纬向平均的风向改变指数与季节转换

通过定义一个能客观定量描述大气环流四维时空变化的风向改变指数WI,用以研究大气环流的时空演变规律和季节转换。在对纬向平均的WI做了经验正交函数(EOF)分析后,得到了其前四个模态。第一模态揭示的是全年平均的WI空间分布的基态。第二模态反映的是WI场的偏差中呈现准调和变化的部分,热带、副热带、温寒带季风区在该模态中均有明显体现。第三模态反映的是WI场的偏差中呈现非调和变化的部分,该部分揭示了因南北半球海陆分布的差异和因大气、海洋流体的非线性效应,其所造成的从春到秋与从秋到春的季节变化的不对称性以及平流层的二月突变现象。第四模态反映的是全球各层盛行风反向区域从春到夏的北进和从夏到秋南撤的现象。     

近30年羌塘自然保护区气候特征分析

本文利用羌塘自然保护区周边6个气象站1978～2007年30年数据,利用气候统计方法,分析了温度、积温、降水的趋势变化。结果表明：该地区年平均温度、年平均最高温度、年平均最低温度都呈上升趋势,且上升幅度远远大于全球、全国平均水平;≥0℃积温、≥5℃积温呈增加趋势,初日提前,终日推迟,持续日数增加;降水的区域特征明显,自东向西呈递减趋势。年降水量呈上升趋势。     

华南地区城市化对区域气候变化的影响

按照人口数将华南地区站点分为大城市站、一般城市站、郊区站,并利用华南地区1960~2011年的站点观测资料分别计算了3类站点年平均、季节平均的气温、高温日数、降水、相对湿度、风速、日照时数距平序列的变化,分析了城市化对华南地区区域气候的影响。结果表明:相较于背景场,大城市的平均气温有更明显的上升趋势;高温日数在3类站点中均有增加的趋势,在城市化的影响下,大城市的高温日数有明显的增加;平均气温日较差在整个华南地区均有下降趋势,特别是在大城市中。在3类站点中,降雨总量均有减少的趋势,且降雨更多的以中雨及以上的形式表现。该地区的相对湿度、风速、日照时数均呈现减少趋势,在城市化影响下,大城市的相对湿度、风速、日照时数均有明显的减少。华南地区处于我国最大的城市群之一——珠江三角洲地区,同时处于气候系统复杂的热带季风区,因此有必要研究城市化对该地区多个气象变量的可能影响。     

边界层臭氧浓度变化特征及相关因子分析

根据广州市城区麓湖、郊区花都测站的2004年污染物监测数据和气象资料,采用统计分析软件SPSS和Excel分析了广州市臭氧浓度的时间变化特征,包括臭氧浓度的年季变化、周变化及日变化特征,并分析了O3与污染物CO、NOx（NO和NO2）、SO2、PM10以及与气象条件之间的相关性。结果表明：广州市臭氧浓度一年出现2个峰值,分别为6月和10月并且郊区浓度大于城区;一周之中最大浓度出现在周末;O3日平均浓度与NOx、NO、CO、相对湿度负相关性较显著,与PM10和气温正相关性较显著;在气温较高、湿度较低的晴朗少云天气时,易造成广州市臭氧的高浓度。     

考虑属性和空间逻辑的地震灾情数据清洗器设计与实现

针对目前地震灾情信息普遍存在的质量问题,根据灾情数据的属性逻辑,采用逻辑分离的清洗框架中基于规则引擎的数据清洗方法进行初步清洗;再从灾情数据的空间逻辑关系出发,通过聚类分析进一步修正数据中存在的错误,弥补基于逻辑分离的清洗框架在孤立点异常检测方面的不足。基于上述规则引擎与空间聚类相结合的清洗技术,设计并实现了一种考虑属性和空间逻辑的地震灾情数据清洗器,并应用于2017年"8·8"九寨沟7.0级地震,分析四川省地震灾情快速上报接收处理系统接收到的客观震感灾情信息。结果表明:地震灾情数据清洗器可快速检测并修正异常的灾情信息,有效提高接收到的灾情数据质量。     

