河西走廊最近一次强沙尘暴的调查分析

1996年5月29~31日在甘肃河西走廊又出现了一次强沙尘暴天气。从这次强沙尘暴和1993年"5·5"强沙尘暴的比较分析可知,春季在河西走廊周围易形成以沙漠为中心的高温低压区,与西西伯利亚向东南方向移动的高压冷气流形成明显的气压梯度,这就是大风的动力源。大风前期,在气温、压温比等方面有明显的预兆,由此可进行强沙尘暴的预测预报。     

Seasonal variation of airborne fungi of the Tiantishan Grottoes and Western Xia Museum,Wuwei, China

In this study, a systematic survey of cultural airborne fungi was carried out in the occurrence environments of wall paintings that are preserved in the Tiantishan Grottoes and the Western Xia Museum, China. A bio-aerosol sampler was used for sampling in four seasons in 2016. Culture-dependent and -independent methods were taken to acquire airborne fungal concentration and purified strains; by the extraction of genomic DNA, amplification of fungal ITS rRNA gene region, sequencing, and phylogenetic analysis, thereafter the fungal community composition and distribution characteristics of different study sites were clarified. We disclosure the main environmental factors which may be responsible for dynamic changes of airborne fungi at the sampling sites. The concentration of cultural airborne fungi was in a range from 13 to 1,576 CFU/m³, no significant difference between the two sites at the Tiantishan Grottoes, with obvious characteristics of seasonal variation, in winter and spring were higher than in summer and autumn. Also, there was a significant difference in fungal concentration between the inside and outside of the Western Xia Museum, the outside of the museum was far more than the inside of the museum in the four seasons, particularly in the winter. Eight fungal genera were detected, including Cladosporium, Penicillium, Alternaria, and Filobasidium as the dominant groups. The airborne fungal community structures of the Tiantishan Grottoes show a distinct characteristic of seasonal variation and spatial distribution. Relative humidity, temperature and seasonal rainfall influence airborne fungal distribution. Some of the isolated strains have the potential to cause biodeterioration of ancient wall paintings. This study provides supporting information for the pre-warning conservation of cultural relics that are preserved at local sites and inside museums.     

基于学籍地址和地理编码的乡村小学教育资源空间可达性分析

基于“学籍信息中的家庭地址承载了学生空间位置”这一假设,通过学籍信息收集了湖南省株洲县小学生的家庭地址,借助高德开放平台提供的地理编码和POI搜索服务,获得到了株洲县小学生的空间位置和分布,并基于最短路径分析和高斯型两步移动搜索法分析了株洲县小学教育资源的空间可达性及其特征,尝试为区域教育资源的空间均衡性分析与规划配置提供新的数据源和方法借鉴。结果表明：① 基于学籍地址和地理编码技术能够较准确地获取株洲县小学生的空间分布。② 株洲县小学生就近入学距离的最大值、平均值和中位数分别为11.83 km、2.10 km和1.81 km,就近入学距离小于2.0 km的学生仅占55.46%,为株洲县兼顾公平和效率的教育资源配置工作带来了挑战。③ 株洲县北部城镇地区因学校数量较多,平均就近入学距离较小,教育资源的空间可达性普遍较高,且空间差异小,均衡性好;而东南部的乡村地区,平均就近入学距离较大,教育资源的空间可达性普遍较低,且空间差异大。④ 基于情景分析,在不造成局地生源稳定性问题的前提下,新增3所学校后,东南部地区的平均就近入学距离和教育资源的空间可达性有很大的改善,龙潭镇和龙门镇的平均入学距离由3784 m和3520 m降低到3116 m和2636 m,教育资源的空间可达性分别由0.0492和0.0982提高到0.0762和0.1496。     

基于POI数据的长沙市生活性服务业空间格局研究

生活性服务业是服务经济的重要组成部分,其合理布局对发展城市经济、满足居民消费需求具有重要作用。基于长沙市六区POI数据,运用核密度分析、熵指数、频数密度分析及空间聚类等方法研究长沙市生活性服务业的空间格局特征,发现长沙市生活性服务业的分布具有以下特点：1）主要受交通及城市规划指向性影响,沿交通主干道集聚分布,整体布局呈“一核四轴多极”且空间分布与人口集中度联系紧密,东西差异明显,东部多而密集、西部少而分散;2）不同类型的生活性服务业分布特征各异,在空间形态上主要表现为“单核心”、“双核心”和“多核心”等;3）其功能多样性布局呈现以五一广场为核心的“中心-外围”结构特征,功能多样且混合程度高的区域位于城市中心,城市边缘区生活性服务业集聚性较弱且多为单一功能或者双功能混合区。     

基于深度学习的GF-1卫星WFV影像赤潮探测方法

赤潮是我国主要的海洋生态灾害,有效监测赤潮的发生和空间分布对于赤潮的防治具有重要意义。传统的赤潮监测以低空间分辨率的水色卫星为主,但是其对于频发的小规模赤潮存在监控盲区。GF-1卫星WFV影像具有空间分辨率高、成像幅宽大和重访周期短等优点,在小规模赤潮监测中表现出较大的潜力。然而,GF-1卫星WFV影像的光谱分辨率较低,波段少,传统面向水色卫星的赤潮探测方法无法应用于GF-1卫星WFV数据。而且赤潮具有形态多变、尺度不一的特点,难以精确提取。基于此,本文提出了一种面向GF-1卫星WFV影像的尺度自适应赤潮探测网络（SARTNet）。该网络采用双层主干结构以融合赤潮水体的形状特征与细节特征,并引入注意力机制挖掘不同尺度赤潮特征之间的相关性,提高网络对复杂分布赤潮的探测能力。实验结果表明,SARTNet赤潮探测精度优于现有方法,F1分数达到0.89以上,对不同尺度的赤潮漏提和误提较少,且受环境因素的影响较小。     

