Using neural networks for calibration of time-domain reflectometry measurements

Abstract

Time-domain reflectometry (TDR) is an electromagnetic technique for measurements of water and solute transport in soils. The relationship between the TDR-measured dielectric constant (K_a ) and bulk soil electrical conductivity ([sgrave]_a) to water content (θ_W) and solute concentration is difficult to describe physically due to the complex dielectric response of wet soil. This has led to the development of mostly empirical calibration models. In the present study, artificial neural networks (ANNs) are utilized for calculations of θ_w and soil solution electrical conductivity ([sgrave]_w) from TDR-measured K_a and [sgrave]_a in sand. The ANN model performance is compared to other existing models. The results show that the ANN performs consistently better than all other models, suggesting the suitability of ANNs for accurate TDR calibrations.     

Semantic segmentation of high spatial resolution images with deep neural networks

Availability of reliable delineation of urban lands is fundamental to applications such as infrastructure management and urban planning. An accurate semantic segmentation approach can assign each pixel of remotely sensed imagery a reliable ground object class. In this paper, we propose an end-to-end deep learning architecture to perform the pixel-level understanding of high spatial resolution remote sensing images. Both local and global contextual information are considered. The local contexts are learned by the deep residual net, and the multi-scale global contexts are extracted by a pyramid pooling module. These contextual features are concatenated to predict labels for each pixel. In addition, multiple additional losses are proposed to enhance our deep learning network to optimize multi-level features from different resolution images simultaneously. Two public datasets, including Vaihingen and Potsdam datasets, are used to assess the performance of the proposed deep neural network. Comparison with the results from the published state-of-the-art algorithms demonstrates the effectiveness of our approach.     

社会资本对区域创新能力的影响

社会资本影响知识创造、知识获取与知识整合,进而影响区域创新能力的提升。基于中国大陆31个省份的截面数据,以无偿献血率、信任度和社会组织密度指标测量区域社会资本,以知识创造、知识获取、企业创新、创新环境和创新绩效等5个指标衡量区域创新能力,采用相关分析和多元回归模型分析社会资本与区域创新能力之间的关系。结果显示：（1）我国各省区间的社会资本与区域创新能力均存在较大差异,但两者的空间分布状况具有相似性;（2）信任纬度与区域创新能力呈显著正相关关系,而规范纬度和网络纬度与区域创新能力呈负相关关系;（3）人均GDP、R&D人员和研发机构数量与区域创新能力均呈正相关关系。最后,提出了提高社会资本、增强区域创新能力的对策。     

Spatiotemporal patterns of road network and road development priority in three parallel rivers region in Yunnan, China: An evaluation based on modified kernel distance estimate

Road network is a critical component of public infrastructure,and the supporting system of social and economic development.Based on a modified kernel density estimate(KDE)algorithm,this study evaluated the road service capacity provided by a road network composed of multi-level roads(i.e.national,provincial,county and rural roads),by taking account of the differences of effect extent and intensity for roads of different levels.Summarized at town scale,the population burden and the annual rural economic income of unit road service capacity were used as the surrogates of social and economic demands for road service.This method was applied to the road network of the Three Parallel River Region,the northwestern Yunnan Province,China to evaluate the development of road network in this region.In results,the total road length of this region in 2005 was 3.70×104km,and the length ratio between national,provincial,county and rural roads was 1∶2∶8∶47.From 1989 to 2005,the regional road service capacity increased by 13.1%,of which the contributions from the national,provincial,county and rural roads were 11.1%,19.4%,22.6%,and 67.8%,respectively,revealing the effect of′All Village Accessible′policy of road development in the mountainous regions in the last decade.The spatial patterns of population burden and economic requirement of unit road service suggested that the areas farther away from the national and provincial roads have higher road development priority(RDP).Based on the modified KDE model and the framework of RDP evaluation,this study provided a useful approach for developing an optimal plan of road development at regional scale.     

A trajectory-oriented carriageway-based road network data model, part 1: Background

Introduction Withthedramaticdevelopmentofpositioning andtelecommunicationtechnologies,lotsoftraj ectorydataofmovingvehiclescanbecalculated,collected,andtransferred.Inthemeanwhile,thisdevelopmentandtheavailabilityoftrajectory datahavealsomotivatedresearche…     

基于模糊综合评判的选址空间决策支持系统

传统的选址空间决策支持系统的数学模型难以全面考虑复杂、抽象的选址影响因素,难以把一些模糊的约束条件纳入数学模型,因而模型存在一定缺陷。利用模糊综合评判进行选址空间决策支持系统的研究,可以充分利用GIS的空间和非空间信息,且考虑的因素更为全面,极大地避免了人为因素的影响,是对选址决策支持系统数学模型的改进。     

运用GPS测量对自贡市城市控制网点的改算

本文通过对运用GPS测量改算自贡市各等级城市控制网点成果的过程及结果的论述分析,证实了运用GPS测量改算城市控制网点成果具有精度好、效率高等特点。在此基础上探讨其可行性,并提出一些看法。     

基于神经网络的遥感影像分类方法研究

本文在研究BP神经网络和模糊理论的基础上,提出了传统BP算法的一种改进方法和基于模糊系统的神经网络遥感影像分类方法。通过试验表明:基于模糊技术的神经网络分类方法要优于BP神经网络方法,取得了令人满意的效果。     

Reductions of PM<Subscript>2.5</Subscript> in Beijing-Tianjin-Hebei urban agglomerations during the 2008 Olympic Games

The Atmospheric Environmental Monitoring Network successfully undertook the task of monitoring the atmospheric quality of Beijing and its surrounding area during the 2008 Olympics.The results of this monitoring show that high concentrations of PM2.5 pollution exhibited a regional pattern during the monitoring period(1 June-30 October 2008).The PM2.5 mass concentrations were 53 μg m 3,66 μg m 3,and 82 μg m 3 at the background site,in Beijing,and in the Beijing-Tianjin-Hebei urban agglomerations,respectively.The PM2.5 levels were lowest during the 2008 Olympic Games(8-24 August):35 μg m 3 at the background site,42 μg m 3 in Beijing and 57 μg m 3 in the region.These levels represent decreases of 49%,48%,and 56%,respectively,compared to the prophase mean concentration before the Olympic Games.Emission control measures contributed 62%-82% of the declines observed in Beijing,and meteorological conditions represented 18%-38%.The concentration of fine particles met the goals set for a "Green Olympics."     

模糊数学在海（咸）水入侵水质评价中的应用—以寿光地区为例

运用模糊数学的基本思想方法,结合海(咸)水入侵的特点,依据寿光地区2015年丰水期地下水水质监测结果,选取Cl-、矿化度、咸化系数、钠吸附比等4项水化学指标作为评价因子,构建模糊综合评价数学模型,对寿光海(咸)水入侵现状进行了模糊综合评价,并验证了此模糊综合评价结果的可靠性。