{"id":773060,"date":"2026-06-16T06:48:25","date_gmt":"2026-06-16T13:48:25","guid":{"rendered":"https:\/\/www.esri.com\/about\/newsroom\/?post_type=blog&#038;p=773060"},"modified":"2026-06-16T07:48:03","modified_gmt":"2026-06-16T14:48:03","slug":"baltimore-police-department-data-driven-territory-alignment","status":"publish","type":"blog","link":"https:\/\/www.esri.com\/about\/newsroom\/blog\/baltimore-police-department-data-driven-territory-alignment","title":{"rendered":"Redrawn: How Baltimore Police Department Used Data to Rethink Territory and Officer Workloads"},"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":[338572,493248,325312,160532,493471],"industry":[],"esri-blog-category":[490742],"esri_blog_department":[478242],"class_list":["post-773060","blog","type-blog","status-publish","format-standard","hentry","tag-baltimore","tag-boundaries","tag-business-analyst","tag-police","tag-workload","esri-blog-category-law-enforcement","esri_blog_department-public-safety"],"acf":{"video_source":"","video_start":"","video_stop":"","short_description":"Baltimore Police used GIS to query crime patterns, simulate boundary changes, and realign every district to balance patrol workloads.","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":"Baltimore Police Department built an enterprise GIS that turned district boundaries, patrol beats, and crime patterns into a shared language.\r\n<p style=\"font-weight: 400;\"><strong>Key Takeaways<\/strong><\/p>\r\n\r\n<ul>\r\n \t<li>Baltimore Police Department spent months analyzing call volume, drive times, and demographic data before redrawing district boundaries.<\/li>\r\n \t<li>GIS analysts went to all stakeholders to show proposed lines and the data behind them.<\/li>\r\n \t<li>Detectives, patrol officers, and commanders now work from the same operational map.<\/li>\r\n<\/ul>","snippet":""},{"acf_fc_layout":"content","content":"<p style=\"font-weight: 400;\">For roughly half a century, the boundaries defining Baltimore\u2019s nine police districts remained the same while the city around them shifted. Some districts fielded hundreds of calls for service every day while neighboring ones were quieter. The map hadn\u2019t kept up. And when a map is wrong, the consequences are operational. If a 911 call for a shooting drops on the wrong side of a boundary, the nearest officer may not be the one who responds. In 2023, a correction to those district lines set a digital transformation in motion that now reaches from the chief\u2019s office to the patrol car.<\/p>\r\n<p style=\"font-weight: 400;\">Data drove every level of it\u2014from the analysts proposing new boundaries to the officer walking the block to confirm them.<\/p>\r\n\r\n<h3 style=\"font-weight: 400;\"><strong>The Science Behind the Lines<\/strong><\/h3>"},{"acf_fc_layout":"image","image":773066,"image_position":"right","orientation":"horizontal","hyperlink":""},{"acf_fc_layout":"content","content":"<p style=\"font-weight: 400;\">Derek Canton, chief technology officer with the Baltimore Police Department (BPD), had a standard for deployment. \u201cWe used science to determine what would be best for our agency,\u201d he said, \u201cnot just cops on dots, but people who are able to respond in a reasonable time.\u201d The old district boundaries had no systematic measure of workload behind them. Some districts carried significantly more calls than others. Getting the balance right meant building a solution the data could defend.<\/p>\r\n<p style=\"font-weight: 400;\">The push came from multiple directions: active federal court oversight, the operational demands of a city where every patrol assignment carries real stakes, and the belief that better data should determine where officers go. \u201cRedistricting kind of forced our hand,\u201d Canton said, \u201cto make sure we had resources where resources needed to be.\u201d<\/p>\r\n<p style=\"font-weight: 400;\">The effort fell to Rajiv Sharma, geographic information system (GIS) manager for the information technology division. When Sharma joined the department nearly a decade earlier, he and Canton built an enterprise GIS from a standing start. The redistricting would be its most demanding test: data driving the new lines and everyone\u2014from commissioners to council members, from patrol cops to residents\u2014discussing the same maps.