Multi-temporal mapping of seagrass cover, species and biomass of the Eastern Banks, Moreton Bay, Australia, with links to shapefiles


Autoria(s): Roelfsema, Christiaan M; Lyons, Mitchell B; Kovacs, Eva M; Maxwell, Paul; Saunders, Megan I; Samper-Villarreal, Jimena; Phinn, Stuart R
Cobertura

LATITUDE: -27.392400 * LONGITUDE: 153.398100 * DATE/TIME START: 2004-09-17T00:00:00 * DATE/TIME END: 2013-08-05T00:00:00

Data(s)

03/07/2014

Resumo

The spatial and temporal dynamics of seagrasses have been studied from the leaf to patch (100 m**2) scales. However, landscape scale (> 100 km**2) seagrass population dynamics are unresolved in seagrass ecology. Previous remote sensing approaches have lacked the temporal or spatial resolution, or ecologically appropriate mapping, to fully address this issue. This paper presents a robust, semi-automated object-based image analysis approach for mapping dominant seagrass species, percentage cover and above ground biomass using a time series of field data and coincident high spatial resolution satellite imagery. The study area was a 142 km**2 shallow, clear water seagrass habitat (the Eastern Banks, Moreton Bay, Australia). Nine data sets acquired between 2004 and 2013 were used to create seagrass species and percentage cover maps through the integration of seagrass photo transect field data, and atmospherically and geometrically corrected high spatial resolution satellite image data (WorldView-2, IKONOS and Quickbird-2) using an object based image analysis approach. Biomass maps were derived using empirical models trained with in-situ above ground biomass data per seagrass species. Maps and summary plots identified inter- and intra-annual variation of seagrass species composition, percentage cover level and above ground biomass. The methods provide a rigorous approach for field and image data collection and pre-processing, a semi-automated approach to extract seagrass species and cover maps and assess accuracy, and the subsequent empirical modelling of seagrass biomass. The resultant maps provide a fundamental data set for understanding landscape scale seagrass dynamics in a shallow water environment. Our findings provide proof of concept for the use of time-series analysis of remotely sensed seagrass products for use in seagrass ecology and management.

Formato

text/tab-separated-values, 54 data points

Identificador

https://doi.pangaea.de/10.1594/PANGAEA.833767

doi:10.1594/PANGAEA.833767

Idioma(s)

en

Publicador

PANGAEA

Direitos

CC-BY: Creative Commons Attribution 3.0 Unported

Access constraints: unrestricted

Fonte

Supplement to: Roelfsema, Christiaan M; Lyons, Mitchell B; Kovacs, Eva M; Maxwell, Paul; Saunders, Megan I; Samper-Villarreal, Jimena; Phinn, Stuart R (2014): Multi-temporal mapping of seagrass cover, species and biomass: A semi-automated object based image analysis approach. Remote Sensing of Environment, 150, 172-187, doi:10.1016/j.rse.2014.05.001

Palavras-Chave #DATE/TIME; EasternBanks; Moreton Bay, Brisbane, South East Queensland, Coral Sea, Australia; MULT; Multiple investigations; Uniform resource locator/link to file
Tipo

Dataset