| dtwsat: Time-weighted dynamic time warping for satellite image time series analysis in r V Maus, G Câmara, M Appel, E Pebesma Journal of Statistical Software 88, 1-31, 2019 | 95 | 2019 |
| On-demand processing of data cubes from satellite image collections with the gdalcubes library M Appel, E Pebesma Data 4 (3), 92, 2019 | 65 | 2019 |
| Open and scalable analytics of large Earth observation datasets: From scenes to multidimensional arrays using SciDB and GDAL M Appel, F Lahn, W Buytaert, E Pebesma ISPRS journal of photogrammetry and remote sensing 138, 47-56, 2018 | 55 | 2018 |
| Spatial interpolation in massively parallel computing environments K Henneböhl, M Appel, E Pebesma Proc. of the 14th AGILE International Conference on Geographic Information …, 2011 | 36 | 2011 |
| Multidimensional arrays for analysing geoscientific data M Lu, M Appel, E Pebesma ISPRS International Journal of Geo-Information 7 (8), 313, 2018 | 20 | 2018 |
| Combining automatic and manual image analysis in a web-mapping application for collaborative conflict damage assessment C Knoth, S Slimani, M Appel, E Pebesma Applied Geography 97, 25-34, 2018 | 18 | 2018 |
| Spatiotemporal multi-resolution approximations for analyzing global environmental data M Appel, E Pebesma Spatial Statistics 38, 100465, 2020 | 11 | 2020 |
| Scalable earth-observation analytics for geoscientists: Spacetime extensions to the array database SciDB M Appel, F Lahn, E Pebesma, W Buytaert, S Moulds EGU General Assembly Conference Abstracts, EPSC2016-11780, 2016 | 9 | 2016 |
| Time-Weighted Dynamic Time Warping for satellite image time series analysis (Software) V Maus, M Appel, T Giorgino v. 0.2. 2, 2017 | 7 | 2017 |
| On-demand processing of data cubes from satellite image collections with the gdalcubes library. Data 4 (3), 92 M Appel, E Pebesma | 6 | 2019 |
| openEO: an open API for cloud-based big Earth Observation processing platforms E Pebesma, W Wagner, P Soille, M Kadunc, N Gorelick, M Schramm, ... EGU General Assembly Conference Abstracts, 4957, 2018 | 6 | 2018 |
| Efficient data-driven gap filling of satellite image time series using deep neural networks with partial convolutions M Appel Artificial Intelligence for the Earth Systems 3 (2), 220055, 2024 | 4 | 2024 |
| SCIDB based framework for storage and analysis of remote sensing big data A Joshi, E Pebesma, R Henriques, M Appel The International Archives of the Photogrammetry, Remote Sensing and Spatial …, 2019 | 4 | 2019 |
| OpenEOcubes: an open-source and lightweight R-based RESTful web service for analyzing earth observation data cubes B Pondi, M Appel, E Pebesma Earth Science Informatics 17 (2), 1809-1818, 2024 | 2 | 2024 |
| Scalable Earth Observation analytics with SciDB M Appel, E Pebesma Retrieved September, 2016 | 2 | 2016 |
| bfast D Masiliūnas, J Verbesselt, A Zeileis, M Appel | | 2021 |
| bfast D Masiliunas, J Verbesselt, A Zeileis, M Appel, R Hyndman, M Jung, ... | | 2021 |
| Implementation of geostatistical models for large spatiotemporal datasets using multi-resolution approximations M Appel, E Pebesma EGU General Assembly Conference Abstracts, EGU21-6585, 2021 | | 2021 |
| Package ‘dtwSat’ V Maus, M Appel, N Kuschnig, T Giorgino, MV Maus | | 2020 |
| Facilitating Statistical Analysis of Large Satellite-based Earth Observation Data M Appel Westfälische Wilhelms-Universität Münster, 2020 | | 2020 |
Edzer PebesmaProfessor of geoinformatics, University of MuensterEmail yang diverifikasi di uni-muenster.de