Publikationen
- Milà, C, Ludwig, M, Pebesma, E, Tonne, C, und Meyer, H. . „Random forests with spatial proxies for environmental modelling: opportunities and pitfalls.“ Geoscientific Model Development, Nr. 2024 (17): 6007–603. doi: 10.5194/gmd-17-6007-2024.
- Schumacher, F, Knoth, C, Ludwig, M, und Meyer, H. . „Estimation of local training data point densities to support the assessment of spatial prediction uncertainty.“ EGUsphere doi: 10.5194/egusphere-2024-2730.
- Nalepa, Jakub, Tulczyjew, Lukasz, Saux, Bertrand Le, Longépé, Nicolas, Ruszczak, Bogdan, Wijata, Agata M, Smykala, Krzysztof, Myller, Michal, Kawulok, Michal, Kuzu, Ridvan Salih, Albrecht, Frauke, Arnold, Caroline, Alasawedah, Mohammad, Angeli, Suzanne, Nobileau, Delphine, Ballabeni, Achille, Lotti, Alessandro, Locarini, Alfredo, Modenini, Dario, Tortora, Paolo, und Gumiela, Michal. . „Estimating Soil Parameters From Hyperspectral Images: A benchmark dataset and the outcome of the HYPERVIEW challenge.“ IEEE Geoscience and Remote Sensing Magazine, Nr. 2024 doi: 10.1109/MGRS.2024.3394040.
- Pondi, Brian, und Pebesma, Edzer. . „Standardizing Machine Learning APIs for Earth Observation Data Cubes.“ Beitrag präsentiert auf der The 5th Spatial Data Science, Online doi: https://doi.org/10.5281/zenodo.13960237.
- Ludwig, M, Moreno-Martinez, A, Hölzel, N, Pebesma, E, und Meyer, H. . „Assessing and improving the transferability of current global spatial prediction models.“ Global Ecology and Biogeography, Nr. 00: 1–13. doi: 10.1111/geb.13635.
- Mogge, L, McDonald, M, Knoth, C, Teickner, H, Purevtseren, M, Pebesma, E, und Kraehnert, K. . „Allocation of humanitarian aid after a weather disaster.“ World Development, Nr. 166: 106204. doi: 10.1016/j.worlddev.2023.106204.
- Ziegler, A, Heisig, J, Ludwig, M, Reudenbach, C, Meyer, H, und Nauss, T. . „Using GEDI as training data for an ongoing mapping of landscape-scale dynamics of the plant area index.“ Environmental Research Letters, Nr. 18 (7) doi: 10.1088/1748-9326/acde8f.
- Mila, C, Mateu, J, Pebesma, E, und Meyer, H. . „Nearest neighbour distance matching leave-one-out cross-validation for map validation.“ Methods in Ecology and Evolution, Nr. 13: 1304–1316. doi: 10.1111/2041-210X.13851.
- Meyer, H, und Pebesma, E. . „Machine learning-based global maps of ecological variables and the challenge of assessing them.“ Nature Communications, Nr. 13 doi: 10.1038/s41467-022-29838-9.
- Ludwig, M, Bahlmann, J, Pebesma, E, und Meyer, H. . „Developing Transferable Spatial Prediction Models: a Case Study of Satellite Based Landcover Mapping.“ Beitrag präsentiert auf der ISPRS, Nice doi: 10.5194/isprs-archives-XLIII-B3-2022-135-2022.
- Kleinewillinghöfer, L, Olofsson, P, Pebesma, E, Meyer, H, Buck, O, Haub, C, und Eiselt, B. . „Unbiased Area Estimation Using Copernicus High Resolution Layers and Reference Data.“ Remote Sensing, Nr. 14 (19): 4903. doi: 10.3390/rs14194903.
- Heisig, Johannes, Olson, Edward, und Pebesma, Edzer. . „Predicting Wildfire Fuels and Hazard in a Central European Temperate Forest Using Active and Passive Remote Sensing.“ Fire, Nr. 5 (1) doi: 10.3390/fire5010029.
- Carmelo, Bonannella, Tomislav, Hengl, Johannes, Heisig, Leandro, Parente, Marvin, Wright N., Martin, Herold, und Sytze, Bruin de. . „Forest tree species distribution for Europe 2000–2020: mapping potential and realized distributions using spatiotemporal machine learning.“ PeerJ, Nr. 10 (e13728) doi: 10.7717/peerj.13728.
- Heisig, J., Olson, E., und Pebesma, E. . „Predicting Wildfire Fuels and Hazard in a Central European Temperate Forest Using Active and Passive Remote Sensing.“ Fire, Nr. 5(1) (29) doi: 10.3390/fire5010029.
- Nüst, Daniel. . „Infrastructures and Practices for Reproducible Research in Geography, Geosciences, and GIScience.“ Dissertationsschrift, Universität Münster. doi: 10.5281/zenodo.4768096.
- Meyer, H, und Pebesma, E. . „Predicting into unknown space? Estimating the area of applicability of spatial prediction models.“ Methods in Ecology and Evolution, Nr. 12: 1620–1633. doi: 10.1111/2041-210X.13650.
- Garzón, Sebastian, und Nüst, Daniel. . „Exploring Research Data Repositories with geoextent.“ In EarthCube 2021 Notebooks, herausgegeben von Turk Matt Shanahan Hugh, Maull Keith Abernathey Ryan, Schreiber Lynne Giglio Donata und McHenry Kenton Katz Daniel S.. Zenodo. doi: 10.5281/zenodo.5496311.
- Ostermann, FO, Nüst, D, Granell, C, Hofer, B, und Konkol, M. . „Reproducible Research and GIScience: An Evaluation Using GIScience Conference Papers.“ In 11th International Conference on Geographic Information Science (GIScience 2021) - Part II, Bd. 208 aus Leibniz International Proceedings in Informatics (LIPIcs), herausgegeben von K Janowicz und JA Verstegen. Wadern: Dagstuhl Publishing. doi: 10.4230/LIPIcs.GIScience.2021.II.2.
- Meyer, H, und Pebesma, E. . „Estimating the Area of Applicability of Remote Sensing-Based Machine Learning Models with Limited Training Data.“ In 2021 IEEE International Geoscience and Remote Sensing Symposium IGARSS doi: 10.1109/IGARSS47720.2021.9553999.
- Eglen, Stephen, und Nüst, Daniel. . CODECHECK: An open science initiative for reproducible computational research,
- Jeremy, Leipzig, Daniel, Nüst, Tapley, Hoyt Charles, Karthik, Ram, und Jane, Greenberg. . „The role of metadata in reproducible computational research.“ Patterns, Nr. 2 (9): 100322. doi: 10.1016/j.patter.2021.100322.
- Nüst, Daniel. . preprint, A Web service for executable research compendia enables reproducible publications and transparent reviews in geospatial sciences, Zenodo. doi: 10.5281/zenodo.4818119.
- Christian, Hauschke, Daniel, Nüst, Anette, Cordts, und Svantje, Lilienthal. . Research Ideas and Outcomes, Bd. 7:e66264, OPTIMETA – Strengthening the Open Access publishing system through open citations and spatiotemporal metadata, doi: 10.3897/rio.7.e66264.
