Enhancing Urban Façades via LiDAR‐Based Sculpting

Buildings with symmetrical façades are ubiquitous in urban landscapes and detailed models of these buildings enhance the visual realism of digital urban scenes. However, a vast majority of the existing urban building models in web‐based 3D maps such as Google earth are either less detailed or heavily rely on texturing to render the details. We present a new framework for enhancing the details of such coarse models, using the geometry and symmetry inferred from the light detection and ranging (LiDAR) scans and 2D templates. The user‐defined 2D templates, referred to as coded planar meshes (CPMs), encodes the geometry of the smallest repeating 3D structures of the façades via face codes. Our encoding scheme, take into account the directions, type as well as the offset distance of the sculpting to be applied at the respective locations on the coarse model. In our approach, LiDAR scan is registered with the coarse models taken from Google earth 3D or Bing maps 3D and decomposed into dominant planar segments (each representing the frontal or lateral walls of the building). The façade segments are then split into horizontal and vertical tiles using a weighted point count function defined over the window or door boundaries. This is followed by an automatic identification of CPM locations with the help of a template fitting algorithm that respects the alignment regularity as well as the inter‐element spacing on the façade layout. Finally, 3D boolean sculpting operations are applied over the boxes induced by CPMs and the coarse model, and a detailed 3D model is generated. The proposed framework is capable of modelling details even with occluded scans and enhances not only the frontal façades (facing to the streets) but also the lateral façades of the buildings. We demonstrate the potentials of the proposed framework by providing several examples of enhanced Google earth models and highlight the advantages of our method when designing photo‐realistic urban façades.     

Geometry and Bonding Rules Position Analysis in the Formation of Traditional Iranian Architectural Brick Facades

Over time, architectural ornaments have had a variety of forms that are created from a combination of different types of materials and factors. Brick decorations are one such example, a type of ornament that is often formed on the exterior façade of buildings. Investigating covert rules and brick bonds geometry can reveal a part of the ancient architectural secrets and ways used to reduce the ravages upon new brick façades. Shaped bricks in traditional Iranian architecture directly affect the placement, size and brick arrangement rules. This article is the first attempt to study the effects of geometry and the principal rules of arrangement that help to shape the formation of brick façades specifically, as well as analysing the samples of brick façades taken from monuments, field recordings and discussion with the workmen themselves. The analysis has revealed that permanent rules govern the bonding of brick façades, along with the size and dimensions of the brick effects, which shape the final look of the decoration.     

Impacts of landscape structure on surface urban heat islands: A case study of Shanghai, China

Urbanization is taking place at an unprecedented rate around the world, particularly in China in the past few decades. One of the key impacts of rapid urbanization on the environment is the effect of urban heat island (UHI). Understanding the effects of landscape pattern on UHI is crucial for improving the ecology and sustainability of cities. This study investigated how landscape composition and configuration would affect UHI in the Shanghai metropolitan region of China, based on the analysis of land surface temperature (LST) in relation to normalized difference vegetation index (NDVI), vegetation fraction (Fv), and percent impervious surface area (ISA). Two Landsat ETM+ images acquired on March 13 and July 2, 2001 were used to estimate LST, Fv, and percent ISA. Landscape metrics were calculated from a high spatial resolution (2.5 × 2.5 m) land-cover/land-use map. Our results have showed that, although there are significant variations in LST at a given fraction of vegetation or impervious surface on a per-pixel basis, NDVI, Fv, and percent ISA are all good predictors of LST on the regional scale. There is a strong negative linear relationship between LST and positive NDVI over the region. Similar but stronger negative linear relationship exists between LST and Fv. Urban vegetation could mitigate the surface UHI better in summer than in early spring. A strong positive relationship exists between mean LST and percent ISA. The residential land is the biggest contributor to UHI, followed by industrial land. Although industrial land has the highest LST, it has limited contribution to the overall surface UHI due to its small spatial extend in Shanghai. Among the residential land-uses, areas with low- to-middle-rise buildings and low vegetation cover have much high temperatures than areas with high-rise buildings or areas with high vegetation cover. A strong correlation between the mean LST and landscape metrics indicates that urban landscape configuration also influences the surface UHI. These findings are helpful for understanding urban ecology as well as land use planning to minimize the potential environmental impacts of urbanization.     

