Abstract
Google Earth (GE) provides very high resolution (VHR) natural-colored (red-green-blue, RGB) images based on commercial spaceborne sensors over worldwide coastal areas. GE is rarely used as a direct data source to address coastal issues despite the tremendous potential of data transferability. This paper describes an inexpensive and easy-to-implement methodology to construct a GE natural-colored dataset with a submeter pixel size over 44 km2 to accurately map the water depth, seabed and land cover along a seamless coastal area in subtropical Japan (Shiraho, Ishigaki Island). The valuation of the GE images for the three mapping types was quantified by comparison with directly-purchased images. We found that both RGB GE-derived mosaic and pansharpened QuickBird (QB) imagery yielded satisfactory results for mapping water depth (R2GE = 0.71 and R2QB = 0.69), seabed cover (OAGE = 89.70% and OAQB = 80.40%, n = 15 classes) and land cover (OAGE = 95.32% and OAQB = 88.71%, n = 11 classes); however, the GE dataset significantly outperformed the QB dataset for all three mappings (ZWater depth = 6.29, ZSeabed = 4.10, ZLand = 3.28, αtwo-tailed < 0.002). The integration of freely available elevation data into both RGB datasets significantly improved the land cover classification accuracy (OAGE = 99.17% and OAQB = 97.80%). Implications and limitations of our findings provide insights for the use of GE VHR data by stakeholders tasked with integrated coastal zone management.
Highlights
The coastal zone constitutes a beacon landscape because of its rich and abundant ecological services [1,2] coupled with its high vulnerability to ocean-climate change and local disturbances [3].Hosting 40% of the world’s population within 100 km of the shoreline [4], the coastal zone is subject to profound and ongoing changes, such as sea-level rise [5], loss of crucial ecosystem functions and disruption of the complex socio-ecological fabric [6]
Meaningful global and regional variables tied to coastal issues such as land cover [9], land elevation [10], coastline [11], sea surface temperature [12], sea chlorophyll concentration [12] or sea elevation [13] have been derived from freely available satellite imagery
Focused on the seamless coastal area of Shiraho (Ishigaki, Japan), we found that both RGB
Summary
The coastal zone constitutes a beacon landscape because of its rich and abundant ecological services [1,2] coupled with its high vulnerability to ocean-climate change and local disturbances [3].Hosting 40% of the world’s population within 100 km of the shoreline [4], the coastal zone is subject to profound and ongoing changes, such as sea-level rise [5], loss of crucial ecosystem functions (e.g., water filtering, food production, carbon sequestration and tourism generation; see [1]) and disruption of the complex socio-ecological fabric [6]. Meaningful global and regional variables tied to coastal issues such as land cover [9], land elevation [10], coastline [11], sea surface temperature [12], sea chlorophyll concentration [12] or sea elevation [13] have been derived from freely available satellite imagery. These spatialized drivers have significantly contributed to coastal sciences, they are not able to elucidate individual processes that shape the complex landscape because of their relatively low spatial resolution [14]. This limitation strongly undermines coherent multi-scale management based on large-scale assemblages of fine-scale elements
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