- Nüst, Daniel, und Eglen, Stephen J. . F1000Research preprints, CODECHECK: an Open Science initiative for the independent execution of computations underlying research articles during peer review to improve reproducibility, F1000Research. doi: 10.12688/f1000research.51738.1.
- Teickner, H, Knoth, C, Bartoschek, T, Kraehnert, K, Vigh, M, Purevtseren, M, Sugar, M, und Pebesma, E. . „Patterns in Mongolian nomadic household movement derived from GPS trajectories.“ Applied Geography, Nr. 122 (September 2020): 102270. doi: 10.1016/j.apgeog.2020.102270.
- Appel Marius, Pebesma Edzer. . „Spatiotemporal multi-resolution approximations for analyzing global environmental data.“ Spatial Statistics, Nr. 38 doi: 10.1016/j.spasta.2020.100465.
- Nüst, Daniel, Sochat, Vanessa, Marwick, Ben, Eglen, Stephen J, Head, Tim, Hirst, Tony, und Evans, Benjamin D. . „Ten simple rules for writing Dockerfiles for reproducible data science.“ PLoS Computational Biology, Nr. 16 (11): e1008316. doi: 10.1371/journal.pcbi.1008316.
- O., Ostermann Frank, Daniel, Nüst, Carlos, Granell, Barbara, Hofer, und Markus, Konkol. . Reproducible Research and GIScience: an evaluation using GIScience conference papers, EarthArXiv. doi: 10.31223/X5ZK5V.
- Nüst Daniel, Pebesma Edzer. . „Practical reproducibility in geography and geosciences.“ Annals of the American Association of Geographers, Nr. 2020 doi: 10.1080/24694452.2020.1806028.
- Graupner, Anika, und Nüst, Daniel. . „Serverless GEO Labels for the Semantic Sensor Web.“ In 11th International Conference on Geographic Information Science (GIScience 2021) - Part I, Bd. 177 aus Leibniz International Proceedings in Informatics (LIPIcs), herausgegeben von Verstegen Judith A. Janowicz Krzysztof. Wadern: Dagstuhl Publishing. doi: 10.4230/LIPIcs.GIScience.2021.I.4.
- Nüst, Daniel, Eddelbuettel, Dirk, Bennett, Dom, Cannoodt, Robrecht, Clark, Dav, Daróczi, Gergely, Edmondson, Mark, Fay, Colin, Hughes, Ellis, Kjeldgaard, Lars, Lopp, Sean, Marwick, Ben, Nolis, Heather, Nolis, Jacqueline, Ooi, Hong, Ram, Karthik, Ross, Noam, Shepherd, Lori, Sólymos, Péter, Lee, Swetnam Tyson, Turaga, Nitesh, Charlotte, Van Petegem, Williams, Jason, Willis, Craig, und Xiao, Nan. . „The Rockerverse: Packages and Applications for Containerisation with R.“ R Journal, Nr. 12 (1): 437–461. doi: 10.32614/RJ-2020-007.
- Konkol, M, Nüst, D, und Goulier, L. . „Publishing computational research - a review of infrastructures for reproducible and transparent scholarly communication.“ Research Integrity and Peer Review, Nr. 5 (10) doi: 10.1186/s41073-020-00095-y.
- Leipzig Jeremy, Nüst Daniel, Hoyt Charles T, Soiland-Reyes Stian, und Ram Karthik, Greenberg Jane. . arXiv.org preprints, The role of metadata in reproducible computational research, arXiv.
- Nüst, Daniel, und Konkol, Markus. . „A Vision for Reproducible Research in Geoinformatics, Geography, and Geosciences.“ Generation Research, Nr. 2020 doi: 10.25815/dm8v-2241.
- Granell, C, Hofer, B, Nüst, D, Ostermann, FO, und Sileryte, R. . „Reproducibilidad en AGILE: Experiencias, logros y recomendaciones.“ Revista Cartográfica, Nr. 2020 (100): 155–172. doi: 10.35424/rcarto.v0i100.668.
- Alexander, Bigga, Martin, Brändle, Ronny, Bölter, Constanze, Decker, Maria, España, Gerhard, Eilbacher, Matthias, Flasko, Frank, Krabbes, H., Leugers-Scherzberg August, Marianna, Mühlhölzer, Dennis, Müller, Philip, Münch, Tom, Niers, Daniel, Nüst, Adrian, Pachzelt, Maximilian, Plich, Ronald, Steffen, Klaus, Thoden, Hanna, Varachkina, Paul, Warner, Nils, Weiher, Daniela, Wolf, und Dulip, Withanage. . OJS Software Workshop Report, Heidelberg, Germany. doi: 10.11588/heidok.00028242.
- Nüst, Daniel, Sochat, Vanessa, Marwick, Ben, Eglen, Stephen, Head, Tim, Hirst, Tony, und Evans, Benjamin. . Ten Simple Rules for Writing Dockerfiles for Reproducible Data Science, OSF Preprints. doi: 10.31219/osf.io/fsd7t.
- Nüst, D, Eddelbuettel, D, Bennett, D, Cannoodt, R, Clark, D, Daroczi, G, Edmondson, M, Fay, C, Hughes, E, Lopp, S, Marwick, B, Nolis, H, Nolis, J, Ooi, H, Ram, K, Ross, N, Shepherd, L, Turaga, N, Willis, C, Xiao, N, und Petegem, CV. . The Rockerverse: Packages and Applications for Containerization with R, arXiv.
- Konkol, M, Nüst, D, und Goulier, L. . Publishing computational research - A review of infrastructures for reproducible and transparent scholarly communication, arXiv.
- Appel, M, und Pebesma, E. . „On-Demand Processing of Data Cubes from Satellite Image Collections with the gdalcubes Library.“ Data, Nr. 4 (3) doi: 10.3390/data4030092.
- Kraehnert, K, Vigh, M, Knoth, C, Teickner, H, Purevtseren, M, Sugar, M, und Pebesma, E. . „Herders Mobility GPS Tracking:Insights From Novel Trajectory Data.“ In Conférence internationale "Systèmes Complexes, Intelligence Territorialeet Mobilité", herausgegeben von P Sajous und C Bertelle.
- Maus, V, Camara, G, Appel, M, und Pebesma, E. . „dtwSat: Time-Weighted Dynamic Time Warping for Satellite Image Time Series Analysis in R.“ Journal of Statistical Software, Nr. 2019
- Kray, C, Pebesma, E, Konkol, M, und Nüst, D. . „Reproducible Research in Geoinformatics: Concepts, Challenges and Benefits (Vision Paper).“ In 14th International Conference on Spatial Information Theory (COSIT 2019), Bd. 142 aus Leibniz International Proceedings in Informatics (LIPIcs), herausgegeben von S Timpf, C Schlieder, M Kattenbeck, B Ludwig und K Stewart. Wadern: Dagstuhl Publishing. doi: 10.4230/LIPIcs.COSIT.2019.8.
- Eglen, Stephen, und Nüst, Daniel. . „CODECHECK: An open-science initiative to facilitate sharing of computer programs and results presented in scientific publications.“ Beitrag präsentiert auf der The 14th Munin Conference on Scholarly Publishing 2019, UiT The Arctic University of Norway, Tromsø, Norway doi: 10.7557/5.4910.
- Nüst, D, und Hinz, M. . „containerit: Generating Dockerfiles for reproducible research with R.“ Journal of Open Source Software, Nr. 4 (40): 1603. doi: 10.21105/joss.01603.
