川滇黔邻区龙马溪组页岩气富集主控因素与勘探方向

中国的页岩气资源评价必须立足于中国主要陆块的地质条件与构造演化特点之上,对于不同层系、不同地区的页岩气选区评价,也必须抓住关键因素。川滇黔邻区的五峰组-龙马溪组富有机质页岩发育,但保存条件较渝东南地区更为复杂。印支期以来,该区经历了多期次构造应力场转换,断裂、褶皱发育,因此,建立针对性的页岩气选区评价参数体系是该区页岩气勘探走出困局的当务之急。本文在分析该区已有页岩气钻井成效的基础上,立足于扬子海相层系页岩气勘探应是基于保存条件的"连续型甜点区"的选区评价基本思路,结合前人研究成果,系统梳理出一套评价指标体系。该体系涵盖5大因素(区域盖层、直接盖层、底板条件、页岩层自身条件、构造改造强度)、4个等级、17个选区评价参数。另外,根据已有相关钻井数据,总结提出了5个页岩气层评价表征参数(含气量、孔隙度、电阻率、氮气组分含量和压力系数)。根据该指标体系,对川滇黔邻区的主要构造单元进行了梳理分析,优选出5个有利区,提出了各有利区的首选可能突破点。本研究对复杂构造区页岩气有利区带优选具有一定的指导意义。     

Satellite estimates and subpixel variability of rainfall in a semi-arid grassland

卫星估雨精度的不确定性受到当地降雨类型和像元内降雨非均匀性影响,而结合这两个关键因素开展半干旱草原卫星估雨的研究有限.2009年夏,我们在中国锡林郭勒半干旱草原用多部微雨雷达和雨量计构建了9 km卫星像元降雨观测网,观测了像元内降雨非均匀性(空间变异系数CV),并评估了卫星估雨精度.结果表明:(1)CV值受像元内平均降雨量,降雨类型,降雨云面积及移向等影响,如高Cv值的降雨过程大多为平均降雨量小,对流性降雨过程,降雨云边缘像元CV值较高;(2)TRMM 3B42V7卫星估雨产品适用性较好,CMORPH和PERSIANN次之,但TRMM 3B42V7易在半干旱草原湖泊处高估降雨.     

Comparison of two types of persistent heavy rainfall events during sixteen warm seasons in the Sichuan Basin

本文筛选出四川盆地西部(盆西型)和盆地东部(盆东型)持续性暴雨个例,深入对比两类持续性暴雨的大气环流特征和直接造成持续性暴雨的西南低涡维持的机理.四川盆地的短波槽和西太平洋副热带高压的配置有利于持续性暴雨的维持,盆东型的降水强度较盆西型个例强,高空急流位置偏南,南亚高压的强度更强,高层辐散更强,对流层中层副热带高压偏东偏南.盆西型的水汽输送主要来自南海,而盆东型的水汽输送主要来自南海和孟加拉湾.合成涡度收支的结果表明散度项是两类持续暴雨中西南涡维持的主要原因,但盆西型中,垂直平流的作用更强.     

遵义市袋栽黑木耳最佳栽培期气候条件分析*

为了找出黑木耳在遵义的最佳栽培期,2019年笔者在遵义市气象观测站开展试验,收集并整理黑木耳生长期内逐日气象资料,结合试验数据综合分析,结果显示：（1）平均气温在20℃左右时,对木耳品质形成较为有利,候平均气温＜5℃或≥30℃时不适宜黑木耳生长。（2）除盛夏和初秋相对湿度较低外,其余大部分时段均能满足木耳自然生长,少部分时段需适当浇水。（3）3月至10月候日照时数普遍在10小时以上,适宜黑木耳生长,其中4月4候至9月4候为最适宜期。（4）遵义立体气候特征明显,海拔高度不同木耳适宜生长期时段不同,大部分地区海拔普遍在600～1100米之间,黑木耳生长最佳适宜期为4月3候至6月6候、8月6候至10月5候。     

VGI and crowdsourced data credibility analysis using spam email detection techniques

Volunteered geographic information (VGI) can be considered a subset of crowdsourced data (CSD) and its popularity has recently increased in a number of application areas. Disaster management is one of its key application areas in which the benefits of VGI and CSD are potentially very high. However, quality issues such as credibility, reliability and relevance are limiting many of the advantages of utilising CSD. Credibility issues arise as CSD come from a variety of heterogeneous sources including both professionals and untrained citizens. VGI and CSD are also highly unstructured and the quality and metadata are often undocumented. In the 2011 Australian floods, the general public and disaster management administrators used the Ushahidi Crowd-mapping platform to extensively communicate flood-related information including hazards, evacuations, emergency services, road closures and property damage. This study assessed the credibility of the Australian Broadcasting Corporation’s Ushahidi CrowdMap dataset using a Naïve Bayesian network approach based on models commonly used in spam email detection systems. The results of the study reveal that the spam email detection approach is potentially useful for CSD credibility detection with an accuracy of over 90% using a forced classification methodology.     

