Aspects of Error Quantification and Evaluation in Digital Elevation Models for Glacier Surfaces
(2020) In Master Thesis in Geographical Information Science GISM01 20192Dept of Physical Geography and Ecosystem Science
- Abstract
- Aspects of Error Quantification and Evaluation in Digital Elevation Models for Glacier Surfaces
This study explores methods to quantify and evaluate error in digital elevation models (DEMs) built from remotely sensed elevation data of the Hintereisferner glacier. A special focus lies on glacier surfaces because glaciers are often inaccessible for field observations but at the same time prone to measurement errors. They would therefore particularly benefit from a comprehensive error assessment.
One of the primary aspects of the study is to find suitable methods that also include the spatial distribution of error because this is generally a somewhat neglected aspect of quality assessment of DEMs, although it has a potentially significant... (More) - Aspects of Error Quantification and Evaluation in Digital Elevation Models for Glacier Surfaces
This study explores methods to quantify and evaluate error in digital elevation models (DEMs) built from remotely sensed elevation data of the Hintereisferner glacier. A special focus lies on glacier surfaces because glaciers are often inaccessible for field observations but at the same time prone to measurement errors. They would therefore particularly benefit from a comprehensive error assessment.
One of the primary aspects of the study is to find suitable methods that also include the spatial distribution of error because this is generally a somewhat neglected aspect of quality assessment of DEMs, although it has a potentially significant impact on the way DEMs are used in research. Especially if geomorphological or topographical aspects are part of this. In addition to identifying and discussing methods to quantify and evaluate existing errors in DEMs, this study also looks at some of the major sources from which the errors stem to find out if the influence of these sources on the resulting errors can be estimated. To this end, two out of three major categories of error sources were selected: interpolation effects and spatial resolution effects.
The explored methods include quantitative error measures, such as RMSE, but also more evaluative approaches, such as correlation analysis. Including spatial distribution as part of the quantification and evaluation of error in DEMs is done by exploring methods like the creation of error surfaces or approaches that quantify the spatial patterning of error values in DEMs, such as Moran’s I.
The results show that when it comes to quantification and evaluation of error in DEMs, error surfaces, in combination with a mapped overview of the Local Moran’s I values, are presumably the most powerful methods to gain insight into both the absolute error values and the spatial distribution of them. Particularly spatial outlier detection is a useful part of this approach. (Less) - Popular Abstract
- Aspects of Error Quantification and Evaluation in Digital Elevation Models for Glacier Surfaces
With the introduction of satellite-based observation techniques in the second half of the 20th century, topographic analysis made a significant leap forward. Not only do the remotely sensed data enable easy digital mapping on a global or regional scale, they also offer many possibilities to analyze both global and local shape and features of the Earth’s surface, including glaciers and glacial landforms.
Remote sensing of glaciers plays a fundamental role in our understanding of their topographical characteristics, such as elevation or slope. There is, however, often a rather large variation in quality with regard to satellite-based remotely... (More) - Aspects of Error Quantification and Evaluation in Digital Elevation Models for Glacier Surfaces
With the introduction of satellite-based observation techniques in the second half of the 20th century, topographic analysis made a significant leap forward. Not only do the remotely sensed data enable easy digital mapping on a global or regional scale, they also offer many possibilities to analyze both global and local shape and features of the Earth’s surface, including glaciers and glacial landforms.
Remote sensing of glaciers plays a fundamental role in our understanding of their topographical characteristics, such as elevation or slope. There is, however, often a rather large variation in quality with regard to satellite-based remotely sensed data.
This is why this study explores methods to quantify and evaluate error in digital elevation models (DEMs) built from remotely sensed elevation data. The Hintereisferner glacier in the Austrian alps serves as study area. A special focus lies on glacier surfaces because glaciers are often inaccessible for field observations but at the same time prone to measurement errors. They would therefore particularly benefit from a comprehensive error assessment.
One of the primary aspects of the study is to find suitable methods of error quantification and evaluation that also include the spatial distribution of error because this is generally a somewhat neglected aspect of quality assessment of DEMs, although it has a potentially significant impact on the way DEMs are used in research. Especially if geomorphological or topographical aspects are part of this. In addition to identifying and discussing methods to quantify and evaluate existing errors in DEMs, this study also looks at some of the major sources from which the errors stem to find out if the influence of these sources on the resulting errors can be estimated.
The results of this study show that, when it comes to quantification and evaluation of error in DEMs, certain methods that result in a mapped overview of the absolute error values and its spatial patterning, are presumably the most powerful. Particularly spatial outlier detection is a useful part of this approach. These methods allow users of the DEM to signal weaknesses in the spatial structure of the model, which can then be corrected by checking data processing or performing additional data acquisition. (Less)
Please use this url to cite or link to this publication:
http://lup.lub.lu.se/student-papers/record/9001615
- author
- van Zoonen, Jip Jan LU
- supervisor
- organization
- course
- GISM01 20192
- year
- 2020
- type
- H2 - Master's Degree (Two Years)
- subject
- keywords
- Geography, Geographical Information Systems, GIS, Physical Geography, Digital Elevation Model, DEM, Glaciology
- publication/series
- Master Thesis in Geographical Information Science
- report number
- 112
- language
- English
- id
- 9001615
- date added to LUP
- 2020-01-17 13:03:39
- date last changed
- 2020-01-17 13:03:39
@misc{9001615,
abstract = {{Aspects of Error Quantification and Evaluation in Digital Elevation Models for Glacier Surfaces
This study explores methods to quantify and evaluate error in digital elevation models (DEMs) built from remotely sensed elevation data of the Hintereisferner glacier. A special focus lies on glacier surfaces because glaciers are often inaccessible for field observations but at the same time prone to measurement errors. They would therefore particularly benefit from a comprehensive error assessment.
One of the primary aspects of the study is to find suitable methods that also include the spatial distribution of error because this is generally a somewhat neglected aspect of quality assessment of DEMs, although it has a potentially significant impact on the way DEMs are used in research. Especially if geomorphological or topographical aspects are part of this. In addition to identifying and discussing methods to quantify and evaluate existing errors in DEMs, this study also looks at some of the major sources from which the errors stem to find out if the influence of these sources on the resulting errors can be estimated. To this end, two out of three major categories of error sources were selected: interpolation effects and spatial resolution effects.
The explored methods include quantitative error measures, such as RMSE, but also more evaluative approaches, such as correlation analysis. Including spatial distribution as part of the quantification and evaluation of error in DEMs is done by exploring methods like the creation of error surfaces or approaches that quantify the spatial patterning of error values in DEMs, such as Moran’s I.
The results show that when it comes to quantification and evaluation of error in DEMs, error surfaces, in combination with a mapped overview of the Local Moran’s I values, are presumably the most powerful methods to gain insight into both the absolute error values and the spatial distribution of them. Particularly spatial outlier detection is a useful part of this approach.}},
author = {{van Zoonen, Jip Jan}},
language = {{eng}},
note = {{Student Paper}},
series = {{Master Thesis in Geographical Information Science}},
title = {{Aspects of Error Quantification and Evaluation in Digital Elevation Models for Glacier Surfaces}},
year = {{2020}},
}