{"id":324122,"date":"2018-09-28T00:00:22","date_gmt":"2018-09-28T07:00:22","guid":{"rendered":"http:\/\/www.esri.com\/arcgis-blog\/?post_type=blog&#038;p=324122"},"modified":"2019-01-17T09:59:07","modified_gmt":"2019-01-17T17:59:07","slug":"use-insights-to-explore-sensor-data","status":"publish","type":"blog","link":"https:\/\/www.esri.com\/arcgis-blog\/products\/insights\/analytics\/use-insights-to-explore-sensor-data","title":{"rendered":"Exploring Ocean Sensors with Insights for ArcGIS"},"author":6671,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","format":"standard","meta":{"_acf_changed":false,"_searchwp_excluded":""},"categories":[23341,22851],"tags":[40691,36121,23161,241122,241132],"industry":[],"product":[36801],"class_list":["post-324122","blog","type-blog","status-publish","format-standard","hentry","category-analytics","category-national-government","tag-analytics","tag-box-plot","tag-maps","tag-sensors","tag-waves","product-insights"],"acf":{"short_description":"This article explores sensor data used to support the understanding of waves and ocean environments using Insights for ArcGIS. ","flexible_content":[{"acf_fc_layout":"content","content":"<p>Sensor data is pivotal in helping communities prepare for large scale coastal events.<\/p>\n<p>While I\u00a0probably will never be a forecaster (or work for the National Hurricane Center), I wanted to put myself in an official&#8217;s role and use <a href=\"http:\/\/bit.ly\/2N8YKqW\">Insights for ArcGIS<\/a> to explore ocean sensor data.\u00a0 The sensors I looked at were mounted on bouys floating in the Atlantic Ocean.\u00a0 In particular (after hearing a news cast) I wanted to discover how unusual an 83 foot wave is during hurricane season and see what kind of data analysis I could apply to add context for those who may appreciate a little frame of reference.<\/p>\n<p>Let me say, if you want to skip to the end, that an 83 foot wave is huge.\u00a0 It&#8217;s big compared to other waves.\u00a0 It&#8217;s big compared to other bouys measuring wave height.<\/p>\n<p>For the analysis I used data from\u00a0the\u00a0<a href=\"https:\/\/www.ndbc.noaa.gov\/\">National Data Bouy Center<\/a>.\u00a0 This team tracks a range of nautical observations from wave heights, water temperature, air temperature to water clarity and much more.\u00a0 If you want the data (from 2017) which includes lat \/ long coordinates ready to go, <a href=\"https:\/\/gist.github.com\/phpmaps\/c3f25fcbfdabda648ac178d9f3afeb3b\">I posted that data here<\/a>.<\/p>\n<p>To learn about my workflow &#8211; I have shared my approach.\u00a0 It focuses on a few foundational features in Insights, which I&#8217;ve broken out in sections below.<\/p>\n<ul>\n<li><strong>Data pane<\/strong> &#8211; to explore field roles, switch field roles and filter data<\/li>\n<li><strong>Field calculator<\/strong> &#8211; to create fields with context and value<\/li>\n<li><strong>Box Plots<\/strong> &#8211; to surface key statistics and outliers<\/li>\n<\/ul>\n<p>Also my results are shared publicly, <a href=\"https:\/\/esri-insights.maps.arcgis.com\/apps\/insights\/index.html#\/view\/16d2e5dff9ac40d894fdaa7a49d08271\">here<\/a>.<\/p>\n<h2>Data Pane, Field Roles and Filter<\/h2>\n<p>The data pane reveals what <em>type<\/em> of fields are in a data set.\u00a0 The data pane exposes many capabilities (this blog only covers a few of them).\u00a0 From the data pane, I can tell that the <a href=\"https:\/\/gist.github.com\/phpmaps\/c3f25fcbfdabda648ac178d9f3afeb3b\">oceans data<\/a> is completely numeric.\u00a0 \u00a0This is apparent by looking at the Field Role icons next to the field&#8217;s name.\u00a0 See some of the images below.<\/p>\n<p>Field roles guide the possibilities for creating different kinds of charts, maps, and summary tables. Field\u00a0roles can be temporal, locational, numeric, categorial or rates.<\/p>\n<p>Consider the following.<\/p>\n<ul>\n<li>What if I wanted to show bouy locations on a <em>map<\/em>?<\/li>\n<li>What if I wanted to categorize wave height in a <em>chart<\/em>?<\/li>\n<\/ul>\n<p>A map requires at least one field with a <em>location role<\/em>.\u00a0 If I want a bar chart showing wave heights grouped into categories like small medium and large &#8211; I will need a field with a\u00a0<em>string role.