- Nüst, D, Ostermann, FO, Sileryte, R, Hofer, B, Granell, C, Teperek, M, Graser, A, Broman, K, und Hettne, K. . AGILE Reproducible Paper Guidelines, OSF. doi: 10.17605/OSF.IO/CB7Z8.
- Nüst, Daniel, Lohoff, Lukas, Einfeldt, Lasse, Gavish, Nimrod, Götza, Marlena, Tariq, Jaswal Shahzeib, Khalid, Salman, Meierkort, Laura, Mohr, Matthias, Rendel, Clara, und Antonia, van Eek. . „Guerrilla Badges for Reproducible Geospatial Data Science.“ In Accepted Short Papers and Posters from the 22nd AGILE Conference on Geo‐information Science, herausgegeben von P Kyriakidis, D Hadjimitsis, D Skarlatos und A Mansourian. Heidelberg: Springer. doi: 10.31223/osf.io/xtsqh.
- Giri, S, Hazra, S, Ghosh, P, Ghosh, A, Das, S, Chanda, A, Das, I, Chakraborty, K, Mukhopadhyay, A, und Maity, S. . „Role of lunar phases, rainfall, and wind in predicting Hilsa shad (Tenualosa ilisha) catch in the northern Bay of Bengal.“ Fisheries Oceanography, Nr. 28 (5): 567–575. doi: 10.1111/fog.12430.
- Nüst, Daniel. . „Packaging geoscience research for transparency and reproducibility: approaches and examples.“ Beitrag präsentiert auf der EGU General Assembly, Vienna, Austria doi: 10.5281/zenodo.2630483.
- Nüst, Daniel, Boettiger, Carl, und Marwick, Ben. . How to Read a Research Compendium, https://arxiv.org/abs/1806.09525: arXiv.
- Ghosh, P., Lahn, F., Gebbert, S., Mohr, M., und Pebesma, E. . „Running user-defined functions in R on Earth observation data in cloud back-ends.“ Beitrag präsentiert auf der 10th Geomundus conference, Lisbon, Portugal
- Nüst, Daniel, Schutzeichel, Marc, und Konkol, Markus. . Opening Reproducible Research: a research project website and blog, doi: 10.5281/zenodo.1485437.
- Granell Carlos, Nüst Daniel, und Ostermann Frank O, Sileryte Rusne. . „Reproducible Research is like riding a bike.“ PeerJ Preprints, Nr. 6 (e27216v1) doi: 10.7287/peerj.preprints.27216v1.
- Pebesma, E, Appel, M, und Lahn, F. . „R vector and raster data cubes for openEO.“ Beitrag präsentiert auf der EGU General Assembly 2018, Vienna, Austria
- Pebesma, E, Wagner, W, Soille, P, Kadunc, M, Gorelick, N, Schramm, M, Verbesselt, J, Reiche, J, Appel, M, Dries, J, Jacob, A, Neteler, M, Gebbert, S, Briese, C, und Kempeneers, P. . „openEO: an open API for cloud-based big Earth Observation processing platforms.“ Beitrag präsentiert auf der EGU General Assembly 2018, Vienna, Austria
- Appel Marius, Lahn Florian, und Buytaert Wouter, Pebesma Edzer. . „Open and scalable analytics of large Earth observation datasets: from scenes to multidimensional arrays using SciDB and GDAL.“ ISPRS Journal of Photogrammetry and Remote Sensing, Nr. 138: 47–56. doi: 10.1016/j.isprsjprs.2018.01.014.
- Knoth, C, Slimani, S, Appel, M, und Pebesma, E. . „Combining automatic and manual image analysis in a web-mapping application for collaborative conflict damage assessment.“ Applied Geography, Nr. 97: 25–34. doi: 10.1016/j.apgeog.2018.05.016.
- Ghosh, P, und Mukhopadhyay, A. . „A modified equation to calculate the potential future shoreline position using transects.“ Beitrag präsentiert auf der European Geosciences Union General Assembly 2018, Vienna, Austria
- Lu, M, Appel, M, und Pebesma, E. . „Multidimensional Arrays for Analysing Geoscientific Data.“ ISPRS International Journal of Geo-Information, Nr. 7 (8) doi: 10.3390/ijgi7080313.
- Nüst, Daniel. . Reproducibility Service for Executable Research Compendia: Technical Specifications and Reference Implementation, doi: 10.5281/zenodo.2203844.
- Chanda, A, Das, S, Mukhopadhyay, A, Ghosh, A, Akhand, A, Ghosh, P, Ghosh, T, Mitra, D, und Hazra, S. . „Sea surface temperature and rainfall anomaly over the Bay of Bengal during the El Niño-Southern Oscillation and the extreme Indian Ocean Dipole events between 2002 and 2016.“ Remote Sensing Applications: Society and Environment, Nr. 12: 10–22. doi: 10.1016/j.rsase.2018.08.001.
- Mukhopadhyay, A, Ghosh, P, Chanda, A, Ghosh, A, Ghosh, S, Das, S, Ghosh, T, und Hazra, S. . „Threats to coastal communities of Mahanadi delta due to imminent consequences of erosion – Present and near future.“ Science of the Total Environment, Nr. 637-638: 717–729. doi: 10.1016/j.scitotenv.2018.05.076.
- Nüst, Daniel, Granell, Carlos, Hofer, Barbara, Konkol, Markus, Ostermann, Frank O, Sileryte, Ruse, und Cerutti, Valentina. . „Reproducible research and GIScience: an evaluation using AGILE conference papers.“ PeerJ, Nr. 6: e5072. doi: 10.7717/peerj.5072.
- Gupta Shivam, Pebesma Edzer, und Mateu Jorge, Degbelo Auriol. . „Air Quality Monitoring Network Design Optimisation for Robust Land Use Regression Models.“ Sustainability, Nr. 10 (5) doi: 10.3390/su10051442.
- Nüst, Daniel, und Bartoschek, Thomas. . „Open Environmental Data Analysis.“ Beitrag präsentiert auf der EGU General Assembly 2018, Vienna, Austria doi: 10.5281/zenodo.1217911.
- Nüst, Daniel, Boettiger, Carl, und Eddelbuettel, Dirk. . „rocker/geospatial: a flexible runtime environment for geoscientific data analysis.“ Beitrag präsentiert auf der EGU General Assembly 2018, Vienna, Austria doi: 10.5281/zenodo.1216750.
- Gupta, Shivam, Mateu, Jorge, Degbelo, Auriol, und Pebesma, Edzer. . „Quality of life, big data and the power of statistics.“ Statistics and Probability Letters, Nr. 136 doi: 10.1016/j.spl.2018.02.030.
- Nüst, Daniel, Granell, Carlos, Hofer, Barbara, Konkol, Markus, Ostermann, Frank, Sileryte, Rusne, und Cerutti, Valentina. . Peerj Preprints, Bd. 6:e26561v1, Reproducible research and GIScience: an evaluation using AGILE conference papers, doi: 10.7287/peerj.preprints.26561v1.
- Roy, A., und Pebesma, E. . „A machine learning approach to demographic prediction using geohashes.“ In Bd. null aus International Workshop on Social Sensing New York, NY: ACM Press. doi: 10.1145/3055601.3055603.
