Introduction to the special issue “Uncertainty in remote sensing image analysis”

Stein, Alfred; Ge, Yong; Fabris-Rotelli, Inger Nicolette

dc.contributor.author	Stein, Alfred
dc.contributor.author	Ge, Yong
dc.contributor.author	Fabris-Rotelli, Inger Nicolette
dc.date.accessioned	2019-06-24T10:29:21Z
dc.date.available	2019-06-24T10:29:21Z
dc.date.issued	2018
dc.description.abstract	Images obtained from satellites are of an increasing resolution. In addition, the frequency of their observations is increasing, and is expected to continue to increase in the near future. Despite these rapid developments, uncertainty is inherent in images. This occurs in all types of images, sensors and platforms, including multi-spectral (hyper-spectral) images, high spatial resolution images and LiDAR images. Uncertainty is, for example, due to mixed pixels, a lack of precise ground control points, atmospheric distortion and the vague definition of ground objects. It includes both low accuracy, as well as ambiguous definitions.	en_ZA
dc.description.department	Statistics	en_ZA
dc.description.librarian	am2019	en_ZA
dc.description.uri	http://www.mdpi.com/journal/remotesensing	en_ZA
dc.identifier.citation	Stein, A., Ge, Y. & Fabris-Rotelli, I. 2019, 'Introduction to the special issue “uncertainty in remote sensing image analysis”', Remote Sensing, vol. 10, no. 1975, pp. 1-3.	en_ZA
dc.identifier.issn	2072-4292 (online)
dc.identifier.other	10.3390/rs10121975
dc.identifier.uri	http://hdl.handle.net/2263/70276
dc.language.iso	en	en_ZA
dc.publisher	MDPI Publishing	en_ZA
dc.rights	© 2018 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license.	en_ZA
dc.subject	Uncertainty	en_ZA
dc.subject	Images	en_ZA
dc.subject	Satellites	en_ZA
dc.subject	Resolution	en_ZA
dc.title	Introduction to the special issue “Uncertainty in remote sensing image analysis”	en_ZA
dc.type	Article	en_ZA