Analysis and prediction of household carbon emission in northwest China北大核心CSCD

The economic development, living standard of residents and carbon emissions in Northwest China are lower than the national average. However,with the favorable policies the economic development is being improved and the household living standard is gradually raised up which will lead to an increase of the residents living carbon emissions, and the emission pattern will also be affected. This is detrimental to the fragile ecological environment of the Northwest China. At present, most of the researches on residents' carbon emissions are focused on the eastern and southern regions of China where there are frequent and significant human activities and high carbon emissions, and less attention has been paid to the northwest region, but the increase of carbon emissions and the increase of environmental costs have a more far-reaching impact on the less developed areas. In addition, when researchers pay attention to the prediction of residents' carbon emissions, they usually focus on the quantitative prediction and ignore the spatial pattern prediction, which is not conducive to the coordinated development between regions. Based on the data of energy consumption and consumption expenditure in the five provinces of Northwest China, including Shaanxi, Gansu, Qinghai, Ningxia and Xinjiang from 1997 to 2016, this paper firstly used the direct coefficient method to measure the residents' direct carbon emissions, and the input-output method to calculate the indirect carbon emissions of the residents and analyzes the present situation of residents' carbon emissions in the northwest region. Secondly, based on standard deviation ellipse and Autoregressive Integrated Moving Average Model, the carbon emissions of residents in Northwest China were predicted in terms of quantity and spatial pattern from 2017 to 2021. Major results are listed as follows: From 1997 to 2016, household carbon emissions in Northwest China showed a rising trend with an initial slow pace followed by a quick pace. The direct carbon emissions were stabilized in the range from 0. 3 × 108 t to 0. 4 × 108 t,and the indirect carbon emissions reached 2. 38 × 108 t. The spatial distribution of household carbon emissions in Northwest China was generally steady with a direction pattern from northwest to southeast. And the moving trend of standard deviation ellipse was from northwest to southeast to northwest, and the center of standard deviation ellipse moved around the point of (99. 07 °E,38. 19°N). From 2017 to 2021, the direct household carbon emissions in Northwest China reach to 0.543 × 108 t and the indirect carbon emissions are 3. 631 × 108 t by 2021. With the development of the western region in China and the promotion of poverty alleviation,Xinjiang Province had a lower emission than Shaanxi,but it had the higher growth rate than Shaanxi. These factors are all driving the main areas of carbon emission northwestward. The purpose of this paper is to recommend how to coordinate between the population and consumption and the environment, leading citizens to establish the value of low-carbon consumption. © 2019 Science Press (China). All rights reserved.     

玉溪市中心城区建设用地集约利用空间差异研究

为科学地分析城市土地集约利用在空间上的分布规律及趋势,以玉溪市中心城区为研究区域,在玉溪市中心城区建设用地集约利用评价的基础上,通过空间相关分析的方法揭示了中心城区建设用地集约度的空间分布特征。结果表明:玉溪市中心城区集约利用度呈现出由城市中心逐渐向外递减的趋势,土地集约利用水平在一定程度上存在集聚效应;从全域空间分析看,各功能区土地利用集约度空间分布在整体上具有较好的正相关性,居住功能区相关性最强,其他功能区最弱;从局部空间的角度来看,集约度的分布既存在空间聚集性又存在空间异质性。     

武汉市不同等级景区旅游吸引力时空变化

收集2018~2019年网络关注度等有关数据,利用地理集中指数和多元线性回归等方法,分析景区旅游吸引力时空变化及影响因素,结果发现:(1)景区级别越高,其吸引力半径越大,景区50%的客源市场集中在900km范围内,80%的客源市场集中在1 200 km范围内.(2)景区级别越高,旅游吸引力集中度往往越小,客源市场较分散.不同季节各景区旅游吸引力差异较大,旅游吸引力集中度有明显的季节变化.(3)各景区的平均旅游吸引力均存在距离衰减现象,级别越高的景区在不同空间距离范围内的吸引力相差较小,衰减速度较小.不同季节的旅游吸引力衰减速度有所不同.(4)在其它条件相同的情况下,城市经济发展水平越高、人口越多、距离越近,景区对其吸引力越强.     

