The application of ResU-net and OBIA for landslide detection from multi-temporal sentinel-2 images-Reference-Cited by-同舟云学术

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The application of ResU-net and OBIA for landslide detection from multi-temporal sentinel-2 images

Published:2022-02-14 Issue: Volume: Page:1-26
ISSN:2096-4471
Container-title:Big Earth Data
language:en
Short-container-title:Big Earth Data

Author:

Ghorbanzadeh Omid¹^ORCID,Gholamnia Khalil²^ORCID,Ghamisi Pedram¹³^ORCID

Affiliation:

1. Institute of Advanced Research in Artificial Intelligence (IARAI), Vienna, Austria

2. Department of Remote Sensing and GIS, University of Tabriz, Tabriz, Iran

3. Machine Learning Group, Helmholtz-Zentrum Dresden-Rossendorf, Helmholtz Institute Freiberg for Resource Technology, Freiberg, Germany

Funder

Institute of Advanced Research in Artificial Intelligence (IARAI) GmbH

Publisher

Informa UK Limited

Subject

Computers in Earth Sciences,Computer Science Applications

Link

https://www.tandfonline.com/doi/pdf/10.1080/20964471.2022.2031544

Reference55 articles.

1. Earthquake-Induced Landslide Mapping for the 2018 Hokkaido Eastern Iburi Earthquake Using PALSAR-2 Data

2. Progressing from object-based to object-oriented image analysis

3. Transferability of object-based image analysis approaches for landslide detection in the Himalaya Mountains of northern Pakistan

4. Multi-resolution, object-oriented fuzzy analysis of remote sensing data for GIS-ready information

5. Geographic Object-Based Image Analysis – Towards a new paradigm

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2. Utilizing multitemporal indices and spectral bands of Sentinel-2 to enhance land use and land cover classification with random forest and support vector machine;Advances in Space Research;2024-08

3. Assessing Many Image Processing Products Retrieved from Sentinel-2 Data to Monitor Shallow Landslides in Agricultural Environments;Remote Sensing;2024-06-22

4. EMR-HRNet: A Multi-Scale Feature Fusion Network for Landslide Segmentation from Remote Sensing Images;Sensors;2024-06-06

5. D2Former: Dual-Domain Transformer for Change Detection in VHR Remote Sensing Images;Electronics;2024-06-05

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