Remote sensing and geostatistics

Research output: Contribution to Journal/Magazine › Journal article › peer-review

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Remote sensing and geostatistics. / Curran, Paul J.; Atkinson, Peter M.
In: Progress in Physical Geography, Vol. 22, No. 1, 03.1998, p. 61-78.

Research output: Contribution to Journal/Magazine › Journal article › peer-review

Harvard

Curran, PJ & Atkinson, PM 1998, 'Remote sensing and geostatistics', Progress in Physical Geography, vol. 22, no. 1, pp. 61-78. https://doi.org/10.1177/030913339802200103

APA

Curran, P. J., & Atkinson, P. M. (1998). Remote sensing and geostatistics. Progress in Physical Geography, 22(1), 61-78. https://doi.org/10.1177/030913339802200103

Vancouver

Curran PJ, Atkinson PM. Remote sensing and geostatistics. Progress in Physical Geography. 1998 Mar;22(1):61-78. doi: 10.1177/030913339802200103

Author

Curran, Paul J. ; Atkinson, Peter M. / Remote sensing and geostatistics. In: Progress in Physical Geography. 1998 ; Vol. 22, No. 1. pp. 61-78.

Bibtex

@article{855c18c556784d658355c1cdc90559ba,

title = "Remote sensing and geostatistics",

abstract = "In geostatistics, spatial autocorrelation is utilized to estimate optimally local values from data sampled elsewhere. The powerful synergy between geostatistics and remote sensing went unrealized until the 1980s. Today geostatistics are used to explore and describe spatial variation in remotely sensed and ground data; to design optimum sampling schemes for image data and ground data; and to increase the accuracy with which remotely sensed data can be used to classify land cover or estimate continuous variables. This article introduces these applications and uses two examples to highlight characteristics that are common to them all. The article concludes with a discussion of conditional simulation as a novel geostatistical technique for use in remote sensing.",

keywords = "Geostatistics, remote sensing, mapping, error, optimum sampling",

author = "Curran, {Paul J.} and Atkinson, {Peter M.}",

note = "M1 - 1",

year = "1998",

month = mar,

doi = "10.1177/030913339802200103",

language = "English",

volume = "22",

pages = "61--78",

journal = "Progress in Physical Geography",

issn = "0309-1333",

publisher = "SAGE Publications Ltd",

number = "1",

}

RIS

TY - JOUR

T1 - Remote sensing and geostatistics

AU - Curran, Paul J.

AU - Atkinson, Peter M.

N1 - M1 - 1

PY - 1998/3

Y1 - 1998/3

N2 - In geostatistics, spatial autocorrelation is utilized to estimate optimally local values from data sampled elsewhere. The powerful synergy between geostatistics and remote sensing went unrealized until the 1980s. Today geostatistics are used to explore and describe spatial variation in remotely sensed and ground data; to design optimum sampling schemes for image data and ground data; and to increase the accuracy with which remotely sensed data can be used to classify land cover or estimate continuous variables. This article introduces these applications and uses two examples to highlight characteristics that are common to them all. The article concludes with a discussion of conditional simulation as a novel geostatistical technique for use in remote sensing.

AB - In geostatistics, spatial autocorrelation is utilized to estimate optimally local values from data sampled elsewhere. The powerful synergy between geostatistics and remote sensing went unrealized until the 1980s. Today geostatistics are used to explore and describe spatial variation in remotely sensed and ground data; to design optimum sampling schemes for image data and ground data; and to increase the accuracy with which remotely sensed data can be used to classify land cover or estimate continuous variables. This article introduces these applications and uses two examples to highlight characteristics that are common to them all. The article concludes with a discussion of conditional simulation as a novel geostatistical technique for use in remote sensing.

KW - Geostatistics

KW - remote sensing

KW - mapping

KW - error

KW - optimum sampling

U2 - 10.1177/030913339802200103

DO - 10.1177/030913339802200103

M3 - Journal article

VL - 22

SP - 61

EP - 78

JO - Progress in Physical Geography

JF - Progress in Physical Geography

SN - 0309-1333

IS - 1

ER -

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