{"id":2606062,"date":"2024-12-03T03:03:18","date_gmt":"2024-12-03T11:03:18","guid":{"rendered":"https:\/\/www.esri.com\/arcgis-blog\/?post_type=blog&p=2606062"},"modified":"2024-12-04T08:05:01","modified_gmt":"2024-12-04T16:05:01","slug":"quantify-the-impact-of-urban-planning-scenarios-using-metrics-in-arcgis-urban","status":"publish","type":"blog","link":"https:\/\/www.esri.com\/arcgis-blog\/products\/urban\/local-government\/quantify-the-impact-of-urban-planning-scenarios-using-metrics-in-arcgis-urban","title":{"rendered":"Quantify the impact of urban planning scenarios using metrics in ArcGIS Urban"},"author":9662,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"open","ping_status":"closed","template":"","format":"standard","meta":{"_acf_changed":false,"_searchwp_excluded":""},"categories":[615021,22841,430212],"tags":[25781,406712,767012,549072,26171],"industry":[],"product":[409602],"class_list":["post-2606062","blog","type-blog","status-publish","format-standard","hentry","category-aec","category-local-government","category-sustainable-development","tag-3d","tag-arcgis-urban","tag-climate-resilience","tag-esrirdzurich","tag-urban-planning","product-urban"],"acf":{"authors":[{"ID":9662,"user_firstname":"Dominik","user_lastname":"Allemann","nickname":"Dominik Allemann","user_nicename":"dallemann","display_name":"Dominik Allemann","user_email":"dallemann@esri.com","user_url":"https:\/\/www.esri.com\/arcgis-blog\/author\/dallemann\/","user_registered":"2019-06-21 06:50:19","user_description":"Dominik studied Geomatics Engineering at ETH Z\u00fcrich. In 2019, he joined the ArcGIS Urban team at the Esri R&D Center in Zurich as a Product Engineer.\r\nHe is curious about how new solutions and digitalization can facilitate future urban development.","user_avatar":""},{"ID":8122,"user_firstname":"Katelyn","user_lastname":"Thompson","nickname":"Katelyn Thompson","user_nicename":"kthompson","display_name":"Katie Thompson","user_email":"KThompson@esri.com","user_url":"","user_registered":"2018-06-26 17:47:19","user_description":"Katie Thompson is a Product Marketing Manager at Esri who got her start with GIS during her undergraduate studies and holds a master's degree in urban and regional planning. Today, she focuses on creating content and messaging to help planners make the most of their GIS, especially through 3D tools like ArcGIS Urban and ArcGIS CityEngine.","user_avatar":""}],"short_description":"Quantify the impact of urban planning scenarios using metrics in ArcGIS Urban. Unlock additional calculation methods with the new metrics. ","flexible_content":[{"acf_fc_layout":"content","content":"

By carefully designing the space between the buildings, urban planners can significantly contribute to livable and resilient future <\/span>developments<\/span>. Specifically, green space and other pervious surfaces deserve special attention. Easy access to green space for relaxation, exercise, and social interaction is important for the well-being of individuals. At the same time, green space and other pervious surfaces can absorb rainwater, reduce runoff and the strain on the drainage system, and minimize the risk of flooding during heavy rain events.\u00a0<\/span>\u00a0<\/span><\/p>\n

 <\/p>\n"},{"acf_fc_layout":"sidebar","content":"

The new metrics can, of course, also be used to quantify other aspects of your urban planning scenario. You can easily create complex calculations by using <\/span>floor area, <\/span>space<\/span>–<\/span>use type dependent parameters<\/span>, global variables, parcel and building measurements, and other inputs.<\/span><\/span>\u00a0<\/span><\/p>\n","image_reference":false,"layout":"standard","image_reference_figure":"","snippet":"","spotlight_name":"","section_title":"","position":"Right","spotlight_image":false},{"acf_fc_layout":"content","content":"

