{"id":21936,"date":"2015-11-05T00:00:00","date_gmt":"2015-11-05T00:00:00","guid":{"rendered":"https:\/\/www.dmh.org.il\/articles\/analysis-of-urban-shadow-patterns\/"},"modified":"2021-12-20T12:45:56","modified_gmt":"2021-12-20T12:45:56","slug":"analysis-of-urban-shadow-patterns","status":"publish","type":"mt_article","link":"https:\/\/www.dmh.org.il\/en\/articles\/analysis-of-urban-shadow-patterns\/","title":{"rendered":"Analysis of Urban Shadow Patterns"},"content":{"rendered":"\n

The article was published first at the Urban shading in Israel Exhibition book (For more details book click here<\/a>).<\/p>\n\n\n\n

Currently over 50% of the world’s population\u00a0are city dwellers. Projections for the foreseeablefuture predict that, by the year 2030, two thirds of\u00a0the world’s population will live in cities. In Israel 85% of the population\u00a0is located in urban settlements. Urbanization will predominate overhumanity’s settlement patterns with all its implications. More than\u00a0ever before, we are now aware how city form impacts the quality of\u00a0life of its inhabitants and how it affects the environment.<\/p>\n\n\n\n

Natural\u00a0land-cover is being replaced by distinctly urban surfaces,\u00a0which affect the energy balance of the city,(1) creating a local\u00a0condition known as urban climate.(2) The urban climate has a significant impact on the\u00a0lives of the city’s inhabitants, including their physical and\u00a0mental well-being indoors and outdoors\u00a0(3). Air temperature,\u00a0for example, has a decisive effect on the thermal comfort\u00a0of human beings, particularly in arid lands where summer\u00a0shading and passive winter heating is beneficial. Thermal\u00a0comfort furthermore, affects the energy people use for cooling and heating, their use of public transportation\u00a0and their outdoor activities. A thermally uncomfortable\u00a0outdoor space is destined to turn into a barely used\u00a0dysfunctional space, causing people to spend more\u00a0time indoors, while increasing the unsustainable use of\u00a0energy to acclimatize indoor spaces. Making cities a more\u00a0pleasant environment to live in, in terms of their local climatic conditions, will therefore significantly enhance the quality of life and health of their inhabitants. Existing studies consider solar radiation as one of the key factors in determining a city’s urban climate (4). The morphology of the\u00a0urban environment, which\u00a0consists of the geometry\u00a0of urban features, such as\u00a0buildings and trees and\u00a0their spatial distribution,\u00a0has a major influence on\u00a0solar access. Availability\u00a0of natural daylight or the\u00a0obstruction of light and theoptimal exposure to solar\u00a0radiation are all affected by\u00a0the form and organization of urban features. The importance of\u00a0selective solar exposure in streets and buildings is well-documented (5).\u00a0It determines whether an open space or a street is shaded in summer or exposed to the sun during winter. Understanding shadow patterns in the urban environment and the effect of shadow casting elements is essential for achieving climatic conscious planning and design, by the optimal spatial arrangement of buildings, vegetation and open spaces.<\/p>\n\n\n\n

\"Fig
Fig 1: Segmented shad <\/figcaption><\/figure>\n\n\n\n

Analysis of urban shadow patterns can be based on simulations\u00a0of 3D urban forms or by modelling shadows cast by different\u00a0urban features and geometries. A pre-requisite, to simulate the 3D\u00a0morphology of urban forms, is the presence of 3D data that includes\u00a0the height of urban features. One option for constructing these\u00a03D databases (especially in cases where no accurate survey datais available) is to use remotely-sensed data, such as satellite and\u00a0aerial images. Urban features and shadows, cast by these features,\u00a0can be extracted from the images using automated objectrecognition techniques. The high temporal and spatial\u00a0resolution of space and airborne data offers an up-to-date\u00a0representation of the urban environment. Yet, a major\u00a0concern in the automated recognition of urban objects\u00a0from 2D images is that, in most cases, output results\u00a0with 2D footprints of urban features without the essential\u00a0height information. One solution is to use cast shadows,\u00a0and particularly the length of the shadows in the image,\u00a0to extract 3D information. The height of the objects can be calculated based on existing algorithms, the sun’s position\u00a0(i.e. the accurate date and time of the image acquisition\u00a0and the geographical latitude), and topographical slope.\u00a0A variety of methods has been developed to recognize\u00a0and segment shadowed areas from an image (6). Fig 1\u00a0illustrates the output of a recognition system developed by Peeters and Etzion (2012) in which recognition is based on readily available, open-source imagery, such as Google EarthTM. Output is used for extracting the length of cast shadows for modelling urban 3D morphology (Fig 2).<\/p>\n\n\n\n

\"Fig
Fig 2: Extraction of shadow length (blue lines) for calculating building\u00a0heights and reconstructing urban 3D morphology <\/figcaption><\/figure>\n\n\n\n

Reconstructed urban 3D morphology and 3D models of proposed\u00a0urban plans, can be used to model shadow patterns at different\u00a0geographical locations and at different times of the year. Evaluation\u00a0of the proposed urban plans is as important as the orientation of\u00a0wall facets and their glazed openings, in relation to the sun. This\u00a0is a major concern in designing indoor and outdoor spaces which\u00a0will be thermally comfortable. Exposure of the building walls to the\u00a0sun, has to be taken into consideration at the planning stage, when\u00a0designing window elements and shading devices. Fig 3 presents\u00a0the outputs of an automated system for computing shadows cast by\u00a0buildings at the urban scale and at different geographical locations.\u00a0The system is based on the building’s location relative to the position\u00a0of the sun at a given point in time (7).<\/p>\n\n\n\n

