ROAD DATA UPDATING 
USING TOOLS OF MATCHING AND MAP GENERALIZATION 
HU Yun gang 3 ’*, CHEN Jun b , LI Zhi lin c , ZHAO Ren liang b 
'Beijing University of Civil Engineering and Architecture, 100044, Beijing, China - hyg@bucea.edu.cn 
b National Geomatics Center of China, Beijing 100044, China 
L Dept. of Land Surveying and Geo-Informatics The Hong Kong Polytechnic University, 999077, Hong Kong Kowloon, 
China 
Commission IV, WG IV/3 
KEY WORDS: Map Generalization, Updating, Road Data, Matching, Selective Omission 
ABSTRACT: 
It is one of the important ways for GIS data updating based on map generalization. This paper analyzes the main steps for road data 
updating based on map generalization. As the core of this updating process, matching method considering the levels analyses and 
selective omission based on mesh density are developed. The approach for road data updating based on these two tools is proposed, 
which is applied in the project of national GIS data updating at 1:50,000 scale from data at 1:10,000 scale ant the results shows its 
feasibility. 
1. INTRODUCTION 
GIS data need to be updated to keep its up-to-date. As the use 
of GIS is spreading into various fields and our environment 
changes over time, the demand for updating GIS data is 
increasing. The old GIS data can be updated using the new data 
at larger scale based on map generalization. It is one of the 
important ways for GIS data updating, due to its efficiency, 
economy and data consistency preserved. 
The methods of GIS data updating have been studied by several 
researchers in recent years, most of which are focused on the 
update of MRDB (Multiple Representation Database). 
Kilpelainen and Sarjakoski (1995) discussed the incremental 
update based on map generalization in a MRDB. Harrie and 
Hellstrom (1999) developed a prototype system for propagating 
updates from large-scale data to small-scale data. Badard and 
Lemarie ( 1999) described a tool of matching for updating, 
and so on. However, how to update the old GIS data at small 
scale using the new data at large scale when the MRDB of these 
data is not built? These approaches mentioned above are still 
very limited, so new tools of matching and generalization 
methods are required for this update process. This paper aims at 
updating GIS data at 1:50,000 using new data at 1:10,000 based 
on map generalization and focus on studying road data updating. 
2. MAIN STEPS FOR UPDATING PROCESS 
This updating process can be divided in two main steps. 
Retrieval of updates from two data at different scales is 
regarded as the first step. Then the second step is to update the 
old database with the information received. 
The first step consists of two main sub-steps, i.e. data matching 
and selective omission. Matching is a critical first step for 
extracting updates and it is to establish the correspondence 
relationships between geographical objects that represent the 
same phenomenon in the real world(Gabay and Doytsher, 
1994; Filin and Doytsher, 1999; Walter and Fritsch, 1999). 
The two representations may have very different scales, levels 
of abstraction and different production time in this study. 
Selective omission is one of generalization operations for road 
feature. It is a process to retain more important road features (or 
to eliminate less important ones), while the essential topological, 
geometric and semantic characteristics of a road network are 
preserved(Jiang and Harrie, 2004; Mackaness, 1995). The 
results of matching and selective omission are overlaid and 
analyzed in order to retrieve updates. The unmatched roads on 
the data at small scale are regarded as the disappearance of 
roads. The roads on this database need to be deleted and can be 
called the disappearance of generalization, which are the 
counterparts of the roads matched and unselected on the data at 
large scale. The roads unmatched and selected on the data at 
large scale are considered as the new or change roads. These 
updates retrieved are coarse and not taken to update directly the 
old data, which operations belong to the second step for 
updating. 
The other operations of map generalization for road feature 
such as simplification, typification and displacement should be 
consisted in the second step. This step also involves addition 
and deletion of database operations as well as the preservation 
spatial integrity. In this step, some operations may be carried 
out according to the algorithms developed, for example 
simplification can be applied the algorithm presented by Li- 
OpenShow (Li and Openshaw, 1992; 1993). However most of 
the operations are difficult to automatic implement. Especially 
the operation of displacement need to deal with the specific 
conflicts to preserve the integrity of the database updated. 
Nevertheless the handled objects are mostly updates in this step, 
so these sub-processes can be implemented by interactive 
operation with the relative few workloads. 
Corresponding author.