2012•˜The œinternational archives of the photogrammetry, remote sensing and spatial information sciences/International archives of the photogrammetry, remote sensing and spatial information sciencesOpen access

GULLIES, GOOGLE EARTH AND THE GREAT BARRIER REEF: A REMOTE SENSING METHODOLOGY FOR MAPPING GULLIES OVER EXTENSIVE AREAS

U. Gilad, R. Denham, D. Tindall

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Abstract

Abstract. Recent work suggests that gully erosion is the main contributor of sediments to the Great Barrier Reef, Australia. The objectives of this study were to identify the location of gullies as well as the landscape characteristics associated with gully presence in the Burdekin Catchment. Data were collected by random sampling using Google Earth. A spatial-statistical analysis allowed the exclusion of areas where gullies were less likely to be present. The remaining gully sensitive areas were then manually mapped by using Google Earth, assisting in the creation of a predictive map. A semi-quantitative gully presence map was also created by visually inspecting imagery at 5 km × 5 km grid cell scale. Results show a strong relationship between gully presence and drainage features, low tree cover and low slopes. The resulting predictive map has correctly allocated more than 90% of gullies within less than 20% of the Burdekin's area, yet uncertainties still remain. The manually derived mapping product comprises the most comprehensive gully data available for the Burdekin, while the high-resolution predictive map and the 5 km × 5 km grid map will allow better targeting of gullied areas in later stages of this research. This study also provides a methodology that can be applied to mapping gullies over extensive areas. It demonstrates how Google Earth could be used as a reliable platform for mapping gullies and discusses the limitations in the use of remotely sensed data for gully mapping and modelling.

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Abstract. Recent work suggests that gully erosion is the main contributor of sediments to the Great Barrier Reef, Australia. The objectives of this study were to identify the location of gullies as well as the landscape characteristics associated with gully presence in the Burdekin Catchment. Data were collected by random sampling using Google Earth. A spatial-statistical analysis allowed the exclusion of areas where gullies were less likely to be present. The remaining gully sensitive areas were then manually mapped by using Google Earth, assisting in the creation of a predictive map. A semi-quantitative gully presence map was also created by visually inspecting imagery at 5 km × 5 km grid cell scale. Results show a strong relationship between gully presence and drainage features, low tree cover and low slopes. The resulting predictive map has correctly allocated more than 90% of gullies within less than 20% of the Burdekin's area, yet uncertainties still remain. The manually derived mapping product comprises the most comprehensive gully data available for the Burdekin, while the high-resolution predictive map and the 5 km × 5 km grid map will allow better targeting of gullied areas in later stages of this research. This study also provides a methodology that can be applied to mapping gullies over extensive areas. It demonstrates how Google Earth could be used as a reliable platform for mapping gullies and discusses the limitations in the use of remotely sensed data for gully mapping and modelling.

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Available abstract

Abstract. Recent work suggests that gully erosion is the main contributor of sediments to the Great Barrier Reef, Australia. The objectives of this study were to identify the location of gullies as well as the landscape characteristics associated with gully presence in the Burdekin Catchment. Data were collected by random sampling using Google Earth. A spatial-statistical analysis allowed the exclusion of areas where gullies were less likely to be present. The remaining gully sensitive areas were then manually mapped by using Google Earth, assisting in the creation of a predictive map. A semi-quantitative gully presence map was also created by visually inspecting imagery at 5 km × 5 km grid cell scale. Results show a strong relationship between gully presence and drainage features, low tree cover and low slopes. The resulting predictive map has correctly allocated more than 90% of gullies within less than 20% of the Burdekin's area, yet uncertainties still remain. The manually derived mapping product comprises the most comprehensive gully data available for the Burdekin, while the high-resolution predictive map and the 5 km × 5 km grid map will allow better targeting of gullied areas in later stages of this research. This study also provides a methodology that can be applied to mapping gullies over extensive areas. It demonstrates how Google Earth could be used as a reliable platform for mapping gullies and discusses the limitations in the use of remotely sensed data for gully mapping and modelling.

Key concepts: Gully erosion, Remote sensing, Scale (ratio), Cartography, Drainage basin, Geology, Erosion, Geography

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