Document Type
Data
Publication Date
9-7-2023
Abstract
Natural disasters pose significant threats to the environment and make land
unsuitable for man. The lava from volcanic eruptions rapidly moves on the
earth surface and affect both natural and man-made features on the earth.
Remote sensing is relevant in extracting information about the areas
affected by lava flows without physically visiting such areas. The
objective of this study is to develop a workflow for determining the
optimal ground sample distance of a digital elevation model to delineate
the lava flow paths using object-based image analysis and geomorphologic
analysis. For the experiment, the satellite images and digital elevation
model of Afar region of Ethiopia was used. The satellite images of the
affected areas were downloaded and segmented using large-scale mean shift
image segmentation algorithm in the Orfeo Toolbox to find the lava objects.
The center line of the lava object from the 2008 ASTER image and the flow
paths from the digital elevation model with varying ground sample distance
were used to find the optimal ground sample distance. The result was
further verified using the Landsat 8 images of the area affected by
volcanic eruption in 2017. In the result, the optimal resolution for
delineating lava flow in the area was found to be 71m with an average
difference of 241.9m. The study showed the successful application of remote
sensing and open-source software to find the optimal ground sample distance
of a DEM to predict lava flow paths. This research can serve as a workflow
for researchers and scientists to make plans for responding to volcanic
eruptions.
Recommended Citation
Ayo, O.,
&
Kim, J.
(2023).
The prediction of lava flow path using remote sensing techniques and geomorphological analysis: the case of volcano eruptions in Afar region of Ethiopia.
Retrieved from: https://digitalcommons.mtu.edu/all-datasets/50
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