- Mariethoz, G., und Pebesma, E. . „Nurturing a growing field: Computers & Geosciences.“ Computers and Geosciences, Nr. 107 (null): A1–A2. doi: 10.1016/j.cageo.2017.08.006.
- Gebbert, S., und Pebesma, E. . „The GRASS GIS temporal framework.“ International Journal of Geographical Information Science, Nr. 31 (7): 1273–1292. doi: 10.1080/13658816.2017.1306862.
- Nanki, Sidhu, Edzer, Pebesma, und Yi-Chen, Wang. . „Usability Study to Assess the IGBP Land Cover Classification for Singapore.“ Remote Sensing, Nr. 2017 (9(10), 1075) doi: 10.3390/rs9101075.
- Nüst, Daniel. . „Executable research compendia in geoscience research infrastructures.“ In Bd. EGU2017-7215 aus Geophysical Research Abstracts
- Knoth, C, und Nüst, D. . „Reproducibility and Practical Adoption of GEOBIA with Open-Source Software in Docker Containers.“ Remote Sensing, Nr. 9 (3) doi: 10.3390/rs9030290.
- Lu, Meng, Appel, Marius, und Pebesma, Edzer. . „Modelling spatiotemporal change using multidimensional arrays.“ Beitrag präsentiert auf der EGU General Assembly 2017, Vienna, Austria
- Marius, Appel, Daniel, Nüst, und Edzer, Pebesma. . „Reproducible Earth observation analytics: challenges, ideas, and a study case on containerized land use change detection.“ Beitrag präsentiert auf der EGU General Assembly 2017, Vienna, Austria
- gupta, Shivam, Pebesma, Edzer, und Mateu, Jorge. . „Air quality monitoring network location optimization for robust Land Use Regression Model.“ Beitrag präsentiert auf der Spatial Statistics 2017: One World: One Health, Lancaster Elsevier.
- Lu, Meng, Hamunyela, Eliakim, Verbesselt, Jan, und Pebesma, Edzer. . „Dimension Reduction of Multi-Spectral Satellite Image Time Series to Improve Deforestation Monitoring.“ Remote Sensing, Nr. 9 (10) doi: 10.3390/rs9101025.
- Nüst, Daniel, und Schutzeichel, Marc. . „An Architecture for Reproducible Computational Geosciences.“ In Societal Geo-Innovation doi: 10.5281/zenodo.1478542.
- Markus, Konkol, Daniel, Nüst, Marc, Schutzeichel, Edzer, Pebesma, Christian, Kray, Holger, Przibytzin, und Jörg, Lorenz. . „Opening reproducible research (o2r).“ Beitrag präsentiert auf der Open Science Conference, Berlin, Germany
- Ghosh, P, Mukhopadhyay, A, Chanda, A, Mondal, P, Akhand, A, Mukherjee, S, Nayak, SK, Ghosh, S, Mitra, D, Ghosh, T, und Hazra, S. . „Application of Cellular automata and Markov-chain model in geospatial environmental modeling- A review.“ Remote Sensing Applications: Society and Environment, Nr. 5: 64–77. doi: 10.1016/j.rsase.2017.01.005.
- Nüst, D, Konkol, M, Pebesma, E, Kray, C, Schutzeichel, M, Przibytzin, H, und Lorenz, J. . „Opening the Publication Process with Executable Research Compendia.“ D-Lib Magazine, Nr. 23 doi: 10.1045/january2017-nuest.
- Knoth, C, und Pebesma, E. . „Detecting dwelling destruction in Darfur through object-based change analysis of very high resolution imagery.“ International Journal of Remote Sensing, Nr. 38 (1): 273–295. doi: 10.1080/01431161.2016.1266105.
- Pebesma, E., Mailund, T., und Hiebert, J. . „Measurement units in R.“ R Journal, Nr. 8 (2): 490–498.
- Gräler, B., Pebesma, E., und Heuvelink, G. . „Spatio-temporal interpolation using gstat.“ R Journal, Nr. 8 (1): 204–218.
- Knoth Christian, Nüst Daniel. . „Enabling Reproducible OBIA with Open-Source Software in Docker Containers.“ Beitrag präsentiert auf der GEOBIA 2016: Solutions & Synergies, Enschede, The Netherlands doi: 10.3990/2.456.
- Stasch, Christoph, und Nüst Daniel, Pross Benjamin. . „Sharing environmental models: An Approach using GitHub repositories and Web Processing Services.“ In Bd. 18 aus Geophysical Research Abstracts, herausgegeben von European Geophysical Union.
- Nüst, Daniel, Konkol, Markus, Pebesma, Edzer, Kray, Christian, Klötgen, Stephanie, Schutzeichel, Marc, Lorenz, Jörg, Przibytzin, Holger, und Kussmann, Dirk. . „Opening Reproducible Research.“ In Bd. 18 aus Geophysical Research Abstracts, herausgegeben von European Geophysical Union.
- Scheider, S., Gräler, B., Pebesma, E., und Stasch, C. . „Modeling spatiotemporal information generation.“ International Journal of Geographical Information Science, Nr. null (null): 1–29. doi: 10.1080/13658816.2016.1151520.
- Marius, Appel, Florian, Lahn, Edzer, Pebesma, Wouter, Buytaert, und Simon, Moulds. . „Scalable Earth-observation Analytics for Geoscientists: Spacetime Extensions to the Array Database SciDB.“ Beitrag präsentiert auf der EGU General Assembly 2016, Vienna, Austria
- Lu, Meng, Pebesma, Edzer, Sanshaz, Alber, und Verbesselt, Jan. . „Spatio-temporal change detection from multidimensionalarrays: Detecting deforestation from MODIS time series.“ ISPRS Journal of Photogrammetry and Remote Sensing, Nr. 117 (227-236)
- Nüst, Daniel, Václavík, Tomáš, und Pross, Benjamin. . „Open and reproducible global land use classification.“ In EGU General Assembly Conference Abstracts, Bd. 17 aus Geophysical Research Abstracts
- Hengl, T., Pebesma, E., und Hijmans, R. . „Spatial and spatio-temporal modeling of meteorological and climatic variables using Open Source software.“ Spatial Statistics, Nr. null (null) doi: 10.1016/j.spasta.2015.06.005.
- Helle, K., und Pebesma, E. . „Optimising sampling designs for the maximum coverage problem of plume detection.“ Spatial Statistics, Nr. 13 (null): 21–44. doi: 10.1016/j.spasta.2015.03.004.
- Lemke, D., Mattauch, V., Heidinger, O., Pebesma, E., und Hense, H. . „Comparing adaptive and fixed bandwidth-based kernel density estimates in spatial cancer epidemiology.“ International Journal of Health Geographics, Nr. 14 (1) doi: 10.1186/s12942-015-0005-9.
- Meng, Lu, und Edzer, Pebesma. . „Spatio-temporal change modeling with array data.“ Beitrag präsentiert auf der EGU 2015, Vienna, Austria
- Lu, M., Pebesma, E., Sanchez, A., und Verbesselt, J. . „Spatio-temporal change detection from multidimensional arrays: Detecting deforestation from MODIS time series.“ ISPRS Journal of Photogrammetry and Remote Sensing, Nr. null (null) doi: 10.1016/j.isprsjprs.2016.03.007.