3D city models for urban farming site identification in buildings

Studies have suggested that there is farming potential in urban residential buildings. However, these studies are limited in scope, require field visits and time-consuming measurements. Furthermore, they have not suggested ways to identify suitable sites on a larger scale let alone means of surveying numerous micro-locations across the same building. Using a case study area focused on high-rise buildings in Singapore, this paper examines a novel application of three-dimensional (3D) city models to identify suitable farming micro-locations (level and orientation) in residential buildings. We specifically investigate whether the vertical spaces of these buildings comprising outdoor corridors, façades and windows receive sufficient photosynthetically active radiation (PAR) for growing food crops and do so at a high resolution. We also analyze the spatio-temporal characteristics of PAR, and the impact of shadows and different weather conditions on PAR in the building. Environmental simulations on the 3D model of the study area indicated that the cumulative daily PAR or Daily Light Integral (DLI) at a location in the building was dependent on its orientation and shape, sun's diurnal and annual motion, weather conditions, and shadowing effects of the building's own façades and surrounding buildings. The DLI in the study area generally increased with building's levels and, depending on the particular micro-location, was found suitable for growing moderately light-demanding crops such as lettuce and sweet pepper. These variations in DLI at different locations of the same building affirmed the need for such simulations. The simulations were validated with field measurements of PAR, and correlation coefficients between them exceeded 0.5 in most cases thus, making a case that 3D city models offer a promising practical solution to identifying suitable farming locations in residential buildings, and have the potential for urban-scale applications.     

Productive high-complexity 3D city modeling with point clouds collected from terrestrial LiDAR

To satisfy the needs of photo-realistic and ground-based representation of three-dimensional (3D) city models for a variety of applications, significant efforts have been made to automatically reconstruct detailed 3D building façades from terrestrial LiDAR data. Nonetheless, in real-world applications for high-quality 3D city modeling, three major problems are typically encountered: (1) very low productivity due to fully manual operation, (2) low geometric accuracy of 3D modeling resulting from the process of reducing original LiDAR data, and (3) system failure when importing huge LiDAR data to 3D drawing software. To overcome these limitations, the present study proposes a semi-automatic method entailing a plane component detection based on RANSAC segmentation, boundary tracing of the planar components, and manual drawing of details using the remaining, significantly reduced points. The proposed method was applied to point clouds of various buildings in a high-density area in Korea. In comparison with manual operation, the proposed method was proved to improve modeling productivity in the time-consumption aspect and to facilitate operators’ accurate object drawing. However, for additional automation and completeness of 3D modeling, further study is necessary. The proposed method requires a segmentation algorithm to heuristically determine parameters for the most desirable results as well as to detect curvilinear surfaces in modeling complex and curved façades.     

Image Registration in a Coarse Three-Dimensional Virtual Environment

In recent years, the availability of off‐the‐shelf geometric data for an urban environment has increased. During rendering, ground level images are mapped onto the façades of the buildings to improve the visual quality of the scene. This paper focuses on a technique that enables ground level images to be automatically integrated into an existing coarse three‐dimensional environment. The approach utilises the planar nature of architectural scenes to enable the automatic extraction of a building façade from an image and its registration into the virtual environment.     

Building renovation adopts mass customization

This work is motivated by an industrial need of manufacturing façades insulating envelopes in order to reduce energy consumption in residential buildings. An insulating envelope is a configuration of a set of rectangular panels that respects a set of limitations. Due to the number of façades to be renovated and the number of possible configurations for a single façade, the envelope configuration is both a mass customization problem as well as a combinatorial one. The paper then introduces a decision support system based on the framework of constraint satisfaction, as it fits neatly the constrained nature of the problem. Two configuration tasks have been identified as prerequisite to envelopes configurations: (1) the configuration of a questionnaire for information inputs and (2) the configuration of a constraint satisfaction problem for each one of the façades to be renovated. The system architecture promotes maintenance, modularity and efficiency as different configuration tasks are divided into web-services. Conception and implementation of the massive building thermal renovation are then supported.     