Spatio-temporal variability of small fishes related with environmental factors in a typical domestic tap water lake,Eastern China

The knowledge of prey small ?sh stock, distribution and abundance is necessary to guide stocking of piscivorous ?sh for the biomanipulation in domestic tap water lakes. This study describes the current status of small ?sh community in Kuilei Lake(China), and examines the spatial and seasonal variations of the community in relation to key environmental factors. Based on submerged macrophyte cover and water depth, the lake was divided into ?ve major habitats:(1) macrophyte covered shallow habitat of water depth< 2.00 m,(2) uncovered or less-covered shallow habitat(2.00 m–3.50 m),(3) uncovered medium shallow habitat(3.50 m–5.00 m),(4) uncovered medium deep habitat(5.00 m–6.50 m) and(5) uncovered deep habitat(6.50 m–8.50 m). The abundance and composition of small ?sh were monitored by benthic fykenet sampling from April 2013 to January 2014. A total of 2881 individuals belonging to 5 families and 21 species were collected. Based on their abundance(accounted for 88.96% of the total) and occurrence(more than 33.33%), Acheilognathus chankaensis, Acheilognathus macropterus, Microphysogobio microstomus,Pseudorasbora parva and Rhinogobius giurinus were recognized as dominant small ?sh species. The results of correlation analysis identi?ed that species richness( Sr), Shannon-Wiener diversity index( H′)and Margalef′s richness index( D) were signi?cantly negatively correlated with water depth, but positively correlated with biomass of submerged macrophytes.Redundancy analysis(RDA) revealed that the spatial distributions of most small ?shes were negatively associated with water depth. The details of these ?ndings are bene?cial to understanding the adaptation of the small ?shes in degraded environments, and to developing suitable biomanipulation strategies for the management of ?sh resources and water quality in the lakes along the lower reach of the Changjiang(Yangtze) River basin.     

基于移动GIS的生态环境智能感知方法

随着全球范围移动互联网的高速发展,人们作为"传感器"行走在真实社会中制造实时的、实地环境的、大范围的地理信息,特别是具有互动性和实时性的区域环境状况的地理信息。这类数据具有交互性、实时性、丰富性、社会性等特点,成为数据科学家眼中的金矿。基于"互联网+"时代背景,随着移动互联网、移动GIS技术和LBS技术日趋成熟,本文提出了基于移动GIS的生态环境智能感知方法,开发基于Android平台的APP,实现查询环境质量指数、查看环境污染地图、污染一键分享和解决等功能,从大众的视角感知和获取生态环境信息,为大众提供实时动态环境信息查询方式,引导鼓励公众参与环境保护,提供治理环境污染和地理信息资源获取的新思路。     

深度学习GoogleNet模型支持下的中分辨率遥感影像自动分类

提出了一种基于深度学习技术的遥感分类方法,它能有效解决中分辨率影像在分类过程中出现的像元混分问题。研究选用2016年5月12日武汉市Landsat 7 ETM+遥感影像,基于GoogleNet模型中的Inception V3网络结构,借助迁移学习方法,构建出遥感分类模型,实现了对武汉市主城区4类典型地物（不透水层、植被、水体和其他用地）的自动分类提取,并将分类结果与传统最大似然分类（ML）结果进行了对比分析。研究表明：基于深度学习方法的遥感影像总体分类精度高达88.33%,Kappa系数为0.834 2,明显优于传统ML方法总体分类精度83%和Kappa系数0.755 0,而且有效抑制了地物在分类过程中出现的像元混分现象。     

多源空间数据融合的城市精细化管理

城市管理体量不断增大且管理对象关联繁多,已经成为影响城市可持续发展的重要问题。在全国智慧城市建设的大背景下,引用新技术提升城市精细化管理水平可以使城市的各管理单元协同、精确、及时地交换信息,形成智慧城市管理的配套方案,让有限的管理资源发挥出最大的使用效能,实现城市管理的最优化目标,促进经济的可持续发展。本文提出了地理信息系统、GPS、遥感、RFID等空间数据融合的技术方案,强调在空间信息和移动信息管理的基础上通过工作流和过程化管理,提高城市精细化管理的综合水平,为实现民众参与监督城市管理和智慧城市建设提供参考。     

