{"id":123461,"date":"2018-03-20T09:27:19","date_gmt":"2018-03-20T09:27:19","guid":{"rendered":"http:\/\/www.esri.com\/arcgis-blog\/products\/product\/uncategorized\/modeling-using-the-language-of-spatial-analysis\/"},"modified":"2021-09-02T05:55:22","modified_gmt":"2021-09-02T12:55:22","slug":"modeling-using-the-language-of-spatial-analysis","status":"publish","type":"blog","link":"https:\/\/www.esri.com\/arcgis-blog\/products\/analytics\/analytics\/modeling-using-the-language-of-spatial-analysis","title":{"rendered":"Modeling: Using the Language of Spatial Analysis"},"author":7391,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","format":"standard","meta":{"_acf_changed":false,"_searchwp_excluded":""},"categories":[23341,22941],"tags":[25071,37091],"industry":[],"product":[36561,37031],"class_list":["post-123461","blog","type-blog","status-publish","format-standard","hentry","category-analytics","category-mapping","tag-learn-arcgis","tag-the-arcgis-book","product-arcgis-pro","product-spatial-analyst"],"acf":{"short_description":"By Clint Brown and Christian Harder. \r\n\r\nSpatial analysis is the process of geographically modeling a problem or issue, deriving results by...","flexible_content":[{"acf_fc_layout":"content","content":"<p><span style=\"color: #000000;\"><a href=\"https:\/\/www.esri.com\/en-us\/arcgis\/products\/spatial-analytics-data-science\/overview\">Spatial analysis<\/a> is the process of geographically modeling a problem or issue, deriving results by computer processing, and then examining and interpreting those model results. The spatial model that you create is based on a set of tools that apply operations on your data to create new results.<!--more--><\/span><\/p>\n<p><strong><span style=\"color: #000000;\">Data Items and Tools<\/span><\/strong><\/p>\n<p><span style=\"color: #000000;\">Each geoprocessing tool performs a small yet essential operation on geographic data, such as adding a field to a table, creating buffer zones around features, computing the least-cost paths between multiple locations, or computing a weighted overlay to combine multiple layers into a single result.<\/span><\/p>\n<p><a href=\"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2018\/03\/05-fig-5-8a-v2.png\"><img loading=\"lazy\" decoding=\"async\" class=\"aligncenter size-full wp-image-102547\" src=\"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2018\/03\/05-fig-5-8a-v2.png\" alt=\"\" width=\"588\" height=\"81\" \/><\/a><\/p>\n<p align=\"center\"><em><span style=\"color: #000000;\">A typical geoprocessing tool performs an operation on an ArcGIS dataset and produces new data as the result.<\/span><\/em><\/p>\n<p><span style=\"color: #000000;\">ArcGIS contains hundreds of analytical tools to perform just about any kind of analytical operation using any kind of geospatial information. For example, see the comprehensively rich set of operators found in the geoprocessing toolboxes that come with ArcGIS Pro. ArcGIS Pro also includes ModelBuilder, a visual programming application you can use to create, edit, and manage geoprocessing models.<\/span><\/p>\n<p><a href=\"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2018\/03\/05-fig-5-8b-v2.png\"><img loading=\"lazy\" decoding=\"async\" class=\"aligncenter size-large wp-image-102548\" src=\"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2018\/03\/05-fig-5-8b-v2-1024x193.png\" alt=\"\" width=\"640\" height=\"120\" \/><\/a><\/p>\n<p align=\"center\"><em><span style=\"color: #000000;\">Here is an example of a spatial model created in ModelBuilder that enables the ability to explore potential relationships between the incidence of childhood asthma and air quality from heavy traffic.<\/span><\/em><\/p>\n<p><span style=\"color: #000000;\">Spatial analysis supports the automation of tasks by providing a rich set of tools that can be combined into a series of tools in a sequence of operations using models and scripts. Through spatial modeling, you can chain together a sequence of tools, feeding the output of one tool into another, enabling you to compose your own model.<\/span><\/p>\n<p><strong><span style=\"color: #000000;\">Case Study:<\/span><span style=\"color: #000000; font-family: Calibri;\">\u00a0 <\/span><span style=\"color: #000000;\">Modeling Mountain Lion Habitat<\/span><\/strong><\/p>\n<p><span style=\"color: #000000;\">The metropolitan area of Greater Los Angeles region extends to 4,850 square miles (12,561 square kilometers) and represents the second-largest metropolitan area in the United States. The region has retained some of its original natural areas, and in the mountains surrounding the metropolis, the mountain lions (cougars) are the largest carnivores that live, hunt, and breed in this Southern California area. Our challenge is to ensure they survive. By connecting their remaining natural habitats to one another, in theory, this will allow the animals to seamlessly move between them.<\/span><\/p>\n<p><a href=\"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2018\/03\/05-fig-5-9a-v2.jpg\"><img loading=\"lazy\" decoding=\"async\" class=\"aligncenter size-full wp-image-102549\" src=\"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2018\/03\/05-fig-5-9a-v2.jpg\" alt=\"\" width=\"588\" height=\"441\" \/><\/a><\/p>\n<p><span style=\"color: #000000;\">This study analyzed ways to connect cougars located in several core areas with cougars in other geographically separated core areas. You will identify potential wildlife corridors that researchers and authorities can use to develop physical connections between cougar habitats located in the Santa Susana Mountains with habitats in the Santa Monica Mountains, the San Gabriel Mountains, and in the Los Padres National Forest. The complete workflow is described in the Learn ArcGIS lesson below.