\u00a0\u00a0<\/em>If I want to show the seasonality of wave height over time, I will need data with a\u00a0<em>date role <\/em>and a <em>number role\u00a0<\/em>(such as wave height).<\/p>\n<p>Insights can let you swap and change field roles.<\/p>\n<p>In the oceans data, I chose to update the following roles:<\/p>\n<ul>\n<li>Bouy field to use a <em>string role<\/em> (since it represents the bouy&#8217;s name)<\/li>\n<li>Latitude and longitude values to use a <em>location role<\/em><\/li>\n<li>Date and time fields to use a single <em>date roll<\/em><\/li>\n<\/ul>\n<p>I did this to better reflect the intended context of the data, which in turn gave me more options for analysis.<\/p>\n"},{"acf_fc_layout":"image","image":{"ID":326702,"id":326702,"title":"swap-fields","filename":"swap-fields.gif","filesize":275919,"url":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2018\/09\/swap-fields.gif","link":"https:\/\/www.esri.com\/arcgis-blog\/products\/insights\/analytics\/use-insights-to-explore-sensor-data\/swap-fields","alt":"","author":"6671","description":"Insights enables swapping Field Roles on the fly to best represent data for analysis.","caption":"The data in its original form is all numeric including the bouy field.  This role when used alone is suitable for creating Box Plot and Histograms.  The image above shows how to change the bouy field to a string field, which better represents the data and unlocks more charting capabilities such as Bar Chart, Column Chart, Tree Map etc.","name":"swap-fields","status":"inherit","uploaded_to":324122,"date":"2018-09-25 00:21:32","modified":"2018-09-28 02:42:35","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":600,"height":375,"sizes":{"thumbnail":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2018\/09\/swap-fields.gif","thumbnail-width":213,"thumbnail-height":133,"medium":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2018\/09\/swap-fields.gif","medium-width":418,"medium-height":261,"medium_large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2018\/09\/swap-fields.gif","medium_large-width":600,"medium_large-height":375,"large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2018\/09\/swap-fields.gif","large-width":600,"large-height":375,"1536x1536":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2018\/09\/swap-fields.gif","1536x1536-width":600,"1536x1536-height":375,"2048x2048":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2018\/09\/swap-fields.gif","2048x2048-width":600,"2048x2048-height":375,"card_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2018\/09\/swap-fields.gif","card_image-width":600,"card_image-height":375,"wide_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2018\/09\/swap-fields.gif","wide_image-width":600,"wide_image-height":375}},"image_position":"center","orientation":"horizontal","hyperlink":""},{"acf_fc_layout":"content","content":"<p>The below image shows how to take latitude and longitude fields and\u00a0<em>enable location<\/em>\u00a0to create a <em>location role<\/em>.\u00a0 Location roles provide a way for showing data on a map.\u00a0 In Insights, a single data set can have many location roles.<\/p>\n"},{"acf_fc_layout":"image","image":{"ID":326752,"id":326752,"title":"location-enablement-final","filename":"location-enablement-final.gif","filesize":328846,"url":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2018\/09\/location-enablement-final.gif","link":"https:\/\/www.esri.com\/arcgis-blog\/products\/insights\/analytics\/use-insights-to-explore-sensor-data\/location-enablement-final","alt":"","author":"6671","description":"Use insights to transform coordinates into a location role to support map cards and spatial analysis.","caption":"Use Insights to transform coordinates into a location role to create map cards and do spatial analysis.","name":"location-enablement-final","status":"inherit","uploaded_to":324122,"date":"2018-09-25 00:34:44","modified":"2018-09-28 