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Details

Autor(en) / Beteiligte
Titel
Human cognition based framework for detecting roads from remote sensing images
Ist Teil von
  • Geocarto international, 2022-04, Vol.37 (8), p.2365-2384
Ort / Verlag
Taylor & Francis
Erscheinungsjahr
2022
Link zum Volltext
Quelle
AUTh Library subscriptions: Taylor & Francis Journals
Beschreibungen/Notizen
  • The complete extraction of roads from remote sensing images (RSIs) is an emergent area of research. It is an interesting topic as it involves diverse procedures for detecting roads. The detection of roads using high-resolution-satellite-images (HRSi) is challenging because of the occurrence of several types of noise such as bridges, vehicles, and crossing lines, etc. The extraction of the correct road network is crucial due to its broad range of applications such as transportation, map updating, navigation, and generating maps. Therefore our paper concentrates on understanding the cognitive processes, reasoning, and knowledge used by the analyst through visual cognition while performing the task of road detection from HRSi. The novel process is performed emulating human cognition within cognitive task analysis which is carried out in five different stages. The suggested cognitive procedure for road extraction is validated with the fifteen HRSi of four different land cover patterns specifically developed-sub-urban (DSUr), developed-urban (DUr), emerging-sub-urban (ESUr), and emerging-urban (EUr). The experimental results and the comparative assessment prove the impact of the presented cognitive method.
Sprache
Englisch
Identifikatoren
ISSN: 1010-6049
eISSN: 1752-0762
DOI: 10.1080/10106049.2020.1810330
Titel-ID: cdi_informaworld_taylorfrancis_310_1080_10106049_2020_1810330

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