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Sampling remotely sensed imagery for storage, retrieval and reconstruction

Sampling remotely sensed imagery for storage, retrieval and reconstruction
Sampling remotely sensed imagery for storage, retrieval and reconstruction
A major difficulty in remote sensing is handling the many data from sensors aboard aircraft and satellites. In this paper we identify an optimal procedure for sampling remotely sensed data before their storage or on their retrieval. The procedure depends on spatial correlation in the scene and uses kriging to estimate values that have been lost. An example in which data from an airborne multispectral scanner could be diminished to only about one tenth without serious loss of precision illustrates the method.
345-353
Atkinson, P.M.
aaaa51e4-a713-424f-92b0-0568b198f425
Curran, P.J.
3f5c1422-c154-4533-9c84-f2afb77df2de
Webster, R.
dc5a4997-e7db-4d88-929c-d4308a3a07a9
Atkinson, P.M.
aaaa51e4-a713-424f-92b0-0568b198f425
Curran, P.J.
3f5c1422-c154-4533-9c84-f2afb77df2de
Webster, R.
dc5a4997-e7db-4d88-929c-d4308a3a07a9

Atkinson, P.M., Curran, P.J. and Webster, R. (1990) Sampling remotely sensed imagery for storage, retrieval and reconstruction. Professional Geographer, 42 (3), 345-353. (doi:10.1111/j.0033-0124.1990.00345.x).

Record type: Article

Abstract

A major difficulty in remote sensing is handling the many data from sensors aboard aircraft and satellites. In this paper we identify an optimal procedure for sampling remotely sensed data before their storage or on their retrieval. The procedure depends on spatial correlation in the scene and uses kriging to estimate values that have been lost. An example in which data from an airborne multispectral scanner could be diminished to only about one tenth without serious loss of precision illustrates the method.

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Published date: 1990

Identifiers

Local EPrints ID: 17461
URI: https://eprints.soton.ac.uk/id/eprint/17461
PURE UUID: 43f694b2-4dda-4649-87f5-e73ebaa2698e

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Date deposited: 29 Sep 2005
Last modified: 17 Jul 2017 16:38

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