不同轴压比RCS梁柱组合件恢复力模型研究

以6个1/2模型RCS梁柱节点拟静力试验为基础,研究不同轴压比下RCS组合件的滞回性能。试验结果表明:梁铰破坏时试件的滞回曲线饱满,耗能能力优于构造破坏;随着轴压比的增大,试件滞回环愈加丰满,初始刚度有所增加,承载力有所增大;随着加载位移的增加,刚度退化速率变慢,且梁铰破坏时随着轴压比增大,刚度退化速率变大。基于试验结果和现有恢复力模型理论,建立的三折线骨架曲线模型与实际试验骨架曲线具有较高的吻合度,能较好的反映轴压比对其滞回特性的影响,可为该RCS梁柱组合件的弹塑性分析及工程应用提供参考。     

城乡结合部土地利用变化的信息提取技术与分析--以无锡市为例

作为两种截然不同的生态系统过渡区,城乡结合部是土地利用/土地覆被变化最激烈地区之一,城乡结合部的土地利用情况日益受到人们重视.本文以无锡市为例,利用3S技术提取城乡结合部的范围和土地利用/土地覆被状况信息,提出了确定无锡市城乡结合部范围边界的半自动提取模型和结合部土地利用类型半自动提取模型,并对无锡市城乡结合部土地利用结构及其变化进行分析,揭示了无锡市城乡结合部土地利用/土地覆被变化特征,据此提出城乡结合部土地合理利用的建议.     

Change detection of linear features in temporally spaced remotely sensed images using edge-based grid analysis

Automatic change detection of land cover features using high-resolution satellite images, is a challenging problem in the field of intelligent remote sensing data interpretation, and is becoming more and more effective for its applications viz. urban planning and monitoring, disaster assessment etc. In the present study, a change in detection approach based on the image morphology that analyses change in the local image grids is proposed. In this approach, edges from both the images are extracted and grid wise comparison is made by probabilistic thresholding and power spectral density analysis for identifying change area. One of the advantages of the proposed methodology is that the temporal images used in the change analysis need not be radiometrically corrected as analysis is based on edge extractions. The grid-based analysis further reduces the error, which might have been introduced by image mis-registration. The proposed methodology is validated by finding the temporal changes in the linear land cover features in parts of Kolkata city, India using three different image data-sets from LISS IV, Cartosat-1 and Google earth having varied spatial resolutions of 5.8 m, 2.5 m and about 1 m, respectively. The overall accuracy in identifying changes is found to be 64.82, 73.86 and 80.93% for LISS IV, Cartosat-1 and Google earth data-set, respectively.     

基于语义规则的高分辨率影像道路交叉口提取方法

为了准确提取遥感影像上道路交叉口目标,提出一种利用特征语义规则从高分辨率影像上提取道路交叉口的方法。该算法构建交叉口模型时将其视为由同质区域像素集合及区域轮廓边界构成的面对象,提取过程分为两步:1)利用辐射、纹理特征语义匹配提取交叉口候选区域;2)通过几何特征语义匹配筛选候选区域、识别交叉口属性。利用多源遥感影像对算法正确性及合理性进行验证,结果表明:算法能准确、完整地提取道路交叉口,可为影像道路网构建提供辅助信息。     

Updating Landsat time series of surface-reflectance composites and forest change products with new observations

The use of time series satellite data allows for the temporally dense, systematic, transparent, and synoptic capture of land dynamics over time. Subsequent to the opening of the Landsat archive, several time series approaches for characterizing landscape change have been developed, often representing a particular analytical time window. The information richness and widespread utility of these time series data have created a need to maintain the currency of time series information via the addition of new data, as it becomes available. When an existing time series is temporally extended, it is critical that previously generated change information remains consistent, thereby not altering reported change statistics or science outcomes based on that change information. In this research, we investigate the impacts and implications of adding additional years to an existing 29-year annual Landsat time series for forest change. To do so, we undertook a spatially explicit comparison of the 29 overlapping years of a time series representing 1984–2012, with a time series representing 1984–2016. Surface reflectance values, and presence, year, and type of change were compared. We found that the addition of years to extend the time series had minimal effect on the annual surface reflectance composites, with slight band-specific differences (r ≥ 0.1) in the final years of the original time series being updated. The area of stand replacing disturbances and determination of change year are virtually unchanged for the overlapping period between the two time-series products. Over the overlapping temporal period (1984–2012), the total area of change differs by 0.53%, equating to an annual difference in change area of 0.019%. Overall, the spatial and temporal agreement of the changes detected by both time series was 96%. Further, our findings suggest that the entire pre-existing historic time series does not need to be re-processed during the update process. Critically, given the time series change detection and update approach followed here, science outcomes or reports representing one temporal epoch can be considered stable and will not be altered when a time series is updated with newly available data.