{"id":774600,"date":"2026-10-15T07:06:08","date_gmt":"2026-10-15T14:06:08","guid":{"rendered":"https:\/\/www.esri.com\/about\/newsroom\/?post_type=blog&#038;p=774600"},"modified":"2026-10-15T10:21:02","modified_gmt":"2026-10-15T17:21:02","slug":"how-gis-connects-pennsylvania-corrections-data","status":"publish","type":"blog","link":"https:\/\/www.esri.com\/about\/newsroom\/blog\/how-gis-connects-pennsylvania-corrections-data","title":{"rendered":"From Cell Blocks to Crime Scenes: How GIS Connects Pennsylvania Corrections Data"},"author":671,"featured_media":0,"parent":0,"menu_order":0,"template":"","format":"standard","meta":{"_acf_changed":false,"sync_status":"","episode_type":"","audio_file":"","transcript_file":"","podmotor_file_id":"","podmotor_episode_id":"","castos_file_data":"","cover_image":"","cover_image_id":"","duration":"","filesize":"","filesize_raw":"","date_recorded":"","explicit":"","block":"","itunes_episode_number":"","itunes_title":"","itunes_season_number":"","itunes_episode_type":"","_links_to":"","_links_to_target":""},"categories":[],"tags":[277252,1521,1151,493567],"industry":[],"esri-blog-category":[490742],"esri_blog_department":[478242],"class_list":["post-774600","blog","type-blog","status-publish","format-standard","hentry","tag-corrections","tag-indoor-mapping","tag-investigation","tag-prisons","esri-blog-category-law-enforcement","esri_blog_department-public-safety"],"acf":{"video_source":"","video_start":"","video_stop":"","short_description":"Pennsylvania corrections investigators use location intelligence to connect facility and parole data, helping staff mitigate risk.","pdf":{"host_remotely":false,"file":"","file_url":""},"flexible_content":[{"acf_fc_layout":"sidebar","layout":"standard","image_reference":null,"image_reference_figure":"","spotlight_image":null,"section_title":"","spotlight_name":"","position":"Right","content":"<p style=\"font-weight: 400;\">Looking at facility and parole data on a map has surfaced patterns Pennsylvania corrections staff couldn\u2019t see before, from gang conflicts brewing inside a cellblock to drug networks operating outside the walls.<\/p>\r\n<p style=\"font-weight: 400;\"><strong>Key Takeaways<\/strong><\/p>\r\n\r\n<ul>\r\n \t<li>Mapping where people are, and whom they\u2019re near, replaces guesswork with evidence.<\/li>\r\n \t<li>Visibility into patterns lets staff intervene before violence happens, not just investigate afterward.<\/li>\r\n \t<li>Intelligence analysts have earned the trust of prison staff over time and requests for maps keep growing.<\/li>\r\n<\/ul>","snippet":""},{"acf_fc_layout":"content","content":"<p style=\"font-weight: 400;\">The illegal firearms dealer should have been out of reach. Instead, calls out of the Pennsylvania prison system suggested he was still doing business from the outside. He offered to supply weapons to those who could not legally purchase them and to help move drugs to inmates.<\/p>\r\n<p style=\"font-weight: 400;\">A year earlier, phone calls tied to a Philadelphia address had caught the attention of intelligence analysts at the Pennsylvania Department of Corrections (PADOC). In those calls, the speakers, using prison slang, discussed a modified rifle trigger. Analysts deciphered the conversation, then alerted the dealer\u2019s parole agent and a search followed. Norman Copper was arrested after authorities found weapons, cash, and drugs.<\/p>\r\n<p style=\"font-weight: 400;\">But when the case went to trial, a legal error undermined the prosecution and Copper was released. Within weeks, analysts saw signs that he had returned to selling firearms to criminals.<\/p>\r\n<p style=\"font-weight: 400;\">Then a new lead emerged. An inmate mentioned someone who could get drugs into the facility and sent that person a video-visit link. When the video call connected, PADOC analysts recognized the visitor as Copper.<\/p>\r\n<p style=\"font-weight: 400;\">The new evidence came via Copper\u2019s GPS ankle monitor. The location data showed him making repeated trips along certain routes, with those movements converging on a property that investigators identified as a stash house. When Copper shifted the stash location into neighboring Montgomery County, local investigators combined the GPS movement data with their own surveillance reports to support a search warrant. The ensuing search produced the evidence needed to convict Copper, who was later sentenced to 45 years in prison.<\/p>\r\n<p style=\"font-weight: 400;\">The case proved something the intelligence unit had been arguing for years. Phone calls, video visits, financial transactions, and GPS points can do more than record what has happened. They can also show where people go and whom they meet. By connecting people, events, and locations across time through geographic information system (GIS) technology, hidden patterns reveal themselves and help investigators identify criminal activity, social networks, and additional suspects.