In this blog post, you\u2019ll learn how ArcGIS Urban\u2019s new metrics allow you to quantify your proposed developments in terms of green space and pervious surfaces and how they contribute to increased flooding resilience. The Pfingstweid Park in Zurich, Switzerland, will be our example to show you the power of the new metrics. You probably know the Pfingstweid Park from one of our <\/span>earlier blog posts<\/span><\/a>. <\/span>\u00a0<\/span><\/p>\n"},{"acf_fc_layout":"image","image":{"ID":2607732,"id":2607732,"title":"Pfingstweid_Development","filename":"Pfingstweid_Development.png","filesize":1256254,"url":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/12\/Pfingstweid_Development.png","link":"https:\/\/www.esri.com\/arcgis-blog\/products\/urban\/local-government\/quantify-the-impact-of-urban-planning-scenarios-using-metrics-in-arcgis-urban\/pfingstweid_development","alt":"An aerial view of the 3D schematic urban model of Pfingstweid Park in Zurich, Switzerland","author":"9662","description":"","caption":"","name":"pfingstweid_development","status":"inherit","uploaded_to":2606062,"date":"2024-12-03 09:17:06","modified":"2024-12-03 09:17:58","menu_order":0,"mime_type":"image\/png","type":"image","subtype":"png","icon":"https:\/\/www.esri.com\/arcgis-blog\/wp-includes\/images\/media\/default.png","width":1492,"height":878,"sizes":{"thumbnail":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/12\/Pfingstweid_Development-213x200.png","thumbnail-width":213,"thumbnail-height":200,"medium":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/12\/Pfingstweid_Development.png","medium-width":444,"medium-height":261,"medium_large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/12\/Pfingstweid_Development.png","medium_large-width":768,"medium_large-height":452,"large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/12\/Pfingstweid_Development.png","large-width":1492,"large-height":878,"1536x1536":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/12\/Pfingstweid_Development.png","1536x1536-width":1492,"1536x1536-height":878,"2048x2048":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/12\/Pfingstweid_Development.png","2048x2048-width":1492,"2048x2048-height":878,"card_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/12\/Pfingstweid_Development-790x465.png","card_image-width":790,"card_image-height":465,"wide_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/12\/Pfingstweid_Development.png","wide_image-width":1492,"wide_image-height":878}},"image_position":"center","orientation":"horizontal","hyperlink":""},{"acf_fc_layout":"content","content":"

<\/h2>\n

Verify greenspace requirements<\/span><\/span><\/h2>\n

Imagine yourself as an urban planner for the City of Zurich. Your task is to ensure that every new development meets two requirements related to green space:<\/span>\u00a0<\/span><\/p>\n

    \n
  1. The development provides at least 9m2 of green space per person<\/strong>.<\/span>\u00a0<\/span><\/li>\n
  2. The runoff of a heavy rain event<\/strong> does not exceed the drainage capacity<\/strong>.<\/span>\u00a0<\/span><\/li>\n<\/ol>\n

     <\/p>\n

    Today, you\u2019re verifying these conditions for the Pfingstweid Park.\u00a0<\/span>\u00a0<\/span><\/p>\n

     <\/p>\n

    Assess<\/span> green space per <\/span>resident<\/span> in <\/span>Pfingstweid Park<\/span><\/span>\u00a0<\/span><\/h2>\n

    Calculate the number of residents<\/span><\/span><\/h3>\n

    Let\u2019s<\/span> start by <\/span>calculating the number of residents in <\/span>Pfingstweid<\/span> Park. <\/span>We divide the net area of all residential spaces by<\/span> the area each person uses on average for living. The net area<\/span> is the area of a building floor available for its assigned purpose.<\/span> It excludes <\/span>walls <\/span>and<\/span> staircases.\u00a0<\/span> The new space-use <\/span>types<\/span> table<\/span> allows us to <\/span>easily <\/span>configure<\/span> different living space <\/span>consumption values <\/span>depending <\/span>on<\/span> each residential <\/span>space-use type.<\/span><\/span>\u00a0<\/span><\/p>\n

