Toward building next-generation Geocoding systems: a systematic review

TL;DR

This systematic review defines the problem of building next-generation geocoding systems and proposes a component-based analysis of inputs, outputs, and workflow stages to identify current gaps. It surveys input heterogeneity, output representations, and the four main components (data storage, parsing, retrieval, and interpolation), articulating research questions and hypotheses to guide evaluation strategies. By outlining benchmarking needs, self-improving architectures, and end-to-end use of large language models, the paper lays a research agenda for improving accuracy, transparency, and adaptability under real-world conditions. The work has practical significance for enabling more reliable spatial analyses and location-based services through standardized evaluation and modular, improvable geocoding pipelines.

Abstract

Geocoding systems are widely used in both scientific research for spatial analysis and everyday life through location-based services. The quality of geocoded data significantly impacts subsequent processes and applications, underscoring the need for next-generation systems. In response to this demand, this review first characterizes the technical requirements for next-generation geocoding inputs and outputs. We then decompose the geocoding workflow into modular functional units and survey existing implementations. For each component, we identify methodological limitations, articulate domain-specific research questions and hypotheses, and outline evaluation strategies needed. Finally, we identify opportunities to improve next-generation geocoding systems in light of recent technological advances. We envision that this review provides a technical foundation and research agenda for advancing the design, assessment, and deployment of next-generation geocoding systems.

Figures (2)

• Figure 1: Geocoding workflow
• Figure 2: The standard address components for U.S. addresses