Spatial Variable Importance Assessment for Yield Prediction in Precision Agriculture. - Georg Ruß; Alexander Brenning (IDA, 2010)

Data Mining in Precision Agriculture: Management of Spatial Information. - Georg Ruß; Alexander Brenning (IPMU, 2010)

Ensemble classification of paired data. - Werner Adler; Alexander Brenning; Sergej Potapov; Matthias Schmid; Berthold Lausen (Comput. Stat. Data Anal., 2011)

Spatial cross-validation and bootstrap for the assessment of prediction rules in remote sensing: The R package sperrorest. - Alexander Brenning (IGARSS, 2012)

Remote Sensing of Soil Moisture in Vineyards Using Airborne and Ground-Based Thermal Inertia Data. - Aiman Soliman; Richard J. Heck; Alexander Brenning; Ralph Brown; Stephen Miller (Remote. Sens., 2013)

Evaluating machine learning and statistical prediction techniques for landslide susceptibility modeling. - Jason Goetz; Alexander Brenning; Helene Petschko; Philip Leopold (Comput. Geosci., 2015)

A geographic approach for combining social media and authoritative data towards identifying useful information for disaster management. - João Porto de Albuquerque; Benjamin Herfort; Alexander Brenning; Alexander Zipf (Int. J. Geogr. Inf. Sci., 2015)

Potential of Space-Borne Hyperspectral Data for Biomass Quantification in an Arid Environment: Advantages and Limitations. - Harald Zandler; Alexander Brenning; Cyrus Samimi (Remote. Sens., 2015)

Do Red Edge and Texture Attributes from High-Resolution Satellite Data Improve Wood Volume Estimation in a Semi-Arid Mountainous Region? - Paul Schumacher; Bunafsha Mislimshoeva; Alexander Brenning; Harald Zandler; Martin Brandt; Cyrus Samimi; Thomas Koellner (Remote. Sens., 2016)

On the Effect of Spatially Non-Disjoint Training and Test Samples on Estimated Model Generalization Capabilities in Supervised Classification With Spatial Features. - Christian Geiß; Patrick Aravena Pelizari; Henrik Schrade; Alexander Brenning; Hannes Taubenböck (IEEE Geosci. Remote. Sens. Lett., 2017)

RQGIS: Integrating R with QGIS for Statistical Geocomputing. - Jannes Muenchow; Patrick Schratz; Alexander Brenning (R J., 2017)

Performance evaluation and hyperparameter tuning of statistical and machine-learning models using spatial data. - Patrick Schratz; Jannes Muenchow; Eugenia Iturritxa; Jakob Richter; Alexander Brenning (CoRR, 2018)

Geographic Object-Based Image Analysis for Automated Landslide Detection Using Open Source GIS Software. - Raphael Knevels; Helene Petschko; Philip Leopold; Alexander Brenning (ISPRS Int. J. Geo Inf., 2019)

2019-feature-selection. - Patrick Schratz; Jannes Muenchow; Eugenia Iturritxa; Alexander Brenning; Bernd Bischl (Zenodo, 2019)

2019-feature-selection. - Patrick Schratz; Jannes Muenchow; Eugenia Iturritxa; Alexander Brenning; Bernd Bischl (Zenodo, 2019)

2019-feature-selection. - Patrick Schratz; Jannes Muenchow; Eugenia Iturritxa; Alexander Brenning; Bernd Bischl (Zenodo, 2019)

2019-feature-selection. - Patrick Schratz; Jannes Muenchow; Eugenia Iturritxa; Alexander Brenning; Bernd Bischl (Zenodo, 2019)

Monitoring forest health using hyperspectral imagery: Does feature selection improve the performance of machine-learning techniques? - Patrick Schratz; Jannes Muenchow; Eugenia Iturritxa; José Cortés; Alexander Brenning; Bernd Bischl (Zenodo, 2020)

Transforming Feature Space to Interpret Machine Learning Models. - Alexander Brenning (CoRR, 2021)

Mlr3spatiotempcv: Spatiotemporal resampling methods for machine learning in R. - Patrick Schratz; Marc Becker; Michel Lang; Alexander Brenning (CoRR, 2021)

Monitoring Forest Health Using Hyperspectral Imagery: Does Feature Selection Improve the Performance of Machine-Learning Techniques? - Patrick Schratz; Jannes Muenchow; Eugenia Iturritxa; José Cortés; Bernd Bischl; Alexander Brenning (Remote. Sens., 2021)

Active-Learning Approaches for Landslide Mapping Using Support Vector Machines. - Zhihao Wang; Alexander Brenning (Remote. Sens., 2021)

Web scraping: a promising tool for geographic data acquisition. - Alexander Brenning; Sebastian Henn (CoRR, 2023)

Accounting for Deciduous Forest Structure and Viewing Geometry Effects Improves Sentinel-1 Time Series Image Consistency. - Markus Zehner; Clémence Dubois; Christian Thiel 001; Konstantin Schellenberg; Marius Rüetschi; Alexander Brenning; Jussi Baade; Christiane Schmullius (IEEE Trans. Geosci. Remote. Sens., 2023)

Spatial machine-learning model diagnostics: a model-agnostic distance-based approach. - Alexander Brenning (Int. J. Geogr. Inf. Sci., 2023)

Interpreting machine-learning models in transformed feature space with an application to remote-sensing classification. - Alexander Brenning (Mach. Learn., 2023)

Unsupervised active-transfer learning for automated landslide mapping. - Zhihao Wang; Alexander Brenning (Comput. Geosci., 2023)

Novel Approaches to Model Assessment and Interpretation in Geospatial Machine Learning. - Alexander Brenning (GISTAM, 2024)

A Transformer Approach for Multi Orbit Per Pixel Time Series Forest Characterization With Sentinel-1. - Markus Zehner; Valentin Kasburg; Clémence Dubois; Christian Thiel 001; Alexander Brenning; Jussi Baade; Nina Kukowski; Christiane Schmullius (IGARSS, 2024)

mlr3spatiotempcv: Spatiotemporal Resampling Methods for Machine Learning in R. - Patrick Schratz; Marc Becker; Michel Lang; Alexander Brenning (J. Stat. Softw., 2024)

A precise and efficient exceedance-set algorithm for detecting environmental extremes. - Thomas Suesse; Alexander Brenning (Comput. Stat., 2025)