Data Repository for "Kite Aerial Photography for Low-cost, Ultra-high Spatial Resolution Multi-Spectral Mapping of Intertidal Landscapes", PLOS ONE, 2013.
Citation
M. Bryson, M. Johnson-Roberson, R. J. Murphy and D. Bongiorno, "Kite Aerial Photography for Low-Cost, Ultra-high Spatial Resolution Multi-Spectral Mapping of Intertidal Landscapes", PLoS ONE 8(9): e73550. doi:10.1371/journal.pone.0073550, 2013. [online]
Abstract
Intertidal ecosystems have primarily been studied using field-based sampling; remote sensing offers the ability to collect data over large areas in a snapshot of time that could complement field-based sampling methods by extrapolating them into the wider spatial and temporal context. Conventional remote sensing tools (such as satellite and aircraft imaging) provide data at limited spatial and temporal resolutions and relatively high costs for small-scale environmental science and ecologically-focussed studies. In this paper, we describe a low-cost, kite-based imaging system and photogrammetric/mapping procedure that was developed for constructing high-resolution, three-dimensional, multi-spectral terrain models of intertidal rocky shores. The processing procedure uses automatic image feature detection and matching, structure-from-motion and photo-textured terrain surface reconstruction algorithms that require minimal human input and only a small number of ground control points and allow the use of cheap, consumer-grade digital cameras. The resulting maps combine imagery at visible and near-infrared wavelengths and topographic information at sub-centimeter resolutions over an intertidal shoreline 200 m long, thus enabling spatial properties of the intertidal environment to be determined across a hierarchy of spatial scales. Results of the system are presented for an intertidal rocky shore at Jervis Bay, New South Wales, Australia. Potential uses of this technique include mapping of plant (micro- and macro-algae) and animal (e.g. gastropods) assemblages at multiple spatial and temporal scales.
Data and Results
Colour Imagery Mosaic Files: colourmosaic.zip (79.4MB)
Normalised Difference Vegetation Index (NDVI) Mosaic Files: ndvimosaic.zip (558.1MB)
Acknowledgments
This work was supported through the Early Career Researcher Development Scheme through the Faculty of Engineering and Information Technologies at the University of Sydney. Thanks to Dr. Nathan Knott from the New South Wales Department of Primary Industries for his discussions and assistance during fieldwork.