基于无人机影像的城市规划指标计算

在采用传统测绘方式形成测绘成果后,基于该成果进行建筑密度、绿地率、建筑占地面积、绿地面积等现状规划指标计算时,存在时效性差、便捷度低等问题。本文提出了一种利用无人机影像进行现状规划指标计算的思路和方法,开展研究并初步设计了一套基于无人机影像的规划指标计算系统。对广州市番禺区洛溪岛区域进行试验航飞,并利用图像分割方法对城市要素进行分析提取后,进行各类规划指标计算。     

城市局部气候分区对地表温度的影响 ——以大连市区为例

以大连市区建筑数据、SPOT 5和Landsat 8遥感数据为基础，运用局部气候带分类、地表温度反演方法，研究大连市局部气候带分区类型和特征，进而分析不同局部气候带对城市地表温度的影响。研究结果表明：①大连市建筑类型高度主要为低层建筑、多层建筑和中高层建筑，建筑密度为中密度和较高密度，甘井子区分布大量森林绿地，中山区具有丰富的公园绿地；②地表温度整体偏高，空间上呈现东高西低的趋势，其中半数以上地区地表温度达到28℃~31℃，并且有超过1%的地区地表温度大于38℃，该区域出现极端高温；③同一建筑高度上，密度越大的建筑区域，地表温度越高；同一建筑密度，多层建筑高度覆盖区地表温度较高。森林绿地地表温度最低，公园绿地和社区绿地地表温度几乎一致，附属绿地地表温度最高。     

沈抚“同城区”生态空间遥感自动识别及动态检测研究

以辽宁省沈抚新城区为研究对象,选择2006、2010及2014年Landsat影像为数据源,利用面向对象方法提取城市生态空间信息,并对研究区内的景观格局动态特征和多方向变化特征进行了相关计算和分析。结果表明:1)多方向变化分析研究区南部城市增长最多,沈抚新城发展中抚顺区域推进较快,不断向沈阳方向发展;2)绿地整体的增加和城市建筑增加呈显著正相关,沈抚新城生态空间结构逐渐靠拢,并向着规划中的打造浑河景观带的目标努力;3)2006~2014年期间,平均斑块面积和最大斑块指数呈增加趋势,散布与并列指数和蔓延度指数逐年递减,说明沈抚同城化过程中景观具有均衡性和规划性。     

基于3DGIS的城市规划可视性分析模型研究

视觉效果是城市规划需要考虑的重要要素之一.基于3 DGIS的计算机技术可以用于定量分析城市三维景观空间的可视性.本文介绍了可视性分析应用于城市规划的流程,提出了针对地形和建筑物可视性分析的数学几何模型.在地形可视性分析模型中,采用了一种结合水平投影和高程插值计算的方法判断地形上两点之间的通视性;在建筑物可视性分析中,采...     

Detecting urban ecological land-cover structure using remotely sensed imagery: A multi-area study focusing on metropolitan inner cities

With increasing attention being paid to sustainable urban development and human habitation improvement, urban ecological land cover (UELC), i.e., surface water and green space, has played an important role of the highly compact inner urban regions. In this study, we developed an efficient approach for UELC mapping by coupling Sentinel-2 multi-spectral imagery and Google Earth high-resolution imagery. In contrast with the conventional single-source and multi-source imagery-based classification methods, the proposed method respectively achieved the highest overall accuracies of 91.50% and 94.05% in the UELC mapping for two test sites (i.e. Shanghai and Seoul). The proposed method is used for urban surface mapping among six world-class cities. For an in-depth analysis of the landscape structures for inner urban regions, seven landscape metrics are introduced for the quantification of the UELC structure based on the obtained high-precision UELC maps. The result shows that London appears to have the best UELC-induced ecological quality, that is, with high percentage of landscape, area-weighted mean fractal dimension, edge density, Shannon’s evenness index values and a low contagion index value, while Tokyo is exactly the opposite. Several common characteristics found through the statistical analysis are: 1) all the inner-city regions have small UELC coverage (< 50%) and low shape complexity; 2) green space generally contributes more to urban eco-environment than the urban surface water; and 3) all cities show high landscape consistency in the inner urban region.     

