2008年大柴旦M_w6.3级地震的InSAR同震形变观测及断层参数反演

2008年11月10日,青海省大柴旦地区发生了Mw6.3级地震。本文利用EnviSat卫星升降轨SAR数据和差分干涉测量技术提取了同震形变场,基于均匀位错模型反演确定了地震断层参数,然后利用格网迭代搜索法确定了较优断层倾角,同时基于非均匀位错模型获得了精细滑动分布。结果表明,地震使得上盘区域沿降轨、升轨视线向分别产生最大约8.5cm、10cm的抬升;较优断层倾角为47.9°;地震滑动未延伸至地表,主要发生在地下8.2~23.7km深度范围内,最大和平均滑动量为0.5m和0.19m,平均滑动角为104.9°。反演的地震矩为3.74×1018 N·m,矩震级为Mw6.35。     

Visualizing spatiotemporal trajectories of mobile social media users using space–time cube

The implementation of social network applications on mobile platforms has significantly elevated the activity of mobile social networking. Mobile social networking offers a channel for recording an individual’s spatiotemporal behaviors when location-detecting capabilities of devices are enabled. It also facilitates the study of time geography on an individual level, which has previously suffered from a scarcity of georeferenced movement data. In this paper, we report on the use of georeferenced tweets to display and analyze the spatiotemporal patterns of daily user trajectories. For georeferenced tweets having both location information in longitude and latitude values and recorded creation time, we apply a space–time cube approach for visualization. Compared to the traditional methodologies for time geography studies such as the travel diary-based approach, the analytics using social media data present challenges broadly associated with those of Big Data, including the characteristics of high velocity, large volume, and heterogeneity. For this study, a batch processing system has been developed for extracting spatiotemporal information from each tweet and then creating trajectories of each individual mobile Twitter user. Using social media data in time geographic research has the benefits of study area flexibility, continuous observation and non-involvement with contributors. For example, during every 30-minute cycle, we collected tweets created by about 50,000 Twitter users living in a geographic region covering New York City to Washington, DC. Each tweet can indicate the exact location of its creator when the tweet was posted. Thus, the linked tweets show a Twitter users’ movement trajectory in space and time. This study explores using data intensive computing for processing Twitter data to generate spatiotemporal information that can recreate the space–time trajectories of their creators.     

DWG三维模型自动转换为X三维模型的方法研究

DWG三维模型作为一种成熟的三维模型格式已广泛应用于各领域,但在实际工作中,往往需要将其放置到多种三维设计平台中,而许多平台并不直接支持该格式,这限制了DWG格式三维模型的重复利用。本文首先分析了DWG三维模型格式,而后利用DWG.SDK二次开发包,实现了将DWG三维模型转换为X三维模型的方法并通过实例对该方法进行了验证,该方法拓宽了DWG三维模型的应用范围。     

河南省农作物虚拟水含量时空分异特征

在GIS技术的支持下,通过对1978—2013年河南省冬小麦、夏玉米、花生、棉花、油料作物、蔬菜6种主要农作物虚拟水量的计算与分析,探讨了其时空分异规律。河南省6种农作物单位质量虚拟水量在不断下降的趋势下有波动,2003年出现峰值,与当年大旱、所有农作物大面积减产有关;在农作物类型中,棉花单位质量虚拟水含量最高,多年平均值达到8 077.4 m3/t,蔬菜最低,多年平均值仅为159.95 m3/t。6种作物的虚拟水含量在空间分布上有明显差异,按其2013年的产量进行加权分析得到,第一等级区域为三门峡、郑州、信阳,第二等级为平顶山、洛阳、济源、开封,第三等级为南阳、驻马店、新乡、鹤壁、安阳、濮阳,第四等级为漯河,最低为许昌、周口、商丘、焦作。从整体看,西部、南部虚拟水含量高,而北部、东部虚拟水含量低。     

图解法和矩值法计算西台吉乃尔盐湖沉积物粒度参数的差异

柴达木盆地西部的西台吉乃尔盐湖既是研究成盐演化的典型湖泊,也是一个重要的盐湖资源产地。盐湖沉积物的粒度组成记录了湖泊沉积环境和动力条件的变化,对于理解盐湖的形成演化具有指示意义。目前有关盐湖沉积物粒度参数(平均粒径、标准偏差、偏度和峰度)计算的报道较少。采用Beckman Coulter LS 13320激光粒度仪测定了西台吉乃尔盐湖沉积剖面(XT剖面,240 cm厚)121个样品的粒度组成,并对图解法和矩值法计算出来的粒度参数进行了比较。分析结果表明,1)图解法和矩值法得出的平均粒径和标准偏差非常一致,二者可以相互替代;2)两种方法得出的偏度和峰度存在显著差别,二者不可替代;3)矩值法计算整体考虑了样品粒度的频率分布特征,得到的粒度参数比图解法更全面。     

