A two-layer model for studying 2D dissolved pollutant runoff over impermeable surfaces

Dissolved pollutants in stormwater are a main contributor to water pollution in urban environments. However, many existing transport models are semi-empirical and only consider one-dimensional flows, which limit their predictive capacity. Combining the shallow water and the advection–diffusion equations, a two-dimensional physically based model is developed for dissolved pollutant transport by adopting the concept of a ‘control layer’. A series of laboratory experiments has been conducted to validate the proposed model, taking into account the effects of buildings and intermittent rainfalls. The predictions are found to be in good agreement with experimental observations, which supports the assumption that the depth of the control layer is constant. Based on the validated model, a parametric study is conducted, focusing on the characteristics of the pollutant distribution and transport rate over the depth. The hyetograph, including the intensity, duration and intermittency, of rainfall event has a significant influence on the pollutant transport rates. The depth of the control layer, rainfall intensity, surface roughness and area length are dominant factors that affect the dissolved pollutant transport. Finally, several perspectives of the new pollutant transport model are discussed. This study contributes to an in-depth understanding of the dissolved pollutant transport processes on impermeable surfaces and urban stormwater management.     

Daily salinity fluctuation alleviates salt stress on seedlings of the mangrove Bruguiera gymnorhiza

Salinity is a vital factor that regulates leaf photosynthesis and growth of mangroves, and it frequently undergoes large seasonal and daily fluctuations creating a range of environments – oligohaline to hyperhaline. Here, we examined the hypotheses that mangroves benefit opportunistically from low salinity resulting from daily fluctuations and as such, mangroves under daily fluctuating salinity (FS) grow better than those under constant salinity (CS) conditions. We compared growth, salt accumulation, gas exchange, and chlorophyll fluorescence of leaves of mangrove Bruguiera gymnorhiza seedlings growing in freshwater (FW), CS (15 practical salinity units, PSU), and daily FS (0–30 PSU, average of 4.8 PSU) conditions. The traits of FS-treated leaves were measured in seedlings under 15 PSU. FS-treated seedlings had greater leaf biomass than those in other treatment groups. Moreover, leaf photosynthetic rate, capacity to regulate photoelectron uptake/transfer, and leaf succulence were significantly higher in FS than in CS treatment. However, leaf water-use efficiency showed the opposite trend. In addition to higher concentrations of Na⁺ and Cl⁻, FS-treated leaves accumulated more Ca²⁺ and K⁺. We concluded that daily FS can enhance water absorption, photosynthesis, and growth of leaves, as well as alter plant biomass allocation patterns, thereby positively affecting B. gymnorhiza. Mangroves that experience daily FS may increase their adaptability by reducing salt build-up and water deficits when their roots are temporally subjected to low salinity or FW and by absorbing sufficient amounts of Na⁺ and Cl⁻ for osmotic adjustment when their roots are subsequently exposed to saline water.     

结合BM3D和多级非线性加权平均中值滤波的遥感影像混合噪声去噪方法

提出了一种基于三维块匹配（BM3D）和多级非线性加权平均中值滤波的遥感影像混合噪声去噪方法，使用coief3小波和sym2小波替换传统三维块匹配算法中的bior1.5和hear参数，将三维块匹配算法和多级非线性加权平均中值滤波相结合以提高算法对混合噪声的去噪能力。进行一个仿真对比试验和一个真实遥感影像去噪试验，试验表明，本文提出的方法在遥感影像混合噪声去噪方面效果要优于传统混合噪声去噪方法。     

利用CEEMD分析中国沿海GNSS站高程时序变化

利用完备经验模态分解方法（CEEMD）对我国沿海地区6个GNSS基准站（2010—2018）的高程时序数据进行了处理分析。结果表明：CEEMD在高程时间序列分析中具有一定的优越性，可准确分解出各GNSS站高程时序中存在的周、月、季节、年等变化周期项，其中周年运动是主要贡献项，各站高程时间序列的短周期变化与潮汐变化周期具有密切关联性；沿海GNSS站的地面沉降既具有区域的一致性，又存在区域间差异性，其中D区DBJO、DZJJ站呈现先下降后上升的趋势，N区NZUH、NWZU站呈下降趋势，B区的BZMW呈上升趋势，而同海区的BLHT站则呈显著的下降趋势。     

