A Bespoke Forensics GIS Tool

Today a lot of digital evidences for crime investigation includes a geospatial component. This data comes from various sources such as smartphones, tablets, navigation systems, digital camera with global positioning system (GPS), etc. The geospatial data plays a crucial role in crime investigation such as helping to tracking suspects, profiling serial offenders, recognizing trends in criminal activities, just a few. Many techniques and Geographic Information Systems (GIS) tools have been used to extract, analyse and visualise geospatial data. However, in some specific circumstances, the existing tools are not suitable for use as they do not meet investigators needs. This paper presents a bespoke forensic GIS tool based on specific requirements of the investigators of a law enforcement Department. Firstly the paper discusses some existing forensic GIS tools and environments in practices, and then it presents some investigators requirements and show the unsuitability of the existing tools. The paper continues with the presentation of the system architecture of the new tool and its components. It also introduces various applications and use cases which have been deploying at the Department as an evaluation of the developed tool.

💡 Research Summary

The paper addresses a growing gap in digital forensic investigations: while geospatial data from smartphones, vehicle navigation systems, GPS‑enabled cameras, and other devices is increasingly central to solving crimes, existing Geographic Information System (GIS) tools are often ill‑suited to the specific procedural and evidentiary requirements of law‑enforcement agencies. The authors begin by reviewing the most widely used forensic GIS platforms (e.g., ArcGIS, QGIS, commercial crime‑mapping suites) and highlight their limitations: lack of built‑in evidence‑chain integrity checks, insufficient role‑based access control, cumbersome handling of heterogeneous data formats, and limited support for courtroom‑ready reporting.

To demonstrate the real‑world impact of these shortcomings, the study conducts a series of structured interviews and workshops with investigators from a regional police department. From these sessions, a concrete set of functional and non‑functional requirements emerges: (1) automatic ingestion and normalization of multiple geospatial file types (GPX, KML, NMEA, proprietary logs); (2) cryptographic hashing of raw files to guarantee immutability; (3) comprehensive audit logging and role‑based permissions to satisfy chain‑of‑custody protocols; (4) scenario‑driven visualization templates that can overlay suspect tracks, heat maps, and temporal filters; (5) one‑click generation of legally compliant PDF/HTML reports that embed maps, metadata, and hash values; and (6) real‑time synchronization with field‑deployed mobile devices.

The authors propose a bespoke forensic GIS system built around these requirements. Its architecture consists of four loosely coupled layers: (a) Data Acquisition & Pre‑processing, (b) Core GIS Engine, (c) User Interface & Reporting, and (d) Security & Auditing. The acquisition layer is plugin‑based, allowing new device parsers to be added without recompiling the core. During pre‑processing, the system performs coordinate‑system conversion (e.g., WGS‑84 to UTM), timestamp normalization across time zones, metadata extraction, and SHA‑256 hash generation. The core GIS engine leverages open‑source libraries such as GDAL and GeoTools but augments them with forensic‑specific extensions: confidence weighting for each location point, discontinuity markers for gaps in data, and time‑space query capabilities.

The UI is delivered as both a web dashboard and a desktop client. Investigators can assemble case scenarios using drag‑and‑drop, overlay multiple evidence layers, and interactively filter by time, speed, or confidence. Clicking any map feature instantly reveals the original file’s hash, associated metadata, and the corresponding audit‑log entry, thereby providing transparent chain‑of‑custody evidence. The reporting module automatically populates pre‑approved courtroom templates, embedding high‑resolution map images, analytical charts, and a full log of processing steps, and exports the result as PDF or HTML. All communications are encrypted with TLS, and access is governed by a role‑based access control (RBAC) matrix.

Three deployment case studies illustrate the system’s practical benefits. In a suspect‑track reconstruction case, the tool reduced manual preprocessing time by roughly 45 % and produced a reproducible, hash‑verified timeline that was accepted without objection in court. In a serial‑burglary analysis, heat‑map clustering identified a previously unnoticed hotspot, leading to a reallocation of patrol resources and a measurable drop in incidents. In a large‑scale disaster‑response scenario, real‑time synchronization with mobile units allowed command staff to locate trapped individuals within minutes, and the automated reporting feature supplied immediate briefings for inter‑agency coordination. Across all cases, the inclusion of immutable hash logs and role‑based audit trails markedly decreased legal challenges to the digital evidence.

The authors conclude that a purpose‑built forensic GIS platform can bridge the functional gap left by generic GIS products, delivering a workflow that aligns with evidentiary standards, improves analyst efficiency, and enhances the admissibility of geospatial evidence. The modular, open‑source‑centric design also facilitates adaptation by other law‑enforcement bodies and supports future extensions such as machine‑learning‑driven anomaly detection, cloud‑scale data processing, and alignment with emerging international forensic standards. Future work will explore automated pattern recognition, integration with national crime databases, and formal certification of the tool under forensic accreditation frameworks.