不动产空间数据二三维一体化存储设计与应用探讨     

陈泽鹏  万宝林  李清 《测绘通报》2019,(4):162-164

通过对不动产空间数据和ArcGIS的GeoDatabase数据模型的分析，设计了不动产登记空间数据成果二三维数据统一存储的规则和方法，从而为不动产登记成果的二三维系统应用提供了数据支撑。  相似文献   

基于YOLOv3深度学习的海雾气象条件下海上船只实时检测     

王飞  刘梦婷  刘雪芹  秦志亮  马本俊  郑毅 《海洋科学》2020,44(8):197-204

海雾气象条件下船只高精度检测识别面临较大困难，传统的目标识别、定位方法效果差强人意。作者围绕海雾气象条件下不同类型船只的实时检测问题，提出一种基于YOLOv3深度学习的实时海上船只检测新思路。首先构建清晰图片和模糊图片（海雾、雨）的判别方法，实现图片清晰度分类处理；其次为提高海雾气象条件下海上船只的实时检测精度，消除海雾遮挡对目标识别的影响，运用暗通道先验去雾方法对含有海雾的图像实行去雾；最后基于YOLOv3深度学习算法对精细处理后的图像进行船只实时检测。实验结果表明该方法能够在海雾气象条件下高效、准确地检测到船只，对海上复杂环境条件下的船只实时检测研究具有一定的理论指导意义。  相似文献   

基于机器学习的高精度高分辨率气象因子时空估计     

方颖  李连发 《地球信息科学学报》2019,21(6):799-813

气象变量常作为重要的影响因子出现在环境污染、疾病健康和农业等领域,而高分辨率的气象资料可作为众多研究的基础数据,对推进相关研究的发展意义重大。本文以中国大陆为研究区域,利用2015年824个气象站点的气温、相对湿度和风速3套数据,结合不同的解释变量组合,分别构建了各自的GAM和残差自编码器神经网络（简称残差网络）模型,以10倍交叉验证判断模型是否过拟合。研究结果表明：① GAM和残差网络方法都不存在过拟合问题,同GAM相比,残差网络显著提高了模型预测的精度（3个气象因素的交叉验证CV R²平均提高了0.21,CV RMSE平均降低了37%）,其中相对湿度模型的提升幅度最大（CV R²:0.85 vs. 0.52,CV RMSE:7.53% vs. 13.59%）;② 残差模型的结果较普通克里格插值结果和再分析资料更接近站点观测数据,表明残差网络可作为高分辨率气象数据研制的可靠方法。此外,研究还发现在相对湿度模型中加入臭氧浓度和气温、在风速模型中加入GLDAS风速再分析资料,可提升模型的性能。  相似文献   

Simulation of site-scale water fluxes in desert and natural oasis ecosystems of the arid region in Northwest China     

Mingjuan Xie  Geping Luo  Olaf Hellwich  Amaury Frankl  Wenqiang Zhang  Chunbo Chen  Chen Zhang  Philippe De Maeyer 《水文研究》2021,35(12):e14444

The study of water fluxes is important to better understand hydrological cycles in arid regions. Data-driven machine learning models have been recently applied to water flux simulation. Previous studies have built site-scale simulation models of water fluxes for individual sites separately, requiring a large amount of data from each site and significant computation time. For arid areas, there is no consensus as to the optimal model and variable selection method to simulate water fluxes. Using data from seven flux observation sites in the arid region of Northwest China, this study compared the performance of random forest (RF), support vector machine (SVM), back propagation neural network (BPNN), and multiple linear regression (MLR) models in simulating water fluxes. Additionally, the study investigated inter-annual and seasonal variation in water fluxes and the dominant drivers of this variation at different sites. A universal simulation model for water flux was built using the RF approach and key variables as determined by MLR, incorporating data from all sites. Model performance of the SVM algorithm (R² = 0.25–0.90) was slightly worse than that of the RF algorithm (R² = 0.41–0.91); the BPNN algorithm performed poorly in most cases (R² = 0.15–0.88). Similarly, the MLR results were limited and unreliable (R² = 0.00–0.66). Using the universal RF model, annual water fluxes were found to be much higher than the precipitation received at each site, and natural oases showed higher fluxes than desert ecosystems. Water fluxes were highest during the growing season (May–September) and lowest during the non-growing season (October–April). Furthermore, the dominant drivers of water flux variation were various among different sites, but the normalized difference vegetation index (NDVI), soil moisture and soil temperature were important at most sites. This study provides useful insights for simulating water fluxes in desert and oasis ecosystems, understanding patterns of variation and the underlying mechanisms. Besides, these results can make a contribution as the decision-making basis to the water management in desert and oasis ecosystems.  相似文献   

Site characterization model using least‐square support vector machine and relevance vector machine based on corrected SPT data (Nc)     

