Water quality mapping using digital camera images

• Published in: International journal of remote sensing Vol. 31; no. 19; pp. 5275 - 5295
• Main Authors: Lim, H. S., Mat Jafri, M. Z., Abdullah, K., Abu Bakar, M. N.
• Format: Journal Article
• Language: English
• Published: Abingdon Taylor & Francis 01.06.2010
• Subjects: Animal, plant and microbial ecology; Applied geophysics; Biological and medical sciences; Digital cameras; Earth sciences; Earth, ocean, space; Exact sciences and technology; Fundamental and applied biological sciences. Psychology; General aspects. Techniques; Internal geophysics; Mapping; Remote sensing; Teledetection and vegetation maps; Water quality; Far East; Asia; Malaysia; altitude; measurement sensor; clouds; solution; Light; estuaries; quantitative analysis; satellites; cost; remote sensing; utilization; cartography; Acquisition; water; Hand; Digital photography; equatorial zone; samples; Global Positioning System; brightness; water quality; Feasibility; Aircraft; digital images; Aerial survey
• ISSN: 0143-1161; 1366-5901
• DOI: 10.1080/01431160903283843

The objective of this study was to implement a low-cost airborne remote sensing system to provide an alternative solution for remote sensing given the difficulty in obtaining cloud-free satellite scenes of the equatorial region. An inexpensive sensor, a Kodak DC 290 digital camera, was used, onboard a light aircraft, Cessna 172Q. The feasibility of using camera images for remote sensing applications was tested for quantifying total suspended solids (TSS) from three estuaries located in the northern region of Peninsular Malaysia. The aircraft was flown at altitudes of 914.4 to 2438.4 m for digital image acquisition of the study areas. Water samples were collected simultaneously with the aircraft overpasses and their locations were determined by using a hand-held Global Positioning System (GPS). Oblique images were corrected for brightness variation. A simple relative atmospheric correction was performed on the multidate images. The captured colour images were then separated into three bands (red, green and blue) for multispectral analysis. The digital numbers (DNs) were extracted corresponding to the sea data locations for each band. A multiband regression algorithm was developed based on a reflectance model, which is a function of the inherent optical properties of water, and this in turn can be related to the concentration of the TSS. Data from different scenes were combined and then divided into two sets, one for calibration of the algorithm and the other for a validation analysis. The calibrated algorithm had a correlation coefficient (R) of 0.96 and a root mean square error (RMSE) of approximately 17 mg l −1 . The validation analysis showed that the algorithm could estimate the TSS concentration within an RMSE of about 23 mg l −1 and an R value of 0.95. The calibrated algorithm was used to generate water quality maps for all images. The maps were geometrically corrected and colour coded for visual interpretation.