    With the new metrics you can now also<\/span>\u00a0configure the resolution of a metric <\/span>result<\/span>.<\/span> T<\/span>hink of <\/span>the <\/span>resolution as the <\/span>metric calculation <\/span>granularity<\/span>.<\/span> Ranging from<\/span> high granularity to low granularity, y<\/span>ou can con<\/span>trol whether<\/span> a metric <\/span>is <\/span>calculated per space, per <\/span>parcel<\/span>,<\/span> or for a <\/span>selection<\/span> of parcels.<\/span> Metrics calculated at a high granularity can be aggregated to a lower granularity. <\/span>In <\/span>the<\/span> first step, we calculate the number of residents per space<\/span>.<\/span><\/p>\n"},{"acf_fc_layout":"image","image":{"ID":2608972,"id":2608972,"title":"population_v8_optimized","filename":"population_v8_optimized.gif","filesize":6736859,"url":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/12\/population_v8_optimized.gif","link":"https:\/\/www.esri.com\/arcgis-blog\/products\/urban\/local-government\/quantify-the-impact-of-urban-planning-scenarios-using-metrics-in-arcgis-urban\/population_v8_optimized","alt":"Configure a metric to calculate the number of residents in Pfingstweid Park.","author":"9662","description":"","caption":"","name":"population_v8_optimized","status":"inherit","uploaded_to":2606062,"date":"2024-12-03 18:05:36","modified":"2024-12-03 18:05:51","menu_order":0,"mime_type":"image\/gif","type":"image","subtype":"gif","icon":"https:\/\/www.esri.com\/arcgis-blog\/wp-includes\/images\/media\/default.png","width":1732,"height":974,"sizes":{"thumbnail":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/12\/population_v8_optimized-213x200.gif","thumbnail-width":213,"thumbnail-height":200,"medium":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/12\/population_v8_optimized.gif","medium-width":464,"medium-height":261,"medium_large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/12\/population_v8_optimized.gif","medium_large-width":768,"medium_large-height":432,"large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/12\/population_v8_optimized.gif","large-width":1732,"large-height":974,"1536x1536":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/12\/population_v8_optimized-1536x864.gif","1536x1536-width":1536,"1536x1536-height":864,"2048x2048":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/12\/population_v8_optimized.gif","2048x2048-width":1732,"2048x2048-height":974,"card_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/12\/population_v8_optimized-826x465.gif","card_image-width":826,"card_image-height":465,"wide_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/12\/population_v8_optimized.gif","wide_image-width":1732,"wide_image-height":974}},"image_position":"center","orientation":"horizontal","hyperlink":""},{"acf_fc_layout":"content","content":"

     <\/p>\n

    In <\/span>the<\/span> next step, we want to <\/span>report the number of residents as<\/span> a whole number per building. <\/span>The new metrics allow us to configure this<\/span> using the rounding operator and selecting the building resolution<\/span>.\u00a0<\/span><\/p>\n"},{"acf_fc_layout":"image","image":{"ID":2607672,"id":2607672,"title":"Population_Rounded_optimized","filename":"Population_Rounded_optimized.gif","filesize":2883324,"url":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/12\/Population_Rounded_optimized.gif","link":"https:\/\/www.esri.com\/arcgis-blog\/products\/urban\/local-government\/quantify-the-impact-of-urban-planning-scenarios-using-metrics-in-arcgis-urban\/population_rounded_optimized","alt":"Round the number of residents per building to a whole number.","author":"9662","description":"","caption":"","name":"population_rounded_optimized","status":"inherit","uploaded_to":2606062,"date":"2024-12-03 08:44:49","modified":"2024-12-03 08:47:27","menu_order":0,"mime_type":"image\/gif","type":"image","subtype":"gif","icon":"https:\/\/www.esri.com\/arcgis-blog\/wp-includes\/images\/media\/default.png","width":1732,"height":974,"sizes":{"thumbnail":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/12\/Population_Rounded_optimized-213x200.gif","thumbnail-width":213,"thumbnail-height":200,"medium":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/12\/Population_Rounded_optimized.gif","medium-width":464,"medium-height":261,"medium_large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/12\/Population_Rounded_optimized.gif","medium_large-width":768,"medium_large-height":432,"large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/12\/Population_Rounded_optimized.gif","large-width":1732,"large-height":974,"1536x1536":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/12\/Population_Rounded_optimized-1536x864.gif","1536x1536-width":1536,"1536x1536-height":864,"2048x2048":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/12\/Population_Rounded_optimized.gif","2048x2048-width":1732,"2048x2048-height":974,"card_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/12\/Population_Rounded_optimized-826x465.gif","card_image-width":826,"card_image-height":465,"wide_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/12\/Population_Rounded_optimized.gif","wide_image-width":1732,"wide_image-height":974}},"image_position":"center","orientation":"horizontal","hyperlink":""},{"acf_fc_layout":"content","content":"

    Green space per person<\/h3>\n

    The new metrics also allow you to divide one metric by another. This comes in handy for assessing the available green space per person. We already know the number of residents in Pfingstweid Park. Now, we also need to know the total green open space in the study area. We can achieve this in two steps:<\/span><\/p>\n