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Adaptive cluster sampling for a temporal-scale population

Adaptive cluster sampling (ACS) is appropriate for rare clustered populations with localization tendencies. Up to now, it has been used exclusively for investigating spatial-scale problems rather than temporal-scale such as t his study is dealing with, i.e.sediment transport in rivers. Suspended se...

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Main Authors: Arabkhedri, Mahmood, Lai, Food See, Ibrahim, Noor Akma, Mohamad Kasim, Mohamad Roslan
Format: Article
Language:English
Published: Institute for Mathematical Research, Universiti Putra Malaysia 2010
Online Access:http://psasir.upm.edu.my/id/eprint/12931/1/Adaptive%20Cluster%20Sampling%20for%20a%20Temporal-Scale%20Population.pdf
http://psasir.upm.edu.my/id/eprint/12931/
http://einspem.upm.edu.my/journal/fullpaper/vol4no1/4.%20Arabkhedri.pdf
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spelling my.upm.eprints.129312015-08-30T00:45:19Z http://psasir.upm.edu.my/id/eprint/12931/ Adaptive cluster sampling for a temporal-scale population Arabkhedri, Mahmood Lai, Food See Ibrahim, Noor Akma Mohamad Kasim, Mohamad Roslan Adaptive cluster sampling (ACS) is appropriate for rare clustered populations with localization tendencies. Up to now, it has been used exclusively for investigating spatial-scale problems rather than temporal-scale such as t his study is dealing with, i.e.sediment transport in rivers. Suspended sediment load is carried mostly during relatively short periods coincide with high flows otherwise negligible. In ACS, more samples from critical river stages can be taken with respect to the aggregation tendencies of sediment loads during transport; thus increasing the level of representativeness of samples. Adoption of ACS to this new area needs further verification and adaptation such as definition of the sampling unit, population frame, neighborhood relation, and threshold. In this study, several scenarios were defined for the purpose of evaluating the ACS in sediment estimation. Numerous sample sets were taken from intensive discharge-load records of Sg. Pangsun River, Malaysia. These sample sets are different with respect to initial sample size, neighborhood relation, and discharge threshold. Total suspended sediment loads were then estimated using modified Horvitz-Thompson method. The comparison made between the symmetric neighborhood relation and the forward method suggested in this study showed that the latter could be used instead of the former in sediment studies without losing the accuracy. The findings also suggested the flow duration curve is a useful tool for ranking initial samples in order to determine an optimum discharge threshold. Institute for Mathematical Research, Universiti Putra Malaysia 2010 Article PeerReviewed application/pdf en http://psasir.upm.edu.my/id/eprint/12931/1/Adaptive%20Cluster%20Sampling%20for%20a%20Temporal-Scale%20Population.pdf Arabkhedri, Mahmood and Lai, Food See and Ibrahim, Noor Akma and Mohamad Kasim, Mohamad Roslan (2010) Adaptive cluster sampling for a temporal-scale population. Malaysian Journal of Mathematical Sciences, 4 (1). pp. 53-75. ISSN 1823-8343; ESSN: 2289-750X http://einspem.upm.edu.my/journal/fullpaper/vol4no1/4.%20Arabkhedri.pdf
institution Universiti Putra Malaysia
building UPM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Putra Malaysia
content_source UPM Institutional Repository
url_provider http://psasir.upm.edu.my/
language English
description Adaptive cluster sampling (ACS) is appropriate for rare clustered populations with localization tendencies. Up to now, it has been used exclusively for investigating spatial-scale problems rather than temporal-scale such as t his study is dealing with, i.e.sediment transport in rivers. Suspended sediment load is carried mostly during relatively short periods coincide with high flows otherwise negligible. In ACS, more samples from critical river stages can be taken with respect to the aggregation tendencies of sediment loads during transport; thus increasing the level of representativeness of samples. Adoption of ACS to this new area needs further verification and adaptation such as definition of the sampling unit, population frame, neighborhood relation, and threshold. In this study, several scenarios were defined for the purpose of evaluating the ACS in sediment estimation. Numerous sample sets were taken from intensive discharge-load records of Sg. Pangsun River, Malaysia. These sample sets are different with respect to initial sample size, neighborhood relation, and discharge threshold. Total suspended sediment loads were then estimated using modified Horvitz-Thompson method. The comparison made between the symmetric neighborhood relation and the forward method suggested in this study showed that the latter could be used instead of the former in sediment studies without losing the accuracy. The findings also suggested the flow duration curve is a useful tool for ranking initial samples in order to determine an optimum discharge threshold.
format Article
author Arabkhedri, Mahmood
Lai, Food See
Ibrahim, Noor Akma
Mohamad Kasim, Mohamad Roslan
spellingShingle Arabkhedri, Mahmood
Lai, Food See
Ibrahim, Noor Akma
Mohamad Kasim, Mohamad Roslan
Adaptive cluster sampling for a temporal-scale population
author_facet Arabkhedri, Mahmood
Lai, Food See
Ibrahim, Noor Akma
Mohamad Kasim, Mohamad Roslan
author_sort Arabkhedri, Mahmood
title Adaptive cluster sampling for a temporal-scale population
title_short Adaptive cluster sampling for a temporal-scale population
title_full Adaptive cluster sampling for a temporal-scale population
title_fullStr Adaptive cluster sampling for a temporal-scale population
title_full_unstemmed Adaptive cluster sampling for a temporal-scale population
title_sort adaptive cluster sampling for a temporal-scale population
publisher Institute for Mathematical Research, Universiti Putra Malaysia
publishDate 2010
url http://psasir.upm.edu.my/id/eprint/12931/1/Adaptive%20Cluster%20Sampling%20for%20a%20Temporal-Scale%20Population.pdf
http://psasir.upm.edu.my/id/eprint/12931/
http://einspem.upm.edu.my/journal/fullpaper/vol4no1/4.%20Arabkhedri.pdf
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score 13.211869

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