- Lemke, D., Berkemeyer, S., Mattauch, V., Heidinger, O., Pebesma, E., und Hense, H. . „Small-area spatio-temporal analyses of participation rates in the mammography screening program in the city of Dortmund (NW Germany) Biostatistics and methods.“ BMC Public Health, Nr. 15 (1) doi: 10.1186/s12889-015-2520-9.
- Appel, Marius, Pebesma, Edzer, und Camara, Gilberto. . „Scalable In-Database Regression Analysis of Large Earth-Observation Datasets.“ Beitrag präsentiert auf der EO Open Science 2.0, Frascati, Italy
- Pebesma, E., R., Bivand, und P.J., Ribeiro. . „Software for Spatial Statistics.“ Journal of Statistical Software, Nr. 63 (1)
- Hengl, T., Roudier, P., Beaudette, D., und Pebesma, E. . „plotKML: Scientific Visualization of Spatio-Temporal Data.“ Journal of Statistical Software, Nr. 63 (5)
- Skoien, J.O., Bloschl, G., Laaha, G., Pebesma, E., Parajka, J., und Viglione, A. . „rtop: An R package for interpolation of data with a variable spatial support, with an example from river networks.“ Computers and Geosciences, Nr. 67: 180–190. doi: 10.1016/j.cageo.2014.02.009.
- Truong, P.N., Heuvelink, G.B.M., und Pebesma, E. . „Bayesian area-to-point kriging using expert knowledge as informative priors.“ International Journal of Applied Earth Observation and Geoinformation, Nr. 30 (1): 128–138. doi: 10.1016/j.jag.2014.01.019.
- Jankowski, P., Fraley, G., und Pebesma, E. . „An exploratory approach to spatial decision support.“ Computers, Environment and Urban Systems, Nr. 45 (null): 101–113. doi: 10.1016/j.compenvurbsys.2014.02.008.
- Knoth, C, und Pebesma, E. . „Detecting Destruction in Conflict Areas in Darfur.“ Beitrag präsentiert auf der GEOBIA 2014 - Geographic Object Based Image Analysis, Thessaloniki, Greece
- Kilibarda, M, Hengl, T, Heuvelink, GBM, Gräler, B, Pebesma, E, Perčec, Tadić M, und Bajat, B. . „Spatio-temporal interpolation of daily temperatures for global land areas at 1 km resolution.“ Journal of Geophysical Research: Atmospheres, Nr. na doi: 10.1002/2013JD020803.
- B., Graler. . „Modelling skewed spatial random fields through the spatial vine copula.“ Spatial Statistics, Nr. na doi: 10.1016/j.spasta.2014.01.001.
- Gebbert, S., und Pebesma, E. . „A temporal GIS for field based environmental modeling.“ Environmental Modelling and Software, Nr. 53 (null): 1–12. doi: 10.1016/j.envsoft.2013.11.001.
- Stasch, C., Scheider, S., Pebesma, E., und Kuhn, W. . „Meaningful spatial prediction and aggregation.“ Environmental Modelling and Software, Nr. 51 (null): 149–165. doi: 10.1016/j.envsoft.2013.09.006.
- Stasch, C., Nüst, D., Rieke, M., Remke, A., und Pebesma, E. . „enviroCar – Open car data and open analysis tools for sustainable transportation development.“ Beitrag präsentiert auf der 2nd International Conference ICT for Sustainability, Stockholm, Schweden
- Meng, Lu, und Edzer, Pebesma. . „Modeling change from large-scale high-dimensional spatio-temporal array data.“ Beitrag präsentiert auf der EGU 2014, Vienna, Austria
- Gerharz, LE, und Pebesma, E. . „Using geostatistical simulation to disaggregate air quality model results for individual exposure estimation on GPS tracks.“ Stochastic Environmental Research and Risk Assessment, Nr. 27 (1): 223–234. doi: 10.1007/s00477-012-0578-9.
- Bastin, L, Cornford, D, Jones, R, Heuvelink, GBM, Pebesma, E, Stasch, C, Nativi, S, Mazzetti, P, und Williams, M. . „Managing uncertainty in integrated environmental modelling: The UncertWeb framework.“ Environmental Modelling and Software, Nr. 39: 116–134.
- Gerharz, LE, Klemm, O, Broich, AV, und Pebesma, E. . „Spatio-temporal modelling of individual exposure to air pollution and its uncertainty.“ Atmospheric Environment, Nr. 64: 56–65. doi: 10.1016/j.atmosenv.2012.09.069.
- Bivand, R., Pebesma, E., und Gómez-Rubio, V. . Applied Spatial Data Analysis with R: Second Edition,, herausgegeben von Bivand Roger, Pebesma Edzer und Gomez-Rubio Virgilio. Heidelberg: Springer. doi: 10.1007/978-1-4614-7618-4.
- Mello, M., Risso, J., Atzberger, C., Aplin, P., Pebesma, E., Vieira, C., und Rudorff, B. . „Bayesian networks for raster data (BayNeRD): Plausible reasoning from observations.“ Remote Sensing, Nr. 5 (11): 5999–6025. doi: 10.3390/rs5115999.
- Diniz, L., Buurman, M., Andrade, P., Camara, G., und Pebesma, E. . „Measuring allocation errors in land change models in amazonia.“ In Bd. null N/A: Selbstverlag / Eigenverlag.
- Stasch, C., Pebesma, E., Graeler, B., und Gerharz, L. . „Error-aware spatio-temporal aggregation in the model web.“ In Bd. null aus AGILE Conference on Geographic Information Science Dordrecht: Kluwer Academic. doi: 10.1007/978-3-319-00615-4_12.
- Mello, M.P., Aguiar, D.A., Rudorff, B.F.T., Pebesma, E., Jones, J., und Santos, N.C.P. . „Spatial statistic to assess remote sensing acreage estimates: An analysis of sugarcane in São Paulo State, Brazil.“ In Bd. null doi: 10.1109/IGARSS.2013.6723768.
- Lemke, D., Mattauch, V., Heidinger, O., Pebesma, E., und Hense, H.-W. . „Detecting cancer clusters in a regional population with local cluster tests and Bayesian smoothing Methods: A simulation study.“ International Journal of Health Geographics, Nr. null (null): 54. doi: 10.1186/1476-072X-12-54.
- García, Millán V E, Müterthies, A, Pakzad, K, Teuwsen, S, Benecke, N, Zimmermann, K, Kateloe, H, Preuße, A, Helle, K, und Knoth, C. . „GMES4Mining: GMES-based Geoservices for Mining Areas.“ Markscheidewesen, Nr. 120 (3): 17–24.
- Knoth, C, Klein, B, Prinz, T, und Kleinebecker, T. . „Unmanned Aerial Vehicles as innovative remote sensing platforms for high-resolution infrared imagery to support restoration monitoring in cut-over bogs.“ Applied Vegetation Science, Nr. 16 (3): 509–517. doi: 10.1111/avsc.12024.
- Brink, Juliane, und Pebesma, Edzer. . „Plume Tracking with a Mobile Sensor Based on Incomplete and Imprecise Information.“ Transactions in GIS, Nr. 2013 doi: 10.1111/tgis.12063.
- Gräler, B, vandenBerg, MJ, Vandenberghe, S, Petroselli, A, Grimaldi, S, DeBaets, B, und Verhoest, NEC. . „Multivariate return periods in hydrology: a critical and practical review focusing on synthetic design hydrograph estimation.“ Hydrology and Earth System Sciences, Nr. 17: 1281–1296. doi: 10.5194/hess-17-1281-2013.
