An automatic water detection approach using Landsat 8 OLI and Google Earth Engine cloud computing to map lakes and reser
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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 Uyen N. T. Nguyen Thanh Duc Dang
&
Lien T. H. Pham &
Received: 19 July 2018 / Accepted: 1 March 2019 # Springer Nature Switzerland AG 2019
Abstract 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 Bbig 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
U. N. T. Nguyen (*) Environmental Research Institute, The University of Waikato, Hamilton, New Zealand e-mail: [email protected] L. T. H. Pham HCMC University of Science, Vietnam National University, Ho Chi Minh City, Vietnam T. D. Dang Institute for Water and Environment Research, Thuy Loi University, Ho Chi Minh City, Vietnam
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. Keywords Automatic water extraction index . Google Earth Engine . Water surface . New Zealand . Landsat 8 OLI
Introduction Modifications to surface water dynamics can result in alterations to lentic and lotic water cycles (Wood et al. 2011). Monitoring is extremely important since any modifications can alter water quality and quantity, water availability, and the functional and physical processes of ecosystem (Cann et al. 2013; Dang et al. 2016). It is, therefore, important to have an accurate and precise water surface mapping method to improve large-scale water management. Before the remote sensing era, the ground survey was the only method available. While this traditional method was costly and time-consuming, results were not always spatially accurate. Remote sensing provides a spatial and temporal technique capable of tracing a historical record; therefore, it is useful for monitoring lake information over a time period in areas not having a ground-based monitoring program. There were extensive efforts to monitor the dynamics of
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