Call number:
AWI G3-22-94687
Description / Table of Contents:
Permafrost is warming globally, which leads to widespread permafrost thaw and impacts the surrounding landscapes, ecosystems and infrastructure. Especially ice-rich permafrost is vulnerable to rapid and abrupt thaw, resulting from the melting of excess ground ice. Local remote sensing studies have detected increasing rates of abrupt permafrost disturbances, such as thermokarst lake change and drainage, coastal erosion and RTS in the last two decades. All of which indicate an acceleration of permafrost degradation. In particular retrogressive thaw slumps (RTS) are abrupt disturbances that expand by up to several meters each year and impact local and regional topographic gradients, hydrological pathways, sediment and nutrient mobilisation into aquatic systems, and increased permafrost carbon mobilisation. The feedback between abrupt permafrost thaw and the carbon cycle is a crucial component of the Earth system and a relevant driver in global climate models. However, an assessment of RTS at high temporal resolution to determine the ...
Type of Medium:
Dissertations
Pages:
xxiv, 134 Seiten
,
Illustrationen, Diagramme, Karten
URL:
https://nbn-resolving.org/urn:nbn:de:kobv:517-opus4-522062
URL:
https://doi.org/10.25932/publishup-52206
URL:
https://d-nb.info/1244920126/34
URL:
https://publishup.uni-potsdam.de/frontdoor/index/index/docId/52206
URN:
urn:nbn:de:kobv:517-opus4-522062
DOI:
10.25932/publishup-52206
Language:
English
Note:
Dissertation, Universität Potsdam, 2021
,
Table of Contents
Abstract
Zusammenfassung
List of Figures
List of Tables
Abbreviations
1 Introduction
1.1 Scientific background and motivation
1.1.1 Permafrost and climate change
1.1.2 Permafrost thaw and disturbances
1.1.3 Abrupt permafrost disturbances
1.1.4 Remote sensing
1.1.5 Remote sensing of permafrost disturbances
1.2 Aims and objectives
1.3 Study area
1.4 General data and methods
1.4.1 Landsat and Sentinel-2
1.4.2 Google Earth Engine
1.5 Thesis structure
1.6 Overview of publications and authors’ contribution
1.6.1 Chapter 2 - Comparing Spectral Characteristics of Landsat-8 and Sentinel-2 Same-Day Data for Arctic-Boreal Regions
1.6.2 Chapter 3 - Mosaicking Landsat and Sentinel-2 Data to Enhance LandTrendr Time Series Analysis in Northern High Latitude Permafrost Regions
1.6.3 Chapter 4 - Remote Sensing Annual Dynamics of Rapid Permafrost Thaw Disturbances with LandTrendr
2 Comparing Spectral Characteristics of Landsat-8 and Sentinel-2 Same-Day Data for Arctic-Boreal Regions
2.1 Abstract
2.2 Introduction
2.3 Materials and Methods
2.3.1 Study Sites
2.3.2 Data
2.3.3 Data Processing
2.3.3.1 Filtering Image Collections
2.3.3.2 Creating L8, S2, and Site Masks
2.3.3.3 Preparing Sentinel-2 Surface Reflectance Images in SNAP
2.3.3.4 Applying Site Masks
2.3.4 Spectral Band Comparison and Adjustment
2.4 Results
2.4.1 Spectral Band Comparison
2.4.2 Spectral Band Adjustment
2.4.3 ES and HLS Spectral Band Adjustment
2.5 Discussion
2.6 Conclusions
2.7 Acknowledgements
2.8 Appendix Chapter 2
3 Mosaicking Landsat and Sentinel-2 Data to Enhance LandTrendr Time Series Analysis in Northern High Latitude Permafrost Regions
3.1 Abstract
3.2 Introduction
3.3 Materials and Methods
3.3.1 Study Sites
3.3.2 Data
3.3.3 Data Processing and Mosaicking Workflow
3.3.4 Data Availability Assessment
3.3.5 Mosaic Coverage and Quality Assessment
3.4 Results
3.4.1 Data Availability Assessment
3.4.2 Mosaic Coverage and Quality Assessment
3.5 Discussion
3.6 Conclusions
4 Remote Sensing Annual Dynamics of Rapid Permafrost Thaw Disturbances with LandTrendr
4.1 Abstract
4.2 Introduction
4.3 Study Area and Methods
4.3.1 Study area
4.3.2 General workflow and ground truth data
4.3.3 Data and LandTrendr
4.3.4 Index selection
4.3.5 Temporal Segmentation
4.3.6 Spectral Filtering
4.3.7 Spatial masking and filtering
4.3.8 Machine-learning object filter
4.4 Results
4.4.1 Focus sites
4.4.2 North Siberia
4.5 Discussion
4.5.1 Mapping of RTS
4.5.2 Spatio-temporal variability of RTS dynamics
4.5.3 LT-LS2 capabilities and limitations
4.6 Conclusion
4.7 Appendix
5 Synthesis and Discussion
5.1 Google Earth Engine
5.2 Landsat and Sentinel-2
5.3 Image mosaics and disturbance detection algorithm
5.4 Mapping RTS and their annual temporal dynamics
5.5 Limitations and technical considerations
5.6 Key findings
5.7 Outlook
References
Acknowledgements
Location:
AWI Reading room
Branch Library:
AWI Library