- Hengl, T, Heuvelink, GBM, Tadić, MP, und Pebesma, EJ. . „Spatio-temporal prediction of daily temperatures using time-series of MODIS LST images.“ Theoretical and Applied Climatology, Nr. 107 (1-2): 265–277. doi: 10.1007/s00704-011-0464-2.
- Pebesma, E, Nüst, D, und Bivand, R. . „The R software environment in reproducible geoscientific research.“ Eos, Transactions American Geophysical Union, Nr. 93 (16): 163. doi: 10.1029/2012EO160003.
- Senaratne, H, Gerharz, L, Pebesma, E, und Schwering, A. . „Usability of Spatio-Temporal Uncertainty Visualisation Methods.“ BRIDGING THE GEOGRAPHIC INFORMATION SCIENCES: 3–23. doi: 10.1007/978-3-642-29063-3_1.
- Stasch, C, Foerster, T, Autermann, C, und Pebesma, E. . „Spatio-temporal aggregation of European air quality observations in the Sensor Web.“ Computers and Geosciences, Nr. 47: 111–118. doi: 10.1016/j.cageo.2011.11.008.
- Heuvelink, GBM, Pebesma, E, und Stein, A. . „Spatial statistics for mapping the environment.“ The ITC Journal
- Helle, K., und Pebesma, E. . „Stationary Sampling Designs Based on Plume Simulations.“ In Spatio-temporal Design: Advances in Efficient Data Acquisition, Bd. null , herausgegeben von Mueller Werner Mateu Jorge. New York City: John Wiley & Sons. doi: 10.1002/9781118441862.ch14.
- Schulz, M., Skøien, J., Gerharz, L., Dubois, G., und Pebesma, E. . „Uncertainty propagation between web services - A case study using the eHabitat WPS to identify unique ecosystems.“ In Bd. null
- Nüst, Daniel. . Accessing Data from Sensor Observation Services: the sos4R Package,
- Pross, B., Gerharz, L., Stasch, C., und Pebesma, E. . „Tools for uncertainty propagation in the model web using Monte Carlo simulation.“ In Bd. null
- Tomi, Kauppinen, Jim, Jones, Alber, Sanchez, Giovana, Mira de Espindola, und Thomas, Bartoschek. . „Linked Brazilian Amazon Rainforest Data.“ Semantic Web Journal, Nr. 2012
- Pebesma, E. . „spacetime: Spatio-Temporal Data in R.“ Journal of Statistical Software, Nr. 51 (7)
- Helle, Kristina, und Pebesma, Edzer. . „Stationary Sampling Designs Based on Plume Simulations.“ In Spatio-Temporal Design, herausgegeben von Wiley. New York City: John Wiley & Sons. doi: 10.1002/9781118441862.ch14.
- Pross, Benjamin, Gerharz, Lydia, Stasch, Christoph, und Pebesma, Edzer. . „Tools for uncertainty propagation in the Model Web using Monte Carlo simulation.“ In Proceedings of the sixth biannial meeting of the International Environmental Modelling and Software Society, herausgegeben von R Seppelt, A Voinov, S Lange und D Bankamp. Leipzig.
- Benedikt, Gräler, Lydia, Gerharz, und Edzer, Pebesma. . „Spatio-temporal analysis and interpolation of PM10 measurements in Europe.“ online.
- Nust, D, Stasch, C, und Pebesma, E. . „Connecting R to the Sensor Web.“ ADVANCING GEOINFORMATION SCIENCE FOR A CHANGING WORLD: 227–246. doi: 10.1007/978-3-642-19789-5_12.
- Stein, A, Pebesma, E, und Heuvelink, G. . „Procedia Environmental Sciences: Editorial.“ Procedia Environmental Sciences, Nr. 3: 1. doi: 10.1016/j.proenv.2011.02.001.
- Helle, KB, Urso, L, Astrup, P, Mikkelsen, T, Kaiser, JC, Pebesma, E, Rojas-Palma, C, Holo, E, Dyve, JE, und Raskob, W. . „Planning sensor locations for the detection of radioactive plumes for Norway and the Balkans *.“ Radioprotection, Nr. 46 (6 SUPPL.): S55–S61. doi: 10.1051/radiopro/20116628s.
- Fritze, H, Stewart, IT, und Pebesma, E. . „Shifts in western North American snowmelt runoff regimes for the recent warm decades.“ Journal of Hydrometeorology, Nr. 12 (5): 989–1006. doi: 10.1175/2011JHM1360.1.
- Baume, O, Skøien, JO, Heuvelink, GBM, Pebesma, EJ, und Melles, SJ. . „A geostatistical approach to data harmonization - Application to radioactivity exposure data.“ International Journal of Applied Earth Observation and Geoinformation, Nr. 13 (3): 409–419. doi: 10.1016/j.jag.2010.09.002.
- Dubois, G, Cornford, D, Hristopulos, D, Pebesma, E, und Pilz, J. . „Introduction to this special issue on geoinformatics for environmental surveillance.“ Computers and Geosciences, Nr. 37 (3): 277–279. doi: 10.1016/j.cageo.2010.06.002.
- Pebesma, E, Cornford, D, Dubois, G, Heuvelink, GBM, Hristopulos, D, Pilz, J, Stöhlker, U, Morin, G, und Skøien, JO. . „INTAMAP: The design and implementation of an interoperable automated interpolation web service.“ Computers and Geosciences, Nr. 37 (3): 343–352. doi: 10.1016/j.cageo.2010.03.019.
- De Espindola, GM, De Aguiar, APD, Pebesma, E, Câmara, G, und Fonseca, L. . „Agricultural land use dynamics in the Brazilian Amazon based on remote sensing and census data.“ Applied Geography, Nr. 32 (2): 240–252.
- Bröring, A, Maué, P, Janowicz, K, Nüst, D, und Malewski, C. . „Semantically-enabled sensor Plug & Play for the Sensor Web.“ Sensors, Nr. 11 (8): 7568–7605. doi: 10.3390/s110807568.
- Fairgrieve, S., Stasch, C., Falke, S., Gerharz, L., und Pebesma, E. . „Error aware near real-time interpolation of air quality observations in GEOSS.“ In Bd. 712
- Schwering, A., Pebesma, E., und Behnke, K., Hrsg. . ifgi prints no 41, Conference Proceedings Geoinformatik 2011, Berlin: Akademische Verlagsgesellschaft.
- Knoth, C, Prinz, T, und Loef, P. . „Microcopter-Based Colour Infrared (CIR) Close Range Remote Sensing as a Subsidiary Tool for Precision Farming.“ In Proceedings of the Workshop on Remote Sensing Methods for Change Detection and Process Modelling
- Helle, Kristina B, Astrup, Poul, Raskob, Wolfgang, und Pebesma, Edzer. . „Comparison of Mapping Methods for Plumes Using Prior Knowledge from Simulations.“ In Proceedings of the Seventh International Symposium on Spatial Data Quality, herausgegeben von Fonte Cidalia C, Goncalves Luisa und Goncalves Gil.
