Gennadii Donchyts

A 30 m Resolution Surface Water Mask Including Estimation of Positional and Thematic Differences Using Landsat 8, SRTM and OpenStreetMap: A Case Study in the Murray-Darling Basin, Australia

Accurate maps of surface water are essential for many environmental applications. Surface water maps can be generated by combining measurements from multiple sources. Precise estimation of surface water using satellite imagery remains a challenging task due to the sensor limitations, complex land cover, topography, and atmospheric conditions. As a complementary dataset, in the case of hilly landscapes, a drainage network can be extracted from high-resolution digital elevation models. Additionally, Volunteered Geographic Information (VGI) initiatives, such as OpenStreetMap, can also be used to produce high-resolution surface water masks. In this study, we derive a high-resolution water mask using Landsat 8 imagery and OpenStreetMap as well as (potential) a drainage network using 30 m SRTM. Our approach to derive a surface water mask from Landsat 8 imagery comprises the use of a lower 15% percentile of Landsat 8 Top of Atmosphere (TOA) reflectance from 2013 to 2015. We introduce a new non-parametric unsupervised method based on the Canny edge filter and Otsu thresholding to detect water in flat areas. For hilly areas, the method is extended with an additional supervised classification step used to refine the water mask. We applied the method across the Murray-Darling basin, Australia. Differences between our new Landsat-based water mask and the OpenStreetMap water mask regarding positional differences along the rivers and overall coverage were analyzed. Our results show that about 50% of the OpenStreetMap linear water features can be confirmed using the water mask extracted from Landsat 8 imagery and the drainage network derived from SRTM. We also show that the observed distances between river features derived from OpenStreetMap and Landsat 8 are mostly smaller than 60 m. The differences between the new water mask and SRTM-based linear features and hilly areas are slightly larger (110 m). The overall agreement between OpenStreetMap and Landsat 8 water masks is about 30%.

Rapid setup of hydrological and hydraulic models using OpenStreetMap and the SRTM derived digital elevation model

A stepwise procedure has been developed in Python to extract information from OpenStreetMap (OSM) for hydrological and hydraulic models using existing and newly developed tools. The procedure focuses on the extraction of paved areas and water bodies. Road density is used to fill in gaps in OSM polygon coverage. Furthermore, it includes automatic downloading of Shuttle Radar Topography Mission (SRTM) elevation data and improving the elevation model with man-made landscape features such as elevated roads that are sampled from OSM. This is useful for hydraulic modelling in data scarce flood plain areas, where sharp elevation differences are dominated by man-made elevated elements. Test cases in Europe, South East Asia and East Africa demonstrate the potential of the procedure, although large differences in completeness of OSM coverage suggest it is best used in combination with other data sources. A tool is presented that extracts data for hydrological modelling from OpenStreetMap.Extracted impervious area shows good correlation with existing sources in Europe.Extracted road density is a good proxy to detect urbanized areas.

A Comparison between WCS and OPeNDAP for Making Model Results and Data Products Available through the Internet

Numerical models produce output with a large number of variables, grid cells and time steps. The same applies to algorithms that produce gridded datasets from sparse or abundant raw data. Further use of the resulting data products has been challenging, especially for dissemination outside the institute of origin. Due to the gradually increasing size of data products, simply downloading copies of them is becoming impossible. A gradual transition from traditional download methods to web services is therefore observed. Web services allow for on-the-fly access to subsets of data that were hitherto considered as indivisible granules. Here we compare the most mature candidates to serve gridded data through the web: the Open-source Project for a Network Data Access Protocol (OPeNDAP) and Web Coverage Service (WCS) protocols. In the framework of the new Dutch National Model and Data Centre (NMDC.eu) a distributed data storage has been created by coupling OPeNDAP servers. A WCS service layer is provided for the same data. This allows us to compare OPeNDAP and WCS. Using several use cases, we compare the usability, performance and features of the two protocols.

The State of the World’s Beaches

Coastal zones constitute one of the most heavily populated and developed land zones in the world. Despite the utility and economic benefits that coasts provide, there is no reliable global-scale assessment of historical shoreline change trends. Here, via the use of freely available optical satellite images captured since 1984, in conjunction with sophisticated image interrogation and analysis methods, we present a global-scale assessment of the occurrence of sandy beaches and rates of shoreline change therein. Applying pixel-based supervised classification, we found that 31% of the world’s ice-free shoreline are sandy. The application of an automated shoreline detection method to the sandy shorelines thus identified resulted in a global dataset of shoreline change rates for the 33 year period 1984–2016. Analysis of the satellite derived shoreline data indicates that 24% of the world’s sandy beaches are eroding at rates exceeding 0.5 m/yr, while 28% are accreting and 48% are stable. The majority of the sandy shorelines in marine protected areas are eroding, raising cause for serious concern.

Author Correction: The State of the World’s Beaches

A correction to this article has been published and is linked from the HTML and PDF versions of this paper. The error has not been fixed in the paper.