A modified mix-differenced approach for estimating multi-GNSS real-time satellite clock offsets

A modified mixed-differenced approach for estimating multi-GNSS real-time clock offsets is presented. This approach, as compared to the earlier presented mixed-differenced approach which uses epoch-differenced and undifferenced observations, further adds a satellite-differenced process. The proposed approach, based on real-time orbit products and a mix of epoch-differenced and satellite-differenced observations to estimate only satellite clock offsets and tropospheric zenith wet delays, has fewer estimated parameters than other approaches, and thus its implementing procedure is efficient and can be performed and extended easily. To obtain high accuracy, the approach involves three steps. First, the high-accuracy tropospheric zenith wet delay of each station is estimated using mixed-differenced carrier phase observations. Second, satellite clock offset changes between adjacent epochs are estimated using also mixed-differenced carrier phase observations. Third, the satellite clock offsets at the initial epoch are estimated using satellite-differenced pseudorange observations. Finally, the initial epoch clock results and clock offset changes are concatenated to obtain the clock results of the current epoch. To validate the real-time satellite clock results, multi-GNSS post-processing clock products from IGS ACs were selected for comparison. From the comparison, the standard deviations of the GPS, GLONASS, BeiDou and Galileo systems clock results are approximately 0.1–0.4 ns, except for the BeiDou GEO satellites. The root mean squares are about 0.4–2.3 ns, which are similar to those of other international real-time products. When the clock estimates were assessed based on a pseudo-kinematic PPP procedure, the positioning accuracies in the East, North and Up components reach 5.6, 5.5 and 7.6 cm, respectively, which meet the centimeter level and are comparable to the application of other products.     

A MATLAB-based Kriged Kalman Filter software for interpolating missing data in GNSS coordinate time series

GNSS coordinate time series data for permanent reference stations often suffer from random, or even continuous, missing data. Missing data interpolation is necessary due to the fact that some data processing methods require evenly spaced data. Traditional missing data interpolation methods usually use single point time series, without considering spatial correlations between points. We present a MATLAB software for dynamic spatiotemporal interpolation of GNSS missing data based on the Kriged Kalman Filter model. With the graphical user interface, users can load source GNSS data, set parameters, view the interpolated series and save the final results. The SCIGN GPS data indicate that the software is an effective tool for GNSS coordinate time series missing data interpolation.     

Mapping hourly dynamics of urban population using trajectories reconstructed from mobile phone records

Understanding the spatiotemporal dynamics of urban population is crucial for addressing a wide range of urban planning and management issues. Aggregated geospatial big data have been widely used to quantitatively estimate population distribution at fine spatial scales over a given time period. However, it is still a challenge to estimate population density at a fine temporal resolution over a large geographical space, mainly due to the temporal asynchrony of population movement and the challenges to acquiring a complete individual movement record. In this article, we propose a method to estimate hourly population density by examining the time‐series individual trajectories, which were reconstructed from call detail records using BP neural networks. We first used BP neural networks to predict the positions of mobile phone users at an hourly interval and then estimated the hourly population density using log‐linear regression at the cell tower level. The estimated population density is linearly correlated with population census data at the sub‐district level. Trajectory clustering results show five distinct diurnal dynamic patterns of population movement in the study area, revealing spatially explicit characteristics of the diurnal commuting flows, though the driving forces of the flows need further investigation.     

An enhanced approach for surface flow routing over drainage‐constrained triangulated irregular networks

The accuracy and efficiency of the simulations in distributed hydrological models must depend on the proper estimation of flow directions and paths. Numerous studies have been carried out to delineate the drainage patterns based on gridded digital elevation models (DEMs). The triangulated irregular network (TIN) has been increasingly applied in hydrological applications due to the advantages of high storage efficiency and multi‐scale adaptive performance. Much of the previous literature focuses mainly on filling the depressions on gridded DEMs rather than treating the special cases in TIN structures, which has hampered its applications to hydrological models. This study proposes a triangulation‐based solution for the removal of flat areas and pits to enhance the simulation of flow routing on triangulated facet networks. Based on the drainage‐constrained TIN generated from only a gridded DEM by the compound point extraction (CPE) method, the inconsistent situations including flat triangles, V‐shape flat edges and sink nodes are respectively identified and rectified. The optimization algorithm is an iterative process of TIN reconstruction, in which the flat areas are generalized into their center points and the pits are rectified by embedding break lines. To verify the proposed algorithm and investigate the potential for flow routing, flow paths of steepest descent are derived by the vector‐based tracking algorithm based on the optimized TIN. A case study of TIN optimization and flow path tracking was performed on a real‐world DEM. The outcomes indicate that the proposed approach can effectively solve the problem of inconsistencies without a significant loss in accuracy of the terrain model.