Rail transportation plays a crucial role in improving travel efficiency and reducing traffic congestion. Due to the concentration of resources, Dongcheng and Xicheng districts in Beijing City face serious traffic congestion, a higher working population compared to residents, and significant commuting pressure which makes green commuting through rail transportation becoming essential for daily life. The convenience and user-friendliness of slow mobility systems around rail stations influence the travel experience and comfort of people on the move. It is also an important aspect of the current urban renewal and rail transportation upgrades in Beijing. Therefore, this study focuses on evaluating the slow mobility systems around rail stations for Dongcheng and Xicheng. This paper utilizes internet and spatial big data to establish a slow mobility evaluation framework, including indicators such as station vitality, population coverage, surrounding environment, accessibility, and detour coefficient by using developed program, FME, GIS network built and analysis methods.

Rail transportation plays a crucial role in improving travel efficiency and reducing traffic congestion. Owing to the concentration of resources, Dongcheng and Xicheng districts in Beijing City face serious traffic congestion. Therefore, rail transportation has become essential for daily commuting in such a region. The convenience and user-friendliness of slow mobility systems around rail stations affect the travel experience and efficiency. It is also an important aspect of the current urban renewal on rail transportation upgrades in Beijing. Therefore, in this study, we focus on evaluating the last mile problems on slow mobility systems around rail stations for Dongcheng and Xicheng districts. We utilize internet and spatial big data to establish a slow mobility evaluation system, including indicators such as station vitality, population coverage, surrounding environment, accessibility, and detour coefficient by using the Python programming language, Feature Manipulation Engine (FME), and Geographic Information System (GIS) network analysis methods.

With the development of computer vision and remote sensor devices, object detection in aerial images has drawn considerable attention because of its ability to provide a wide field of view and a large amount of information. Despite this, object detection in aerial images is a challenging task owing to densely packed objects, oriented diversity, and complex background. In this study, we optimized three aspects of the YOLOv5 algorithm to detect arbitrary oriented objects in remote sensing images, including head structure, features from the backbone, and angle prediction. To improve the head structure, we decoupled it into four submodules, which are used for object localization, foreground, category, and oriented angle classification. To increase the accuracy of the features from the backbone, we designed a block dimensional attention module, which is developed by splitting the image into smaller patches based on a dimensional attention module. Compared with the original YOLOv5 algorithm, our approach has a better performance for oriented object detection-the mAP on DOTA-v1.5 is increased by 1.25%. It was tested to be effective on DOTA-v1.0, HRSC2016, and DIOR-R datasets as well.

The general survey of geographical conditions based on remote sensing technology has been the main land space monitoring activity in China in recent years.To make census results better serve society, in this paper, we evaluate the livability of Beijing's land space.Based on socioeconomic data and the data from the census of national geographical conditions, an analytic hierarchy process was used to quantitively calculate the livability scores.Six subsystems were included in our calculations: social development, economic development, ecological environment, resource carrying capacity, infrastructure, and public safety, and finally, a comprehensive score is calculated.The Xicheng, Chaoyang, and Haidian Districts of Beijing are ranked highest for livability, and Yanqing, Daxing, and Fangshan Districts are ranked lowest.We find that social development, economic development, infrastructure, and the ecological environment contribute the most to livability scores, while public safety and resource carrying capacity contribute the least.To improve comprehensive regional livability, it is necessary to pay attention to the balanced development of public security and resource carrying capacity.

The issues of housing and traffic in China's mega cities have become increasingly pressing problems, particularly for middle/low-income tenant workers. These tenants are from less advantaged socioeconomic backgrounds, which has resulted in a significant geographical separation between their workplace and their residence. Although a large number of studies have confirmed that built environment factors have a solid impact on residents’ commuting distance, few studies have investigated the mechanism underlying the nonlinear influence on middle/low-income tenants. This paper aims to provide an in-depth analysis of the key factors and nonlinear influencing mechanism of the built environment on middle/low-income tenant workers’ commuting distance by establishing a gradient-boosting decision tree model, using Beijing as an empirical case. The paper reveals three primary findings: (1) An important nonlinear relationship between the surrounding built environment and peoples’ jobs–housing spatial proximity can be observed for those middle/low-income tenant workers who use slow and public modes of commuting. Specifically, the density of public transport stations, road networks, and workplaces, and the land use mix play a dominant role. (2) A limited effect of built environment factors can be found for the same group of tenant workers who choose cars as their mode of commuting. (3) The differences in self-selected commuting modes have a significant mediating effect on the relationship between the built environment and jobs–housing situation among middle/low-income tenant workers. Given this, effective policy guidance for residents’ travel modes is necessary to optimize the built environment indicators to achieve the best effect. In addition, we should consider giving priority to the matching indicators such as land use mix and resident population density. Another possibility is to strengthen the connection to the public transport stations, which in turn can optimize the walkability in residential environments.