基于卫星遥感的城市绿地景观格局变化研究进展

城市绿地景观是城市景观自然要素和社会经济可持续发展的生态基础,在城市景观结构、功能及其变化中起重要作用。利用卫星遥感技术开展城市绿地格局研究已成为热点。本文通过梳理相关研究成果,阐述了城市绿地景观遥感分类方法、景观格局指数的选择及城市绿地景观格局动态变化驱动力分析的具体内容,分析出基于遥感技术的城市绿地景观格局研究在数据源和景观格局指数选择时所存在的不足,并且从遥感数据源、分类方法、景观指数筛选和多学科、多角度交叉综合的研究方法等方面对城市绿地景观格局分析提出展望。     

Effects of green space spatial pattern on land surface temperature: Implications for sustainable urban planning and climate change adaptation

The urban heat island (UHI) refers to the phenomenon of higher atmospheric and surface temperatures occurring in urban areas than in the surrounding rural areas. Mitigation of the UHI effects via the configuration of green spaces and sustainable design of urban environments has become an issue of increasing concern under changing climate. In this paper, the effects of the composition and configuration of green space on land surface temperatures (LST) were explored using landscape metrics including percentage of landscape (PLAND), edge density (ED) and patch density (PD). An oasis city of Aksu in Northwestern China was used as a case study. The metrics were calculated by moving window method based on a green space map derived from Landsat Thematic Mapper (TM) imagery, and LST data were retrieved from Landsat TM thermal band. A normalized mutual information measure was employed to investigate the relationship between LST and the spatial pattern of green space. The results showed that while the PLAND is the most important variable that elicits LST dynamics, spatial configuration of green space also has significant effect on LST. Though, the highest normalized mutual information measure was with the PLAND (0.71), it was found that the ED and PD combination is the most deterministic factors of LST than the unique effects of a single variable or the joint effects of PLAND and PD or PLAND and ED. Normalized mutual information measure estimations between LST and PLAND and ED, PLAND and PD and ED and PD were 0.7679, 0.7650 and 0.7832, respectively. A combination of the three factors PLAND, PD and ED explained much of the variance of LST with a normalized mutual information measure of 0.8694. Results from this study can expand our understanding of the relationship between LST and street trees and vegetation, and provide insights for sustainable urban planning and management under changing climate.     

城市建设用地遥感信息提取方法研究

本文利用CBERS-02B影像,通过分析各个地类的光谱特征,发现了长沙市城市建设用地和其他背景地物的区别,并在此基础上选取了土壤调节植被指数(SAVI)、归一化水体指数(NDWI)和比值居民地指数(RRI)作为三个指数波段,重新进行波段组合,从而减少了波段数据的冗余,最后采用最大似然法分类,提取出城市建设用地信息,其正确率达到85.6%。     

基于GIS的大连市沙河口区城市绿地公平性研究——以可持续人居环境为视角

我国快速城市化进程正在遭受着环境污染、交通拥挤、住房紧张等一系列的城市问题,城市生态环境质量持续下降。城市绿地对城市碳氧平衡的调节具有重要作用,大力发展城市绿化将有助于改善城市环境问题。但目前我国城市绿地建设缺乏具体的空间分布规划,只注重绿地覆盖率和人居绿地面积,绿地服务功能的公平性问题没有得到充分重视。本文利用ArcGIS对大连市沙河口区的绿地可达性进行了研究,通过对比绿地可达性与沙河口区人居环境类型发现,高收入社会群体拥有比低收入社会群体更高的绿地可达性。城市规划者应该注意到这些问题,并在今后的建设中关注社会各阶层对绿地的需要,使城市居民在享受公共服务资源上更为公平。     

Geospatial scenario based modelling of urban and agricultural intrusions in Ramsar wetland Deepor Beel in Northeast India using a multi-layer perceptron neural network

In recent decades, the world has experienced unprecedented urban growth which endangers the green environment in and around urban areas. In this work, an artificial neural network (ANN) based model is developed to predict future impacts of urban and agricultural expansion on the uplands of Deepor Beel, a Ramsar wetland in the city area of Guwahati, Assam, India, by 2025 and 2035 respectively. Simulations were carried out for three different transition rates as determined from the changes during 2001–2011, namely simple extrapolation, Markov Chain (MC), and system dynamic (SD) modelling, using projected population growth, which were further investigated based on three different zoning policies. The first zoning policy employed no restriction while the second conversion restriction zoning policy restricted urban-agricultural expansion in the Guwahati Municipal Development Authority (GMDA) proposed green belt, extending to a third zoning policy providing wetland restoration in the proposed green belt. The prediction maps were found to be greatly influenced by the transition rates and the allowed transitions from one class to another within each sub-model. The model outputs were compared with GMDA land demand as proposed for 2025 whereby the land demand as produced by MC was found to best match the projected demand. Regarding the conservation of Deepor Beel, the Landscape Development Intensity (LDI) Index revealed that wetland restoration zoning policies may reduce the impact of urban growth on a local scale, but none of the zoning policies was found to minimize the impact on a broader base. The results from this study may assist the planning and reviewing of land use allocation within Guwahati city to secure ecological sustainability of the wetlands.     

