植被叶面积指数估算的红边指数建模分析

针对在路域环境监测中,如何精确估算叶面积指数问题,该文提出以长韶娄高速路域为研究区,筛选出4种常用植被指数和4种红边指数两类指数,分别构建了经验模型和机器学习的反演模型,利用Sentinel-2影像数据和同步的LAI-2000地面实测数据完成路域植被叶面积指数反演。结果表明,红边波段参与运算的植被指数与植被叶面积指数敏感性是显著相关,红边指数在反演精度上更优。由此可知,相较于常见植被指数,红边指数增强了其与叶面积指数的敏感性,提高了叶面积指数估算模型精度。     

建设数字孪生城市的逻辑与创新思考

介绍了数字孪生城市的提出背景以及基本概念,分析了数字孪生城市与智慧城市之间的关系,并介绍了构建数字孪生城市的主要支撑技术,最后总结了数字孪生城市的应用现状及发展趋势。作者认为,数字孪生技术要在智慧城市建设中得以更广泛的应用还将面临数据、基础知识库、系统融合以及人才问题等方面的挑战,并从宏观与微观层面提出解决这些问题的制度路径和技术路径。     

一种基于空间分析服务链组合的自然资源保护红线审计模型方法

区别于传统的审计方法,针对领导干部自然资源资产离任审计,提出一种空间分析服务链组合的自然资源保护红线审计空间分析建模方法,实现了自然资源保护红线审计的地理处理分析服务链模型,并将其应用到云南省领导干部自然资源资产离任审计工作中。实验表明,该模型具有可行性能够辅助审计部门工作人员快速发现疑点线索,简化用户操作,提高审计效率。     

长潭岗水库汛期日平均进库流量预报模型设计

摘要：为了指导长潭岗水库安全、高效运行,保护下游人民生命财产,本文对长潭岗水库的日平均进库流量进行了建模。本文使用水库上游集雨面积的降水量、蒸发量资料以及水库的日平均进库流量数据建立人工神经网络模型,通过对模型隐含层和输出层的层函数进行不同的组合,得到了4种复杂程度和表达能力逐渐增加的模型。各模型训练结果较好,验证结果均能在0.05的显著性水平上通过检验,其中模型2111（第一隐含层为一元二次线性函数其余层次均为一元一次线性函数）的效果最好,层函数的复杂程度对峰值输出的准确度有一定的正面的贡献。该模型能够满足气象局的专业气象服务需求。     

Evaluation of Linear and Non-Linear Downscaling Methods in Terms of Daily Variability and Climate Indices: Surface Temperature in Southern Ontario and Quebec,Canada

We downscaled atmospheric reanalysis data using linear regression and Bayesian neural network (BNN) ensembles to obtain daily maximum and minimum temperatures at ten weather stations in southern Quebec and Ontario, Canada. Performance of the linear and non-linear downscaling models was evaluated using four different sets of predictors, not only in terms of their ability to reproduce the magnitude of day-to-day variability (i.e., “weather,” mean absolute error between the daily values of the predictand(s) and the downscaled data) but also in terms of their ability to reproduce longer time scale variability (i.e., “climate,” indices of agreement between the predictand's observed annual climate indices and the corresponding downscaled values). The climate indices used were the 90th percentile of the daily maximum temperature, 10th percentile of the daily minimum temperature, number of frost days, heat wave duration, growing season length, and intra-annual temperature range.

Our results show that the non-linear models usually outperform their linear counterparts in the magnitude of daily variability and, to a greater extent, in annual climate variability. In particular, the best model simulating weather and climate was a BNN ensemble using stepwise selection from 20 reanalysis predictors, followed by a BNN ensemble using the three leading principal components from the aforementioned predictors. Finally, we showed that, on average, the first three indices presented higher skills than the growing season length, number of frost days, and the heat wave duration.     

