EnviReader

The ENVI-met webReader is a cutting-edge web-based solution designed for advanced environmental data analysis and visualization of EDX/EDT files produced by ENVI-met. Built on a modular ES6 framework, it offers a robust and adaptable architecture for seamless integration of various components and future scalability. The user interface focuses on user experience, offering light and dark mode options and a comprehensive feature set for efficient data management, representation, and comparative analysis. Key capabilities include: Sophisticated data manipulation tools (filtering, aggregation, statistical analysis). Powerful visualization components (charts, 3D renderings, interactive maps). Comparative analysis tools for juxtaposing datasets and deriving insights. Local file handling, enabling users to open EDX/EDT files directly on their computer without the need for uploading or transferring data, ensuring instant access and maintaining data privacy. Integration with ECharts elevates the user experience, providing dynamic, interactive visualizations such as line graphs, scatter plots, and heatmaps. The system is optimized through data caching and performance techniques for a smooth, responsive user experience. Designed for environmental scientists, urban planners, and decision-makers, the ENVI-met webReader is a robust tool for handling complex environmental data. Project Objectives Develop a web-based platform for efficient analysis and visualization of EDX/EDT files produced by ENVI-met. Create a modular ES6 framework for a robust, adaptable architecture with seamless integration and scalability. Design an intuitive user interface with light and dark modes, comprehensive data management, and comparative analysis tools. Implement advanced data manipulation tools for filtering, aggregation, and statistical analysis. Integrate charting and visualization components (charts, 3D renderings, interactive maps) for meaningful data representation. Enable instant local file handling, allowing users to open and analyze files directly on their device without data upload or server interaction. Leverage ECharts for dynamic, interactive data visualizations, including customizable chart types. Develop tools for data comparison, highlighting differences with customizable color schemes and palette inversion. Optimize performance through data caching and efficient DOM manipulation for a responsive user experience. Create an adaptive, responsive layout for various screen sizes and devices. Add terrain-following and wind integration for enhanced environmental data analysis. Develop a centralized state management system to maintain data integrity across the application. Implement advanced wind visualization features, including opacity, density controls, and animations. Optimize rendering with lazy loading and other techniques for improved performance. Provide data export capabilities for interdisciplinary collaboration.