Establishing the relationship between urban land-cover configuration and night time land-surface temperature using spatial regression

Studies suggest that urban form can influence microclimate regulation. Remote sensing studies have contributed to these findings through analysis of high-resolution land cover maps, landscape ecology metrics, and thermal imagery. Collectively, these have been referred to as land cover configuration studies. There are three objectives to this study. The first is to assess the relationship between nighttime land surface temperatures (LST) and land cover configuration and composition. The second objective is to outline a comprehensive methodology that includes ordinary least squares (OLS), spatial regression, variable selection, and multicollinearity analysis. Our last objective is to test three hypotheses about the relationship between LST and land cover, which can briefly be described as: 1) the importance of land-use regimes in modeling LST from land cover composition and configuration variables; 2) the strength of the correlation between LST and roads, buildings, and vegetation; and 3) the improved quality of models using landscape metrics in modeling the relationship between LST and land cover. Based on 16 different models (8 OLS, 8 spatial regression) we could confirm the above hypotheses, but we found that the configuration of buildings, roads, and vegetation have a complex relationship with LST. Our interpretation of this complexity, combined with the strength of composition variables, is that parsimonious models, for now, are more useful to urban planners because they are more generalizable. Finally, spatial regression models of land cover configuration and LST demonstrated an improvement over non-spatial linear models (OLS). Spatial regression models reduced heteroskedasticity and clusters of residuals, and tempered coefficients, suggesting that the OLS models could be biased. OLS models were still found to be a valuable tool for exploratory analysis.     

Quantifying how landscape composition and configuration affect urban land surface temperatures using machine learning and neutral landscapes

The urban heat island effect is an important 21st century issue because it intersects with the complex challenges of urban population growth, global climate change, public health and increasing energy demand for cooling. While the effects of urban landscape composition on land surface temperature (LST) are well-studied, less attention has been paid to the spatial arrangement of land cover types especially in smaller, often more diverse cities. Landscape configuration is important because it offers the potential to provide refuge from excessive heat for both people and buildings.We present a novel approach to quantifying how both composition and configuration affect LST derived from Landsat imagery in Southampton, UK. First, we trained a machine-learning (generalized boosted regression) model to predict LST from landscape covariates that included the characteristics of the immediate pixel and its surroundings. The model achieved a correlation between predicted and measured LST of 0.956 on independent test data (n = 102,935) and included predictors for both the immediate and adjacent land use. In contrast to other studies, we found adjacency effects to be stronger than immediate effects at 30 m resolution. Next, we used a landscape generation tool (Landscape Generator) to alter landscape configuration by varying natural and built patch sizes and arrangements while holding composition constant. The generated neutral landscapes were then fed into the machine learning model to predict patterns of LST.When we manipulated landscape configuration, the average city temperature remained the same but the local minima varied by 0.9 °C and the maxima by 4.2 °C. The effects on LST and heat island metrics correlated with landscape fragmentation indices. Moreover, the surface temperature of buildings could be reduced by up to 2.1 °C through landscape manipulation.We found that the optimum mix of land use types is neither at the land-sharing nor land-sparing extremes, but a balance between the two. In our city, maximum cooling was achieved when ~60% of land was left natural and distributed in 7–8 patches km⁻² although this could be location dependent and further work is needed. Opportunities for urban cooling should be required in the planning process and must consider both composition and configuration at the landscape scale if cities are to build capacity for a growing population and climate change.     

Interaction with Media Façades

Media façades are a prominent example of the digital augmentation of urban spaces. They denote the concept of turning the surface of a building into a large-scale urban screen. Because of their enormous size, they require interaction at a distance and they have a high level of visibility. Additionally, they are situated in a highly dynamic urban environment with rapidly changing conditions, which results in settings which are neither comparable, nor reproducible. Altogether, this makes the development of interactive media façade installations a challenging task.     

Automatic façade recovery from single nighttime image

Nighttime images are difficult to process due to insufficient brightness,lots of noise,and lack of details.Therefore,they are always removed from time-lapsed image analysis.It is interesting that nighttime images have a unique and wonderful building features that have robust and salient lighting cues from human activities.Lighting variation depicts both the statistical and individual habitation,and it has an inherent man-made repetitive structure from architectural theory.Inspired by this,we propose an automatic nighttime fa?ade recovery method that exploits the lattice structures of window lighting.First,a simple but efficient classification method is employed to determine the salient bright regions,which may be lit windows.Then we groupwindows into multiple lattice proposals with respect to fa?ades by patch matching,followed by greedily removing overlapping lattices.Using the horizon constraint,we solve the ambiguous proposals problem and obtain the correct orientation.Finally,we complete the generated fa?ades by filling in the missing windows.This method is well suited for use in urban environments,and the results can be used as a good single-view compensation method for daytime images.The method also acts as a semantic input to other learning-based 3D image reconstruction techniques.The experiment demonstrates that our method works well in nighttime image datasets,and we obtain a high lattice detection rate of 82.1%of 82 challenging images with a low mean orientation error of 12.1±4.5 degrees.     

