Radiometric and Photometeric Determinations of Simulated Shallow-Water Environment

Abstract

Optical remote sensing is increasingly becoming a preferred economic alternative to the traditional in situ observations and physical sampling for mapping and monitoring habitats. Submersed habitats, such as eelgrass and corals, are especially challenging for field work. Even for remote-sensing work, a priori knowledge of environmental factors is required for highly accurate analysis. Background illumination and water clarity are two key factors that affect the optical remote-sensing imagery, which may vary widely with season, time of year, geographic location, or water depth. This article presents efforts to simulate natural oceanic conditions in a laboratory setting. Solar radiation predicted at different latitudes under varying water clarity conditions and depth were replicated using a 2.5 m deep wave tank at the University of New Hampshire. The goals of the study were: (1) to simulate illumination and water clarity conditions that approximate coastal and oceanic waters, and (2) to quantify the impact of the simulated illumination and water clarity conditions at different depths on the apparent colours that can be observed from an aerial platform. The empirical radiometric measurements included irradiance, radiance, and remote-sensing reflectance from an underwater array of light sources. The results of the study show good correlation (r 2 = 0.89–0.93) between the natural daylight spectrum at the water surface and the irradiance measurements between 350 nm and 590 nm, at 3.5 m from the light array. The colours of the clear and murky water types were photometrically calculated from the radiometric measurements and validated using underwater video imagery. Using this methodology, illumination and water clarity can be replicated under controlled laboratory conditions and used to assist in studying the physical, chemical, and biological processes in habitats, at varied geographic locations and differing environments.

Department

Center for Coastal and Ocean Mapping

Publication Date

2013

Volume

34, Issue 18

Journal Title

International Journal of Remote Sensing

Pages

6437-6450

Publisher

Elsevier

Digital Object Identifier (DOI)

10.1080/01431161.2013.800657

Document Type

Journal Article

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