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The National Agricultural Library is one of four national libraries of the United States, with locations in Beltsville, Maryland and Washington, D.C. It houses one of the world's largest and most accessible agricultural information collections and serves as the nexus for a national network of state land-grant and U.S. Department of Agriculture field libraries. In fiscal year 2011 (Oct 2010 through Sept 2011) NAL delivered more than 100 million direct customer service transactions.

فعّال (مزود البيانات قام بتقديم البيانات الوصفية السنة الماضية)
Journal Article

مقال مجلة

Application of a Bayesian network for land-cover classification from a Landsat 7 ETM+ image  [2011]

Dlamini, Wisdom M.;

استعراض النص الكامل

This article describes the use of a Bayesian network (BN) for the classification of land cover from satellite imagery in northern Swaziland. The main objective of this work was to apply and evaluate the efficacy of a BN for land-cover classification using gap-filled and terrain-corrected Landsat 7 Enhanced Thematic Mapper Plus (ETM+) imagery acquired on 15 May 2007. The posterior probabilities (parameters) were estimated using the expectation-maximization (EM) and conjugate gradient descent (CGD) algorithms. A comparison of the results obtained from the algorithms indicates similar and excellent overall classification accuracies of 93.01%, and kappa coefficient values of 0.9143. The main result obtained in this study is that both algorithms considered here provide relatively similar and accurate solutions for the classification of the multispectral image although the EM algorithm is marginally competitive relative to CGD algorithm when measured in terms of the Brier score and the logarithmic loss.
المجلة
International journal of remote sensing
الرقم التسلسلي المعياري الدولي (ردمد) : 1366-5901

معلومات ببليوغرافية

اللغة:
English
النوع:
Journal Article
في أجريس منذ:
2014
المجلد:
10 v. 32
الإصدار:
21
صفحة البداية:
6569
صفحة النهاية:
6586
الناشر:
Taylor & Francis
جميع العناوين:
"Application of a Bayesian network for land-cover classification from a Landsat 7 ETM+ image"@eng
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معلومات ببليوغرافية

اللغة:
English
النوع:
Journal Article
في أجريس منذ:
2014
المجلد:
10 v. 32
الإصدار:
21
صفحة البداية:
6569
صفحة النهاية:
6586
الناشر:
Taylor & Francis
جميع العناوين:
"Application of a Bayesian network for land-cover classification from a Landsat 7 ETM+ image"@eng