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Optimized watershed delineation library for server-side and client-side web applications
Journal article   Open access   Peer reviewed

Optimized watershed delineation library for server-side and client-side web applications

Muhammed Sit, Yusuf Sermet and Ibrahim Demir
Open Geospatial Data, Software and Standards, Vol.4(1), pp.1-10
08/26/2019
DOI: 10.1186/s40965-019-0068-9
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Published (Version of record)CC BY V4.0 Open Access
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https://doi.org/10.1186/s40965-019-0068-9View
Published (Version of record)Open geospatial data, softw. stand. (2019) 4: 8.

Abstract

Abstract The advancements and new techniques in information technologies are making it possible to acquire large-scale spatial data through satellites, radars and sensor networks. The collection of vast amounts of environmental data increased the demand for applications which can manage and process large-scale and high-resolution data sets in real-time. One of the important tasks for organizing and customizing hydrological data sets is the delineation of watersheds on demand. Watershed delineation is a process for creating a boundary that represents the contributing area for a specific control point or water outlet, with the intent of characterization and analysis of portions of a study area. Although many GIS tools and software are available for watershed analysis on desktop systems, there is a need for optimized libraries for client-side and server-side web applications for creating a dynamic and interactive environment for exploring hydrological data. In this project, we developed and demonstrated several watershed delineation techniques on the web, with seven different use cases implemented on the client-side using JavaScript, WebAssembly, and WebGL and on the server-side using Python, Go, C, and Node.js. We also developed a client-side GPGPU (General Purpose Graphical Processing Unit) algorithm to analyze high-resolution terrain data for watershed delineation by benefiting from the parallelizable nature of GPUs. The web-based real-time analysis of watershed segmentation can be helpful for decision-makers and stakeholders while eliminating the need of installing complex software packages and dealing with large-scale data sets.
Data Compression Web-based visualization Catchment delineation GPGPU OAfund

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