Integrating Quickbird Multi-Spectral Satellite and Field Data: Mapping Bathymetry, Seagrass Cover, Seagrass Species and Change in Moreton Bay, Australia in 2004 and 2007

Chris Roelfsema,Stuart Phinn,Mitchell Lyons

doi:10.3390/rs3010042

Abstract

Shallow coastal ecosystems are the interface between the terrestrial and marine environment. The physical and biological composition and distribution of benthic habitats within these ecosystems determines their contribution to ecosystem services and biodiversity as well as their connections to neighbouring terrestrial and marine ecosystem processes. The capacity to accurately and consistently map and monitor these benthic habitats is critical to developing and implementing management applications. This paper presents a method for integrating field survey data and high spatial resolution, multi-spectral satellite image data to map bathymetry and seagrass in shallow coastal waters. Using Quickbird 2 satellite images from 2004 and 2007, acoustic field survey data were used to map bathymetry using a linear and ratio algorithm method; benthic survey field data were used to calibrate and validate classifications of seagrass percentage cover and seagrass species composition; and a change detection analysis of seagrass cover was performed. The bathymetry mapping showed that only the linear algorithm could effectively and accurately predict water depth; overall benthic map accuracies ranged from 57–95%; and the change detection produced a reliable change map and showed a net decrease in seagrass cover levels, but the majority of the study area showed no change in seagrass cover level. This study demonstrates that multiple spatial products (bathymetry, seagrass and change maps) can be produced from single satellite images and a concurrent field survey dataset. Moreover, the products were produced at higher spatial resolution and accuracy levels than previous studies in Moreton Bay. The methods are developed from previous work in the study area and are continuing to be implemented, as well as being developed to be repeatable in similar shallow coastal water environments.

Highlights

Seagrass communities are vital contributors to ecosystem services and biodiversity in shallow coastal areas [1]
There was no linear relationship between water depth and observed reflectance over seagrass cover type
The seagrass cover type has a higher degree of internal variance; in a linear relationship, variance in albedo is confused with variance in water depth

Summary

Introduction

Seagrass communities are vital contributors to ecosystem services and biodiversity in shallow coastal areas [1]. The spatial distribution of seagrass beds determines their effectiveness as ecosystem stabilisers, disturbances to seagrass, in particular habitat fragmentation, can effect the entire coastal ecosystem [2]. The dynamics of long term change in spatial distribution of seagrass communities are largely unknown, stemming from the lack of understanding in short-term change in spatial patterns [3]. Seagrass mapping is generally performed to derive three main biophysical properties: seagrass cover or projected foliage cover; seagrass species composition and seagrass biomass [10]. Higher spatial resolution image data increases both the accuracy and precision of image classification and modelling [11] and is a prerequisite for delineating species composition of seagrass patches [12]

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Conclusion