TY - JOUR

T1 - Knowledge based interpretation of moorland in aerial images

AU - Pakzad, Kian

AU - Heipke, Christian

PY - 2000

Y1 - 2000

N2 - For the interpretation of remote sensing data the traditional methods such as multispectral classification are in many cases not sufficient. This applies especially to more complex scenes. In order to interpret such scenes it is necessary to include and use more prior knowledge about the depicted objects, e.g. knowledge about the possible object structure or, in a multitemporal interpretation, knowledge about the possible temporal changes. In this paper we present an approach for the automatic interpretation of moorland from aerial images. The first step is a monotemporal interpretation. We use a knowledge based system with an explicit knowledge representation through semantic nets. This system is suitable to formulate explicitly (i.e. in a standard language) prior knowledge and to use it for the interpretation. In our case we divided moorland into different relevant land use classes and described them in a semantic net. For every class we described the obligatory parts. Obligatory parts are features and structures, which have to be detected in the particular areas in order to assign them the corresponding class. Because in moorland areas monitoring of changes is very important we extended the monotemporal system to a multitemporal one. The multitemporal interpretation also exploits explicitly represented prior knowledge about the possible temporal changes. The results show that the presented approach is suitable for the interpretation of moorland. The exploited additional prior knowledge led to an improvement of the interpretation, especially for the multitemporal one.

AB - For the interpretation of remote sensing data the traditional methods such as multispectral classification are in many cases not sufficient. This applies especially to more complex scenes. In order to interpret such scenes it is necessary to include and use more prior knowledge about the depicted objects, e.g. knowledge about the possible object structure or, in a multitemporal interpretation, knowledge about the possible temporal changes. In this paper we present an approach for the automatic interpretation of moorland from aerial images. The first step is a monotemporal interpretation. We use a knowledge based system with an explicit knowledge representation through semantic nets. This system is suitable to formulate explicitly (i.e. in a standard language) prior knowledge and to use it for the interpretation. In our case we divided moorland into different relevant land use classes and described them in a semantic net. For every class we described the obligatory parts. Obligatory parts are features and structures, which have to be detected in the particular areas in order to assign them the corresponding class. Because in moorland areas monitoring of changes is very important we extended the monotemporal system to a multitemporal one. The multitemporal interpretation also exploits explicitly represented prior knowledge about the possible temporal changes. The results show that the presented approach is suitable for the interpretation of moorland. The exploited additional prior knowledge led to an improvement of the interpretation, especially for the multitemporal one.

KW - Change detection

KW - Knowledge representation

KW - Model-based processing

KW - Monitoring

KW - Multi-temporal

UR - http://www.scopus.com/inward/record.url?scp=85046350501&partnerID=8YFLogxK

M3 - Conference article

AN - SCOPUS:85046350501

VL - 33

SP - 1103

EP - 1110

JO - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives

JF - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives

SN - 1682-1750

T2 - 19th International Congress for Photogrammetry and Remote Sensing, ISPRS 2000

Y2 - 16 July 2000 through 23 July 2000

ER -