COSMO-SkyMed颜色变换强度RC法南京建设用地变化检测

基于非局部滤波的SAR强度RC合成变化检测法对小图斑、线型地物等动态监测灵敏,且对数据获取无时空基线要求,在多云多雨城市地表要素变化检测中具备潜力。本文研究以多时相SAR强度RC合成图为数据源,提出一种基于色彩空间变换的变化图斑半自动提取方法,即通过色彩空间转换、训练样本选取、监督分类影像分割、变化区域提取4步骤,可实现基于SAR强度图的城市建设用地动态监测与图斑高效更新。选取南京河西新城与江北新区为示范,以最优参数配置（3特征向量与10样本类别）进行试验,实现了优于88%的建设用地查准率指标。     

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。     

典型喀斯特城市的热岛时空变化及其成因分析

利用1989、2003、2018年的Landsat影像对安顺市西秀区的地表温度进行反演,分析研究区在30年发展中的热岛时空变化及其成因。使用基于影像的反演算法,结合分类回归树算法进行地表温度的反演,用气象站数据对反演结果进行精度验证,并建立缓冲区对研究区进行相关性分析等定量分析。结果表明：研究区受喀斯特地貌的影响,除主城区外,郊区也存在大量高温区;近30年研究区热效应与不透水面、绿地的面积有极显著相关;1989-2003年研究区城市热岛面积随城市扩张逐渐增大,但2018年主城区城市热岛现象几乎完全消失,排除气象因素和城市形态因子影响的可能后,发现这与安顺市城市绿化的大力进行有密切关系。     

A high-precision heuristic model to detect home and work locations from smart card data

Smart card-automated fare collection systems now routinely record large volumes of data comprising the origins and destinations of travelers. Processing and analyzing these data open new opportunities in urban modeling and travel behavior research. This study seeks to develop an accurate framework for the study of urban mobility from smart card data by developing a heuristic primary location model to identify the home and work locations. The model uses journey counts as an indicator of usage regularity, visit-frequency to identify activity locations for regular commuters, and stay-time for the classification of work and home locations and activities. London is taken as a case study, and the model results were validated against survey data from the London Travel Demand Survey and volunteer survey. Results demonstrate that the proposed model is able to detect meaningful home and work places with high precision. This study offers a new and cost-effective approach to travel behavior and demand research.     

A novel spatial index using spatial analyses and hierarchical fuzzy expert system for obtaining green TOD: a case study in Tehran city

Sustainable development is a vital and challenging factor for managing urban growth smartly. This factor contains three main components, namely economic growth, ecological protection and social justice. Green Transit-Oriented Development (GTOD) is a consummate planning approach in line with those components. Implementation of GTOD in an urban area is underpinned by its quantification. Therefore, a quantitative spatial index based on several indicators related to TOD and Green urbanism concepts should be developed. In this study, Geo-spatial Information Science and hierarchical fuzzy inference system (HFIS) were employed to calculate the indicators and aggregate them, respectively. In order to showcase the feasibility of the proposed method, it was implemented in a case study area in the City of Tehran, Iran. The result of this method is an integrated spatial GTOD index, which measures the neighbourhoods’ GTOD levels. These measurements specify weaknesses and strengths of neighbourhoods’ factors. Therefore, this index helps decision-makers to plan neighbourhoods based on land use and public transit views. Additionally, the HFIS method helps decision-makers to consider criteria and indicators with their inherent uncertainties and aggregate them with much fewer rules. For evaluating the results, the developed GTOD index was assessed with municipal action planning and attraction maps. According to the outcomes of the assessment, it is concluded that the proposed method is adequately robust and efficient for smart and sustainable urban planning.     

Geographical information system-based groundwater quality index assessment of northern part of Kolkata,India for drinking purpose

Groundwater is a resource under stress. In both developed and developing countries, it has been found that increasing human influence has led to the contamination of the groundwater resource. To understand the magnitude of this problem, a study was conducted in 58 wards within Northern part of Kolkata, India, where water samples from tube wells were collected and analysed on essential drinking water quality parameters, prescribed by WHO. Using Principal component analysis, and Water quality index mapping, the aforementioned results have been interpreted. This has helped to depict that not only is the groundwater unsuitable for drinking, but that the parametric values have a tendency to increase abruptly within the shortest of ranges, indicating urban pollution as the root cause of contamination. This paper shall thus discuss the spatial change in groundwater quality in northern Kolkata and suggest measures which might be implemented to secure a sustainable future for the city.     

