黄河流域乡村社会经济与生态环境耦合协调测度及影响因素分析

基于黄河流域2008、2010、2012、2014年136个区县面板数据,本文运用熵权TOPSIS分析法、耦合协调度模型和地理探测器模型对其耦合协调水平和影响因素进行了分析。结果表明:①研究期内黄河流域社会经济发展和生态环境质量耦合协调度变化趋势呈“U”形曲线,总体处于高度耦合低级协调阶段。区域间差异变化趋势呈倒“U”形曲线。从相对发展度模型来看,2010—2014年乡村生态环境质量相对滞后。②空间格局上存在显著的空间分异特征,耦合协调度呈“上游>中游>下游”的分布格局。③自然环境因素是影响耦合协调度空间分异的主导因素,其次是社会经济因素。其中,乡村人口密度、PM_2.5年均浓度、人均耕地面积、地形起伏度、高程和年均气温是主要因子,并且两个因子的交互作用明显大于单一因子的影响。基于此,建议黄河流域以协调发展理念为指引,重点提高生态环境的保护和修复,采用差异化、特色化的发展策略,以期早日实现黄河流域生态保护和高质量发展。     

耕地质量与三农发展水平耦合研究——以四川省为例

耕地质量与三农发展水平密切相关,耕地质量与三农的耦合协调发展是和谐社会可持续发展的重要基础。本文采用系统分析的思路,以四川省为实例,在建立耕地质量及三农发展水平评价指标体系的基础上,运用耦合协调度模型、相对发展度模型等探讨耕地质量与三农发展水平的交互耦合关系并分析其空间分异特征。分析得出:四川省21个地级市的耕地质量与三农发展的协调耦合属于中偏上水平,大多数地区处于高度协调耦合阶段;空间格局上呈现西低东高、南北方向有微弱的倒U形趋势。两系统相对发展不均衡,各地市应因地制宜,采取措施优先发展相对滞后的系统,促进耕地质量与三农的协调发展。     

"一带一路"沿线城市区域经济与交通优势度耦合协调度分析

交通与经济协调发展对于推动"一带一路"发展战略具有重要意义.基于"一带一路"战略背景,本文以"一带一路"沿线城市经济数据和交通数据为基础,构建交通优势度综合评价数理模型和区域经济水平评价模型,对"一带一路"沿线城市经济发展水平与交通优势度之间的耦合协调关系进行分析,为相关部门决策提供信息参考.研究表明:1)"一带一路"沿线各市域交通优势度具有比较明显的空间差异,形成"东部地区高于西部地区,北部区域高于南部地区"的空间分布格局;2)"一带一路"沿线城市经济综合指数低值集聚现象明显,共形成3个低值集聚区,分别是广东段的西部地区、广东段和广西段的交界区域和海南省的中西部;3)"一带一路"沿线各市域的区域经济与交通耦合协调发展水平整体不高,处于中低度协调阶段.     

中山市土地集约利用与紧凑度耦合关系研究

土地利用是城市发展过程的关键。以中山市为研究区,构建城市土地集约利用和紧凑发展评价指标体系,运用耦合协调发展模型和空间分析方法,对2019年中山市24个镇(区)的城市土地集约利用和紧凑度发展水平及协调关系进行研究。结果表明：(1)中山市各镇(区)之间土地集约利用度和城市紧凑度发展水平存在明显地域差异,其中,火炬开发区、石岐区和西区街道土地利用集约度和紧凑度较高,其他镇(区)则处于较低水平;(2)中山市各镇(区)间耦合协调程度差别较明显,且发展较为协调的区域主要集中在中山市主城区以及火炬开发区街道,除这几个镇(区)外的其他地区耦合协调程度呈现由西北向东南递减的趋势。     

自然资源生态空间现状与适宜性分析评价 ——以上海市金山区为例

本文以上海市金山区为例,利用地理国情普查和监测数据,从生态空间规模水平、生态空间稳定水平、生态空间保障度等角度出发,在常规基础评价指标之外,结合生态空间景观格局指数、生物丰富度指数的综合评价模型方法,对金山区各街镇的生态空间适宜性进行了评价。其技术方法与路线,可为相关部门开展生态环境评价、统筹各类规划的空间要求及强化土地用途管制等提供一定的技术支撑。     

山东省城镇化发展水平格局相关性研究

中国城镇化向着“城乡一体化”发展。为更好地支持山东省城镇化发展决策,本文以山东省17地市为研究对象对山东省城镇化发展水平分布格局及其空间相关性进行了研究。采用复合指标法从人口、经济、社会发展三方面选取10个指标建立评价体系,借助SPSS计算城镇化水平得分,并对城镇化发展水平得分进行探索性空间数据分析,利用ArcGIS对城镇化发展格局进行离散度分析以及可视化表达。分析显示:山东省17个地级市的城镇化水平在全局上具有显著性不强的负相关性,局部区域具有显著性较强的集聚现象。     