The Qilian Mountains (QMs), located in the northeast part of the Qinghai–Tibetan Plateau in China, have a fragile ecological environment, complex and sensitive climate, and diverse land-cover types. It plays an important role in the “Qinghai–Tibetan Plateau Ecological Barrier” and “Northern Sand Control Belt” in China’s “two screens and three belts” ecological security strategy. Based on land use data of 1980, 1990, 1995, 2000, 2005, 2010, 2015, and 2020, we utilized GIS technology, land use dynamic degree, and land use transition matrixes to analyze the spatial and temporal evolution of land use in the QMs from 1980 to 2020. The results showed the following: (1) From 1980 to 2020, grassland, forest land, and unused land were the main land-use types in the QMs, and the proportion of construction land accounted for only 0.31% of all land-use types. (2) The single land use dynamic degree showed that the dynamic degree of construction land was the highest and the fastest change rate from 2010 to 2015. The comprehensive land use dynamic degree showed that the intensity of land-use change was relatively drastic in the three time periods of 1990–1995, 1995–2000, and 2015–2020. (3) The land-use types in the study area switched infrequently during 2000–2005, 2005–2010, and 2010–2015. (4) The main transition directions of land-use types were grassland and unused land to other land-use types. These changes altered the spatial distributions of different land-use types. The study is critical for understanding the spatial and temporal change patterns of land-use change in the QMs and providing guidance for the optimization of land use in the study area and the improvement of regional eco-environmental protection.

With the development of the census and monitoring of national geographical conditions in China, the availability of information has sharply increased.Progress in data mining methods and social application tools has provided a way for solving the problems of low resource allocation and high uncertainty in decision-making regarding planning.To relieve non-capital functions and serve the healthy development of the Beijing Metropolitan Area, we propose a new model of self-adaptive cellular automaton based on ensemble learning (EL-CA).The method is based on the data collected by monitoring geographical conditions and is guided by complex geocomputing that simulates city-scale evolution in Beijing.A comparison of predicted and real data for Beijing in 2015 demonstrated that the predictions made by the EL-CA model proposed significantly outperformed those by traditional cellular automaton (CA) models based on empirical statistics.Data on the geographical conditions in Beijing in 2007 and 2015 were employed in model simulation and training to predict the scale of the city in 2023.The urban agglomeration points in Beijing tended to be dense, the overall construction land tended to be saturated, and the growth rate of land use areas slowed.Results from the model also established that the construction land in Beijing is close to saturation from a quantitative perspective, and the potential urban expansion hotspots in the future are mainly concentrated in the Tongzhou District, the Daxing District, the Fangshan District, the south side of the fourth and fifth ring roads, and the southwest side of Pinggu District.These results can provide decision-makers in urban planning with supporting data and support Beijing to relieve Beijing of functions nonessential to its role as China's capital.

利用2009、2018年分辨率为1 m的卫星遥感影像,依据地理国情监测的分类体系,获取了两个年份石家庄8个区县的地表覆盖数据,展示了该区域林地、草地和水域三类自然生态空间要素10 a间的变化情况,并采用生境质量指数、水源涵养指数两项指标对该区域的生态环境状况进行了评价.归因于该区域固有的自然地理特征,大部分地区生境质量指数处在"较差"区间,水源涵养指数处在"差"的区间,且由于石家庄城市化进程较快,十年间部分区域的两项指数有小幅降低.