- Helle Kristina B., Urso Laura, Astrup Poul, Mikkelsen Torben, Kaiser Jan C., Pebesma Edzer, Rojas-Palma Carlos, Holo Eldri, und Dyve Jan E., Raskob Wolfgang. . „Planning sensor locations for the detection of radioactive plumes for Norway and the Balkans.“ In Proceedings of the International Conference on Radioecology & Environmental Radioactivity, Bd. 46 (6) aus Radioprotection, herausgegeben von J-C Barescut, D Lariviere und T Stocki. Les Ulis: EDP Sciences. doi: 10.1051/radiopro/20116628s.
- Gerharz, Lydia, Gräler, Benedikt, und Pebesma, Edzer. . „Disaggregating gridded air quality data for individual exposure modelling.“ Procedia Environmental Sciences, Nr. 7: 146–151. doi: 10.1016/j.proenv.2011.07.026.
- Gräler Benedikt, Pebesma Edzer. . „The pair-copula construction for spatial data: a new approach to model spatial dependency.“ Procedia Environmental Sciences, Nr. 7: 206–211. doi: 10.1016/j.proenv.2011.07.036.
- Daniel, Nüst, Christoph, Stasch, und Edzer, Pebesma. . „Connecting R to the Sensor Web.“ In Advancing Geoinformation Science for a Changing World, Springer Lecture Notes in Geoinformation and Cartography, herausgegeben von S Geertman, W Reinhardt und F Toppen. Heidelberg: Springer.
- Knoth, C, Klein, B, Kleinebecker, T, Prinz, T, und Sieg, B. . „UAV-Based Close Range Remote Sensing as a Monitoring Tool for the Restoration of Bog Ecosystems.“ In Proceedings of the Joint Meeting of Society of Wetland Scientists, WETPOL and Wetland Biogeochemistry Symposium 2011
- Geipel, J, Knoth, C, Elsässer, O, und Prinz, T. . „DGPS- and INS-Based Orthophotogrammetry on Micro UAV Platforms for Precision Farming Services.“ In Proceedings of the GEOINFORMATIK 2011 – GEOCHANGE
- Sluiter, R, und Pebesma, EJ. . „Comparing techniques for vegetation classification using multi- and hyperspectral images and ancillary environmental data.“ International Journal of Remote Sensing, Nr. 31 (23): 6143–6161. doi: 10.1080/01431160903401379.
- Hiemstra, PH, Pebesma, EJ, Heuvelink, GBM, und Twenhöfel, CJW. . „Using rainfall radar data to improve interpolated maps of dose rate in the Netherlands.“ Science of the Total Environment, Nr. 409 (1): 123–133. doi: 10.1016/j.scitotenv.2010.08.051.
- Skøien, JO, Baume, OP, Pebesma, EJ, und M, Heuvelink GB. . „Identifying and removing heterogeneities between monitoring networks.“ Environmetrics, Nr. 21 (1): 66–84.
- de Nijs, T, und Pebesma, E. . „Estimating the influence of the neighbourhood in the development of residential areas in the Netherlands.“ Environment and Planning B: Planning and Design, Nr. 37 (1): 21–41.
- Jirka, Simon, und Nüst, Daniel. . OGC Discussion Paper 10-171: Sensor Instance Registry, Open Geospatial Consortium.
- Jirka, Simon, Bröring, Arne, und Nüst, Daniel. . OGC Discussion Paper 09-112r1 - Sensor Observable Registry, Open Geospatial Consortium.
- Pebesma, E., Cornford, D., Nativi, S., und Stasch, C. . „The uncertainty enabled model web (UncertWeb).“ In Bd. 679
- Helle, Kristina B., und Pebesma, Edzer. . „Conservative Updating of Sampling Designs.“ In Proceedings of the Ninth International Symposium on Spatial Accuracy Assessment in Natural Resources and Environmental Sciences, herausgegeben von Nicholas J. Tate und Peter F. Fisher.
- Helle, Kristina B., und Pebesma, Edzer. . „Optimizing Spatio-Temporal Sampling Designs of Synchronous, Static, or Clustered Measurements.“ Beitrag präsentiert auf der European Geosciences Union General Assembly, Vienna
- Jirka, S, Nüst, D, Schulte, J, und Houbie, F. . „Integrating the OGC Sensor Web Enablement Framework into the OGC Catalogue.“ In WebMGS 2010: 1st International Workshop on Pervasive Web Mapping, Geoprocessing and Services. 26.-27. August 2010. Como, Italy.
- Jirka, S, Bröring, A, und Nüst, D. . OGC Discussion Paper 09-112r1 - Sensor Observable Registry, Open Geospatial Consortium.
- Gerharz, L., Pebesma, E., und Hecking, H. . „Visualizing uncertainty in spatio-temporal data.“ In Bd. null aus International Symposium on Spatial Accuracy Assessment in Natural Resources and Environmental Sciences N/A: Selbstverlag / Eigenverlag.
- Helle, K., und Pebesma, E. . „Conservative updating of sampling designs.“ In Bd. null aus International Symposium on Spatial Accuracy Assessment in Natural Resources and Environmental Sciences N/A: Selbstverlag / Eigenverlag.
- Gerharz, L, Pebesma, E, und Hecking, H. . „Visualizing uncertainty in spatio-temporal data.“ In Proceedings of the Ninth International Symposium on Spatial Accuracy Assessment in Natural Resources and Environmental Sciences, herausgegeben von NJ Tate und PF Fisher.
- Gräler, Benedikt, Kazianka, Hannes, und deEspindola, Giovana. . „Copulas, a novel approach to model spatial and spatio-temporal dependence.“ GIScience for Environmental Change Symposium Proceedings, Nr. 2010 (40): 49–54.
- Hiemstra, PH, Pebesma, EJ, Twenhöfel, CJW, und Heuvelink, GBM. . „Real-time automatic interpolation of ambient gamma dose rates from the Dutch radioactivity monitoring network.“ Computers and Geosciences, Nr. 35 (8): 1711–1721. doi: 10.1016/j.cageo.2008.10.011.
- Beelen, R, Hoek, G, Pebesma, E, Vienneau, D, de Hoogh, K, und Briggs, DJ. . „Mapping of background air pollution at a fine spatial scale across the European Union.“ Science of the Total Environment, Nr. 407 (6): 1852–1867. doi: 10.1016/j.scitotenv.2008.11.048.
- Houbie, F, Skivee, F, Robin, A, Jirka, S, Bröring, A, und Nüst, D. . OGC Discussion Paper 09-163 - OGC Catalogue Services Specification 2.0 - Extension Package for ebRIM Application Profile: SensorML, Open Geospatial Consortium.
- E.J., Pebesma. . „How we build geostatistical models and deal with their output.“ In Interfacing Geostatistics and GIS, Bd. null , herausgegeben von Springer. Düsseldorf: Springer VDI Verlag. doi: 10.1007/978-3-540-33236-7_1.
- Dubois, G., De Jesus, J., Doherty, B., Cornford, D., und Pebesma, E. . „Lessons learned from INTAMAP, an interoperable web service for the real-time interpolation of environmental variables.“ In Bd. null
- Houbie, F, Skivee, F, Robin, A, Jirka, S, Bröring, A, und Nüst, D. . „OGC Discussion Paper 09-163 - OGC Catalogue Services Specification 2.0 - Extension Package for ebRIM Application Profile: SensorML.“ Wayland, MA: Open Geospatial Consortium.
