Auf dem Luftbildsektor vollziehen sich seit einigen Jahren grundsätzliche Veränderungen. Digitale flugzeuggetragene Kamerasysteme und hochauflösende Satellitensysteme bieten neue Potentiale der Datenakquise und -auswertung. Diese digitalen Datensätze werden in absehbarer Zeit das herkömmliche Luftbild ersetzen und Kartographie, Photogrammetrie und Fernerkundung erheblich verändern. Die neue Generation von digitalen Kameras wird zwei zentrale Bereiche der Kartographie einschneidend beeinflussen: Die Orthokartenherstellung und die Kartenaktualisierung.

Extracting GIS features from high resolution imagery for map production or to update or generate GIS databases will be a common task in remote sensing in the coming years. These features are often described and defined in feature catalogues such as the German ATKIS or the military Vmap catalogues.

GEOmedia: abbiamo appreso delle vostre soluzioni orientate all'approccio object-oriented nell'analisi di Amsterdam.

Important semantic information necessary to interpret an image is mostly not represented in single pixels but in meaningful image objects and their mutual relations. Delphi2 Creative Technologies has developed a new technology and software for object-oriented and multi-scale image analysis. The procedure is based on the so called 'Fractal Net Evolution' approach which is a efficient method to describe complex semantics within largely self constructing and dynamic networks. It combines insights in the fractal structure of the world and of semantics with object orientation.

Large scale fire monitoring using remote sensing imagery is an important environmental task. Following the severe wildfires of 1997/98 in Indonesia, the need for an operational monitoring system became obvious. Based on object oriented image analysis techniques an application was implemented to generate fire damage maps out of a combination of ERS SAR images, vegetation maps and NOAA-AVHRR hotspot data.

Objektbasierte Verfahren bieten besonders für hochaufgelöste Bilddaten neue Möglichkeiten der Objektextraktion, da neben spektralen Merkmalen auch zusätzliche Informationen über Form, Größe und Kontext in die Klassifikation eingebracht werden können. Grundlage der objektbasierten Verfahren bildet die Segmentierung der Bilddaten. Der Segmentierungsalgorithmus der Bildanalysesoftware eCognition wird vorgestellt und dessen Wirkungsweise an Hand von Untersuchungen mit künstlichen Bildern demonstriert.

The classification of remote sensing images has been an important process for thematic mapping, and one of the main sources for geographic information systems. And has been improved as a result of the development of new sensors technology. Because of that, the efficiency of spectral classification algorithms was put in doubt and new methods are needed to extract information. Artificial Neural Nets arises as a powerful choice to the statistics based classificators, since no previous information or hypotheses about data distribution is required and input data can have different scales.

Wetlands are transitional lands between terrestrial and aquatic systems that provide many goods and services, including flood water retention, water quality maintenance, wildlife habitat, and soil erosion control. Wetlands in Iowa have decreased over 95% in the last 200 years. The loss of these resources and benefits shows a need to map and monitor wetlands in Iowa, especially where current wetland maps are outdated, as is the case in Black Hawk County.

Till now analysis of digital remote sensing data needs specific knowledge and software tools. In addition, the user has to deal with a broad range of different data formats, which often leads to converting expenditure and lack of compatibility.

Methods of image segmentation become more and more important in the field of remote sensing image analysis – in particular due to the increasing spatial resolution of imagery. The most important factor for using segmentation techniques is segmentation quality. Thus, a method for evaluating segmentation quality is presented and used to compare results of presently available segmentation programs. Firstly, an overview of the software used is given. Moreover the quality of the individual segmentation results is evaluated based on pan-sharpened multi-spectral IKONOS data.