Ecosystem service assessments have been conducted for coastal management with a primary focus on tangible natural capital. Thus far, the explicit variation of cultural ecosystem services (CESs) and particularly the sentiments of CES-related ecotourism are not well understood. This paper takes advantage of big social media data to unravel the patterns of CESs and visiting sentiments in coastal areas of Hong Kong. Through machine-learned keyword labels, we employed content analysis to derive visual information for geotagged photographs. Applying natural language processing to apps with machine learning in cloud computing, we derived the sentiments based on user-generated textual content associated with coastal ecotourism. Based on regression analysis and multiple comparisons analysis, we identify the association between critical demographic and temporal factors with CES and related visiting sentiments. Referring to previous studies, we identified the main intangible benefits into six basic divisions based on 424 keyword labels for coastal areas. Our results show that hotspots of CESs are spatially concentrated in both cultural attractions and protected areas, which are critical for coastal ecosystem management and protection. More specifically, these areas of high CES value have good spatiotemporal accessibility, high infrastructure coverage, and spatially explicit population and economic growth. Furthermore, we discover that sentiments related to coastal CESs vary based on social media characteristics. Our study renews the indicators of quantitative CES evaluation based on crowdsourcing geospatial data.

为了有效评估生态保护红线的实施情况,该文提出以植被净初级生产力作为指标动态监测生态保护红线区域内外生态植被情况的方法,并基于Mann-Kendall检验方法分析其变化趋势,较好地反映了房山区生态保护红线划定实施的成效.研究结果表明:房山区植被净初级生产力呈现西北部山地区域高、东南部平原地区低的特征,并在2014-2019年6年间呈缓慢波动上升趋势,在2019年生态保护红线内植被NPP均值达到最大,房山区生态整体呈改善的趋势.该文提出的生态保护红线监测方法,实现了对生态保护红线区域整体及内外的快速精确评估.

生态保护红线是一种新型区域生态管控制度体系,是党中央、国务院在新时代做出的一项重大决策.针对生态保护红线存在边界不规则、生产建设用地扣除偏差、精度和现势性不足等问题,基于遥感影像和GIS技术,提出了生态保护红线校核技术路线,制定了5个一级类、24个二级类的生态保护红线优化调整指标体系;提出了多源数据融合、三条控制线协调、红线边界优化、勘界定标、数据建库等数据管理和更新技术流程,并阐明生态保护红线在城市规划建设和生态环境保护中的应用.可为其他城市生态保护红线的校核、优化和调整提供参考.

城市承载力是指一定范围内,特定目标、特定时期城市的资源禀赋、生态环境、基础设施和公共服务对人口及经济社会活动的承载能力.基于房屋建筑和手机信令数据,从城市管理的空间特性出发,构建以居住空间承载力、就业空间承载力、公共服务空间承载力和道路空间承载力为切入点的评价指标,并以北京市为例,结合相应的规划、标准,进行城市功能空间承载力的测算,评估北京市城市功能空间承载力的现状情况.结果 表明,①北京市居住空间、就业空间和公共服务空间总量充足,但分布不均,承载压力由高到低显现出从城区内向城区外多中心逐级递减的趋势;②北京市道路空间承载力不容乐观,人均占有率较低,易产生交通拥堵;③北京市城市功能空间集聚现象明显,呈现出由城区内向城区外多中心逐级递减的现象;④进一步对比研究发现,道路空间和居住空间是北京城市功能空间发展的短板因素.

标准是经济社会发展的技术支撑,也是国家质量技术基础建设的重要内容.项目依托第一次地理国情普查和北京市地理国情常态化监测工作,编制适合北京市具体特点的地理国情监测内容与指标、内业采集、外业调查、调绘底图制作、质量检查和统计分析等系列标准,并在数据建模理论与方法、城市监测技术体系、统计分析单元与计算方法、产品体系和应用模式等方面进行了创新,保证其实用性、针对性、先进性和可操作性,对地理国情监测的开展具有指导和促进作用.

地理国情监测是顺应新时期空间信息科学发展而产生的一项重大国情调查.立足北京市特点,结合实际需求,2019年度北京市地理国情监测完成对全市域范围内重要城市监测要素变化情况监测,面向交通、水务、房屋和生态环境等方面展开专题监测工作,形成现势性强、精度高的2019年全市地理国情监测成果.总结北京市2019年度地理国情监测的工作流程、主要技术方法以及成果应用领域,在自然资源改革新时期下,调整把控未来地理国情监测方向.

