Sains Malaysiana 51(3)(2022): 911-927

http://doi.org/10.17576/jsm-2022-5103-24

Improved Spatial Outlier Detection Method Within a River Network

(Kaedah Pengesanan Pencilan Reruang DiPerbaik dalam Suatu Jaringan Sungai)

NUR FATIHAH MOHD ALI¹, ROSSITA MOHAMAD YUNUS^1,*, IBRAHIM MOHAMED¹ & FARIDAH OTHMAN²

¹Institute of Mathematical Sciences, Faculty of Science, Universiti Malaya, 50603 Kuala Lumpur, Federal Territory, Malaysia

  ²Department of Civil Engineering, Faculty of Engineering, Universiti Malaya, 50603 Kuala Lumpur, Federal Territory, Malaysia

Received: 1 February 2021/Accepted: 13 August 2021

Abstract

A spatial outlier refers to the observation whose non-spatial attribute values are significantly different from those of its neighbors. Such observations can also be found in water quality data at monitoring stations within a river network. However, existing spatial outlier detection procedures based on distance measures such as the Euclidean distance between monitoring stations do not take into account the river network topology. In general, water quality levels in lower streams will be affected by the flow from the upper streams. Similarly, the water quality at some tributaries may have little influence on the other tributaries. Hence, a method for identifying spatial outliers in a river network, taking into account the effect of river flow connectivity on the determination of the neighbors of the monitoring stations, is proposed. While the robust Mahalalobis distance is used in both methods, the proposed method uses river distance instead of the Euclidean distance. The performance of the proposed method is shown to be superior using a synthetic river dataset through simulation. For illustration, we apply the proposed method on the water quality data from Sg. Klang Basin in 2016 provided by the Department of Environment, Malaysia. The finding provides a better identification of the water quality in some stations that significantly differ from their neighbouring stations. Such information is useful for  the authorities in their planning of the environmental monitoring of water quality in the areas.

Keywords: Euclidean distance; river distance; robust multivariate; spatial outlier; water quality

Abstrak

Reruang terpencil merujuk kepada cerapan dengan nilai atribut reruang berbeza secara signifikan berbanding daripada nilai kejiranannya. Cerapan ini boleh dikesan daripada data kualiti air yang dikumpul di stesen-stesen dalam jaringan sungai. Walau bagaimanapun, kaedah semasa untuk mengenal pasti pencilan reruang menggunakan jarak yang diukur antara stesen seperti jarak Euclidean tidak mengambil kira aspek topologi jaringan sungai. Secara umumnya, aras kualiti air pada hilir jaringan sungai dipengaruhi oleh aliran daripada hulu sungai. Begitu juga, kualiti air pada sesuatu jaringan sungai mungkin mempengaruhi sedikit kualiti air pada jaringan sungai yang berbeza. Kaedah dalam mengenal pasti reruang terpencil dalam jaringan sungai dengan mengambil kira kesan terhadap hubung kait aliran sungai bagi menentukan kejiranan sesebuah stesen dicadangkan. Walaupun penganggar kukuh jarak Mahalanobis digunakan dalam kedua-dua kaedah, tetapi kaedah yang dicadangkan ini menggunakan jarak aliran sungai dan bukannya jarak Euclidean. Berpandukan kaedah simulasi set data sungai sintetik, prestasi kaedah yang diperkenalkan ini terbukti lebih baik. Sebagai ilustrasi, kaedah yang diperkenalkan ini diterapkan pada data kualiti air yang diperoleh daripada Sg. Klang pada tahun 2016 yang disediakan oleh Jabatan Alam Sekitar, Malaysia. Keputusan daripada hasil kajian dapat membantu mengenal pasti kualiti air di beberapa buah stesen yang jauh lebih baik daripada stesen berdekatan. Maklumat ini sangat berguna kepada pihak berwajib dalam merancang pemantauan kualiti air di kawasan sekitarnya.

Kata kunci: Jarak aliran sungai; jarak Euclidean; kualiti air; penganggar multivariat; reruang terpencil

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^*Corresponding author; email: rossita@um.edu.my