- Gerharz, L, und Pebesma, E. . „Usability of interactive and non-interactive visualisation of uncertain geospatial information.“ In Geoinformatik 2009 Konferenzband, Bd. 35 aus ifgiprints, herausgegeben von W Reinhardt, A Krüger und M Ehlers.
- Skøien, JO, Pebesma, EJ, und Blöschl, G. . „Geostatistics for automatic estimation of environmental variables-some simple solutions.“ Georisk, Nr. 2 (4): 257–270.
- ter, Braak C JF, Brus, DJ, und Pebesma, EJ. . „Comparing sampling patterns for kriging the spatial mean temporal trend.“ Journal of Agricultural, Biological, and Environmental Statistics, Nr. 13 (2): 159–176.
- Bivand, R, Pebesma, E, und Gomez-Rubio, V. . UseR!, Applied Spatial Data Analysis with R, Düsseldorf: Springer VDI Verlag.
- Pebesma, Edzer, Bishr, Mohammed, und Bartoschek, Thomas, Hrsg. . ifgiPrints, Bd. 32, Proceedings of the 6th Geographic Information Days, 400. Aufl. N/A: unbekannt / n.a. / unknown.
- Addink, EA, De Jong, SM, und Pebesma, EJ. . „The importance of scale in object-based mapping of vegetation parameters with hyperspectral imagery.“ Photogrammetric Engineering and Remote Sensing, Nr. 73 (8): 905–912.
- Pebesma, EJ, de Jong, K, und Briggs, D. . „Interactive visualization of uncertain spatial and spatio-temporal data under different scenarios: An air quality example.“ International Journal of Geographical Information Science, Nr. 21 (5): 515–527. doi: 10.1080/13658810601064009.
- Pebesma, EJ, Switzer, P, und Loague, K. . „Error analysis for the evaluation of model performance: Rainfall-runoff event summary variables.“ Hydrological Processes, Nr. 21 (22): 3009–3024. doi: 10.1002/hyp.6529.
- Schuurmans, JM, Bierkens, MFP, Pebesma, EJ, und Uijlenhoet, R. . „Automatic prediction of high-resolution daily rainfall fields for multiple extents: The potential of operational radar.“ Journal of Hydrometeorology, Nr. 8 (6): 1204–1224. doi: 10.1175/2007JHM792.1.
- Dubois, G, Pebesma, EJ, und Bossew, P. . „Automatic mapping in emergency: A geostatistical perspective.“ International Journal of Emergency Management, Nr. 4 (3): 455–467. doi: 10.1504/IJEM.2007.014297.
- EJ, Pebesma. . „The role of external variables and GIS databases in geostatistical analysis.“ Transactions in GIS, Nr. 10 (4): 615–632. doi: 10.1111/j.1467-9671.2006.01015.x.
- Pebesma, E., Karssenberg, D., und De Jong, K. . „Dynamic visualisation of spatial and spatio-temporal probability distribution functions.“ In Bd. null aus International Symposium on Spatial Accuracy Assessment in Natural Resources and Environmental Sciences N/A: Selbstverlag / Eigenverlag.
- Pebesma, EJ, Duin, RNM, und Burrough, PA. . „Mapping sea bird densities over the North Sea: Spatially aggregated estimates and temporal changes.“ Environmetrics, Nr. 16 (6): 573–587. doi: 10.1002/env.723.
- EJ, Pebesma. . „Mapping radioactivity from monitoring data: Automating the classical geostatistical approach.“ Applied GIS, Nr. 1 (2)
- Pebesma, EJ, Switzer, P, und Loague, K. . „Error analysis for the evaluation of model performance: Rainfall-runoff event time series data.“ Hydrological Processes, Nr. 19 (8): 1529–1548. doi: 10.1002/hyp.5587.
- EJ, Pebesma. . „Multivariable geostatistics in S: The gstat package.“ Computers and Geosciences, Nr. 30 (7): 683–691. doi: 10.1016/j.cageo.2004.03.012.
- Pfeffer, K, Pebesma, EJ, und Burrough, PA. . „Mapping alpine vegetation using vegetation observations and topographic attributes.“ Landscape Ecology, Nr. 18 (8): 759–776. doi: 10.1023/B:LAND.0000014471.78787.d0.
- De Jong, SM, Pebesma, EJ, und Lacaze, B. . „Above-ground biomass assessment of Mediterranean forests using airborne imaging spectrometry: The DAIS Peyne experiment.“ International Journal of Remote Sensing, Nr. 24 (7): 1505–1520.
- Van Horssen, PW, Pebesma, EJ, und Schot, PP. . „Uncertainties in spatially aggregated predictions from a logistic regression model.“ Ecological Modelling, Nr. 154 (1-2): 93–101.
- Kros, J, Mol-Dijkstra, JP, und Pebesma, EJ. . „Assessment of the prediction error in a large-scale application of a dynamic soil acidification model.“ Stochastic Environmental Research and Risk Assessment, Nr. 16 (4): 279–306.
- De Wit, MJM, und Pebesma, EJ. . „Nutrient fluxes at the river basin scale. II: The balance between data availability and model complexity.“ Hydrological Processes, Nr. 15 (5): 761–775.
- Thorsen, M, Refsgaard, J, Hansen, S, Pebesma, E, Jensen, J, und Kleeschulte, S. . „Assessment of uncertainty in simulation of nitrate leaching to aquifers at catchment scale.“ Journal of Hydrology, Nr. 242 (3–4): 210–227. doi: 10.1016/S0022-1694(00)00396-6.
- Heuvelink, GBM, Musters, P, und Pebesma, EJ. . „Spatio-temporal kriging of soil water content.“ Geostatistics Wollongong 96 - Proceedings of the Fifth International Geostatistics Congress, Wollongong, Australia, September 1996: 1020–1030.
- Heuvelink, GBM, und Pebesma, EJ. . „Spatial aggregation and soil process modelling.“ Geoderma, Nr. 89 (1-2): 47–65. doi: 10.1016/S0016-7061(98)00077-9.
- Pebesma, EJ, und Heuvelink, GBM. . „Latin hypercube sampling of Gaussian random fields.“ Technometrics, Nr. 41 (4): 303–312. doi: 10.1080/00401706.1999.10485930.
- Kros, J, Pebesma, EJ, Reinds, GJ, und Finke, PA. . „Uncertainty assessment in modelling soil acidification at the European scale: A case study.“ Journal of Environmental Quality, Nr. 28 (2): 366–377. doi: 10.2134/jeq1999.00472425002800020002x.
- Finke, PA, Wladis, D, Kros, J, Pebesma, EJ, und Reinds, GJ. . „Quantification and simulation of errors in categorical data for uncertainty analysis of soil acidification modelling.“ Geoderma, Nr. 93 (3-4): 177–194. doi: 10.1016/S0016-7061(99)00056-7.
- Pebesma, EJ, und Wesseling, CG. . „Gstat: A program for geostatistical modelling, prediction and simulation.“ Computers and Geosciences, Nr. 24 (1): 17–31. doi: 10.1016/S0098-3004(97)00082-4.
- Pebesma, EJ, und de Kwaadsteniet, J. . „Mapping groundwater quality in the Netherlands.“ Journal of Hydrology, Nr. 200 (1–4): 364–386. doi: 10.1016/S0022-1694(97)00027-9.