Mapping VHR Water Depth, Seabed and Land Cover Using Google Earth Data
AbstractGoogle 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. View Full-Text
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Collin, A.; Nadaoka, K.; Nakamura, T. Mapping VHR Water Depth, Seabed and Land Cover Using Google Earth Data. ISPRS Int. J. Geo-Inf. 2014, 3, 1157-1179.
Collin A, Nadaoka K, Nakamura T. Mapping VHR Water Depth, Seabed and Land Cover Using Google Earth Data. ISPRS International Journal of Geo-Information. 2014; 3(4):1157-1179.Chicago/Turabian Style
Collin, Antoine; Nadaoka, Kazuo; Nakamura, Takashi. 2014. "Mapping VHR Water Depth, Seabed and Land Cover Using Google Earth Data." ISPRS Int. J. Geo-Inf. 3, no. 4: 1157-1179.