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An automatic water detection approach using Landsat 8 OLI and Google Earth Engine cloud computing to map lakes and reservoirs in New Zealand

Nguyen, Uyen N. T., Pham, Lien T. H., Dang, Thanh Duc
Environmental monitoring and assessment 2019 v.191 no.4 pp. 235
Internet, Landsat, aerial photography, case studies, climate, cloud computing, humans, lakes, land cover, land use, monitoring, temporal variation, water reservoirs, New Zealand
Monitoring water surface dynamics is essential for the management of lakes and reservoirs, especially those are intensively impacted by human exploitation and climatic variation. Although modern satellites have provided a superior solution over traditional methods in monitoring water surfaces, manually downloading and processing imagery associated with large study areas or long-time scales are time-consuming. The Google Earth Engine (GEE) platform provides a promising solution for this type of “big data” problems when it is combined with the automatic water extraction index (AWEI) to delineate multi-temporal water pixels from other forms of land use/land cover. The aim of this study is to assess the performance of a completely automatic water extraction framework by combining AWEI, GEE, and Landsat 8 OLI data over the period 2014–2018 in the case study of New Zealand. The overall accuracy (OA) of 0.85 proved the good performance of this combination. Therefore, the framework developed in this research can be used for lake and reservoir monitoring and assessment in the future. We also found that despite the temporal variability of climate during the period 2014–2018, the spatial areas of most of the lakes (3840) in the country remained the same at around 3742 km². Image fusion or aerial photos can be employed to check the areal variation of the lakes at a finer scale.