New publication on decision fusion

New publication on decision fusion

August 1, 2015

Decision_fusion_loewOur new publication in ISPRS is accepted: “Decision fusion and non-parametric classifiers for land use mapping using multi-temporal RapidEye data”.

This study addressed the classification of multi-temporal satellite data from RapidEye by considering different classifier algorithms and decision fusion. Four non-parametric classifier algorithms, decision tree (DT), random forest (RF), support vector machine (SVM), and multilayer perceptron (MLP), were applied to map crop types in various irrigated landscapes in Central Asia. A novel decision fusion strategy to combine the outputs of the classifiers was proposed. This approach is based on randomly selecting subsets of the input data-set and aggregating the probabilistic outputs of the base classifiers with another meta-classifier. During the decision fusion, the reliability of each base classifier algorithm was considered to exclude less reliable inputs at the class-basis. The spatial and temporal transferability of the classifiers was evaluated using data sets from four different agricultural landscapes with different spatial extents and from different years. A detailed accuracy assessment showed that none of the stand-alone classifiers was the single best performing. Despite the very good performance of the base classifiers, there was still up to 50% disagreement in the maps produce by the two single best classifiers, RF and SVM. The proposed fusion strategy, however, increased overall accuracies up to 6%. In addition, it was less sensitive to reduced training set sizes and produced more realistic land use maps with less speckle. The proposed fusion approach was better transferable to data sets from other years, i.e. resulted in higher accuracies for the investigated classes. The fusion approach is computationally efficient and appears well suited for mapping diverse crop categories based on sensors with a similar high repetition rate and spatial resolution like RapidEye, for instance the upcoming Sentinel-2 mission.

 

you may also like:

Meeting with majors and local stakeholders within EO4CAM project

Meeting with majors and local stakeholders within EO4CAM project

On Wednesday, 30 October, a delegation from the EO4CAM project (comprising three members of the EORC and one from the ZKI, DLR) visited the small town of Markt Burgheim in Bavaria. They joined a meeting of local authorities and other stakeholders to discuss strategies...

social bouldering event

social bouldering event

Last Friday did we organize again a social event for all staff members and EAGLEs to get to know the new students, meet and chat with old students and just have a nice time outside the office for all staff members. We spend 4 hours together in the Rock In boulder gym...

snow cover conditions at Zugspitze with UAS sensors

snow cover conditions at Zugspitze with UAS sensors

Our UAS team travelled to Umweltforschungsstation Schneefernerhaus at Zugspitze to continue the time-series analysis for landscape analysis using drones. At an average elevation of 2500 meters, the team, Luisa Pflumm, Baturalp Arisoy, Konstantin Müller and Basil...

Guest lecture at KonGeoS conference

Guest lecture at KonGeoS conference

The KonGeoS conference (24-27.10.2024 in Würzburg) of geodesy student councils in Germany, Switzerland and Austria invited our Professor Hannes Taubenböck to give a guest lecture. On 25 October 2024, he gave a lecture on settlement development in Germany and discussed...

OPTIPLAN – Driving Innovation in Traffic and Urban Planning

OPTIPLAN – Driving Innovation in Traffic and Urban Planning

Driving Innovation in Traffic and Urban Planning: Insights from OPTIPLAN On October 24, 2024, the OPTIPLAN research consortium (German Aerospace Center (DLR)/University of Würzburg, Ingenieurbüro Behringer & Partner, and OBERMEYER GmbH) gathered to advance...