  The geodatabase (vectorized data) nowadays becomes a rather standard digital
city infrastructure; however, updating geodatabase efficiently and economically
remains a fundamental and practical issue in the geospatial industry. The cost
of building a geodatabase is extremely high and labor intensive, and very often
the maps we use have several months and even years of latency. One solution is
to develop more automated methods for (vectorized) geospatial data generation,
which has been proven a difficult task in the past decades. An alternative
solution is to first detect the differences between the new data and the
existing geospatial data, and then only update the area identified as changes.
The second approach is becoming more favored due to its high practicality and
flexibility. A highly relevant technique is change detection. This article aims
to provide an overview the state-of-the-art change detection methods in the
field of Remote Sensing and Geomatics to support the task of updating
geodatabases. Data used for change detection are highly disparate, we therefore
structure our review intuitively based on the dimension of the data, being 1)
change detection with 2D data; 2) change detection with 3D data. Conclusions
will be drawn based on the reviewed efforts in the field, and we will share our
outlooks of the topic of updating geodatabases.
