SBAS-InSAR analysis for deformation monitoring in landslide-prone areas: A case study of Murang’a and Nyeri Counties in Kenya
Mass movement events impact thousands globally, causing loss of life, displacement of people and destruction of farmland and infrastructure, among other devastating impacts. This study focuses on monitoring land deformation over two landslide prone counties in Kenya (Murang’a and Nyeri). Interferom...
Saved in:
| Main Authors: | , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Society of Land Measurements and Cadastre from Transylvania (SMTCT)
2025-07-01
|
| Series: | Nova Geodesia |
| Subjects: | |
| Online Access: | https://novageodesia.ro/index.php/ng/article/view/423 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Summary: | Mass movement events impact thousands globally, causing loss of life, displacement of people and destruction of farmland and infrastructure, among other devastating impacts. This study focuses on monitoring land deformation over two landslide prone counties in Kenya (Murang’a and Nyeri). Interferometric Synthetic Aperture RADAR (InSAR) technique is applied on RADAR datasets acquired by the Advanced Land Observing Satellite (ALOS) and Sentinel-1 satellite. Sentinel-1 RADAR images (ascending and descending tracks) and ALOS PALSAR imagery are analysed using the Small BAseline Subset (SBAS) method. The study processes 24, 60, and 72 interferograms for ALOS PALSAR, Sentinel-1 ascending, and Sentinel-1 descending nodes, respectively. The deformation time series spans July 2007 to July 2010 (ALOS PALSAR), October 2016–November 2021 (Sentinel-1 ascending), and January 2015–November 2021 (Sentinel-1 descending). Findings reveal an annual mean land deformation trend, with subsidence to the North and uplift to the South of the study area. Sentinel data shows uplift rates of up to 210 mm/yr and subsidence rates of up to −201 mm/yr, while ALOS PALSAR data records uplift of up to 101 mm/yr and subsidence of up to −716 mm/yr. Correlation analysis reveals that elevation has the strongest influence on deformation, followed by surface roughness, slope, and aspect, in that order. These findings provide valuable insights for landslide risk assessment and mitigation strategies.
|
|---|---|
| ISSN: | 2810-2754 |