Neurocomputing for Earth Observation — Recent Developments and Future Challenges
Graeme G. Wilkinson
Additional contact information
Graeme G. Wilkinson: Joint Research Centre
Chapter 15 in Recent Developments in Spatial Analysis, 1997, pp 289-305 from Springer
Abstract:
Abstract Earth observation, or satellite remote sensing, is now well-established as one of the principle methods of obtaining spatial information concerning the terrestrial environment. Its primary advantages over ground-based survey approaches are timeliness, spatial coverage, and low cost, though these advantages are often bought at the expense of descriptive precision. However, the enormous wealth of timely and low cost information, coupled with the need to generate high precision spatial products descriptive of landscapes poses some of the most challenging computational problems in geographical science -both in terms of data throughput and complexity of analysis. Neurocomputing is one tool that has recently made a significant and growing contribution to this discipline.
Keywords: Neural Network; Land Cover; Remote Sensing; Land Cover Mapping; Projection Pursuit (search for similar items in EconPapers)
Date: 1997
References: Add references at CitEc
Citations:
There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:spr:adspcp:978-3-662-03499-6_15
Ordering information: This item can be ordered from
http://www.springer.com/9783662034996
DOI: 10.1007/978-3-662-03499-6_15
Access Statistics for this chapter
More chapters in Advances in Spatial Science from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().