A mechanism for the origin and development of the large-scale dunefield on the right flank of the lower reach of Laoha River, Northeast China

By viewing satellite imagery, a striking large-scale dunefield can be clearly perceived, with a size of nearly 63 km long and 11 km wide, and trending NE–SW, on the right flank of the lower Laoha River, Northeast China. By means of remote sensing imagery analysis and field observation as well as a comparison with a small-scale dunefield on the right flank of the lower Xiangshui River, analogous to the case of the lower Laoha River, this paper presents a new mechanism for its origin and development. The results show that:(1) the large-scale dunefield bears a tile-style framework overwhelmingly composed of transverse barchanoid ridges perpendicular to the predominant winds, and inlaid diverse blowouts.(2) The small-scale dunefield, referred to as a primary structural unit of the large one, is typical of an incipient dunefield, following the same rules of evolution as the larger.(3) A succession of barchanoid ridge chains can steadily migrate downwind in much the same manner as surface wave propagation in air or water stimulated by an incised valley, and ultimately tend to bear roughly the same wavelength and amplitude under stable climate and hydrologic regimes.(4) The first ridge chain acquires its sand source substantially from the downwind escarpments exposing the loose Quaternary sandy sediments to the air, while the ensuing ridges derive their sands dominantly from in situ deflation of the underlain Quaternary loose sandy sediments in blowouts, partly from the upwind ridges through northern elongated horns. Theoretically, the sands from riparian escarpments can be transported by wind to the downwind distal end of a dunefield after sufficient long duration.(5) The lower Laohahe region experienced probably three significant climatic changes in the past, corresponding to the three active dune belts, suggesting that once a large-scale dunefield occurs, it is nearly impossible to be completely stabilized, at least in its central portions. At present, seasonal shrinkage and stagnation of the lower Laoha River, widespread farming and afforestation in the valley, and establishing windbreaks downwind of the valley as well as surrounding the dunefield, appear to have significantly modified local flow fields and sand sources, engendering significant degradation of the dunefield.     

安徽省含山县土地整理耕地质量评价及其变化研究

土地整理是改善土地利用条件,提高土地质量的有效措施,对土地整理后的耕地质量进行评价是土地整理重要工作之一。从耕地质量的内涵和土地整理项目的基本要求出发,选取耕地自然条件和耕地利用条件2个基本因素和12个影响因子,将特尔斐法与层次分析法相结合,确定各因子权重,构建基于土地整理的耕地质量评价指标体系。以安徽省含山县铜闸镇土地整理项目为例,采用传统的土壤调查与3S技术相结合的方法,分析土地整理复垦过程中耕地质量时空格局变化,得出整理前、后耕地质量的级别变化。研究结果表明,通过土地整理,研究区的耕地质量空间分布和级别发生了很大变化,整理后一级、二级、三级质量的土地比整理前分别增加了7.20%,11.95%和0.65%,四级、五级则分别减少了15.65%和4.16%,整理后的耕地质量总体水平是整理前的1.291倍。     

Exploring the hydrologic response to the urban building coverage ratio by model simulation

Theoretical and Applied Climatology - The increasing building coverage ratio accompanied by the increase in impervious surfaces during the urbanization process may change the flow concentration...     

随机森林机器算法在江苏省小麦赤霉病病穗率预测中的应用

基于2002—2018年江苏省13个市的小麦赤霉病病穗率资料与生育期观测资料、相应时段内的逐日气象数据,应用随机森林机器学习算法,分生育期、分区域定量评估影响病穗率的主要气象因子特征变量和贡献率,按不同起报时间建立预测模型并进行验证。结果表明,各生育期重要特征变量贡献率的排序为:抽穗扬花期＞拔节期＞越冬期。抽穗扬花期湿度、连续≥3 d的雨日和日照对赤霉病起主导作用,拔节期日照、降雨量、湿度和雨日与越冬期气温和降雪对赤霉病均具有前期影响,甄别出的重要特征变量排序结果符合赤霉病菌发育、释放、侵染和流行规律;基于随机森林算法建立的病穗率预测模型的精度与重要特征变量个数、赤霉病发生区域、M_try参数设定、生育期有关;最早可在3月初进行预测,预测时效近3个月,起报时间越接近乳熟期,输入的重要特征变量越多,则病穗率预测准确率越高,病穗率模拟值与实测值的波动趋势完全一致,对赤霉病“中等”和“偏重”等级模拟效果好,表明随机森林算法在赤霉病预测中有较高的可靠性和业务应用潜力。