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Journal Articles
- 2024
[j13]Nafiseh Kakhani
, Setareh Alamdar, Ndiye Michael Kebonye, Meisam Amani, Thomas Scholten:
Uncertainty Quantification of Soil Organic Carbon Estimation from Remote Sensing Data with Conformal Prediction. Remote. Sens. 16(3): 438 (2024)- [j12]Hadi Shokati, Mahmoud Mashal, Aliakbar Noroozi, Ali Akbar Abkar, Saham Mirzaei, Zahra Mohammadi-Doqozloo, Ruhollah Taghizadeh-Mehrjardi, Pegah Khosravani, Kamal Nabiollahi, Thomas Scholten:
Random Forest-Based Soil Moisture Estimation Using Sentinel-2, Landsat-8/9, and UAV-Based Hyperspectral Data. Remote. Sens. 16(11): 1962 (2024) - [j11]Kamal Nabiollahi, Ndiye M. Kebonye, Fereshteh Molani, Mohammad Hossein Tahari-Mehrjardi, Ruhollah Taghizadeh-Mehrjardi, Hadi Shokati, Thomas Scholten:
Assessment of Land Suitability Potential Using Ensemble Approaches of Advanced Multi-Criteria Decision Models and Machine Learning for Wheat Cultivation. Remote. Sens. 16(14): 2566 (2024) - [j10]Nafiseh Kakhani, Moien Rangzan, Ali Jamali, Sara Attarchi, Seyed Kazem Alavipanah, Michael Mommert, Nikolaos Tziolas, Thomas Scholten:
SSL-SoilNet: A Hybrid Transformer-Based Framework With Self-Supervised Learning for Large-Scale Soil Organic Carbon Prediction. IEEE Trans. Geosci. Remote. Sens. 62: 1-15 (2024) - 2023
- [j9]Tom Broeg, Michael Blaschek, Steffen Seitz, Ruhollah Taghizadeh-Mehrjardi, Simone Zepp, Thomas Scholten:
Transferability of Covariates to Predict Soil Organic Carbon in Cropland Soils. Remote. Sens. 15(4): 876 (2023) - 2022
- [j8]Ruhollah Taghizadeh-Mehrjardi, Hossein Khademi, Fatemeh Khayamim, Mojtaba Zeraatpisheh, Brandon Heung, Thomas Scholten:
A Comparison of Model Averaging Techniques to Predict the Spatial Distribution of Soil Properties. Remote. Sens. 14(3): 472 (2022) - [j7]Mona Morsy, Silas C. Michaelides, Thomas Scholten, Peter Dietrich:
Monitoring and Integrating the Changes in Vegetated Areas with the Rate of Groundwater Use in Arid Regions. Remote. Sens. 14(22): 5767 (2022) - 2021
- [j6]Mona Morsy, Thomas Scholten, Silas C. Michaelides, Erik Borg, Youssef Sherief, Peter Dietrich:
Comparative Analysis of TMPA and IMERG Precipitation Datasets in the Arid Environment of El-Qaa Plain, Sinai. Remote. Sens. 13(4): 588 (2021) - [j5]Ruhollah Taghizadeh-Mehrjardi, Mostafa Emadi, Ali Cherati, Brandon Heung, Amir Mosavi, Thomas Scholten:
Bio-Inspired Hybridization of Artificial Neural Networks: An Application for Mapping the Spatial Distribution of Soil Texture Fractions. Remote. Sens. 13(5): 1025 (2021) - [j4]Ruhollah Taghizadeh-Mehrjardi, Hassan Fathizad, Mohammad Ali Hakimzadeh Ardakani, Hamid Sodaiezadeh, Ruth Kerry, Brandon Heung, Thomas Scholten:
Spatio-Temporal Analysis of Heavy Metals in Arid Soils at the Catchment Scale Using Digital Soil Assessment and a Random Forest Model. Remote. Sens. 13(9): 1698 (2021) - [j3]Mona Morsy, Ruhollah Taghizadeh-Mehrjardi, Silas C. Michaelides, Thomas Scholten, Peter Dietrich, Karsten Schmidt:
Optimization of Rain Gauge Networks for Arid Regions Based on Remote Sensing Data. Remote. Sens. 13(21): 4243 (2021) - 2020