06:34:56","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":600,"height":375,"sizes":{"thumbnail":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2018\/09\/location-enablement-final.gif","thumbnail-width":213,"thumbnail-height":133,"medium":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2018\/09\/location-enablement-final.gif","medium-width":418,"medium-height":261,"medium_large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2018\/09\/location-enablement-final.gif","medium_large-width":600,"medium_large-height":375,"large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2018\/09\/location-enablement-final.gif","large-width":600,"large-height":375,"1536x1536":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2018\/09\/location-enablement-final.gif","1536x1536-width":600,"1536x1536-height":375,"2048x2048":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2018\/09\/location-enablement-final.gif","2048x2048-width":600,"2048x2048-height":375,"card_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2018\/09\/location-enablement-final.gif","card_image-width":600,"card_image-height":375,"wide_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2018\/09\/location-enablement-final.gif","wide_image-width":600,"wide_image-height":375}},"image_position":"center","orientation":"horizontal","hyperlink":""},{"acf_fc_layout":"content","content":"<h3>Filter<\/h3>\n<p>Insights enables filtering from the data pane.\u00a0 There are various types of filters included with Insights (such as <em>card filters<\/em> and <em>cross filters<\/em>).\u00a0 When filtering data from the data pane (using the filter icon) &#8211; every map, chart and table will include that filter.\u00a0 \u00a0Since the National Data Bouy Center denotes missing data using numerals 99 and 999, I had to filter these out.<\/p>\n<h2>Field Calculations<\/h2>\n<p>Field calculations are perfect for cleaning data and adding value to data.\u00a0 I applied field calculations to the oceans data to create a proper <em>date role<\/em>, which helped me to understand the seasonal variation in ocean wave height over time.\u00a0 This was important because I wanted to see how abnormal an 83 foot wave was in hurricane season.<\/p>\n<p>For this dataset, I use field calculations for the following things.<\/p>\n<ul>\n<li>Creating dates by calculating several numeric fields<\/li>\n<li>Classifying wave height into 3 easy to conceptualize categories (small, medium, large)<\/li>\n<li>Converting meters to feet<\/li>\n<\/ul>\n<h3>Create dates<\/h3>\n<p>Create dates using the DATE() function.<\/p>\n"},{"acf_fc_layout":"image","image":{"ID":327672,"id":327672,"title":"date-calc","filename":"date-calc.gif","filesize":619714,"url":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2018\/09\/date-calc.gif","link":"https:\/\/www.esri.com\/arcgis-blog\/products\/insights\/analytics\/use-insights-to-explore-sensor-data\/date-calc","alt":"","author":"6671","description":"Use Field Calculation to create date roles which can be used in time series.  ","caption":"","name":"date-calc","status":"inherit","uploaded_to":324122,"date":"2018-09-25 17:30:58","modified":"2018-09-25 17:31:54","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":600,"height":375,"sizes":{"thumbnail":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2018\/09\/date-calc.gif","thumbnail-width":213,"thumbnail-height":133,"medium":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2018\/09\/date-calc.gif","medium-width":418,"medium-height":261,"medium_large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2018\/09\/date-calc.gif","medium_large-width":600,"medium_large-height":375,"large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2018\/09\/date-calc.gif","large-width":600,"large-height":375,"1536x1536":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2018\/09\/date-calc.gif","1536x1536-width":600,"1536x1536-height":375,"2048x2048":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2018\/09\/date-calc.gif","2048x2048-width":600,"2048x2048-height":375,"card_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2018\/09\/date-calc.gif","card_image-width":600,"card_image-height":375,"wide_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2018\/09\/date-calc.gif","wide_image-width":600,"wide_image-height":375}},"image_position":"center","orientation":"horizontal","hyperlink":""},{"acf_fc_layout":"content","content":"<h3>Classify and Convert<\/h3>\n<p>Use AND and IF functions to create meaningful categories.\u00a0 Here&#8217;s the <a href=\"https:\/\/gist.github.com\/phpmaps\/6b60f597751c5884bf3ae0d006bc4660\">field calc expression<\/a> I wrote.