Monitoring turbidity in prai river estuary using digital camera imagery
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Monitoring Turbidity in Prai River Estuary Using Digital Camera Imagery. School of Physics, Universiti Sains Malaysia, 11800 Penang, Malaysia. E-mail: hslim@ usm.my , [email protected], [email protected] Tel: +604-6533663, Fax: +604-6579150. Presentation Outline. Objective Introduction

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Monitoring turbidity in prai river estuary using digital camera imagery l.jpg

Monitoring Turbidity in Prai River Estuary Using Digital Camera Imagery

School of Physics,

Universiti Sains Malaysia,

11800 Penang, Malaysia.

E-mail: [email protected], [email protected], [email protected]

Tel: +604-6533663, Fax: +604-6579150


Presentation outline l.jpg
Presentation Outline Camera Imagery

  • Objective

  • Introduction

  • Study Areas And Data Acquisition

  • Water Optical Model

  • Data Analysis and Results

  • Conclusion


Objective l.jpg
Objective Camera Imagery

  • To evaluate the performance of our empirical turbidity retrieval algorithm for water turbidity mapping.


Introduction l.jpg
Introduction Camera Imagery

  • Water quality monitoring is crucial for any effort to produce information in support of water conservation and decision-making.

  • Traditionally, monitoring of water quality is carried out through shipboard water sampling and laboratory analysis.

  • Such methods are not only labour-intensive, but sampling is also discrete in time and space.

  • Remote sensing offers an alternative method for monitoring water bodies on a large scale.


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Introduction Camera Imagery

  • Airborne digital camera imageries were selected in this present study because of several reasons.

    - First, the airborne digital image provides higher spatial resolution data for mapping a small study area.

    - Second, the airborne digital data acquisition can be carried out according to our planned surveys. The satellite observation times are fixed for a particular study area.

    - Third, the digital imagery offers many advantages over film-based cameras.

  • Furthermore, the study areas were located in the equatorial region where the sky is often covered by clouds.


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Introduction Camera Imagery

  • An algorithm was generated the retrieval of turbidity distribution.

  • A normal digital camera, Kodak DC290 was used as a sensor to capture images from a light aircraft, Cessna 172Q, at low altitude of 4400 feet.


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Study Areas And Data Acquisition Camera Imagery

  • The study area, Prai River estuary, Penang, Malaysia is located between latitudes 5º 22’ N to 5º 24’ N and longitude 100º 21’ E to 100o 23’ E


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Study Areas And Data Acquisition Camera Imagery

A conventional digital

camera Kodak DC290

A light aircraft Cessna 172Q


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Study Areas And Data Acquisition Camera Imagery

Prai estuary


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Water Optical Model Camera Imagery

R()


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Water Optical Model Camera Imagery

  • A physical model relating radiance from the water column and the concentrations of the water quality constituents provides the most affective way for analyzing remotely sensed data for water quality studies.

  • Reflectance is particularly dependent on inherent optical properties: the absorption coefficient and the backscattering coefficient.


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Water Optical Model Camera Imagery

Two water quality components chlorophyll, C, and suspended sediment, P.

2-band equation can be expressed as


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3-band Regression Algorithm Camera Imagery

Research conducted by other studies showed a simple linear regression between turbidity and sediment measurements


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Data Analysis and Results Camera Imagery

  • Eight colour digital imageries of the Prai River Estuary were selected for algorithm calibration.

  • The digital imageries were acquired in visible multispectral (3-bands: red, green and blue).

  • The size of each raw airborne colour digital image of the Prai river estuary, Penang was 480 pixels by 720 lines.

  • The eight images were mosaiced together for a bigger coverage area.

  • The mosaic image was then separated into three bands, (red, green and blue bands) for multispectral analysis using PCI Geomatica 10.1 software package.


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Raw Digital Image Camera Imagery


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Mosaic Image Camera Imagery




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Turbidity Map concentrations

Map of turbidity near Prai River Estuary [Blue = (< 10 NTU), Green = (10-20) NTU, Orange = (20-30)

NTU, yellow = (30-40) NTU, Red = (>40) NTU, Brown = Land and Black = area outside image]


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Conclusion concentrations

  • This study showed that the generated algorithm produced accurate result for turbidity mapping.

  • A bigger converge of study area can be obtained by mosaic several overlapped images.

  • It also showed that a digital camera could provide useful remotely sensed images for water quality application.


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ACKNOWLEDGEMENTS concentrations

IRPA - MOSTE


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Terima Kasih concentrations

THANK YOU


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