A comparative analysis of gridding systems for point-based land cover/use analysis

For spatial analyses, raster land cover/use maps are converted into points, where each point holds attribute of its corresponding land cover/use. However, these are not identical in terms of areas or shapes; thus assigning a point to each isolated shape is not an adequate solution and for that gridding is suggested. Square, hexagon and triangle are among the basic land use gridding systems where each of them has its own advantages in such process. This research aims to compare the systems in providing accurate representations of the original land cover/use maps, assess the data loss while increasing resolution and suggest suitable gridding system. The research finds the errors in area and feature numbers as criteria for selected classes. Modules that find out errors in each scale considering each criterion and class alone are proposed. The modules suggest both the best system for each criterion alone and for combined criteria.     

Statistical analysis of surface urban heat island intensity variations: A case study of Babol city,Iran

The urban heat island is considered as one of the most important climate change phenomena in urban areas, which can result in remarkable negative effects on flora, concentration of pollutants, air quality, energy and water consumption, human health, ecological and economic impacts, and even on global warming. The variation analysis of the surface urban heat island intensity (SUHII) is important for understanding the effect of urbanization and urban planning. The objective of this study was to present a new strategy based on the Shannon’s entropy and Pearson chi-square statistic to investigate the spatial and temporal variations of the SUHII. In this study, Landsat TM, ETM+, OLI and TIRS images, MODIS products, meteorological data, topographic and population maps of the Babol city, Iran, from 1985 to 2017, and air temperature data recorded by ground recorder devices in 2017 were used. First, Single-Channel algorithm was used to estimate land surface temperature (LST), and the maximum likelihood classifier was employed to classify Landsat images. Then, based on LST maps, surface urban heat island ratio index was employed to calculate the SUHII. Further, several statistical methods, such as the degree-of-freedom, degree-of-sprawl and degree-of-goodness, were used to analyse the SUHII variation along different geographic directions and in various time periods. Finally, correlation between various parameters such as air temperature, SUHII, population variation and degree-of-goodness index values were investigated. The results indicated that the SUHII value increased by 24% in Babol over different time periods. The correlation coefficient yielded 0.82 between the values of the difference between the mean air temperature of the urban and suburbs and the SUHII values for the geographic directions. Furthermore, the correlation coefficient between the population variation and the degree-of-goodness index values reached 0.8. The results suggested that the SUHII variation of Babol city had a high degree-of-freedom, high degree-of-sprawl and negative degree-of-goodness.     

雾霾的影响因子分析及其区域相关性研究

成都、重庆作为中国西南地区快速发展的城市,是雾霾频发的区域,研究其雾霾因子联系以及区域空间分布特征及其规律,对于城市发展、创建绿色城市具有重要意义。通过分析2016年12月~2017年2月的PM2.5等污染物浓度数据可知:①成渝地区雾霾产生的高峰期在1月,并以成都、重庆为中心向四周减弱;②在时间分布上,成都和重庆的雾霾污染物浓度呈协同变化趋势,说明两地雾霾在区域上相互影响,协同作用;③在气象因素中,两地的湿度和风速对雾霾集聚、转移和扩散具有重要作用;④两地的位置和地形特征是其雾霾具有相关性的重要因素,因此只有两地同时防治雾霾,才能达到最好的效果。根据不同地域特征,积极改进生产结构,采取相应措施,才是治理雾霾的根本所在。     

无人机倾斜摄影三维模型在城市雨洪风险评估中的应用

研究城市雨洪风险问题,对提高城市洪涝灾害监测、预报的准确性,以及促进城市防洪决策制定具有重要的意义。鉴于高精度的城市三维模型可以提供丰富地理信息,便于准确分析淹没情况,本文针对当前城市洪涝模型对地形数据的高敏感性,且雨洪风险评估研究的准确性受限于地形数据精度的问题,提出利用无人机倾斜摄影测量技术重建高精度实景三维模型,并结合GIS的空间分析功能,以淹没深度为关键指标进行研究区的雨洪风险评估。通过提取不同重现期下研究区的淹没深度信息,进行可视化渲染实现三维淹没分析,可以直观地看到研究区的淹没情况,作为暴雨内涝风险管理依据,同时对城市规划布局有一定的参考价值。