<\/p>\r\n\r\n<h3 style=\"font-weight: 400;\"><strong>Increasing Volumes of Data<\/strong><\/h3>\r\n<p style=\"font-weight: 400;\">The PADOC supervises approximately 39,000 inmates across 22 state prisons as well as more than 28,000 individuals under parole supervision in communities across the state. These inmates complete more than two million phone calls a month. Add video visits, email, GPS traces, and financial transactions, and the sheer volume becomes impossible to search manually.<\/p>\r\n<p style=\"font-weight: 400;\">Damien Mscisz supervises the analysts responsible for turning that data into actionable intelligence. He thinks about the department\u2019s blind spots the same way that the statistician <a href=\"https:\/\/www.ams.org\/publicoutreach\/feature-column\/fc-2016-06\">Abraham Wald<\/a> recognized a WWII problem for the military. Commanders wanted to reinforce the spots on returning aircraft where there were the most bullet holes. Wald showed the commanders the flaw: Those aircraft were the planes that had made it back. The real vulnerabilities were on the planes that didn\u2019t return.<\/p>"},{"acf_fc_layout":"sidebar","layout":"standard","image_reference":null,"image_reference_figure":"","spotlight_image":null,"section_title":"","spotlight_name":"","position":"Right","content":"<h3 style=\"font-weight: 400;\"><strong>From Hunches to Targets<\/strong><\/h3>\r\n<p style=\"font-weight: 400;\">Corrections intelligence used to run on chance. Phone monitors clicked into live calls at random, taking notes when something sounded worth flagging.<\/p>\r\n<p style=\"font-weight: 400;\">The Pennsylvania Department of Corrections Bureau of Investigations and Intelligence rebuilt that process around connections. Calls, video visits, GPS points, and commissary payments, once scattered across separate systems, now feed a single environment where patterns surface. The department hired additional phone monitors and changed their job priorities: follow what the data flags, then listen.<\/p>\r\n<p style=\"font-weight: 400;\">The geospatial data side needed the same kind of investment, championed by Laura Bomgardner, PADOC\u2019s first analyst and now chief of the Analytics Division. As the mapping proved its value, Mscisz pushed to bring on dedicated staff to grow it, drawing on ideas picked up from conversations with power GIS users at the Pennsylvania Game Commission along the way. The department hired its first two geospatial technology specialists, Logan Bonewitz and Nicholas Guida, both with GIS backgrounds outside of law enforcement. In their interviews, Mscisz asked each of them to think through how they\u2019d map out a prison. Their answers told him he\u2019d found the right people.<\/p>\r\n<p style=\"font-weight: 400;\">\u201cWe don\u2019t have a data problem,\u201d Mscisz said. \u201cWe have tons of data. We just didn\u2019t always know where to go to get it, how to bring it together, and what to do with it.\u201d<\/p>\r\n<p style=\"font-weight: 400;\">The result shows up in what gets found. Canine units sent to map-identified cells alert on hidden drugs almost every time. A parole agent who once could see only one person\u2019s GPS trail at a time can now see who else was nearby, and for how long. None of this replaces judgment on the ground. It gives that judgment more to work with to build a case and correct behavior that harms whole communities.<\/p>","snippet":""},{"acf_fc_layout":"content","content":"<p style=\"font-weight: 400;\">Mscisz applies the same logic. Inmates who get caught, and the location where incidents happen, are the visible data. A quiet cell might mean nothing is happening there or it might mean someone is good at not getting caught.<\/p>\r\n<p style=\"font-weight: 400;\">Solving for that gap became the design principle behind Pennsylvania\u2019s corrections geospatial intelligence program, built on ArcGIS Enterprise and organized around three questions: What\u2019s happening inside the walls? What invisible relationships connect the people involved? And what happens once they\u2019re released?<\/p>\r\n\r\n<h3 style=\"font-weight: 400;\"><strong>Inside the Walls<\/strong><\/h3>\r\n<p style=\"font-weight: 400;\">One of the first steps to implementing GIS, was for Mscisz\u2019s team to create digital representations of PADOC facilities. Knowing the layout of each State Correctional Institution (SCI) would show where incidents were occurring, where inmates were housed, and where the problem locations were.<\/p>\r\n<p style=\"font-weight: 400;\">Every one of Pennsylvania\u2019s 22 institutions has its own cell-numbering convention, and numbering plans often changed during or after construction. The unit\u2019s staff ended up asking every facility\u2019s critical incident manager to walk the buildings and write down what they found by hand.<\/p>\r\n<p style=\"font-weight: 400;\">Once the maps went live, counselors who used to sort information in a spreadsheet by cell number to check for gang conflicts, can see the same information layered over the building itself, down to individual beds. They could keep problem inmates separate from the general population or apart from each other if they were in rival gangs or had a history of conflict.