西沙赵述岛海域珊瑚礁生态修复效果的初步评估

珊瑚恢复是一个协助退化、受损的珊瑚礁生态系统恢复的过程.近10 a来,西沙珊瑚礁生态系统不断退化,至2009年珊瑚覆盖率已下降至不足10%.针对西沙群岛珊瑚礁生态系统的退化状况,2011年12月于西沙赵述岛海域投放人工礁基并开展珊瑚移植实验,比较了人工修复区和自然恢复区1a后的修复效果.结果显示,投放礁基且进行珊瑚移植的区域,移植珊瑚的存活率不到10%;投放礁基但未进行珊瑚移植的区域,珊瑚补充量高达6~7 ind/m2;自然恢复区其珊瑚覆盖率提高了19.4%.依据珊瑚礁生态修复效果评估方法,人工修复且进行移植珊瑚的区域的生物修复权重值为27.5,人工修复但未移植珊瑚区及自然恢复区的生物修复权重值为39.3,珊瑚修复生物指标为亚健康.我们的结果表明,在健康、有良好珊瑚幼虫补充的珊瑚礁生态系统中,珊瑚礁群落可以自行恢复,其恢复只是一个时间的问题;而在缺少珊瑚幼虫附着基底的区域,通过人为增加一些附着基底,可加速其恢复进程.     

基于高低潮的风暴增水人工神经网络预报模型

针对只有高低潮数据的情况,利用人工神经网络建立起一种预报当前台风时刻后第一个高潮时增水的模型。该模型选取台风在当前时刻、前6 h、前12 h、前18 h的中心经度、纬度、最大风速、中心气压以及当前时刻前第一个高潮时刻的风暴增水为输入单元。台风当前时刻后第一个高潮时刻风暴增水为模型输出单元。利用历史资料形成的规范化后的模式对,对模型进行训练,训练成功后,结合台风因子预报模型,即可用于风暴增水的预报。经过长江口高桥站高低潮实测资料的检验,结果表明该模型提取到了风暴增水效应,说明该模型可用于风暴增水的预报。     

人工神经网络在凡纳滨对虾养殖水质预测中的应用研究

以BP神经网络为基础,建立了凡纳滨对虾养殖水质预测模型。采用3层结构,通过灵敏度分析得到网络的输入变量,在确定了模型的各结构参数后,建立了凡纳滨对虾养殖水质预测模型,并根据整个对虾养殖周期内的水质监测数据对模型进行了训练和仿真。结果显示,水质的实测值与预测值之间的相关系数为0.991 8,预测误差率结果显示,最大误差率为4.37%,最小误差率为0.12%,平均误差率为1.20%,总体预测结果较好。BP神经网络能够以较高精度预测养殖水质状况,为水质恶化的早期预报提供了有效途径。     

Use of calcein and alizarin red S for immersion marking of black rockfish Sebastes schlegelii juveniles

Black rockfi sh Sebastes schlegelii juveniles(30–40 mm total length) were immersed in a range of calcein(CAL) solutions at concentrations ranging from 50 to 250 mg/L and alizarin red S(ARS) solutions at concentrations ranging from 100 to 500 mg/L in fi ltered seawater(salinity 30) for 24 h. Fluorescent marks were detected in otoliths(sagittae, asteriscus), scales, fi n rays(dorsal, pectoral, ventral, anal, and caudal fi n rays), and fi n spines(dorsal, ventral, and anal fi n spines) after a 60-d growth experiment. With the exception of 50–100 mg/L CAL, acceptable marks were produced in the otoliths and fi n spines by all concentrations of CAL and ARS. In particular, marks were clearly visible under normal light in the sagittae, asteriscus, and fi n spines of fi sh immersed in 200–500 mg/L, 300–500 mg/L, and 200–500 mg/L ARS, respectively. Scales and fi n rays had acceptable marks at much higher concentrations(≥50 mg/L CAL, ≥300 mg/L ARS for scales and ≥50 mg/L CAL, ≥200 mg/L ARS for fi n rays). The mark quality was highest(i.e., acceptable marks were observed in all sampled structures after immersion marking) in fi sh immersed in 150–250 mg/L CAL or 300–500 mg/L ARS. In addition, there was no signifi cant difference in survival and growth of marked fi sh compared with controls 60 d post-marking( P 0.05).     

WUSH-TV2型超声蒸发传感器的安装与维护

介绍WUSH-TV2型超声蒸发传感器的系统组成、工作原理以及安装方法,并对实际工作运行中遇到的故障进行分析,提出了合理的保障维护方法和处理思路.