- [j2]Ruhollah Taghizadeh-Mehrjardi, Karsten Schmidt, Alireza Amirian-Chakan, Tobias Rentschler, Mojtaba Zeraatpisheh, Fereydoon Sarmadian, Roozbeh Valavi, Naser Davatgar, Thorsten Behrens, Thomas Scholten:
Improving the Spatial Prediction of Soil Organic Carbon Content in Two Contrasting Climatic Regions by Stacking Machine Learning Models and Rescanning Covariate Space. Remote. Sens. 12(7): 1095 (2020) - [j1]Mostafa Emadi, Ruhollah Taghizadeh-Mehrjardi, Ali Cherati, Majid Danesh, Amir Mosavi, Thomas Scholten:
Predicting and Mapping of Soil Organic Carbon Using Machine Learning Algorithms in Northern Iran. Remote. Sens. 12(14): 2234 (2020)
Conference and Workshop Papers
- 2024
- [c4]Nafiseh Kakhani, Michael Mommert, Thomas Scholten:
Advanced Prediction of Soil Organic Carbon: A Hybrid Transformer Network with Cost-Sensitive Learning Using Remote Sensing and Climate Data. IGARSS 2024: 1594-1598 - 2021
- [c3]Matthias Karlbauer, Tobias Menge, Sebastian Otte, Hendrik P. A. Lensch, Thomas Scholten, Volker Wulfmeyer, Martin V. Butz:
Latent State Inference in a Spatiotemporal Generative Model. ICANN (4) 2021: 384-395 - 2020
- [c2]Matthias Karlbauer, Sebastian Otte, Hendrik P. A. Lensch, Thomas Scholten, Volker Wulfmeyer, Martin V. Butz:
A Distributed Neural Network Architecture for Robust Non-Linear Spatio-Temporal Prediction. ESANN 2020: 303-308 - [c1]Matthias Karlbauer, Sebastian Otte, Hendrik P. A. Lensch, Thomas Scholten, Volker Wulfmeyer, Martin V. Butz:
Inferring, Predicting, and Denoising Causal Wave Dynamics. ICANN (1) 2020: 566-577
Informal and Other Publications
- 2023
- [i6]Jannik Thümmel, Matthias Karlbauer, Sebastian Otte, Christiane Zarfl, Georg Martius, Nicole Ludwig, Thomas Scholten, Ulrich Friedrich, Volker Wulfmeyer, Bedartha Goswami, Martin V. Butz:
Inductive biases in deep learning models for weather prediction. CoRR abs/2304.04664 (2023) - [i5]Nafiseh Kakhani, Moien Rangzan, Ali Jamali, Sara Attarchi, Seyed Kazem Alavipanah, Thomas Scholten:
SoilNet: An Attention-based Spatio-temporal Deep Learning Framework for Soil Organic Carbon Prediction with Digital Soil Mapping in Europe. CoRR abs/2308.03586 (2023) - 2020
- [i4]Mostafa Emadi, Ruhollah Taghizadeh-Mehrjardi, Ali Cherati, Majid Danesh, Amir Mosavi, Thomas Scholten:
Predicting and Mapping of Soil Organic Carbon Using Machine Learning Algorithms in Northern Iran. CoRR abs/2007.12475 (2020) - [i3]Matthias Karlbauer, Sebastian Otte, Hendrik P. A. Lensch, Thomas Scholten, Volker Wulfmeyer, Martin V. Butz:
Inferring, Predicting, and Denoising Causal Wave Dynamics. CoRR abs/2009.09187 (2020) - [i2]Matthias Karlbauer, Tobias Menge, Sebastian Otte, Hendrik P. A. Lensch, Thomas Scholten, Volker Wulfmeyer, Martin V. Butz:
Hidden Latent State Inference in a Spatio-Temporal Generative Model. CoRR abs/2009.09823 (2020) - 2019
- [i1]Matthias Karlbauer, Sebastian Otte, Hendrik P. A. Lensch, Thomas Scholten, Volker Wulfmeyer, Martin V. Butz:
A Distributed Neural Network Architecture for Robust Non-Linear Spatio-Temporal Prediction. CoRR abs/1912.11141 (2019)
Coauthor Index
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