<\/span><\/p>\n<p><strong><span style=\"color: #000000;\">Suitability\/Corridor Model<\/span><\/strong><\/p>\n<p><a href=\"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2018\/03\/05-fig-5-9b-v2.png\"><img loading=\"lazy\" decoding=\"async\" class=\"aligncenter size-large wp-image-102552\" src=\"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2018\/03\/05-fig-5-9b-v2-1024x420.png\" alt=\"\" width=\"640\" height=\"262\" \/><\/a><\/p>\n<p><strong><span style=\"color: #000000;\">Learn ArcGIS Lesson: Big Cats, Big Challenges\u2014Claws, Cars, and Casualties<\/span><\/strong><\/p>\n<p><span style=\"color: #000000;\">The mega city of Los Angeles is one of the few world cities that have big cats living within the natural areas of the city. But the city landscape is becoming increasingly fragmented by urban development, roads, and freeways, thus leaving less space for mountain lions (cougars) to survive. As they attempt to cross roads and freeways in search of prey and mates, cougars often get struck and killed. For the Los Angeles cougar population to survive as well as maintain genetic diversity, and overall population health, a long-term solution must be found that will allow them to move safely between the isolated pockets of land they currently occupy.<\/span><\/p>\n<p><a href=\"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2018\/03\/05-fig-5-12-v2.jpg\"><img loading=\"lazy\" decoding=\"async\" class=\"aligncenter size-full wp-image-102553\" src=\"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2018\/03\/05-fig-5-12-v2.jpg\" alt=\"\" width=\"588\" height=\"441\" \/><\/a><\/p>\n<p><span style=\"color: #000000;\">In this project, your goal is to identify current cougar distributions and build a spatial model that identifies corridors we can establish to connect the various core mountain lion habitat areas within the city to each other.<\/span><\/p>\n<p><span style=\"color: #000000;\">The workflow emphasizes setting analysis goals which lead to questions that will give meaningful results. Following the workflow, you will examine and interpret analysis results, seek explanations for observed patterns, and explore their meaning from a spatial or temporal perspective. A strong emphasis of this workflow is on locating and using community and Living Atlas of the World data, and then contributing and sharing results and findings back to the community. The workflow also emphasizes the use of infographics and GeoEnrichment tools to provide deeper explanations and support for further inquiry.<\/span><\/p>\n<p><a href=\"http:\/\/go.esri.com\/l\/82202\/2017-05-10\/f43ph6\"><span style=\"color: #0000ff;\">Start the Lesson<\/span><\/a><\/p>\n<p align=\"center\"><span style=\"color: #000000;\">&#8212;&#8211;<\/span><\/p>\n<p><em><span style=\"color: #000000;\">This post is excerpted from <\/span><\/em><span style=\"color: #000000;\">The ArcGIS Book, Second Edition: 10 Big Ideas about Applying The Science of Where<em>, by Christian Harder and Clint Brown<\/em><\/span><em><span style=\"color: #000000;\">. The twin goals of this book are to open your eyes to what is now possible with Web GIS, and then spur you into action by putting the technology and deep data resources in your hands. The book is available through <\/span><\/em><a href=\"https:\/\/www.amazon.com\/dp\/1589484878\/\" target=\"_blank\" rel=\"noopener\"><em>Amazon.com<\/em><\/a><em><span style=\"color: #000000;\"> and other booksellers, and is also available at <\/span><\/em><a href=\"http:\/\/www.thearcgisbook.com\/\" target=\"_blank\" rel=\"noopener\"><em>TheArcGISBook.com<\/em><\/a><em><span style=\"color: #000000;\"> for free.<\/span><\/em><\/p>\n"}],"authors":[{"ID":7391,"user_firstname":"","user_lastname":"","nickname":"esripressbloggers","user_nicename":"esripressbloggers","display_name":"Esri Press Team","user_email":"esripressbloggers@esri.com","user_url":"","user_registered":"2018-03-21 18:21:17","user_description":"","user_avatar":"<img alt='' src='https:\/\/secure.gravatar.com\/avatar\/72ec2683ca5daf48758dfe6023a22a42cddac43c1d52c0947d602502212d95ea?s=96&#038;d=blank&#038;r=g' srcset='https:\/\/secure.gravatar.com\/avatar\/72ec2683ca5daf48758dfe6023a22a42cddac43c1d52c0947d602502212d95ea?s=192&#038;d=blank&#038;r=g 2x' class='avatar avatar-96 photo' height='96' width='96' loading='lazy' decoding='async'\/>"}],"related_articles":"","card_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2017\/07\/ArcGISBook_Card.jpg","wide_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2017\/07\/ArcGISBook_Header.jpg"},"yoast_head":"<!-- This site is optimized with the Yoast SEO Premium plugin v25.9 (Yoast SEO v25.9) - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>Modeling: Using the Language of Spatial Analysis<\/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.esri.com\/arcgis-blog\/products\/analytics\/analytics\/modeling-using-the-language-of-spatial-analysis\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Modeling: Using the Language of Spatial Analysis\" \/>\n<meta property=\"og:description\" content=\"By Clint Brown and Christian Harder. 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