粒子加速器中高精度丝线绝对位置测量技术研究

粒子加速器中采用振动线技术进行共架单元上多块磁铁的高精度预准直,需要将振动线代表的磁中心引出进行共架单元之间的相对准直。为了获取以振动线为代表的丝线高精度空间绝对位置,本文对采用近景摄影测量技术进行点、线位置求解的方法进行了研究。利用单相机多站位的方法进行拍摄,通过标定板提供的高精度控制点坐标,采用自标定光束法平差对相机进行标定,并提出将空间直线离散成空间2点进行直线整体精确求解。对标定板上由2点组成的模拟直线进行测量验证,并与标定板提供的理论值进行对比,结果显示空间直线位置获取精度优于5 μm。这表明了本文理论和方法的正确性,为进一步研究丝线高精度空间绝对位置测量打下了基础。     

大气污染物排放量与颗粒物环境空气质量的空间非协同耦合研究——以武汉市为例

针对区域大气污染物排放量与空气质量在时空分布上存在不完全协同、匹配的现象,论文选择SO₂、NO_X、PM_2.5、CO和VOCs作为大气污染物指标,选择气溶胶光学厚度(Aerosol Optical Depth, AOD)表征颗粒物环境空气质量,以武汉市为例,综合应用耦合模型和空间错位指数模型研究2类指标之间的空间非协同耦合规律。主要结论如下：① 武汉市大气污染物排放量与颗粒物空气质量具有不同空间分布特征,大气污染物排放量呈现由城市中心城区向远城区递减的趋势,其中SO₂、PM_2.5和VOCs的排放具有明显的中心聚集现象,而NO_X和CO聚集现象不显著,且与道路分布明显相关;AOD分布具有明显的空间差异性,总体上呈由西北向东南依次递减的趋势。② 武汉市大气污染物排放与颗粒物空气质量的空间非协同耦合规律：越靠近城市中心城区,空间协同耦合现象越显著,空间错位现象越弱;越远离主城区,空间非协同耦合现象越显著,空间错位现象越显著;SO₂排放量与AOD在武汉市远城区的空间错位指数均大于0.7,且耦合度指数小于0.3,呈现较强的非协同耦合特征,NO_X、VOCs、PM_2.5的排放量与AOD在武汉中心城区的空间错位指数均小于0.5,且耦合度指数大于0.5,协同耦合现象较为显著。③ 基于时空非协同耦合分析城市大气环境污染治理建议：针对污染物与AOD空间错位不显著的城市中心城区,以本地减排治理为主;针对污染物与AOD空间错位显著的远城区,应在污染溯源分析的基础上进行区域协调综合治理。     

珠三角村镇建成区的空间型态：特征、类型和产业影响因素

改革开放以来,珠三角地区的工业迅速发展,村镇土地利用快速非农化,其中以东莞、中山、佛山3市最为典型。论文以3市为案例,探讨2010年来珠三角村镇建成区空间型态。研究数据主要包括广东省2015年土地利用现状数据和2009—2015年间3市的土地利用数据。首先,通过斑块密度、空间离散度、空间均匀度、平均斑块面积、分形维数、景观破碎度、缓冲区分析、Moran's I指数这8个指标,分析建设用地的空间形态特征。其次,分析工业用地与非工业建设用地、建设用地与交通道路的空间分布关系,比较并总结3市的村镇建成区空间类型。最后,基于灰色关联分析法,探讨影响空间类型的产业发展因素。研究发现,东莞村镇建设用地呈现高度破碎均匀分布型,佛山呈现团状离散型,中山介于二者之间,为中度碎化分散型;3市的产业发展能较大程度上影响其形成不同的建成区空间型态。未来,基于产业经济作为村镇建成区空间特征变化的主因,珠三角可以结合粤港澳大湾区规划建设,通过调整产业结构、布局以及交通和土地利用,优化村镇空间布局。