\u00a0 Use calculate functions, like division, to convert meters to feet.<\/p>\n<p>&nbsp;<\/p>\n"},{"acf_fc_layout":"image","image":{"ID":328142,"id":328142,"title":"advanced-calc","filename":"advanced-calc.gif","filesize":577915,"url":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2018\/09\/advanced-calc.gif","link":"https:\/\/www.esri.com\/arcgis-blog\/products\/insights\/analytics\/use-insights-to-explore-sensor-data\/advanced-calc","alt":"","author":"6671","description":"","caption":"","name":"advanced-calc","status":"inherit","uploaded_to":324122,"date":"2018-09-25 20:44:29","modified":"2018-09-28 03:25:46","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":600,"height":375,"sizes":{"thumbnail":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2018\/09\/advanced-calc.gif","thumbnail-width":213,"thumbnail-height":133,"medium":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2018\/09\/advanced-calc.gif","medium-width":418,"medium-height":261,"medium_large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2018\/09\/advanced-calc.gif","medium_large-width":600,"medium_large-height":375,"large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2018\/09\/advanced-calc.gif","large-width":600,"large-height":375,"1536x1536":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2018\/09\/advanced-calc.gif","1536x1536-width":600,"1536x1536-height":375,"2048x2048":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2018\/09\/advanced-calc.gif","2048x2048-width":600,"2048x2048-height":375,"card_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2018\/09\/advanced-calc.gif","card_image-width":600,"card_image-height":375,"wide_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2018\/09\/advanced-calc.gif","wide_image-width":600,"wide_image-height":375}},"image_position":"center","orientation":"horizontal","hyperlink":""},{"acf_fc_layout":"content","content":"<h2>Box Plot<\/h2>\n<p>Now that we&#8217;ve classified wave height into a few meaningful categories and converted meters to feet adding context, let&#8217;s quickly quantify ocean waves so we can better understand the distribution of height values at each bouy.\u00a0 Box Plot is great for this, as it not only succinctly reports key statistics like quartiles and the median, it identifies outliers within your data.<\/p>\n<p>Here&#8217;s how that works.<\/p>\n"},{"acf_fc_layout":"image","image":{"ID":328182,"id":328182,"title":"box-plot","filename":"box-plot.gif","filesize":315923,"url":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2018\/09\/box-plot.gif","link":"https:\/\/www.esri.com\/arcgis-blog\/products\/insights\/analytics\/use-insights-to-explore-sensor-data\/box-plot-2","alt":"","author":"6671","description":"","caption":"","name":"box-plot-2","status":"inherit","uploaded_to":324122,"date":"2018-09-25 20:59:11","modified":"2018-09-25 20:59:11","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":600,"height":375,"sizes":{"thumbnail":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2018\/09\/box-plot.gif","thumbnail-width":213,"thumbnail-height":133,"medium":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2018\/09\/box-plot.gif","medium-width":418,"medium-height":261,"medium_large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2018\/09\/box-plot.gif","medium_large-width":600,"medium_large-height":375,"large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2018\/09\/box-plot.gif","large-width":600,"large-height":375,"1536x1536":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2018\/09\/box-plot.gif","1536x1536-width":600,"1536x1536-height":375,"2048x2048":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2018\/09\/box-plot.gif","2048x2048-width":600,"2048x2048-height":375,"card_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2018\/09\/box-plot.gif","card_image-width":600,"card_image-height":375,"wide_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2018\/09\/box-plot.gif","wide_image-width":600,"wide_image-height":375}},"image_position":"center","orientation":"horizontal","hyperlink":""},{"acf_fc_layout":"content","content":"<p>From a Box Plot I can quickly access information about median wave height at each bouy and compare statistics side by side.\u00a0 I can also see min and max wave height values.