<\/p>\r\n<p style=\"font-weight: 400;\">A lieutenant at SCI Albion watched recurring fights break out between inmates from Philadelphia and Erie. He asked to see where people from those cities were housed. The resulting hot spot map explained the friction and allowed the superintendent to make moves that would ease tensions.<\/p>\r\n<p style=\"font-weight: 400;\">Drug activity follows a similar pattern of proximity. Positive drug tests, mapped by cell and cross-referenced against deposits in inmate accounts, can be used to separate users from dealers. Canine units, sent to sniff for drugs, have increased their alerts and finds based on better targeting.<\/p>"},{"acf_fc_layout":"gallery","gallery_images":[774603,774872,774604,774608]},{"acf_fc_layout":"content","content":"<h3 style=\"font-weight: 400;\"><strong>The Network Beneath It<\/strong><\/h3>\r\n<p style=\"font-weight: 400;\">The cell-level map lays out the geography. It doesn\u2019t show the connections. For that, Mscisz built Python scripts that pull together phone records, video-visit logs, and commissary package senders. The scripts flag inmates who all call the same number and get visited by the same person.<\/p>\r\n<p style=\"font-weight: 400;\">Money reveals similar hidden connections. In Pennsylvania, roughly 62,000 outside senders deposit close to $20 million into inmate accounts every month, and every deposit carries a name, an address, and a phone number. Mapped by geography, the data shows senders clustered in the same Philadelphia neighborhood, all supporting inmates at the same facility. It also shows that a single sender is sending money to 10 different people on one cell block. That pattern might mean someone is being forced to traffic items or perform services for protection, commissary packages, or drugs. Recognizing the pattern gives staff a chance to step in and disrupt coercion.<\/p>\r\n<p style=\"font-weight: 400;\">Moving inmates within a prison or between facilities is an obvious answer to proximity problems, but it only buys time. An inmate skilled in exploiting the system often creates a new network wherever they land. Seasoned staff can spot when an inmate or a group of inmates is making a move. A shared map, informed by past patterns, allows every staff member to see it too.<\/p>"},{"acf_fc_layout":"image","image":774605,"image_position":"center","orientation":"horizontal","hyperlink":""},{"acf_fc_layout":"content","content":"<h3 style=\"font-weight: 400;\"><strong>Beyond the Gate<\/strong><\/h3>\r\n<p style=\"font-weight: 400;\">Supervision doesn\u2019t end at release, and neither does the data. About 450 parolees currently wear GPS ankle monitors, generating a rolling week of location history that updates hourly. Before this system existed, a parole agent could only view one person\u2019s trail at a time.<\/p>\r\n<p style=\"font-weight: 400;\">Layered together, GPS tracks show relationships. Two parolees, assigned to different agents but showing up in the same places at the same times, are flagged as co-travelers, a pattern that\u2019s worth examining to see if they\u2019re conducting business together. The system also signals when someone on GPS visits another parolee\u2019s registered home address, a pattern that investigators connected to drug distribution networks.<\/p>\r\n<p style=\"font-weight: 400;\">The department has also started cross-referencing GPS traces against public crime data, looking for monitored parolees who were near the location of a reported crime shortly after it happened. It recently placed its first analyst inside the Delaware Valley Intelligence Center specifically to offer support to local law enforcement, because a pattern alone isn\u2019t evidence. It\u2019s a starting point.<\/p>\r\n<p style=\"font-weight: 400;\">Mscisz has an insatiable curiosity about inmate and parolee patterns and how each indoor map captures the unique nature of every facility. With every successful discovery or intervention, he\u2019s receiving more requests for maps and analysis. Facility lieutenants who were skeptical at first are now asking where to conduct their next canine search.<\/p>\r\n&nbsp;\r\n<p style=\"font-weight: 400;\">Learn more about how\u00a0<a href=\"https:\/\/www.esri.com\/en-us\/industries\/law-enforcement\/overview\">law enforcement agencies use GIS to analyze crime patterns, share intelligence across jurisdictions<\/a>, and deploy resources more effectively.<\/p>"}],"references":null},"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>How GIS Connects Pennsylvania Corrections Data<\/title>\n<meta name=\"description\" content=\"Pennsylvania corrections investigators use location intelligence to connect facility and parole data, helping staff mitigate risk.\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" 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