The importance of data quality assessment has significantly increased with the boom of information technology and the growing demand for remote sensing (RS) data. The Remote Sensing Data Quality Working Group of the International Society for Photogrammetry and Remote Sensing aimed to conduct an investigation on the principles of data quality. Literature review revealed that most publications introduce data quality models for application specific processing chains and quality schemes are built case by case with particular domain indicators only. Yet no general concept independent from applications has been developed so far. This paper focuses on the formulation of a RS quality concept adopted from information technology domain describing a triangular RS data quality scheme that relates data sources, quality dimensions and lifecycle phases. Following the introduction it provides examples of international standards and fundamentals of theoretic quality modelling. After a short overview on platforms/sensors, definitions of different quality dimensions are presented with their metrics organised in clusters (like resolution or accuracy). The main achievement of the paper relates lifecycle phases to different quality dimensions of high relevance. The objective is not only to address experts of RS but to raise awareness of uncertainty for the general RS user community.

The reconstruction of military defense systems, (e.g. World War II defense lines) is generally based on military object identification and mapping. Since unexploded bombs can be still dangerous today, detecting bomb craters can be useful in creating hazard maps. The most significant problem is managing the large amount of relevant data. Therefore, there is a strong demand for automatically select the potential danger zones and also automate the entire processing workflow. Automatic methods have been developed to reduce the areas of interest. In addition, this method can be applied in other tasks as well, for example in settlement detection.

Technical Commission V, WG V/2 KEY WORDS: LiDAR, remote sensing, GIS, archaeology, military historical reconstruction ABSTRACT:LiDAR technology has become one of the major remote sensing methods in the last few years. There are several areas, where the scanned 3D point clouds can be used very efficiently. In our study we review the potential applications of LiDAR data in military historical reconstruction. Obviously, the base of this kind of investigation must be the archive data, but it is an interesting challenge to integrate a cutting edge method into such tasks. The LiDAR technology can be very useful, especially in vegetation covered areas, where the conventional remote sensing technologies are mostly inefficient. We review two typical sample projects where we integrated LiDAR data in military historical GIS reconstruction. Finally, we summarize, how laser scanned data can support the different parts of reconstruction work and define the technological steps of LiDAR data processing.

Technical Commission V, WG V/2 KEY WORDS: LiDAR, remote sensing, GIS, archaeology, military historical reconstruction ABSTRACT:LiDAR technology has become one of the major remote sensing methods in the last few years. There are several areas, where the scanned 3D point clouds can be used very efficiently. In our study we review the potential applications of LiDAR data in military historical reconstruction. Obviously, the base of this kind of investigation must be the archive data, but it is an interesting challenge to integrate a cutting edge method into such tasks. The LiDAR technology can be very useful, especially in vegetation covered areas, where the conventional remote sensing technologies are mostly inefficient. We review two typical sample projects where we integrated LiDAR data in military historical GIS reconstruction. Finally, we summarize, how laser scanned data can support the different parts of reconstruction work and define the technological steps of LiDAR data processing.

GIS is increasingly becoming popular in many humane disciplines such as archaeology, anthropology. In our research we use it to support military historical reconstruction. We deal with the Attila-line, which was a defence line around Budapest in the secnd World War. Up to now the researchers could find only short descriptions and sketches about this defence line. Our goal was a detailed and reliable reconstruction, which contains environmental, object, and event parts. To get through with this task we had to collect and manage a lot of variable-quality archive data. This information comes from different sources: libraries, archives, archive maps and aerial photographs, field measurements, and personal reminiscences. We can manage this information in a standard system with GIS. The investigation consists of three main parts: the reconstruction of the contemporary environment, the reconstruction of the defence objects, and the reconstruction of the military events. This database can be used as a reference system to support further research and to identify new parts of the defence line. Using the attributes we can make queries and various reviews. The database is usable as a digital data archive, too. Our next research goal is to follow the search of the Attila-line and other defence lines and to present them to wider scientific and public audiences.