\u00a0 I can say definitively that an 83 foot wave far surpasses the highest wave height reported at these two sensors in 2017 &#8211; by 59 feet.<\/p>\n<p>But why stop there?\u00a0 After creating Box Plots I too can see that offshore bouy (orange) experiences waves that are typically just over 1 foot higher then the nearshore bouy (blue).\u00a0 What I found interesting is a comparison on normal wave ranges.\u00a0 \u00a0The normal wave range of the offshore bouy (data between the top and bottom line) is larger then the inshore bouy.\u00a0 \u00a0In simple terms it says the further you go offshore, the chances are you will see bigger waves ranging between 1.5 &#8211; 12 feet.\u00a0 Another fun way to interpret Box Plots would be to look at the outliers and summarize that waves on rough days can range anywhere between 12 to 24 feet offshore.<\/p>\n<h2>Conclusion<\/h2>\n<p>An 83 foot wave is huge!\u00a0\u00a0To see my completed workbook, which highlights how hurricane season does in fact produce the largest of waves\u00a0<a href=\"https:\/\/esri-insights.maps.arcgis.com\/apps\/insights\/index.html#\/view\/16d2e5dff9ac40d894fdaa7a49d08271\">checkout the publicly shared page<\/a>.\u00a0 From the workbook, there is the following content to review.<\/p>\n<ul>\n<li>A map showing the location of the bouys used in the analysis<\/li>\n<li>Scatter plot charts explaining wave height based on atmospheric pressure<\/li>\n<li>Scatter plot charts explaining wave height based on water temperature<\/li>\n<li>A time series showing the seasonal effect on wave height<\/li>\n<li>And a column chart classifying wave height categorically (in groups &#8211; small, medium and large)<\/li>\n<\/ul>\n<p>Want to read more? Visit our\u00a0<a href=\"https:\/\/doc.arcgis.com\/en\/insights\/\" target=\"_blank\" rel=\"noopener\">documentation<\/a>.<\/p>\n<p>Want to try analyzing sensors with your data?\u00a0 Don\u2019t have access to\u00a0<a href=\"http:\/\/bit.ly\/2N8YKqW\" target=\"_blank\" rel=\"noopener\">Insights for ArcGIS<\/a>, follow this link to\u00a0<a href=\"http:\/\/bit.ly\/2R4CotO\" target=\"_blank\" rel=\"noopener\">get a free trial<\/a>!<\/p>\n"}],"authors":[{"ID":6671,"user_firstname":"Doug","user_lastname":"Carroll","nickname":"doogle_startups","user_nicename":"doogle_startups","display_name":"Doug Carroll","user_email":"DCarroll@esri.com","user_url":"","user_registered":"2018-03-02 00:18:39","user_description":"I am a developer on the Insights for ArcGIS team and have a passion for helping partners integrate GIS into their core business.  When not working at Esri to make spatial insights actionable, my family and I run an online retail business which started in downtown Los Angeles.  My degree is from the Department of Human Ecology at Rutgers University.","user_avatar":"<img data-del=\"avatar\" src='https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2018\/08\/bio-pic-dougcarroll.jpeg' class='avatar pp-user-avatar avatar-96 photo ' height='96' width='96'\/>"}],"related_articles":[{"ID":314572,"post_author":"6671","post_date":"2018-09-15 07:15:52","post_date_gmt":"2018-09-15 14:15:52","post_content":"","post_title":"Perform Spatial Joins, Geo-Enablement, and Spatial Aggregation all with Insights for ArcGIS","post_excerpt":"","post_status":"publish","comment_status":"closed","ping_status":"closed","post_password":"","post_name":"perform-spatial-joins-geo-enablement-classic-data-joins-and-spatial-aggregation-all-with-insights-for-arcgis","to_ping":"","pinged":"","post_modified":"2021-09-02 06:07:47","post_modified_gmt":"2021-09-02 13:07:47","post_content_filtered":"","post_parent":0,"guid":"http:\/\/www.esri.com\/arcgis-blog\/?post_type=blog&#038;p=314572","menu_order":0,"post_type":"blog","post_mime_type":"","comment_count":"0","filter":"raw"},{"ID":307652,"post_author":"6671","post_date":"2018-08-28 14:27:31","post_date_gmt":"2018-08-28 21:27:31","post_content":"","post_title":"How-to: Join your data and create relationships in Insights for ArcGIS","post_excerpt":"","post_status":"publish","comment_status":"closed","ping_status":"closed","post_password":"","post_name":"how-to-join-your-data-and-create-relationships-in-insights-for-arcgis","to_ping":"","pinged":"","post_modified":"2018-08-29 14:05:03","post_modified_gmt":"2018-08-29 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