<\/p>\r\n\r\n<h3 style=\"font-weight: 400;\"><strong>Drawing the New Lines<\/strong><\/h3>\r\n<p style=\"font-weight: 400;\">Baltimore police analyzed more than 200,000 crime records and five years of call data before a line was moved on the map. Working with Esri\u2019s territory design tools in ArcGIS Business Analyst, Sharma built the solution around fixed anchors: police stations and hospitals, seeds from which new boundaries grew outward. Into that framework the team fed call volume, unit counts, drive-time approximations, and 2020 census data tracking population shifts across Baltimore\u2019s 278 neighborhoods. From there Sharma\u2019s team ran scenarios, weighed tradeoffs\u2014drive time against crime volume, workload against district size\u2014and adjusted until the boundaries held up on every axis.<\/p>\r\n<p style=\"font-weight: 400;\">Sharma took the analysis to post officers and cops on the beat\u2014people with years on specific blocks whose knowledge the data couldn\u2019t capture. Their input surfaced complications buried in the geography for decades.<\/p>"},{"acf_fc_layout":"gallery","gallery_images":[773067,773065,773064,773062,773061]},{"acf_fc_layout":"content","content":"<p style=\"font-weight: 400;\">Old boundaries had accumulated anomalies, some cutting directly through properties. \u201cMr. and Mrs. Smith\u2019s bed was cut in half,\u201d Sharma said. \u201cIf Mrs. Smith called the police, one post would respond. If Mr. Smith\u2019s side had a problem, he would get a different post.\u201d The same problem scaled to a major trucking facility whose front entrance fell within one district and loading docks in another.<\/p>\r\n<p style=\"font-weight: 400;\">Resolving each anomaly meant going segment by segment, with one governing rule: Every district boundary follows the same side of every road centerline. No street would divide two districts.<\/p>\r\n<p style=\"font-weight: 400;\">The department\u2019s geocoder also had to be aligned with the new district geometry, synchronized with computer-aided dispatch, and coordinated with fire and emergency medical services (EMS)\u2014so that every first responder arrives at the same address. When the geocoder is wrong, a shooting at a busy intersection drops on the wrong side of the line. \u201cIf the point drops on the other side, you\u2019re calling for the wrong people to go to the wrong place,\u201d Sharma said. Getting the address right meant aligning the 911 call, the patrol response, and the incident record from the moment someone picked up the phone.<\/p>\r\n<p style=\"font-weight: 400;\">Refinements followed: gaps closed, community concerns were addressed, including a mall and a neighborhood on York Road bisected by the first version. In January 2025, Commissioner Richard Worley approved restructured sectors within each district, improving digital recordkeeping and sharpening supervisory coverage.<\/p>\r\n\r\n<h3 style=\"font-weight: 400;\"><strong>What the Map Changed<\/strong><\/h3>\r\n<p style=\"font-weight: 400;\">Workload balanced across all nine districts. The redistricting also created space for communication. Officers assigned to new territory learned it from colleagues who\u2019d worked it for years. Commanders from adjacent districts sat down and shared what they knew.<\/p>\r\n<p style=\"font-weight: 400;\">\u201cThere was greater opportunity for communication,\u201d Canton said. \u201cCommanders were able to have a discussion about who, what, when, where, and how things were happening.\u201d It started around maps and moved to the streets, commanders walking new territory together, pointing out features no dataset could convey.<\/p>\r\n<p style=\"font-weight: 400;\">The new geometry also went public. A find-your-district tool on the BPD website lets any resident enter an address and identify their district commander. Maps of each BPD post\u2014individual patrol beats, with their specific intersections and alleys\u2014went online for the first time.