1 A Survey of Digital Map Processing Techniques YAO-YI CHIANG, University of Southern California STEFAN LEYK, University of Colorado, Boulder CRAIG A. KNOBLOCK, University of Southern California Maps depict natural and human-induced changes on earth at a fine resolution for large areas and over long periods of time. In addition, maps—especially historical maps—are often the only information source about the earth as surveyed using geodetic techniques. In order to preserve these unique documents, increasing numbers of digital map archives have been established, driven by advances in software and hardware technologies. Since the early 1980s, researchers from a variety of disciplines, including computer science and geography, have been working on computational methods for the extraction and recognition of geographic features from archived images of maps (digital map processing). The typical result from map processing is geographic information that can be used in spatial and spatiotemporal analyses in a Geographic Information System environment, which benefits numerous research fields in the spatial, social, environmental, and health sciences. However, map processing literature is spread across a broad range of disciplines in which maps are included as a special type of image. This article presents an overview of existing map processing techniques, with the goal of bringing together the past and current research efforts in this interdisciplinary field, to characterize the advances that have been made, and to identify future research directions and opportunities. Categories and Subject Descriptors: A.1 [Introduction and Survey]; H.2.8 [Database Management; Database Applications]: Spatial Databases and GIS General Terms: Design, Algorithms Additional Key Words and Phrases: Map processing, geographic information systems, image processing, pattern recognition, graphics recognition, color segmentation ACM Reference Format: Yao-Yi Chiang, Stefan Leyk, and Craig A. Knoblock. 2014. A survey of digital map processing techniques. ACM Comput. Surv. 47, 1, Article 1 (April 2014), 44 pages. DOI: http://dx.doi.org/10.1145/2557423 1. INTRODUCTION This article presents an overview of the techniques for digital map processing (or simply map processing), which refers to computational procedures aimed at the automatic or semiautomatic extraction and/or recognition of geographic features contained in images (usually scanned) of maps. Digital map processing is a relatively young research field that grew out of image processing, document analysis, graphics recognition, and digital cartography. Over the past 40 years, researchers have become increasingly Authors’ addresses: Yao-Yi Chiang, University of Southern California, Spatial Sciences Institute, 3616 Trousdale Parkway, AHF B55, Los Angeles, CA 90089-0374; email: yaoyic@usc.edu; Stefan Leyk, Uni- versity of Colorado at Boulder, Department of Geography, 260 UCB, Boulder, Colorado 80309-0260, USA; email: stefan.leyk@colorado.edu; Craig A. Knoblock, University of Southern California, Information Sci- ences Institute and Department of Computer Science, 4676 Admiralty Way, Marina del Rey, CA 90292; email: knoblock@isi.edu. Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies show this notice on the first page or initial screen of a display along with the full citation. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, to republish, to post on servers, to redistribute to lists, or to use any component of this work in other works requires prior specific permission and/or a fee. Permissions may be requested from Publications Dept., ACM, Inc., 2 Penn Plaza, Suite 701, New York, NY 10121-0701 USA, fax +1 (212) 869-0481, or permissions@acm.org. c  2014 ACM 0360-0300/2014/04-ART1 $15.00 DOI: http://dx.doi.org/10.1145/2557423 ACM Computing Surveys, Vol. 47, No. 1, Article 1, Publication date: April 2014.