针对现有职住空间关系的研究难以在微观维度上有效促进大城市职住功能空间的均衡发展以及规划政策与现状发展存在的时序错位问题,该文以北京市为例,从房屋建筑使用用途的角度切入,运用空间自相关分析模型、热点分析模型和职住用地比三个评价方法,同时借用ArcGIS软件平台进行空间分析与可视化表达,探究北京职住空间在乡镇尺度下的组织特征.研究发现:北京市职住空间表现为聚类分布的空间格局特征,以首都功能核心区为中心,大致呈现出环状圈层分布,北京市职住空间的"热点区"在空间分布上存在差异,而"冷点区"在空间分布上基本相同,职住空间关系存在失衡,与规划目标存在一定的偏差.提出的研究方法从微观维度分析了城市职住空间的组织特征,促进了城市规划与发展时序的有效结合,可在特大城市的职住空间关系的研究中进行推广应用.

减量提质是城市发展到一定阶段后的必然要求.针对在治理城市病过程中存在的数据不够丰富、方法不够创新、挖掘不深入、监测不够及时等问题,制定了"全、细、实"的城市空间信息监测内容与指标体系,构建了复杂环境下的城市空间监测数据获取、处理、质检、展示等技术体系,提出了基本、综合、专题"三位一体"的统计分析体系,并创建了社会化应用的软件体系、产品体系和应用模式.成果能够提升城市治理能力、精细化管理水平,可为其他城市提供借鉴和参考.

针对保障生态保护红线精准落地、服务国土空间规划问题,该文基于北京市生态保护红线评估工作实践,以国土空间规划为视角,提出生态保护红线成效评估指标,分析了北京市生态保护红线校核前后边界规则程度、地表覆盖以及与自然保护区协调程度的变化.研究结果表明,北京市生态保护红线校核后边界复杂程度降低;房屋建筑区、构筑物、人工堆掘地、铁路与道路、种植土地均有所减少,荒漠与裸露地表基本没有变化,林草覆盖、水域明显增加;自然保护区各功能分区面积都有所增加.在今后生态保护红线动态更新过程中要全面掌握空间规划需求,推进"多规合一"实施,实现全市"一张图".

Transit-oriented development (TOD), which is regarded as an efficient planning strategy for urban sustainability, has surged in use across the globe in the recent past. While the lessons learned from case studies of individual cities can provide valuable references, they also result in a gap between existing theoretical principles and actual planning practices. The comparative analysis of TOD typologies among cities affords unique strengths for addressing such a challenge. By extending the classic ‘node–place’ model with a third dimension, this paper first constructs a ‘node–functionality–place’ model in the form of a magic cube as the theoretical basis for classifying TOD typologies. Then, the model is applied to five typical Chinese megacities, namely, Beijing, Shanghai, Shenzhen, Wuhan and Hangzhou. After establishing an indicator system, the analytic hierarchy process (AHP) is used to determine the TOD degree, and a two-step cluster is employed to classify TOD typologies. The results show that the TOD degree, although it varies with cities, presents a similar spatial pattern, with a general tendency to decline from the central core to the outskirts. In total, six TOD types are distinguished and present notable variations within and across the five megacities. The identified TOD typologies thus equip urban planners and policymakers with a useful tool for designing more targeted strategies. The discoveries made in the comparative context differ from those made in the individual context in prior studies. This paper is thus believed to make a new contribution to the existing TOD literature.

Based on the construction of an evaluation index system for land urbanization quality, this paper evaluates and analyzes the variability of spatial-temporal in land urbanization quality during 2005-2015 in China. Results shows that: (1) Among the three aspects of land urbanization quality, sustainable development capacity scores the highest, land urbanization development quality follows, land-population coordinated development is the lowest. (2) The quality of land urbanization in China is generally improving, and the spatial distribution has a “gradient difference”, showing a pattern of high east and low west. In conclusion, to improve the quality of land urbanization, all aspects should be considered comprehensively; each region should combine its own conditions to formulate strategies for improving the quality of land urbanization.

地理国情监测是一项重大国情国力调查,是一个国家基础性、战略性资源,是城市规划、建设和治理的重要基础,也是监测“城市病”的重要手段,具有不可替代的重要作用.北京等大城市在住房、交通、人口、环境等方面深受“城市病”困扰,迫切需要创建城市地理国情监测技术、方法、装备、软件服务体系.本文针对大城市特点,阐述了北京市地理国情监测具体工作内容,充分利用测绘的先进技术、数据资源等优势,积极开展地理国情变化监测与统计分析,对重要城市地理要素进行动态监测,及时发布监测成果和分析报告,为科学发展提供依据.同时,重点对北京市监测成果的应用进行了归纳,可为其他城市地理国情监测的成果转化提供参考,拓宽业务领域.