<\/p>"},{"acf_fc_layout":"gallery","gallery_images":[773072,773071]},{"acf_fc_layout":"content","content":"<p style=\"font-weight: 400;\">Violent crime in Baltimore has fallen in recent years. Canton attributes it to a broader set of reforms\u2014resulting in smarter call prioritization, reduced response burden, better data at every level\u2014redistricting among them. \u201cI would like to think the city is safer,\u201d he said, \u201cbecause we\u2019re able to provide the data that\u2019s necessary to effectively deploy where we need to.\u201d<\/p>\r\n\r\n<h3 style=\"font-weight: 400;\"><strong>A Foundation Still Being Built<\/strong><\/h3>\r\n<p style=\"font-weight: 400;\">Canton\u2019s goal was to create a department where any officer could work with spatial data, with GIS training pushed to detectives, patrol officers, and analysts. \u201cWe\u2019re pushing the tools down as far as we can get them so that everyone can do it,\u201d he said. \u201cYou don\u2019t have to rely on someone from my shop providing information.\u201d Training, he said, creates something else: an environment where officers start asking what\u2019s possible, and the requests come from the ground up.<\/p>\r\n<p style=\"font-weight: 400;\">Om Poudel, a senior application developer Sharma calls his wingman, produces be-on-the-lookout bulletins three times a day\u2014warrant data, mug shots, area-specific crime patterns\u2014giving officers in every district the same picture before they go out.<\/p>\r\n<p style=\"font-weight: 400;\">The same geographic framework underlies Hot Streets, BPD\u2019s block-level analysis of where calls are most heavily concentrated. Each district gets a map showing its 20 highest-call blocks, rendered as red lines\u2014thicker where calls are heaviest\u2014so that a commander can see the weight of a place before deploying anyone to it. Hot Streets applies the redistricting logic at finer resolution: not nine districts to balance, but specific blocks, often just one or two, where proactive patrols will make the most difference.<\/p>\r\n<p style=\"font-weight: 400;\">Sharma\u2019s team also builds ArcGIS StoryMaps briefings for active investigations: shell casings from recent shootings linked forensically to incidents years earlier; ShotSpotter audio tied to precise locations; suspect galleries connected to gang turf and victim networks (see sidebar). Sharma said that when you start building an ArcGIS StoryMaps story, \"You get that knowledge graph\u2014from the shell casing to the gun to the criminal who used it, to the gang he belongs to, to the turf area where it happened.\u201d<\/p>\r\n<p style=\"font-weight: 400;\">That geographic awareness extends to the building level. Officers on mobile terminals can see which structures the housing department has condemned and whether a building is known to be occupied. Vacant housing was one of the strongest correlations in the original redistricting analysis\u2014a signal of where workload concentrates, now visible on the screen during a foot pursuit. When a suspect disappears inside, the officer already knows the structure and whether anyone is likely to be in it.<\/p>\r\n<p style=\"font-weight: 400;\">The reach of what Sharma and Canton built extends beyond the city of Baltimore. Departments from Baltimore County to Cary, North Carolina to San Diego have come to study it.<\/p>\r\n<p style=\"font-weight: 400;\">Canton is deliberate about what drives the results. The department\u2019s GIS platform is central, but the transformation depends on integration across systems and partners\u2014housing data from the Baltimore Department of Housing &amp; Community Development, geocoder alignment with fire and EMS, call data from 911, coordination across every agency having the same operational picture.\u00a0 \u201cI will not allow this organization to do something because it\u2019s cool,\u201d he said. \u201cWhat we do must benefit our officers or the city.\u201d The redistricting qualified. So did the geocoder alignment, the ArcGIS StoryMaps briefings, and the training program that put spatial tools in the hands of officers who, a decade ago, were reading PDF maps pinned to a notice board.<\/p>\r\n<p style=\"font-weight: 400;\">Officers now pull up maps before they start their shifts, checking what happened while they were off duty. The data doesn\u2019t forget those places. Neither does the officer who works the beat.<\/p>\r\n<p style=\"font-weight: 400;\">Learn more about how <a href=\"https:\/\/www.esri.com\/en-us\/industries\/law-enforcement\/overview\">GIS supports data-driven policing<\/a>.