高分辨率遥感影像分割的城市绿地提取研究

城市绿地是生态文明建设的重要组成部分，绿地信息提取是城市绿地规划和建设的基础和前提。遥感影像分割是绿地信息分类提取的关键步骤，选择合适的影像分割方法能有效提高城市绿地提取精度。传统的遥感分割方法分割结果中边缘锯齿现象严重，与绿地实地边界相差较大，不符合绿地信息提取的要求。本文以高分辨率的WorldView影像为数据源，使用深度学习网络DeepLab-v3+对城市绿地进行分割研究，在分割基础上进行城市绿地信息提取。同时，本研究将该网络模型的分割和分类结果与基于Ostu、MeanShift、FNEA分割算法的分类精度进行比较。研究表明：DeepLab-v3+的分割性能最好，其分割边缘光滑，与绿地实地边界吻合度高，有效解决了传统分割算法的边缘锯齿问题；在各种分割分类算法中，DeepLab-v3+的分类精度最高，达到98.01%。     

关键点检测的复杂建筑物模型自动重建

利用机载LiDAR点云数据进行建筑物重建是当今摄影测量与遥感领域的一个热点问题,特别是复杂形状建筑物模型的精确自动构建一直是一个难题。本文提出一种基于关键点检测的复杂建筑物模型自动重建方法,采用RANSAC法与距离法相结合的分割方法自动提取建筑物屋顶各个平面的点云,并利用Alpha Shape算法提取出各个平面的精确轮廓,根据屋顶平面之间的空间拓扑关系分析建筑物的公共交线特征,在此特征约束下对提取的初始关键点进行修正,最终重建出精确的建筑物3维模型。选取不同类型复杂建筑物与包含复杂建筑物的城市区域点云进行实验,结果表明该算法具有较强实用价值。     

城市规划建筑面积指标自动化计算方法探讨

针对建筑面积指标计算方法当前各地复杂且不统一的问题,该文从建筑的层级结构出发,介绍了规划建筑面积指标的自动化计算模型,详细阐述了建筑空间基本面积、公摊面积,以及单体建筑面积指标与建设项目宏观面积指标的计算方法,并在此基础上开发相关软件,实现了城市规划建筑面积指标的自动化计算。     

RNDSI: A ratio normalized difference soil index for remote sensing of urban/suburban environments

Understanding land use land cover change (LULCC) is a prerequisite for urban planning and environment management. For LULCC studies in urban/suburban environments, the abundance and spatial distributions of bare soil are essential due to its biophysically different properties when compared to anthropologic materials. Soil, however, is very difficult to be identified using remote sensing technologies majorly due to its complex physical and chemical compositions, as well as the lack of a direct relationship between soil abundance and its spectral signatures. This paper presents an empirical approach to enhance soil information through developing the ratio normalized difference soil index (RNDSI). The first step involves the generation of random samples of three major land cover types, namely soil, impervious surface areas (ISAs), and vegetation. With spectral signatures of these samples, a normalized difference soil index (NDSI) was proposed using the combination of bands 7 and 2 of Landsat Thematic Mapper Image. Finally, a ratio index was developed to further highlight soil covers through dividing the NDSI by the first component of tasseled cap transformation (TC1). Qualitative (e.g., frequency histogram and box charts) and quantitative analyses (e.g., spectral discrimination index and classification accuracy) were adopted to examine the performance of the developed RNDSI. Analyses of results and comparative analyses with two other relevant indices, biophysical composition index (BCI) and enhanced built-up and bareness Index (EBBI), indicate that RNDSI is promising in separating soil from ISAs and vegetation, and can serve as an input to LULCC models.     