1961-2008年中国西南地区极端气候变化幅度的海拔效应(英文)

A total of 12 indices of temperature extremes and 11 indices of precipitation ex-tremes at 111 stations in southwestern China at altitudes of 285-4700 m were examined for the period 1961-2008. Significant correlations of temperature extremes and elevation in-cluded the trends of diurnal temperature range, frost days, ice days, cold night frequency and cold day frequency. Regional trends of growing season length, warm night frequency, coldest night and warmest night displayed a statistically significant positive correlation with altitude. These characteristics indicated the obvious warming with altitude. For precipitation extreme indices, only the trends of consecutive dry days, consecutive wet days, wet day precipitation and the number of heavy precipitation days had significant correlations with increasing alti-tude owing to the complex influence of atmospheric circulation. It also indicated the increased precipitation mainly at higher altitude areas, whereas the increase of extreme precipitation events mainly at lowers altitude. In addition, the clearly local influences are also crucial on climate extremes. The analysis revealed an enhanced sensitivity of climate extremes to ele-vation in southwestern China in the context of recent warming.     

吉林省西部沙化土地持续农业体系建立的实践

吉林省沙化土地的８７．９％分布在吉林省西部白城、松原半干旱地区，统属科尔沁和松嫩沙地，面积９２１６．５ｋｍ２，占吉林省西部总面积的１９．６％。８年（１９８６年～１９９３年）实践证明：针对沙地环境特点建立的“乔、灌、草”、“果、药、杂”、“田、林、草”为主体的三种持续农业体系效果明显。     

祁连山中部亚高山草地作物系数估算

利用Lysimeter蒸散仪于2011-2014年对祁连山中部黑河上游天涝池流域亚高山草地实际蒸散量进行观测。用FAO Penman-Monteith模型对草地参考蒸散量进行估算,根据草地植被高度结合气象数据,以估算日尺度作物系数,以估算的作物系数与模拟的参考蒸散量计算草地实际蒸散量,并用观测值进行验证。结果表明：FAO改进后的作物系数计算方法适合该区域草地作物系数的计算;以FAO Penman-Monteith模型估算的日蒸散量为0.50~7.26 mm,生长季日均蒸散量有年际变化,2011年 > 2014年 > 2012年 > 2013年。总体来看,土壤蒸发总量年际变化不大,影响蒸散量年际变化的主要部分是植被的蒸腾。     

基于银行网点布局的河南省金融网络格局及结构特征

以河南省126个县域(市区)为研究单元,运用2014年银行业的12 369个网点数据,借鉴连锁型网络模型,运用复杂网络分析工具和空间分析软件对河南省金融网络进行综合测度与结构分析。研究发现:1从金融连接度看,郑州是河南省的金融核心,洛阳是次金融核心;2金融核心具有较高的金融联系度和较强的对外金融联系,同时银行网点在空间上的布局并不完全遵循传统地理空间的行政等级制度;3在实体基础设施网络和银行网点虚拟网络共同作用下,河南省金融网络表现出了等级化和网络化的双重特征;4金融网络中,郑州—洛阳的金融连接度最高,金融连接度存在着一定程度的极化现象,并在空间上呈现出"一体两翼"的格局,且豫北的金融聚集现象较豫南明显;5河南省金融网络拓扑结构图具有较大的集聚系数和较小的平均最短路径,同时度分布在对数坐标中呈现幂律分布,说明整个网络同时具有复杂网络中的小世界网络和无标度网络结构特征。     

Predicting the visualization intensity for interactive spatio-temporal visual analytics: a data-driven view-dependent approach

The continually increasing size of geospatial data sets poses a computational challenge when conducting interactive visual analytics using conventional desktop-based visualization tools. In recent decades, improvements in parallel visualization using state-of-the-art computing techniques have significantly enhanced our capacity to analyse massive geospatial data sets. However, only a few strategies have been developed to maximize the utilization of parallel computing resources to support interactive visualization. In particular, an efficient visualization intensity prediction component is lacking from most existing parallel visualization frameworks. In this study, we propose a data-driven view-dependent visualization intensity prediction method, which can dynamically predict the visualization intensity based on the distribution patterns of spatio-temporal data. The predicted results are used to schedule the allocation of visualization tasks. We integrated this strategy with a parallel visualization system deployed in a compute unified device architecture (CUDA)-enabled graphical processing units (GPUs) cloud. To evaluate the flexibility of this strategy, we performed experiments using dust storm data sets produced from a regional climate model. The results of the experiments showed that the proposed method yields stable and accurate prediction results with acceptable computational overheads under different types of interactive visualization operations. The results also showed that our strategy improves the overall visualization efficiency by incorporating intensity-based scheduling.