运用GD-PBIBD编码的矢量空间数据数字指纹算法

针对矢量空间数据叛逆者追踪难及编码效率低的问题，本文提出了一种运用GD-PBIBD码的指纹算法。首先运用GD-PBIBD构造指纹编码，将待嵌入指纹序列运用Logistic映射置乱，通过D-P算法提取矢量空间数据的特征点，对特征点实施DFT变换得到相位系数和幅度系数；然后运用QIM方法将指纹嵌入DFT变换域的幅度系数上；最后应用DFT逆变换得到含指纹的矢量空间数据。试验选取部分中国路网数据和某区域绿地数据，运用该算法嵌入指纹后，对其进行线性和非线性模拟攻击，成功提取指纹序列，利用汉明距离追踪出合谋者。该算法编码构造简单，在码长一定的情况下，较BIBD码可容纳更多的用户，效率高；算法抗单用户指纹攻击及多重攻击的稳健性较好，也能够抵抗多用户最小值和最大最小值攻击，追踪到所有叛逆者，可用于矢量空间数据版权保护，为矢量空间数据叛逆者追踪提供依据。     

基于像元二分模型的地表植被覆盖度估算模块化设计与实现

地表植被覆盖度是的一种应用广泛的定量遥感产品,在水文、生态、区域变化等方面都具有重要的意义。像元二分模型是应用最多的一种遥感估算地表覆盖度的方法。目前,用遥感的方法进行地表植被覆盖度估算没有完整、系统的工具,用户只能逐步进行操作,效率低下,鉴于上述情况,本文运用IDL交互式数据语言,基于ENVI二次开发了一个植被覆盖度估算程序,取得了一定的成效,对遥感定量产品的生产、应用具有一定意义。     

基于已知特征平面的移动测量系统安置参数检校

安置误差是影响移动测量系统激光点云精度的主要因素之一。当激光点云中存在特征平面时,安置误差会导致该平面与真实平面之间产生较大的偏差,如果存在多个空间上位置关系较好的特征平面,就能够全面反映出系统的安置误差。本文以此为依据,给出了一种基于已知特征平面的移动测量系统安置参数检校方法,并详细阐述了检校场的布设、数据获取及处理等内容。实验证明,该方法是一种简单、可靠的检校方法,具有较高的实用性。     

基于时相变化的晴空条件下Himawari-8 AHI火点检测

Himawari-8静止气象卫星具有高空间分辨率、高观测频次和高时效特点,对于火点检测具有很强优势。对Himawari-8卫星的3.9μm和11.2μm两通道亮温进行了连续时相变化研究,得出两通道的亮温在时间上的变化差值稳定且规律明显。根据两通道的亮温时相特征,考虑白天可见光对3.9μm通道的影响,并结合火点产生时引起的亮温变化特征,提出了适用于晴空条件下改进的火点检测算法。在多处进行了此算法的实验,例如2018-11-27 T 16:40(UTC时)河北张家口市桥东区一化工厂附近发生的严重爆炸起火事件以及2019-02-28澳大利亚西南部发生的火灾事件,均快速有效的检测到了火点。实验表明,改进的火点检测算法能很好的进行火点检测,并能解决晨昏交界、冰雪下垫面、常规火源点、太阳耀光等火点检测的难题。     

香坊老工业区搬迁改造监测分析

利用地理信息技术及遥感监测方法,监测香坊老工业区搬迁改造试点进展情况,主要针对搬迁改造过程中地表覆盖、用地性质、空气质量变化情况,开展综合统计分析,客观评价香坊老工业搬迁改造实施成效。     

邮轮属性评价与品牌定位

以全球最大的邮轮点评网站——邮轮评论家为数据来源渠道，以编辑（Editor/Expert）的文本点评以及对167艘邮轮10大属性的打分数据为样本，利用词频分析、回归分析、聚类分析和方差分析等方法，对全球21个邮轮品牌的产品属性、总体评价以及品牌定位问题进行了系统研究。结果表明，对于专业型游客来说，餐饮、客房和娱乐是关注度最高的船上属性，服务、性价比和公共空间是满意度最高的船上属性，客房、餐饮、公共空间、性价比和娱乐属性对邮轮总评具有显著影响。方差分析表明，与行业界定下的品牌行为相比，基于专业型游客感知的品牌划分更有效。