国土空间开发及格局优化研究:现状述评、战略方向、技术路径与总体框架

研究目的:国土空间开发是国家发展战略的基础和重要组成部分,优化国土空间开发格局、统筹协调生产、生活、生态——"三生"空间配置,是未来20年我国实现可持续发展的重点任务和根本途径。研究方法:文献梳理、理论分析与顶层设计。研究结果与结论:1国土空间优化开发研究方兴未艾,在多元数据融合、空间格局时空变化模拟预测、空间开发格局评价、优化格局评判模式和标准等方面潜力很大;2未来20年,我国应围绕大力推进生态文明建设,通过实施"点、线(轴)、面"有机结合的多中心网络式、功能差别化的国土空间优化开发战略,构建安全、和谐、开放、富有竞争力和可持续发展的美丽国土新格局;3国土空间优化开发研究,应重点开展国土空间开发时空格局的关系耦合与预测、情景模拟与优化,完善政策建议,形成国土空间开发优化模式并开展应用示范,对未来国土空间开发进行引导和管控,指导基于空间格局的区域和省级国土规划的编制和实施。     

湘江流域主要城市土地利用效率差异性评价

基于社会经济数据构建湘江流域城市土地利用效率评价指标体系,运用熵权法确定指标体系权重,对湘江流域主要城市地区土地利用效率进行了综合评价和协调度分析。研究结果表明,湘江流域主要城市地区土地利用效率整体效率一般,协调度较高,经济效益和投入水平评价差距大,而生态效益和社会效益差距较小,与可持续发展要求有一定差距;土地利用效率在空间格局上存在明显的差异性,呈现出由上游至下游逐渐升高的分布趋势;土地利用效率与协调度的关系为:长沙处于高效高度协调状态,湘潭和株洲处于中效高度协调状态,衡阳与岳阳处于中效基本协调状态,永州处于低效高度协调状态,郴州处于低效基本协调状态。     

甘肃省城乡互动发展空间变化分析

本文基于甘肃省1999年和2008年的基础数据资料,借鉴之前学者关于构建我国城乡关联度评价指标体系的思想,归纳影响研究区城乡互动发展的几类因素,运用因子分析法提取主导因子,并将因子得分信息导入ArcGIS9.2软件进行空间化,对比分析"西部大开发"政策实施前后影响甘肃省城乡互动的驱动力变化,得出结论:近10年影响甘肃省城乡互动发展的主导因子为社会经济发展因子、基础设施建设因子和综合城市化发展水平因子。     

黄河下游影响区城镇化-生态和谐机制与耦合协调发展分析

本文通过和谐度与耦合度双重评价,利用和谐度模型、耦合协调度模型及协调发展度模型,对黄河下游影响区2005—2018年城镇化与生态环境耦合水平在时空上的变化规律进行研究。结果表明：①研究区域耦合水平在整体上呈现先下降后升高的变化规律,耦合关系在阶段上属于由磨合向高水平耦合过渡的阶段,城镇化发展多滞后于生态环境。②黄河下游影响区形成了以郑州和济南为核心的高耦合程度聚集区,且表现出先聚集后辐射扩散的空间聚集与溢出效应。③当前研究区城镇经济发展对耦合水平的贡献较大,现阶段城镇发展对生态环境的综合影响无明显负向倾向。     

湖北省县域交通和经济发展空间格局与耦合

在湖北省县域交通优势度和经济发展水平综合测度的基础上,采用洛伦兹曲线、基尼系数、空间自相关等方法探究交通、经济发展的均衡性及空间集聚效益,计算其耦合协调度,根据两者相对发展度进行交通经济发展类型的划分。结果表明,湖北省县域交通优势度呈现出以武汉、襄阳和宜昌为核心的格局,西部山区交通优势度较低;县域经济以武汉市和宜昌市为核心,武汉市周边形成圈层状递减结构;各县市区交通优势度相对平均,交通发展均衡性优于经济发展;县域交通优势度和经济发展水平均呈正空间自相关,两者的高值聚集区和低值聚集区存在明显的空间重叠;湖北省交通与经济耦合度整体较高,协调性相对较低,绝大多数县市区交通优势未得到充分发挥。湖北省各县市区应充分发挥交通优势,促进经济快速发展。     

协调发展导向的宁夏空间规划战略实施对策研究

研究《宁夏空间发展战略规划》的实施对策,对落实规划总体战略、促进宁夏协调发展具有重要的战略意义。实施"一主三副"战略,推进区域协调发展,重点破解区域发展中差别化不明显的问题;实施"两带两轴"战略,推进城乡协调发展,重点破解城乡二元结构问题;实施"产业集群"战略,推进经济社会协调发展,重点破解产业支撑能力弱的问题;实施"山河为脉"战略,推进人与自然协调发展,重点破解发展的粗放低效和资源约束问题;实施"内陆开放"战略,推进区内开发与对外开放协调发展,重点破解国内开放与国外开放程度较低的问题。     

