Modeling errors for remotely sensed data input to GIS

Michael Goodchild, Min-Hua Wang Min-Hua

Research output: Contribution to journalArticle

9 Citations (Scopus)

Abstract

Different views of spatial resolution and accuracy present a major obstacle to the integration of remote sensing and GIS. Accuracy in remote sensing is modeled using probabilities of class membership in each pixel; in vector-based GIS it is modeled using concepts such as the epsilon band. The problem of linking the two views of accuracy reduces to one of realizing a stochastic process which must satisfy conditions of prior and posterior probabilities, and spatial dependence. We propose two suitable methods, one storage intensive and the other computationally intensive. The methods can be adapted to incorporate various forms of prior knowledge. -Authors

Original languageEnglish (US)
Pages (from-to)530-537
Number of pages8
JournalUnknown Journal
StatePublished - Jan 1 1989
Externally publishedYes

Fingerprint

Geographic information systems
Remote sensing
GIS
Stochastic Processes
remote sensing
stochasticity
Random processes
modeling
pixel
spatial resolution
Pixels
method

ASJC Scopus subject areas

  • Environmental Science(all)
  • Earth and Planetary Sciences(all)

Cite this

Modeling errors for remotely sensed data input to GIS. / Goodchild, Michael; Wang Min-Hua, Min-Hua.

In: Unknown Journal, 01.01.1989, p. 530-537.

Research output: Contribution to journalArticle

@article{e1ac33cb05e340e1b14dd4a57a792063,
title = "Modeling errors for remotely sensed data input to GIS",
abstract = "Different views of spatial resolution and accuracy present a major obstacle to the integration of remote sensing and GIS. Accuracy in remote sensing is modeled using probabilities of class membership in each pixel; in vector-based GIS it is modeled using concepts such as the epsilon band. The problem of linking the two views of accuracy reduces to one of realizing a stochastic process which must satisfy conditions of prior and posterior probabilities, and spatial dependence. We propose two suitable methods, one storage intensive and the other computationally intensive. The methods can be adapted to incorporate various forms of prior knowledge. -Authors",
author = "Michael Goodchild and {Wang Min-Hua}, Min-Hua",
year = "1989",
month = "1",
day = "1",
language = "English (US)",
pages = "530--537",
journal = "Scanning Electron Microscopy",
issn = "0586-5581",
publisher = "Scanning Microscopy International",

}

TY - JOUR

T1 - Modeling errors for remotely sensed data input to GIS

AU - Goodchild, Michael

AU - Wang Min-Hua, Min-Hua

PY - 1989/1/1

Y1 - 1989/1/1

N2 - Different views of spatial resolution and accuracy present a major obstacle to the integration of remote sensing and GIS. Accuracy in remote sensing is modeled using probabilities of class membership in each pixel; in vector-based GIS it is modeled using concepts such as the epsilon band. The problem of linking the two views of accuracy reduces to one of realizing a stochastic process which must satisfy conditions of prior and posterior probabilities, and spatial dependence. We propose two suitable methods, one storage intensive and the other computationally intensive. The methods can be adapted to incorporate various forms of prior knowledge. -Authors

AB - Different views of spatial resolution and accuracy present a major obstacle to the integration of remote sensing and GIS. Accuracy in remote sensing is modeled using probabilities of class membership in each pixel; in vector-based GIS it is modeled using concepts such as the epsilon band. The problem of linking the two views of accuracy reduces to one of realizing a stochastic process which must satisfy conditions of prior and posterior probabilities, and spatial dependence. We propose two suitable methods, one storage intensive and the other computationally intensive. The methods can be adapted to incorporate various forms of prior knowledge. -Authors

UR - http://www.scopus.com/inward/record.url?scp=0024836980&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=0024836980&partnerID=8YFLogxK

M3 - Article

SP - 530

EP - 537

JO - Scanning Electron Microscopy

JF - Scanning Electron Microscopy

SN - 0586-5581

ER -