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Root system estimation based on satellite remote sensing : An applied study in Eastern Uganda

Pilesjö, Petter LU ; Ahlbäck, Malin ; Ahlgren, Maya ; Ekström, Hanna LU orcid ; Hansson, Malin ; Mužić, Iris ; Rosenström, Nike and Weichert, Franziska (2018) 21st AGILE Conference on Geographic Information Science, 2018
Abstract
The density of roots is an important factor influencing the rate and magnitude of landslides. Due to the increased variability in climate, mainly rainfall, Eastern Uganda is severely struck by an increasing number of these mass movements, often with human casualties as one of the negative impacts. The aim of this study is to explore the possibility to estimate the depth and density of the root system influencing the resistance to landslides, from satellite remote sensing data. 104 samples were collected in field, where the root system was classified into 5 different classes, from non-existing to dense and deep (forest). The study was carried out in the Mount Elgon area located at the Ugandan-Kenyan border. The field data were then compared... (More)
The density of roots is an important factor influencing the rate and magnitude of landslides. Due to the increased variability in climate, mainly rainfall, Eastern Uganda is severely struck by an increasing number of these mass movements, often with human casualties as one of the negative impacts. The aim of this study is to explore the possibility to estimate the depth and density of the root system influencing the resistance to landslides, from satellite remote sensing data. 104 samples were collected in field, where the root system was classified into 5 different classes, from non-existing to dense and deep (forest). The study was carried out in the Mount Elgon area located at the Ugandan-Kenyan border. The field data were then compared with 30 m Landsat TM data, in order to investigate possible links between reflectance (single bands as well as indices) and ground truth data. The results indicate that, following this methodology, it is not possible to estimate the root system density based on the remotely sensed data, since the maximum Cohen’s kappa value of 0.081 is judged deficient. (Less)
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author
; ; ; ; ; ; and
organization
publishing date
type
Chapter in Book/Report/Conference proceeding
publication status
published
subject
keywords
Landslides, Remote sensing, Uganda, Root system density, NDVI, EVI
host publication
Geospatial Technologies for All : short papers, posters and poster abstracts of the 21th AGILE Conference on Geographic Information Science. Lund University 12-15 June 2018, Lund, Sweden - short papers, posters and poster abstracts of the 21th AGILE Conference on Geographic Information Science. Lund University 12-15 June 2018, Lund, Sweden
editor
Mansourian, Ali ; Pilesjö, Petter ; Harrie, Lars and van Lammeren, Ron
pages
5 pages
publisher
Association of Geographic Information Laboratories for Europe
conference name
21st AGILE Conference on Geographic Information Science, 2018
conference location
Lund, Sweden
conference dates
2018-06-12 - 2018-06-15
language
English
LU publication?
yes
additional info
21st AGILE Conference on Geographic Information Science, 2018 ; Conference date: 12-06-2018 Through 15-06-2018
id
069db6e0-e8da-43a1-a1a6-4d07a30a89b9
alternative location
https://agile-online.org/conference_paper/cds/agile_2018/shortpapers/Petter2_AGILE_2018_Final_Paper_Uganda.pdf
date added to LUP
2018-11-12 16:53:35
date last changed
2025-04-04 15:48:21
@inproceedings{069db6e0-e8da-43a1-a1a6-4d07a30a89b9,
  abstract     = {{The density of roots is an important factor influencing the rate and magnitude of landslides. Due to the increased variability in climate, mainly rainfall, Eastern Uganda is severely struck by an increasing number of these mass movements, often with human casualties as one of the negative impacts. The aim of this study is to explore the possibility to estimate the depth and density of the root system influencing the resistance to landslides, from satellite remote sensing data. 104 samples were collected in field, where the root system was classified into 5 different classes, from non-existing to dense and deep (forest). The study was carried out in the Mount Elgon area located at the Ugandan-Kenyan border. The field data were then compared with 30 m Landsat TM data, in order to investigate possible links between reflectance (single bands as well as indices) and ground truth data. The results indicate that, following this methodology, it is not possible to estimate the root system density based on the remotely sensed data, since the maximum Cohen’s kappa value of 0.081 is judged deficient.}},
  author       = {{Pilesjö, Petter and Ahlbäck, Malin and Ahlgren, Maya and Ekström, Hanna and Hansson, Malin and Mužić, Iris and Rosenström, Nike and Weichert, Franziska}},
  booktitle    = {{Geospatial Technologies for All : short papers, posters and poster abstracts of the 21th AGILE Conference on Geographic Information Science. Lund University 12-15 June 2018, Lund, Sweden}},
  editor       = {{Mansourian, Ali and Pilesjö, Petter and Harrie, Lars and van Lammeren, Ron}},
  keywords     = {{Landslides; Remote sensing; Uganda; Root system density; NDVI; EVI}},
  language     = {{eng}},
  month        = {{06}},
  publisher    = {{Association of Geographic Information Laboratories for Europe}},
  title        = {{Root system estimation based on satellite remote sensing : An applied study in Eastern Uganda}},
  url          = {{https://agile-online.org/conference_paper/cds/agile_2018/shortpapers/Petter2_AGILE_2018_Final_Paper_Uganda.pdf}},
  year         = {{2018}},
}