Pijush Samui  T. G. Sitharam 《国际地质力学数值与分析法杂志》2010,34(7):755-770

Statistical learning algorithms provide a viable framework for geotechnical engineering modeling. This paper describes two statistical learning algorithms applied for site characterization modeling based on standard penetration test (SPT) data. More than 2700 field SPT values (N) have been collected from 766 boreholes spread over an area of 220 sqkm area in Bangalore. To get N corrected value (N_c), N values have been corrected (N_c) for different parameters such as overburden stress, size of borehole, type of sampler, length of connecting rod, etc. In three‐dimensional site characterization model, the function N_c=N_c (X, Y, Z), where X, Y and Z are the coordinates of a point corresponding to N_c value, is to be approximated in which N_c value at any half‐space point in Bangalore can be determined. The first algorithm uses least‐square support vector machine (LSSVM), which is related to a ridge regression type of support vector machine. The second algorithm uses relevance vector machine (RVM), which combines the strengths of kernel‐based methods and Bayesian theory to establish the relationships between a set of input vectors and a desired output. The paper also presents the comparative study between the developed LSSVM and RVM model for site characterization. Copyright © 2009 John Wiley & Sons, Ltd.  相似文献   

天地图·安徽综合服务系统的设计与实现     

赵栋梁  张耀波  杨友长 《测绘与空间地理信息》2016,(1):138-140

统计数据基于地理信息的集成,可以弥补传统的统计信息单一、不直观的表现形式,充分发挥其在政府管理决策中所起的重要作用以及对社会发展的导向作用。本文通过研究建立综合统计数据模型,阐述了数据来源、数据组织、空间数据模型建立及查询逻辑。以安徽省综合信息服务系统为例,在基于天地图·安徽的地图服务和Arc GIS API For Flex开发包的基础上,完成Flex框架下的客户端设计,采用Web Service数据通信技术来完成综合统计信息服务系统的设计与实现。  相似文献   

基于“一张图”平台的国土资源执法监察系统设计与研究     

董星星 《测绘与空间地理信息》2016,(1):153-155

从土地执法监察管理的实际需求出发,探讨了基于"一张图"平台的国土资源执法监察系统建设方案,设计了土地执法监察系统结构和功能模块,并进一步给出了土地执法监察数据库建设和数据交换的技术方法。该系统方案的应用将有利于快速、准确地监控国土资源违法行为,强化对国土资源违法行为的监控能力,有效地提高了国土部门执法监察工作效率和执法水平。  相似文献   

浅析GIS的地下管线查询与管理系统     

孙毓晗  魏东岚  王鸿燕 《测绘与空间地理信息》2016,(9):127-129

城镇地下管线就像是城镇的脉络,对于城镇的运转非常重要,肩负着为城镇运送物质能量、输出废弃物的重要使命。随着城镇的扩建,敷设于地下的管线不断向周围扩张,其规模不断膨胀,因此,也变得越来越复杂。传统的管线管理方式不仅数据的查询效率低,导致因管线错挖而造成的爆管事故频发,而且不能及时准确地进行应急处理。所以在告别传统落后的地下管线管理方式的同时,我们应思考如何能够更好的管理大量的地下管线数据,从而提高了数据的查询与应急管理的效率,为城镇规划和发展提供更好的支撑作用。  相似文献   

国产机载LiDAR系统安置角误差检校方案研究   总被引：1，自引：0，他引：1  

谢劭峰  刘田龙 《测绘与空间地理信息》2016,(6):50-55

机载激光扫描仪(Light Detection And Ranging,LiDAR)系统是由多个子系统集成,其中,安置角误差是集成误差中最大的误差源,安置角误差检校的方法多种多样,高效率、高精度的检校方式还需要试验的支撑。本文对平差模型法和几何模型法进行了试验分析,试验结果很好地证明了不同方法的优越性,为机载LiDAR系统的安置角检校提供了参考。  相似文献   

迁移学习支持下的高分影像山地滑坡灾害解译模型     

郭加伟  李永树  李政  刘锟铭  张帅毅 《测绘科学技术学报》2016,(5):496-501

无人机低空遥感是近年来新兴的一种快速获取灾情信息的手段,如何利用无人机高分影像构建滑坡灾害解译模型是实现快速自动解译滑坡的关键。针对该问题,对比了多种影像特征提取方法,将迁移学习(TL)特征和支持向量机(SVM)引入到构建滑坡灾害自动解译模型中,提出了一种TL支持下的高分影像滑坡灾害解译模型。选取5·12汶川地震及4·20芦山地震系列无人机影像构建了滑坡灾害样本库并进行了实验,TL特征方法整体分类准确度ACC为95%,ROC达到0.98,识别准确率达到97%。结果表明,所提方法可用于高分影像滑坡自动解译,同时可用于大面积高分影像中快速山地滑坡灾害定位及检测。  相似文献