中一个基本的研究问题,针对当前时空数据模型较多,而可视化研究相对较少的现状,总结、探讨了时态信息可视化所需要的插值、动画、交互等相关技术,重点研究了当前我国卫星影像实时获取能力不能满足用户较高时间分辨率分析的情况,提出了相应的改进方法,探索了时空尺度与分辨率的匹配与可视化表达方法、多目标时间协调等问题,并在影像数据的基础上,实现了时态信息的动态显示。     

基于动态基态方法的基态修正时空数据模型

本文在分析现有时空数据基态修正模型的基础上,提出一种基于动态基态的时空数据基态修正方法,引入了动态基态数据与动态数据存储区域的概念。解决了重复检索历史数据以及对时间段的检索效率低下的问题,具有基态数据占用空间较小,数据检索速度快的特点,且当历史年代久远时,存储空间最小。     

基于变点的时空异常模式研究

异常模式的探测具有很好的实用价值和生产指导意义,本文首先对目前国内外时空异常模式方面的研究工作做了介绍。然后基于时空变点的概念给出了时空异常的定义,在此基础上结合大气污染监测数据对基于变点的时空异常模式进行探测。     

A spatio-temporal method for crime prediction using historical crime data and transitional zones identified from nightlight imagery

ABSTRACT

Accurate crime prediction can help allocate police resources for crime reduction and prevention. There are two popular approaches to predict criminal activities: one is based on historical crime, and the other is based on environmental variables correlated with criminal patterns. Previous research on geo-statistical modeling mainly considered one type of data in space-time domain, and few sought to blend multi-source data. In this research, we proposed a spatio-temporal Cokriging algorithm to integrate historical crime data and urban transitional zones for more accurate crime prediction. Time-series historical crime data were used as the primary variable, while urban transitional zones identified from the VIIRS nightlight imagery were used as the secondary co-variable. The algorithm has been applied to predict weekly-based street crime and hotspots in Cincinnati, Ohio. Statistical tests and Predictive Accuracy Index (PAI) and Predictive Efficiency Index (PEI) tests were used to validate predictions in comparison with those of the control group without using the co-variable. The validation results demonstrate that the proposed algorithm with historical crime data and urban transitional zones increased the correlation coefficient by 5.4% for weekdays and by 12.3% for weekends in statistical tests, and gained higher hit rates measured by PAI/PEI in the hotspots test.     

吉林市土地利用时空变化及驱动力分析

为了借助系统论中的信息论为城市土地利用结构的优化提供决策支持,文章基于吉林市1996—2008年的土地利用变更数据和特征年份的遥感影像,选取信息熵、均衡度与优势度等评价指标,对该地区土地利用变化进行时空分析,并探索影响其结构变化的主要驱动因子。结果表明,吉林市近年来土地利用的信息熵在逐渐降低,其土地利用结构在稳步趋于有序化;信息熵的空间差异明显,表现出由市区向周边市县递减,东南低西北高的趋势;经济增长及产业结构调整、人口增长与相关政策等作为驱动因素均在不同程度上制约其发展变化。     

城市空间结构对惠州市中心城区交通事故影响的时间差异分析

利用惠州的交通事故数据,结合惠州的土地利用类型及重要设施的分布数据来探讨城市空间结构对交通事故的影响,使用Kernel核心密度法定性探讨交通事故密度的时空变化,把土地类型及重要设施抽象化为点空间要素,建立对数线性回归模型定量讨论城市空间结构对城市交通事故影响的时间差异。分析结果表明,在各个时期惠城区商业用地对交通事故的影响均很显著;工作地和车站对交通事故的影响主要体现在交通流高峰及消散期2个时间段内,但影响程度比商业用地低;在交通流次高峰时,交叉口和工作地的交互作用容易导致事故的高发;城市空间结构通过聚集人流或影响人们的出行等方式对交通事故的发生产生影响。     

基于GIS的区域群发性降雨型滑坡时空预报研究

以滑坡灾害突出的雅安市雨城区为例,综合考虑降雨强度、前期降雨量及下垫面(地形、岩性、植被覆盖等)构建了基于GIS分析获取的易发指数+BP型神经网络时空预报模型。首先通过试验确定了模型的网络参数和网络结构,然后通过危险性区划图获取降雨型滑坡易发指数,并利用GIS的空间插值功能和雨量站数据获取相应降雨型滑坡的雨量数据,将量化后下垫面的易发指数和降雨数据作为神经元输入层数据。将模型应用于研究区,其中46个降雨型滑坡数据作为训练样本,10个降雨型滑坡数据作为检验样本,预测精度达到90%,显示该模型对于降雨型滑坡的时空预报精度较高。     

2001-2010年蒙古国MODIS-NDVI时空变化监测分析

利用2001 - 2010年的空间分辨率为1km的MODIS-NDVI数据,以蒙古国为研究区域,利用最大值合成法、均值法与差值法、一元线性回归等方法,分析了不同季节下植被覆盖的年内变化、年际变化与波动趋势、空间变化特征.结果表明:M(ODIS- NDVI对植被的生长变化具有较高的敏感度,可有效应用于植被生态的评估和监测...     

A spatio-temporal data model for road network in data center based on incremental updating in vehicle navigation system

The technique of incremental updating,which can better guarantee the real-time situation of navigational map,is the developing orientation of navigational road network updating.The data center of vehicle navigation system is in charge of storing incremental data,and the spatio-temporal data model for storing incremental data does affect the efficiency of the response of the data center to the requirements of incremental data from the vehicle terminal.According to the analysis on the shortcomings of several ...     

Long-term trends in the structure of eastern Adriatic littoral fish assemblages: Consequences for fisheries management

Long-term interannual changes in abundance, biomass, diversity and structure of littoral fish assemblages were examined between 1993 and 2009 by experimental trammel net fishing up to six times per year, within the warm period - May to September, at multiple areas along the eastern Adriatic coast with the aim of testing for the consistency of patterns of change across a large spatial scale (∼600 km). The results revealed spatially consistent increasing trends of total fish abundance and biomass growing at an average rate of 15 and 14% per year, respectively. Of the diversity indices analysed, the same pattern of variability was observed for Shannon diversity, while Pielou evenness and average taxonomic distinctness measures Δ^∗ and Δ⁺ showed spatial variability with no obvious temporal trends. Multivariate fish assemblage structure underwent a directional change displaying a similar pattern through time for all the areas. The structural change in fish assemblages generally involved most of the species present in trammel net catches. A large pool of fish species responsible for producing the temporal pattern of assemblage change was relatively different in each of the areas reflecting a large geographic range covered by the study. An analysis of 4 fish species (Symphodus tinca, Pagellus erythrinus, Mullus surmuletus, Scorpaena porcus) common to each of the study areas as the ones driving the temporal change indicated that there were clear increasing trends of their mean catches across the years at all the study areas. A common pattern among time trajectories across the spatial scale studied implies that the factor affecting the littoral fish assemblages is not localised but regional in nature. As an underlying factor having the potential to induce such widespread and consistent improvements in littoral fish assemblages, a more restrictive artisanal fishery management that has progressively been put in place during the study period, is suggested and discussed.