Uncertainties of Human Perception in Visual Image Interpretation in Complex Urban Environments
Today satellite images are mostly exploited automatically due to advances in image classification methods. Manual visual image interpretation (MVII), however, still plays a significant role e.g., to generate training data for machine-learning algorithms or for validation purposes. In certain urban e...
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doaj-7785305f2f6a4255a2a202b9567b6e062021-06-03T23:06:30ZengIEEEIEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing2151-15352020-01-01134229424110.1109/JSTARS.2020.30115439146616Uncertainties of Human Perception in Visual Image Interpretation in Complex Urban EnvironmentsNicolas Johannes Kraff0https://orcid.org/0000-0002-4375-2590Michael Wurm1https://orcid.org/0000-0001-5967-1894Hannes Taubenbock2https://orcid.org/0000-0003-4360-9126Department of Geo-Risks and Civil Security, German Aerospace Center, Earth Observation Center, German Remote Sensing Data Center, Oberpfaffenhofen, GermanyDepartment of Geo-Risks and Civil Security, German Aerospace Center, Earth Observation Center, German Remote Sensing Data Center, Oberpfaffenhofen, GermanyDepartment of Geo-Risks and Civil Security, German Aerospace Center, Earth Observation Center, German Remote Sensing Data Center, Oberpfaffenhofen, GermanyToday satellite images are mostly exploited automatically due to advances in image classification methods. Manual visual image interpretation (MVII), however, still plays a significant role e.g., to generate training data for machine-learning algorithms or for validation purposes. In certain urban environments, however, of e.g., highest densities and structural complexity, textural and spectral complications in overlapping roof-structures still demand the human interpreter if one aims to capture individual building structures. The cognitive perception and real-world experience are still inevitable. Against these backgrounds, this article aims at quantifying and interpreting the uncertainties of mapping rooftop footprints of such areas. We focus on the agreement among interpreters and which aspects of perception and elements of image interpretation affect mapping. Ten test persons digitized six complex built-up areas. Hereby, we receive quantitative information about spatial variables of buildings to systematically check the consistency and congruence of results. An additional questionnaire reveals qualitative information about obstacles. Generally, we find large differences among interpreters' mapping results and a high consistency of results for the same interpreter. We measure rising deviations correlate with a rising morphologic complexity. High degrees of individuality are expressed e.g., in time consumption, in-situ- or geographic information system (GIS)-precognition whereas data source mostly influences the mapping procedure. By this study, we aim to fill a gap as prior research using MVII often does not implement an uncertainty analysis or quantify mapping aberrations. We conclude that remote sensing studies should not only rely unquestioned on MVII for validation; furthermore, data and methods are needed to suspend uncertainty.https://ieeexplore.ieee.org/document/9146616/Cognitionearth observationelements of image interpretationlevel of individual buildings (LoD-1)manual visual image interpretation (MVII)perception |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Nicolas Johannes Kraff Michael Wurm Hannes Taubenbock |
spellingShingle |
Nicolas Johannes Kraff Michael Wurm Hannes Taubenbock Uncertainties of Human Perception in Visual Image Interpretation in Complex Urban Environments IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing Cognition earth observation elements of image interpretation level of individual buildings (LoD-1) manual visual image interpretation (MVII) perception |
author_facet |
Nicolas Johannes Kraff Michael Wurm Hannes Taubenbock |
author_sort |
Nicolas Johannes Kraff |
title |
Uncertainties of Human Perception in Visual Image Interpretation in Complex Urban Environments |
title_short |
Uncertainties of Human Perception in Visual Image Interpretation in Complex Urban Environments |
title_full |
Uncertainties of Human Perception in Visual Image Interpretation in Complex Urban Environments |
title_fullStr |
Uncertainties of Human Perception in Visual Image Interpretation in Complex Urban Environments |
title_full_unstemmed |
Uncertainties of Human Perception in Visual Image Interpretation in Complex Urban Environments |
title_sort |
uncertainties of human perception in visual image interpretation in complex urban environments |
publisher |
IEEE |
series |
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing |
issn |
2151-1535 |
publishDate |
2020-01-01 |
description |
Today satellite images are mostly exploited automatically due to advances in image classification methods. Manual visual image interpretation (MVII), however, still plays a significant role e.g., to generate training data for machine-learning algorithms or for validation purposes. In certain urban environments, however, of e.g., highest densities and structural complexity, textural and spectral complications in overlapping roof-structures still demand the human interpreter if one aims to capture individual building structures. The cognitive perception and real-world experience are still inevitable. Against these backgrounds, this article aims at quantifying and interpreting the uncertainties of mapping rooftop footprints of such areas. We focus on the agreement among interpreters and which aspects of perception and elements of image interpretation affect mapping. Ten test persons digitized six complex built-up areas. Hereby, we receive quantitative information about spatial variables of buildings to systematically check the consistency and congruence of results. An additional questionnaire reveals qualitative information about obstacles. Generally, we find large differences among interpreters' mapping results and a high consistency of results for the same interpreter. We measure rising deviations correlate with a rising morphologic complexity. High degrees of individuality are expressed e.g., in time consumption, in-situ- or geographic information system (GIS)-precognition whereas data source mostly influences the mapping procedure. By this study, we aim to fill a gap as prior research using MVII often does not implement an uncertainty analysis or quantify mapping aberrations. We conclude that remote sensing studies should not only rely unquestioned on MVII for validation; furthermore, data and methods are needed to suspend uncertainty. |
topic |
Cognition earth observation elements of image interpretation level of individual buildings (LoD-1) manual visual image interpretation (MVII) perception |
url |
https://ieeexplore.ieee.org/document/9146616/ |
work_keys_str_mv |
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1721398574068006912 |