Studies of chlorophyll-a distribution in Northern Region Coast of Peninsular Malaysia using satellite remote sensing

Hashim, Suhaila; Narashid, Rohayu Haron; Arof, Zakaria Mat

doi:10.1109/iconspace.2011.6015896

Cited by 3 publications

(3 citation statements)

References 3 publications

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“…The study by Muthurajah et al (2021) also revealed that there is a high concentration of chlorophyll-a from March to May and from October to November. According to Hashim et al (2011) and Shaari & Ahmad Mustapha (2017)'s remote sensing study findings, the concentration of chlorophyll-a is higher during the SW monsoon than NE monsoon. The findings of this study are supported by earlier research, where high chlorophyll-a concentration readings were recorded in Pengerang followed by Pulau Besar where sampling was carried out during the SW monsoon (October).…”

Section: Resultsmentioning

confidence: 99%

Effect of Water Circulation on the Distribution of Zooplankton in the Southern Waters of Peninsular Malaysia

Shafie,

Juneng,

Abdul Rahim

2023

JRBA

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The waters of Peninsular Malaysia located between the South China Sea and the Straits of Malacca are greatly influenced by two different monsoons: the Southwest Monsoon (SW) and the Northeast Monsoon (NE). Zooplankton are known to be receptive to any environmental changes. Apart from biotic and abiotic changes, the movement of water currents also has an impact on the distribution and composition of zooplankton, as this group is considered a passive swimmer that is dependent on the movement of water currents. This study was conducted to determine the effect of water movement in the southern waters of Peninsular Malaysia on the distribution of zooplankton. Sampling was done in three main areas: Kukup, Pengerang, and Pulau Besar. A total of 16 stations with three replicates per station were performed using a plankton net with a mesh size of 140µm. Results show that zooplankton in Pengerang recorded the highest with 256.157 ind/ m3, followed by Kukup (132.412 ind/m3) and Pulau Besar (54.066 ind/m3). There were seven dominant species of copepods recorded in this study, namely Acrocalanus gracilis, Bestiolona similis, Euterpina acutifrons, Oithona nana, Oithona similis, Paracalanus aculeatus, and Paracalanus denudatus. Generally, this study has shown a notable relationship between local current circulation patterns and zooplankton distribution.

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Section: Resultsmentioning

confidence: 99%

Effect of Water Circulation on the Distribution of Zooplankton in the Southern Waters of Peninsular Malaysia

Shafie,

Juneng,

Abdul Rahim

2023

JRBA

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“…Wang suggested neural network technology to simulate the mathematical relationship between chl-a concentration and remote sensing reflectance in the Yellow Sea and East China Sea [15]. Hashim used satellite remote sensing images to study the chl-a distribution at Northern Region Coast of Peninsular Malaysia [16].…”

Section: Introductionmentioning

confidence: 99%

Application of Extreme Learning Machine for Predicting Chlorophyll‐a Concentration Inartificial Upwelling Processes

Wei

Huang

Chen

et al. 2019

Mathematical Problems in Engineering

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Artificial upwelling, artificially pumping up nutrient-rich ocean waters from deep to surface, is increasingly applied to stimulating phytoplankton activity. As a proxy for the amount of phytoplankton present in the ocean, the concentration of chlorophyll a (chl-a) may be influenced by water physical factors altered in artificial upwelling processes. However, the accuracy and convenience of measuring chl-a are limited by present technologies and equipment. Our research intends to study the correlations between chl-a concentration and five water physical factors, i.e., salinity, temperature, depth, dissolved oxygen (DO), and pH, possibly affected by artificial upwelling. In this paper, seven models are presented to predict chl-a concentration, respectively. Two of them are based on traditional regression algorithms, i.e., multiple linear regression (MLR) and multivariate quadratic regression (MQR), while five are based on intelligent algorithms, i.e., backpropagation-neural network (BP-NN), extreme learning machine (ELM), genetic algorithm-ELM (GA-ELM), particle swarm optimization-ELM (PSO-ELM), and ant colony optimization-ELM (ACO-ELM). These models provide a quick prediction to study the concentration of chl-a. With the experimental data collected from Xinanjiang Experiment Station in China, the results show that chl-a concentration has a strong correlation with salinity, temperature, DO, and pH in the process of artificial upwelling and PSO-ELM has the best overall prediction ability.

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“…Unfortunately, this is difficult to achieve with traditional monitoring approaches. Today monitoring campaigns are generally performed by means of dedicated vessels [4], fixed monitoring stations (buoys), and, more recently, by remote sensing from space [5] but, nevertheless, these monitoring methodologies can hardly guarantee the desired spatial and temporal resolution. Sampling campaigns conducted by dedicated vessels are expensive [4] and can sample the water at a limited number of locations during each survey; fixed monitoring stations can provide information only at their deployment site while satellites are effective only for monitoring specific phenomena such as oil dispersion or chlorophyll concentration.…”

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confidence: 99%

An Autonomous Water Monitoring and Sampling System for Small-Sized ASVs

Fornai

Ferri

Manzi

et al. 2016

IEEE J. Oceanic Eng.

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In recent years, sensorized autonomous vehicles (either AUVs or ASVs) have been increasingly used for in situ water measurements. However, collection of water samplings at depth by small-sized ASVs and their subsequent physical/chemical analysis onboard remains difficult due to size and weight constraints. This paper addresses this issue and describes the design and testing of an autonomous water monitoring and sampling system intended for operations onboard small-sized man-portable ASVs. The system is designed to collect water samples up to 50 m in depth and to measure physical water parameters along the water column. The system is composed of a probe lowered by a winch measuring physical water parameters and able to collect water samples at different selectable depths. Once the probe is returned onboard, a water distribution system transfers the collected water samples to sensors lodged in the ASV for the monitoring of chemical parameters, or into containers to transport the samples to laboratories on the mainland. The system combines small dimensions, self-cleaning capabilities, low weight, and limited power consumption allowing it to be easily installable and used on an autonomous small-sized ASVs. The sampling system was installed and tested in a robotic small-sized catamaran belonging to the HydroNet ASV class

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Studies of chlorophyll-a distribution in Northern Region Coast of Peninsular Malaysia using satellite remote sensing

Cited by 3 publications

References 3 publications

Effect of Water Circulation on the Distribution of Zooplankton in the Southern Waters of Peninsular Malaysia

Effect of Water Circulation on the Distribution of Zooplankton in the Southern Waters of Peninsular Malaysia

Application of Extreme Learning Machine for Predicting Chlorophyll‐a Concentration Inartificial Upwelling Processes

An Autonomous Water Monitoring and Sampling System for Small-Sized ASVs

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