基于DMSP-OLS和MODIS数据的宁夏城市化与生态环境耦合协调分析

科学认识城市化与生态环境耦合协调机制,对推动黄河流域及黄河所经地区生态保护和高质量发展具有重要意义。本文以宁夏回族自治区为例,采用长时间序列DMSP-OLS夜间灯光数据建立了适用于宁夏的城市夜间灯光指数（UNLI）,并利用MOD09A1、MOD11A2提出了一种面向大区域尺度的遥感生态指数（RSEI）构建方法。在此基础上,采用耦合协调度模型（CCDM）,探讨分析了2000—2012年宁夏5个地级市城市化与生态环境耦合协调发展过程。结果表明：①基于DMSP-OLS数据建立的宁夏城市夜间灯光指数与人均GDP,以及第一、二、三产业GDP相关性显著（p<0.001）,能够较好地反映宁夏城市化水平。②基于MOD09A1、MOD11A2建立的遥感生态指数能够较好地反映宁夏生态环境质量时空变化特征。③宁夏城市化与生态环境耦合协调度呈稳定上升趋势,整体处于基本协调-生态环境滞后的转型阶段。研究结果对沿黄城市生态保护和高质量发展具有重要参考价值。     

Quantifying spatiotemporal dynamics of agricultural landscapes using remotely sensed data and landscape metrics

This study focuses on the spatiotemporal dynamics of agricultural lands and differences in rapidly developing urban and declining rural counties in Iowa, USA between 1984 and 2000. The study presents an analysis of land-cover maps derived from Landsat TM and ETM+ satellite imagery and different landscape metrics using FRAGSTATS and IDRISI software. The study provides evidence of both loss of croplands and change in fragmentation between 1984 and 2000. Fragmentation in agriculture-dominated areas increased with the development of urban centres and diversification of land uses. Fragmentation of landscapes, including agricultural land, was found to be higher in the urbanized counties, but was stable or even declined over time in these counties. In contrast, in the context of remote rural areas, agricultural landscapes experienced rapid increase in fragmentation and farmland loss. The urban–rural gradient analysis used in this study showed that the highest fragmentation occurred on the city edges. These findings suggest that farmland fragmentation is a complex process associated with socio-economic trends at regional and local scales. In addition, socio-economic determinants of landscape fragmentation differ between areas with diverging development trajectories. Intensive cropland fragmentation in remote agricultural regions, detected by this research, should be further studied and its possible effects on both agricultural productivity and biodiversity should be carefully considered.     

山地丘陵与平原地区城乡聚落空间分布分形特征研究

本文以河南省区域系统的不同地域单元为例,运用城镇体系研究的空间关联维数模型对山地丘陵区及平原地区城乡聚落体系空间结构进行分析,结果表明农村聚落具有与城市聚落相同的空间分布分形特征;山地丘陵城市的城乡聚落空间可达性不及平原城市;城乡聚落空间分布的乌鸦维数集中在1左右,差别不大,表明河南省作为中原地区所具有的城乡聚落空间布局的总体均衡性。基于此提出了中部农区城乡聚落空间优化、撤乡并镇、新农村社区建设应结合地域城乡聚落分布特点制定适宜的规划方案等有益的建议。     

The urban greenness score: A satellite-based metric for multi-decadal characterization of urban land dynamics

Canada’s urban areas have experienced extensive growth over the past quarter century; however, there has been no consistent, spatially explicit approach for quantifying the loss and gain of greenness in cities nationally. Herein, we developed a novel urban greenness score metric using greenness fractions from a multi-decadal time series (1984–2016) of spectrally unmixed annual Landsat satellite image composites to characterize final year (2016) greenness and its overall change for 18 major Canadian urban areas, summarized by census dissemination area (DA). The applied validation procedure confirmed correlation coefficients (ρ) ranging from 0.67 – 0.85 between reference and estimated greenness fractions, indicating that spectral unmixing is an appropriate method for extracting urban greenness from a time series of medium spatial resolution satellite imagery. Most DAs across Canada sustained a moderate (∼20 % – 40 %) or low (≲ 20 %) level of greenness between 1984 and 2016, but overall there was a decreasing trend in greenness. Eastern urban areas maintained the most greenness over time, while urban areas in the Prairies had the greatest increase in greenness. Densely populated urban areas experienced the greatest loss in greenness (16 % of DAs); whereas, urban areas with a moderately-low density experienced the greatest increase (14 % of DAs). In agreement with previous studies, we found that greenness was negatively associated with urban infilling, with lower greenness levels typically found in urban cores, and greenness loss most often found in the urban periphery in conjunction with urban expansion. Methods presented in this analysis take advantage of the open and longstanding Landsat archive, as well as multiple spatial scales, including sub-pixel unmixing techniques, pixel level greenness faction data summarized for management units, and analysis conducted nationally. The developed urban greenness score provides a comprehensive framework to understand current urban greenness and relate it to its recent past, which supports long-term strategic planning, and can be transferred to other regions across spatial and temporal scales.     