一种用于三维城市建筑物的可视域分析算法

作为3DGIS的一种空间分析方法,可视域分析在城市规划、军事和考古等方面有着广泛的应用,其实现则主要基于点对点的通视分析。本文基于多数城市建筑物外形相对规则的特点,提取建筑物的最小矩形包围盒,基于视点位置得到每个模型的可视面角点和视点构成锥体,通过计算其他锥体底面在某一锥体底面所在平面上的投影区和该锥体底面多边形的差集得到每个模型的可视面,避免通过计算建筑物模型每个点的通视性得到建筑物的可视域,以减少计算量,提高计算效率,最后的实现效果证明了本文算法的可行性和有效性。     

基于指数分析法的西安市土地利用变化及驱动力研究

基于2000和2007年2期TM遥感影像,利用指数分析法,分别提取出归一化差异建筑指数(NDBI)、修正归一化差异水体指数(MNDWI)和归一化差异植被指数(NDVI)3种指数模型,分别代表西安市的3种最主要的土地利用类型--建筑用地、水体和植被.采用神经网络分类器进行监督分类,借助ERDAS Imagine 9.0、ENVI、ArcGIS 9.2和Matlab等软件平台,计算出西安市土地利用类型的动态转移矩阵,构建了土地利用变化动态度指数模型,定量分析西安市土地利用的时空变化.依据研究区土地利用变化的结果分析,变化的驱动力因子主要是人口增长、经济增长和政策变动.     

Semi-automatic mapping of anthropogenic impervious surfaces in an urban/suburban area using Landsat 8 satellite data

Impervious surfaces have a significant impact on urban runoff, groundwater, base flow, water quality, and climate. Increase in Anthropogenic Impervious Surfaces (AIS) for a region is a true representation of urban expansion. Monitoring of AIS in an urban region is helpful for better urban planning and resource management. Cost effective and efficient maps of AIS can be obtained for larger areas using remote sensing techniques. In the present study, extraction of AIS has been carried out using Double window Flexible Pace Search (DFPS) from a new index named as Normalized Difference Impervious Surface Index (NDAISI). NDAISI is developed by enhancing Biophysical Composition Index (BCI) in two stages using a new Modified Normalized Difference Soil Index (MNDSI). MNDSI has been developed from Band 7 and Band 8 (PAN) of Landsat 8 data. In comparison to existing impervious surface extraction methods, the new NDAISI approach is able to improve Spectral Discrimination Index (SDI) for bare soil and AIS significantly. Overall accuracy of mapping of AIS, using NDAISI approach has been found to be increased by nearly 23% when compared with existing impervious surface extraction methods.     

基于高分一号卫星的城市扩张变化监测研究

廊坊是京津冀城市群的地理中心,位于京津两个国际都市之间。本文选取廊坊市中心为研究对象,利用高分一号卫星数据和航空影像,分析廊坊市2010~2016年的城市扩张变化情况,为京津冀协同发展制定政策并为城市制订规划提供依据。首先对遥感影像进行预处理,对高分一号卫星影像,按用地类型分别采用监督分类、面向对象和植被指数法提取城市2016年地表现状信息,并进行精度评价;对2010年的航空影像进行数字化,两类数据结合进行基于分类的变化检测和精度评价,分析城市空间变化特征。结果表明,厂房、建筑和未建成区分别采用监督分类、建筑阈值分类和面向对象法分类效果较好;廊坊市城市扩张的驱动力主要为经济发展、政策因素、历史条件、地形等。     

Spatiotemporal variability of urban growth factors: A global and local perspective on the megacity of Mumbai

The rapid growth of megacities requires special attention among urban planners worldwide, and particularly in Mumbai, India, where growth is very pronounced. To cope with the planning challenges this will bring, developing a retrospective understanding of urban land-use dynamics and the underlying driving-forces behind urban growth is a key prerequisite. This research uses regression-based land-use change models – and in particular non-spatial logistic regression models (LR) and auto-logistic regression models (ALR) – for the Mumbai region over the period 1973–2010, in order to determine the drivers behind spatiotemporal urban expansion. Both global models are complemented by a local, spatial model, the so-called geographically weighted logistic regression (GWLR) model, one that explicitly permits variations in driving-forces across space. The study comes to two main conclusions. First, both global models suggest similar driving-forces behind urban growth over time, revealing that LRs and ALRs result in estimated coefficients with comparable magnitudes. Second, all the local coefficients show distinctive temporal and spatial variations. It is therefore concluded that GWLR aids our understanding of urban growth processes, and so can assist context-related planning and policymaking activities when seeking to secure a sustainable urban future.     

基于街景图像的福州城区主要道路绿视率研究

道路的视觉感知是衡量城市绿化景观功能的重要途径,绿视率被认为是评价城市绿色空间的重要指标.本文根据植物对太阳光吸收和反射波谱特性,对应街景图像中红、绿、蓝三分量的特点,提取植被信息,从而计算绿视率.以福州市城区(鼓楼区、仓山区、台江区、晋安区)主要道路作为研究对象,计算每个观测点的绿视率和道路的平均绿视率,分析道路绿视...