杭州市城市空间扩展及其热环境变化

通过Landsat卫星影像分别获取了杭州市1989、2000和2010年的城市空间扩张、地表温度及作为主要地表参数的建筑用地和植被的信息,用以研究杭州市城市扩展及其城市热环境变化。结果表明:在21 a间,杭州市建成区范围有了大幅扩展,且城市热岛区域的空间变化与建成区的空间扩展变化基本一致。研究还发现杭州市区的特高温区面积比例在逐渐减小,城市热岛比例指数(URI)从0.78降至0.71,表明城市热岛效应有一定缓解。建筑用地比例的减小与建筑用地密度的下降是城市热岛得以缓解的主要原因。定量分析表明建筑用地的升温效应要强于植被的降温效应。总的看来,杭州市的城市热岛效应现象在整个研究时段内虽有一定的改善,但仍一直处于较强烈的状态。     

一种基于指数的新型遥感建筑用地指数及其生态环境意义

城市建筑用地是一种复杂的土地利用类型,在电磁波反射光谱上表现出明显的异质性。因此,很难用简单的方法将其从遥感影像中准确地提取出来。在详细研究了城市建筑用地的光谱特征以后,创建了一种不直接采用影像的原始波段,而是采用由它们衍生的3个指数波段来构成新型建筑用地指数(IBI)。通过对ASTER和Landsat ETM+两种多光谱影像进行的实验表明,新指数除了能够有效地增强影像中的建筑用地信息外,还能和植被指数、水体指数一样,用于进行数值运算,从而实现了建筑用地对城市生态环境影响的定量研究。对厦门、福州两城市的实例分析表明,新的建筑指数与地表温度呈正相关关系,而与植被指数、水体指数呈负相关关系。研究进一步发现,建筑指数与地表温度的关系不是简单的线性关系,而是一种指数函数关系,说明高建筑用地比例地区的升温效应要明显高于低建筑用地比例地区,因此,对城市热岛的形成起着更大的作用。     

Procedural Modeling of a Building from a Single Image

Creating a virtual city is demanded for computer games, movies, and urban planning, but it takes a lot of time to create numerous 3D building models. Procedural modeling has become popular in recent years to overcome this issue, but creating a grammar to get a desired output is difficult and time consuming even for expert users. In this paper, we present an interactive tool that allows users to automatically generate such a grammar from a single image of a building. The user selects a photograph and highlights the silhouette of the target building as input to our method. Our pipeline automatically generates the building components, from large‐scale building mass to fine‐scale windows and doors geometry. Each stage of our pipeline combines convolutional neural networks (CNNs) and optimization to select and parameterize procedural grammars that reproduce the building elements of the picture. In the first stage, our method jointly estimates camera parameters and building mass shape. Once known, the building mass enables the rectification of the façades, which are given as input to the second stage that recovers the façade layout. This layout allows us to extract individual windows and doors that are subsequently fed to the last stage of the pipeline that selects procedural grammars for windows and doors. Finally, the grammars are combined to generate a complete procedural building as output. We devise a common methodology to make each stage of this pipeline tractable. This methodology consists in simplifying the input image to match the visual appearance of synthetic training data, and in using optimization to refine the parameters estimated by CNNs. We used our method to generate a variety of procedural models of buildings from existing photographs.     

Complete residential urban area reconstruction from dense aerial LiDAR point clouds

We present an automatic system to reconstruct 3D urban models for residential areas from aerial LiDAR scans. The key difference between downtown area modeling and residential area modeling is that the latter usually contains rich vegetation. Thus, we propose a robust classification algorithm that effectively classifies LiDAR points into trees, buildings, and ground. The classification algorithm adopts an energy minimization scheme based on the 2.5D characteristic of building structures: buildings are composed of opaque skyward roof surfaces and vertical walls, making the interior of building structures invisible to laser scans; in contrast, trees do not possess such characteristic and thus point samples can exist underneath tree crowns. Once the point cloud is successfully classified, our system reconstructs buildings and trees respectively, resulting in a hybrid model representing the 3D urban reality of residential areas.     