Such systems for analyzing and modelling urban shadow patterns\u00a0can support: detecting areas exposed to direct solar radiation for\u00a0climate-conscious open space planning and integration of climatic\u00a0considerations in city zoning, calculating shadow maps and analyzing\u00a0solar exposure of urban vegetation to optimize landscape planning in\u00a0open spaces and detecting solar access for building integrated solar\u00a0photovoltaics and thermal solar collectors on roofs. Understanding\u00a0urban shadow patterns cast by urban features, is therefore essential\u00a0for developing sustainable planning and policy-driven solutions, that\u00a0will significantly enhance the well-being and quality of human lifein urban environments.<\/p>\n\n\n\n

\"Fig
Fig 3: Shadow footprint polygons generated by the system according to different date\u00a0and time configurations (8) <\/figcaption><\/figure>\n\n\n\n

1.
Grimmond, C. S. B. 1 and C. Souch (1994), Surface description for urban climate studies: A GIS based methodology, Geocarto International 9: 47-59<\/p>\n\n\n\n

2.<\/p>\n\n\n\n

Oke, T. R. (1987), Boundary Layer Climates, London, Routledge, Taylor and Francis Group<\/p>\n\n\n\n

3.
Nikolopoulou, M., N. Baker and K. Steemers (2001), Thermal comfort in outdoor urban spaces: understanding the human parameter, Solar Energy 70(3): 227-235<\/p>\n\n\n\n

4.<\/p>\n\n\n\n

Szokolay, S. V. (1996), Solar Geometry, PLEA Design Tools and Techniques, Queensland, PLEA: Passive and Low Energy Architecture International<\/p>\n\n\n\n

5.
Knowles, R. L. 5 (1981), Sun Rhythm Form, Cambridge, MA, The MIT Press<\/p>\n\n\n\n

6.
Irvin, R. B. and D.\u00a0M. McKeown (1989),\u00a0Methods for exploiting\u00a0the relationship\u00a0between buildings\u00a0and their shadows in\u00a0aerial imagery, IEEE\u00a0Transactions on Systems,\u00a0Man and Cybernetics\u00a019 (6): 1564-1575Al-Najdawi, N. Bez,\u00a0H.E. Singhai, J. and\u00a0Edirisinghe, E.A. (2012),\u00a0A survey of cast shadow\u00a0detection algorithms,\u00a0Pattern Recognition\u00a0Letters 33:6:752-764 Adeline, K.R.M. Chen,\u00a0M. Briottet, X. Pang,\u00a0S.K. and Paparoditis,\u00a0N. (2013), Shadow\u00a0detection in very high\u00a0spatial resolution aerial\u00a0images: A comparative\u00a0study, ISPRS Journal\u00a0of Photogrammetry\u00a0and Remote Sensing\u00a080:0:21-38<\/p>\n\n\n\n

7.
iImage: \u00a92008 DigitalGlobe \u00a92008 Europa Technologies \u00a92008 Google   <\/p>\n\n\n\n

8.
Weisthal, M. (2014) Assessment of potential energy savings in Israel through climate-aware residential building design, Master Thesis, Ben-Gurion University of the Negev, Be’er- Sheva<\/p>\n","protected":false},"excerpt":{"rendered":"

The article was published first at the Urban shading in Israel Exhibition book (For more details book click here). Currently over 50% of the world’s population\u00a0are city dwellers. Projections for the foreseeablefuture predict that, by the year 2030, two thirds of\u00a0the world’s population will live in cities. In Israel 85% of the population\u00a0is located in […]<\/p>\n","protected":false},"featured_media":0,"template":"","meta":{"_acf_changed":false,"footnotes":""},"article_cat":[52],"class_list":["post-21936","mt_article","type-mt_article","status-publish","hentry","article_cat-features"],"acf":[],"ACF":{"header_image":{"ID":42715,"id":42715,"title":"Fig 1: Segmented shad","filename":"Fig1_673_WEB-1024x841-1.jpg","filesize":229089,"url":"https:\/\/www.dmh.org.il\/wp-content\/uploads\/2015\/11\/Fig1_673_WEB-1024x841-1.jpg","link":"https:\/\/www.dmh.org.il\/en\/articles\/analysis-of-urban-shadow-patterns\/fig1_673_web-1024x841\/","alt":"Fig 1: Segmented shad","author":"7","description":"","caption":"","name":"fig1_673_web-1024x841","status":"inherit","uploaded_to":21936,"date":"2021-12-20 12:13:40","modified":"2021-12-20 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shadows, represented in red from satellite imagery","bg_img_credit":"","show_banner":"site","featured_image":false,"subtitle":"November 05, 2015","article_author":"Aviva Peters","related_posts":"by_cat"},"yoast_head":"\nAnalysis of Urban Shadow Patterns • Design Museum Holon<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/www.dmh.org.il\/en\/articles\/analysis-of-urban-shadow-patterns\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Analysis of Urban Shadow Patterns • Design Museum Holon\" \/>\n<meta property=\"og:description\" content=\"The article was published first at the Urban shading in Israel Exhibition book (For more details book click here). Currently over 50% of the world’s population\u00a0are city dwellers. Projections for the foreseeablefuture predict that, by the year 2030, two thirds of\u00a0the world’s population will live in cities. 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