Next Article in Journal
Matching Multi-Sensor Remote Sensing Images via an Affinity Tensor
Previous Article in Journal
Vertically Resolved Precipitation Intensity Retrieved through a Synergy between the Ground-Based NASA MPLNET Lidar Network Measurements, Surface Disdrometer Datasets and an Analytical Model Solution
Previous Article in Special Issue
Soil Moisture Monitoring in a Temperate Peatland Using Multi-Sensor Remote Sensing and Linear Mixed Effects
Open AccessArticle

Long-Term Peatland Condition Assessment via Surface Motion Monitoring Using the ISBAS DInSAR Technique over the Flow Country, Scotland

1
Faculty of Engineering, University of Nottingham, Nottingham NG7 2RD, UK
2
School of Geography, University of Nottingham, Nottingham NG7 2RD, UK
3
Geomatic Ventures Ltd., Nottingham NG7 2TU, UK
4
Forest Research, Northern Research Station, Roslin, Midlothian EH25 9SY, UK
5
Environmental Research Institute, North Highland College, University of the Highlands and Islands, Inverness IV3 5SQ, UK
*
Author to whom correspondence should be addressed.
Remote Sens. 2018, 10(7), 1103; https://doi.org/10.3390/rs10071103
Received: 2 May 2018 / Revised: 28 June 2018 / Accepted: 6 July 2018 / Published: 11 July 2018
(This article belongs to the Special Issue Remote Sensing of Peatlands)
  |  
PDF [7105 KB, uploaded 20 July 2018]
  |  

Abstract

Satellite Earth Observation (EO) is often used as a cost-effective method to report on the condition of remote and inaccessible peatland areas. Current EO techniques are primarily limited to reporting on the vegetation classes and properties of the immediate peat surface using optical data, which can be used to infer peatland condition. Another useful indicator of peatland condition is that of surface motion, which has the potential to report on mass accumulation and loss of peat. Interferometic SAR (InSAR) techniques can provide this using data from space. However, the most common InSAR techniques for information extraction, such as Persistent Scatterers’ Interferometry (PSI), have seen limited application over peat as they are primarily tuned to work in areas of high coherence (i.e., on hard, non-vegetated surfaces only). A new InSAR technique, called the Intermittent Small BAseline Subset (ISBAS) method, has been recently developed to provide measurements over vegetated areas from SAR data acquired by satellite sensors. This paper examines the feasibility of the ISBAS technique for monitoring long-term surface motion over peatland areas of the Flow Country, in the northeast of Scotland. In particular, the surface motions estimated are compared with ground data over a small forested area (namely the Bad a Cheo forest Reserve). Two sets of satellite SAR data are used: ERS C-band images, covering the period 1992–2000, and Sentinel-1 C-band images, covering the period 2015–2016. We show that the ISBAS measurements are able to identify surface motion over peatland areas, where subsidence is a consequence of known land cover/land use. In particular, the ISBAS products agree with the trend of surface motion, but there are uncertainties with their magnitude and direction (vertical). It is concluded that there is a potential for the ISBAS method to be able to report on trends in subsidence and uplift over peatland areas, and this paper suggests avenues for further investigation, but this requires a well-resourced validation campaign. View Full-Text
Keywords: Interferometric SAR; peatland condition; surface motion; Flow Country; Intermittent Small BAaseline Subset (ISBAS); Sentinel-1; ERS Interferometric SAR; peatland condition; surface motion; Flow Country; Intermittent Small BAaseline Subset (ISBAS); Sentinel-1; ERS
Figures

Graphical abstract

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
SciFeed

Share & Cite This Article

MDPI and ACS Style

Alshammari, L.; Large, D.J.; Boyd, D.S.; Sowter, A.; Anderson, R.; Andersen, R.; Marsh, S. Long-Term Peatland Condition Assessment via Surface Motion Monitoring Using the ISBAS DInSAR Technique over the Flow Country, Scotland. Remote Sens. 2018, 10, 1103.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Related Articles

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
Remote Sens. EISSN 2072-4292 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top