<\/p>"},{"acf_fc_layout":"sidebar","layout":"standard","image_reference":null,"image_reference_figure":"","spotlight_image":null,"section_title":"","spotlight_name":"","position":"Center","content":"<h3 style=\"font-weight: 400;\"><strong>Gathering Context, Starting Conversations<\/strong><\/h3>\r\n<p style=\"font-weight: 400;\">Baltimore crime analysts tracked gang activity documented in spreadsheets and printed photographs. Details lived in people\u2019s heads or were scattered across documents with no way to connect them. The BPD\u2019s use of ArcGIS StoryMaps changed that by gathering the data in one place and giving it geographic context. A map of where incidents cluster, where shots were fired, or where a weapon has traveled across years of crime, becomes a surface everyone can examine together, point at, and push back on. That shared picture is where understanding of a place forms.<\/p>\r\n<p style=\"font-weight: 400;\">Rajiv Sharma, GIS manager for the information technology division at Baltimore Police Department, helped crime analysts convert ArcGIS StoryMaps stories into living, operational briefings. Each one is organized around a single gang and built to scroll: key takeaways at the top, then main players, then incidents, then a victim-versus-suspect map, then incident details. Tabs hold the full picture in sequence.<\/p>\r\n<p style=\"font-weight: 400;\">The GIS unit trained analysts, helped build the first maps, then stepped back. The analysts built the second and third on their own and kept going. Sharma and his team stay involved\u2014reviewing what analysts produce, suggesting improvements, occasionally bringing in outside expertise\u2014but the maps belong to the people working the cases. They update them as events happen.<\/p>\r\n<p style=\"font-weight: 400;\">One map shows where shots were fired, pinned to the intersection where ShotSpotter sensors registered gunfire. Another plots every incident tied to a single weapon across a span of years. Another shows turf, though gang territory is always moving. \u201cTracing the turf areas is very difficult because they are amorphous,\u201d Sharma said. \u201cThey keep changing.\u201d Analysts use the map to track turf wars and the loss or gain of territory.<\/p>\r\n<p style=\"font-weight: 400;\">No detective can hold all of the gang threads in their head, and they shouldn\u2019t have to. There\u2019s a wider group of peers they need to communicate with to plan interventions. With a shared map, everyone points to the same block, the same cluster of incidents, and says what they know about that place. The map extends the conversation, gives them a place to plan and dig into movements and incidents as they develop.<\/p>\r\n<p style=\"font-weight: 400;\">In Baltimore's highest-violence district, a\u00a0<a href=\"https:\/\/popcenter.asu.edu\/sites\/g\/files\/litvpz3631\/files\/baltimore_pd_reducing_gun_violence_in_baltimore_2024.pdf\">2024 analysis<\/a> by BPD's Data Driven Strategies Division and the University of Pennsylvania found that roughly 72 percent of homicides stemmed from disputes involving gang members\u2014groups representing about two percent of the district's population. Baltimore tracks roughly 14 active gangs. ArcGIS StoryMaps briefings have been built for most, with more in progress. Citywide, homicides fell to 201 in 2024 and 133 in 2025, the lowest in nearly 50 years\u2014the result of broader reforms across the department, redistricting, and better data among them. Keeping the map current helps users understand what drives the violence that remains.<\/p>","snippet":""}],"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 Baltimore Police Remapped Where Help Comes From<\/title>\n<meta name=\"description\" content=\"Baltimore Police used GIS to query crime patterns, simulate boundary changes, and realign every district to balance patrol workloads.\" \/>\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\/about\/newsroom\/blog\/baltimore-police-department-data-driven-territory-alignment\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Redrawn: How Baltimore Police Department Used Data to Rethink 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