Level Learning Objectives
Remembering Define remote sensing (RS) principles, including the interaction between electromagnetic radiation and surface/atmosphere.
List types and sources of free remote sensing data, such as optical, radar, and DEMs.
Identify basic GIS and QGIS functions for thematic mapping and RS data processing.
Understanding Explain how vegetation indices (e.g., NDVI) are derived from multispectral data and what they indicate about vegetation health and vigor.
Describe the purpose of thematic maps such as land cover/use, elevation, slope, and temperature maps.
Understand the fundamental hydrological processes behind rainfall-runoff and urban flood modeling.
Applying Use QGIS to download and process free remote sensing data.
Create and interpret thematic maps (e.g., vegetation, slope, temperature) relevant to urban ecosystem monitoring.
Apply the SCS method and runoff calculations to assess flood risks in urban areas.
Operate basic SWMM models using provided datasets to simulate urban flooding and surface changes.
Analyzing Analyze multitemporal satellite and UAV data to detect environmental changes across seasons and years.
Compare vegetation conditions across urban areas using calculated indices and derived maps.
Evaluate the impacts of land surface characteristics (e.g., impermeability, slope) on runoff and flooding scenarios using SWMM and GIS.
Evaluating Assess the ecological status of urban vegetation based on spectral indices and elevation/topographic data.
Critically evaluate the accuracy and limitations of RS data sources and processing techniques.
Review the effectiveness of monitoring systems and their integration into urban water management.
Creating Develop comprehensive thematic map products (e.g., vegetation stress maps, flood risk zones) for urban planning and biodiversity assessment.
Design a scenario using SWMM that integrates rainfall data, land use changes, and mitigation strategies for urban flood protection.
Propose a local hydrological monitoring plan combining remote sensing, GIS analysis, and on-ground sensor networks for a selected urban area.