| Vol-3207 urn:nbn:de:0074-3207-7 Copyright © 2022 for the individual papers by the papers' authors. Copyright © 2022 for the volume as a collection by its editors. This volume and its papers are published under the Creative Commons License Attribution 4.0 International (CC BY 4.0).

# CDCEO 2022
Complex Data Challenges in Earth Observation 2022

### Proceedings of the Second Workshop on Complex Data Challenges in Earth Observation (CDCEO 2022)
co-located with 31st International Joint Conference on Artificial Intelligence and the 25th European Conference on Artificial Intelligence (IJCAI-ECAI 2022)

### Vienna, Austria, July 25th, 2022.

Edited by

### Aleksandra Gruca1
Caleb Robinson2
Naoto Yokoya3, 4
Jun Zhou5
Pedram Ghamisi6, 7

1 Silesian University of Technology, Poland
2 Microsoft AI for Good Research Lab, USA
3 University of Tokyo, Japan
4 RIKEN Center for Advanced Intelligence Project, Japan
5 Griffith University, Australia
6 Institute of Advanced Research in Artificial Intelligence, Austria
7 Helmholtz-Zentrum Dresden-Rossendorf, Germany

## Table of Contents

- Preface
  i-iv

### Regular Track

- A Center-Masked Convolutional Transformer for Hyperspectral Image Classification 1-6
  Yifan Wang, Shuguo Jiang, Meng Xu, Shuyu Zhang, Sen Jia
- A Deep Feature Retrieved Network for Bitemporal Remote Sensing Image Change Detection 7-13
  Shizhen Chang, Michael Kopp, Pedram Ghamisi
- "Disaster Detection from SAR Images with Different Off-Nadir Angles Using Unsupervised Image Translation 14-20
  Jian Song, Bruno Adriano, Naoto Yokoya
- Knowledge-Aware Cross-Modal Text-Image Retrieval for Remote Sensing Images 21-26
  Li Mi, Siran Li, Christel Chappuis, Devis Tuia
- Mapping Slums with Deep Learning Feature Extraction 27-32
  Agatha Mattos, Michela Bertolotto, Gavin McArdle
- METER-ML: A Multi-Sensor Earth Observation Benchmark for Automated Methane Source Mapping 33-43
  Bryan Zhu, Nicholas Lui, Jeremy Irvin, Jimmy Le, Sahil Tadwalkar, Chenghao Wang, Zutao Ouyang, Frankie Y. Liu, Andrew Y. Ng, Robert B. Jackson
- Model-Centric vs Data-Centric Deep Learning Approaches for Landslide Detection 44-49
  Hejar Shahabi, Omid Ghorbanzadeh
- Multimodal Crop Type Classification Fusing Multi-Spectral Satellite Time Series with Farmers Crop Rotations and Local Crop Distribution 50-57
  Valentin Barriere, Martin Claverie
- Predicting Flood Inundation Depth Based-on Machine Learning and Numerical Simulation 58-64
  Bruno Adriano, Naoto Yokoya, Satoru Oishi
- Radar-Based Volumetric Precipitation Nowcasting: A 3D Convolutional Neural Network with U-Net Architecture 65-72
  Peter Pavlík, Viera Rozinajová, Anna Bou Ezzeddine
- Task-Guided Denoising Network for Adversarial Defense of Remote Sensing Scene Classification 73-78
  Yonghao Xu, Weikang Yu, Pedram Ghamisi
- Weak-Supervision Based on Label Proportions for Earth Observation Applications from Optical and Hyperspectral Imagery 79-85
  Laura E. Cué La Rosa, Dário A. Borges Oliveira, Sam Thiele, Pedram Ghamisi, Richard Gloaguen

### Landslide4Sense Track

- The Landslide4Sense Competition 2022 86-87
  Pedram Ghamisi, Omid Ghorbanzadeh, Yonghao Xu, Pedro Herruzo, David Kreil, Michael Kopp, Sepp Hochreiter
- Progressive Label Refinement-Based Distribution Adaptation Framework for Landslide Detection 88-91
  Hengwei Zhao, Junjue Wang, Yang Pan, Ailong Ma, Xinyu Wang, Yanfei Zhong
- SwinLS: Adapting Swin Transformer to Landslide Detection 92-96
  Dong Zhao, Qi Zang, Zining Wang, Dou Quan, Shuang Wang
- On the Generalization of the Semantic Segmentation Model for Landslide Detection 97-101
  Fahong Zhang, Yilei Shi, Qingsong Xu, Zhitong Xiong, Wei Yao, Xiao Xiang Zhu
- Multispectral U-Net: A Semantic Segmentation Model Using Multispectral Bands Fusion Mechanism for Landslide Detection 102-105
  Lin Bai, Weile Li, Qiang Xu, Weihang Peng, Kai Chen, Zhenzhen Duan, Huiyan Lu

2022-08-23: submitted by Aleksandra Gruca, metadata incl. bibliographic data published under Creative Commons CC0
2022-09-07: published on CEUR Workshop Proceedings (CEUR-WS.org, ISSN 1613-0073) |valid HTML5|