Nighttime light data-based analysis of spatiotemporal patterns evolution and driving forces of economic development in China at prefecture level (1992–2020)

Intercity lighting data are an important resource for studying spatial and temporal patterns in regional urban development as an indicator of the intensity of urban social and economic activity. Understanding the evolutionary characteristics of the spatial pattern of regional economic development can support decision-making in regional economic coordination and sustainable development strategies. Based on a long time series of nighttime lighting data from 1992 to 2020, this study used the Theil index, Markoff transfer matrix, spatial autocorrelation, and spatial regression to analyze spatiotemporal evolutionary characteristics and drivers of urban economic development in China. The study found that from 1992 to 2020, China's economic development hot spots have been concentrated in highly developed urban agglomerations namely the Beijing–Tianjin–Hebei region, Shandong Peninsula, Yangtze River Delta, and Pearl River Delta. Cold spots were mainly concentrated in the central-west and southwest of the country. The economic growth rate shows an opposite spatial pattern, which demonstrates the effectiveness of the national coordinated development strategy for regions. The Theil index for urban economic development in China shows an overall downward trend, and the overall economic disparity is mainly due to the relatively low economic development of Tibet, Xinjiang, Gansu, and other western provinces. Therefore, regional economic development remains significantly uneven. In China, the economic type of cities is relatively stable, and the probability of leapfrogging types is low; however, the level of cities with high resource dependence or a single economic structure easily downgrades. The level of economic development and the related socioeconomic factors of neighboring cities influence an obvious spatial spillover effect in the development of urban economies in China. The pattern of China's urban economic development is mainly affected by innovation capacity, financial support, capital investment, transportation infrastructure, and industrial structure.     

基于GIS的石家庄市雾霾分析

为了得出雾霾气象成因机制、影响因素和时空分布特征,以石家庄市区与郊县为研究区域,将2013年9月至2016年12月石家庄市各市区、郊县的PM2.5历史监测数据中的有效数据进行了数据分析处理得到雾霾浓度数据,还有温度、降水、风速、地形和人口密度等数据,运用GIS分析的方法,模拟绘制石家庄雾霾的时空分布图、雾霾与各影响因子的专题对比图,得到雾霾形成机制的因子、雾霾的时空分布规律、雾霾季节变化特征、雾霾与地形间的关系等;运用数据分析软件OriginPro8.SR3分析雾霾浓度与风速数据、降雨数据、温度数据间的相关性。     

Positional Accuracy of TIGER 2000 and 2009 Road Networks

The Topologically Integrated Geographic Encoding and Referencing (TIGER) data are an essential part of the US Census and represent a critical element in the nation's spatial data infrastructure. TIGER data for the year 2000, however, are of limited positional accuracy and were deemed of insufficient quality to support the 2010 Census. In response the US Census Bureau embarked on the MAF/TIGER Accuracy Improvement Project (MTAIP) in an effort to improve the positional accuracy of the database, modernize the data processing environment and improve cooperation with partner agencies. Improved TIGER data were released for the entire US just before the 2010 Census. The current study characterizes the positional accuracy of the TIGER 2009 data compared with the TIGER 2000 data based on selected road intersections. Three US counties were identified as study areas and in each county 100 urban and 100 rural sample locations were selected. Features in the TIGER 2000 and 2009 data were compared with reference locations derived from high resolution natural color orthoimagery. Results indicate that TIGER 2009 data are much improved in terms of positional accuracy compared with the TIGER 2000 data, by at least one order of magnitude across urban and rural areas in all three counties for most accuracy metrics. TIGER 2009 is consistently more accurate in urban areas compared with rural areas, by a factor of at least two for most accuracy metrics. Despite the substantial improvement in positional accuracy, large positional errors of greater than 10 m are relatively common in the TIGER 2009 data, in most cases representing remnant segments of minor roads from older versions of the TIGER data. As a result, based on the US Census Bureau's suggested accuracy metric, the TIGER 2009 data meet the accuracy expectation of 7.6 m for two of the three urban areas but for none of the three rural areas. The suggested metric is based on the National Standard for Spatial Data Accuracy (NSSDA) protocol and was found to be very sensitive to the presence of a small number of very large errors. This presents challenges during attempts to characterize the accuracy of TIGER data or other spatial data using this protocol.