The relationship between land surface temperature and NDVI with remote sensing: application to Shanghai Landsat 7 ETM+ data

The relationship between land surface temperature (LST) and Normalized Difference Vegetation Index (NDVI) associated with urban land‐use type and land‐use pattern is discussed in the City of Shanghai, China using data collected by the Enhanced Thematic Mapper Plus (ETM+) and aerial photographic remote sensing system. There is an apparent correlation between LST and NDVI from the visual interpretation of LST and NDVI contrasts. Mean LST and NDVI values associated with different land‐use types are significantly different. Multiple comparisons of mean LST and NDVI values associated with pairings of each land‐use type are also shown to be significantly different. The result of a regressive analysis shows an inverse correlation relationship between LST and NDVI within all land‐use polygons, the same to each land‐use type, but correlation coefficients associated with land‐use types are different. An analysis on the relationship between LST, NDVI and Shannon Diversity Index (SHDI) shows a positive correlation between LST and SHDI and a negative correlation between NDVI and SHDI. According to the above results, LST, SHDI and NDVI can be considered to be three basic indices to study the urban ecological environment and to contribute to further validation of the applicability of relatively low cost, moderate spatial resolution satellite imagery in evaluating environmental impacts of urban land function zoning, then to examine the impact of urban land‐use on the urban environment in Shanghai City. This provides an effective tool in evaluating the environmental influences of zoning in urban ecosystems with remote sensing and geographical information systems.     

Numerical modelling for analysis of the effect of different urban green spaces on urban heat load patterns in the present and in the future

This paper focuses on urban green spaces in terms of climate and human thermal comfort containing their effect on heat load mitigation. It incorporates a modelling study in which the role of green spaces was investigated in terms of heat stress modification by applying MUKLIMO_3 model. During the experiment, the thermal effects of dense trees, scattered trees, grasslands and mixed green infrastructure has been investigated in the case of Szeged (Hungary) and assessed using different climate indices. The investigations encompassed 3 climatological time periods (1981–2010, 2021–2050 and 2071–2100) and two emission scenarios for future climate (RCP4.5 and RCP8.5). It was found that urban green spaces (e.g. parks) generally cool the environment, although, the cooling potential of the different green types differs. The highest reduction of heat load was found in the case of large urban parks comprising of dense trees near the downtown. The spatial extension of detected cooling was found small. However, it would increase during the future, especially in the case of grasslands. For urban planners, it is highly recommended to introduce new green sites within a city and to increase the spatial extension of the existing ones to mitigate and adapt to the impacts of climate change in the urban environment.     

Land-use/land-cover change and its influence on surface temperature: a case study in Beijing City

Rapid global economic development has resulted in a corresponding intensification of urbanization, which has in turn impacted the ecology of vast regions of the world. A series of problems have thus been introduced, such as changes in land-use/land-cover (LULC) and changes in local climate. The process of urbanization predominantly represents changes in land-use, and is deemed by researchers to be the chief cause of climate change and ecological change. One of the principal purposes of the research in this field is to find ways to mitigate the influence of land-use change on local or global environments. In the study presented in this article, satellite images were utilized to extract information regarding land-use in Beijing City, and to develop maps of land surface temperature (LST) during two different periods of time: 2 August 1999 and 8 August 2010. A supervised classification scheme, a support vector machine, was used to derive the land-use change map for the above periods. Maps of surface temperature are derived from the thermal band of Landsat images using the mono-window algorithm. Results from post-classification comparison indicated that an increase in impervious surface areas was found to be dramatic, while the area of farmland decreased rapidly. The changes in LULC were found to have led to a variation in surface temperature, as well as a spatial distribution pattern of the urban heat island phenomenon. This research revealed that the hotspots were mainly located in areas dominated by three kinds of material: bare soil, rooftops, and marble surfaces. Results from the local Moran's I index indicated that the use of lower surface temperature materials will help to mitigate the influence of the urban heat island phenomenon. The results of this research study provide a reference for government departments involved in the process of designing residential regions. Such a reference should enable the development of areas sympathetic to environmental changes and hence mitigate the effects of the growing intensity of urbanization.