Green in the City

 

Content

The Green in the City project, developed for high school teachers of grade 11 and 12, will enable you as a teacher to engage your students in exploring the potential of satellite images for environmental analysis. Your students will explore the basic principles of remote sensing in a step-by-step approach. Using QGIS, they will map urban green and analyze the distribution of green spaces across different neighborhoods.

Besides satellite images, a variety of other data are provided, including population density and income levels, enabling the students to examine spatial relationships. Questions such as whether wealthier neighborhoods are better endowed with green spaces than poorer ones, and the impact of greenery on urban temperatures, will be analyzed.

The application of GIS within an urban and environmental framework allows for addressing themes such as spatial planning, environmental challenges, the urban heat island effect, and social inequality in cities. This approach also facilitates skill development. As a teacher you can challenge your students in formulating research questions using the available data, enhancing their understanding of how spatial data can be used to map urban environments and recommend specific improvements.

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Project structure

The Green in the City workshop is structured into three distinct parts:

• Part 1: Students will create a vegetation map of the city using satellite images to assess the extent of greenery and its distribution within the urban landscape.
• Part 2: The analysis progresses as students compare the spatial distribution of green spaces within the city to temperature data.
• Part 3: The focus shifts to examining the relationship between vegetation cover, temperature, and various socio-economic factors.

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Project materials

The Green in the City project provides a series of materials carefully designed to support both students and teachers. Firstly, we offer worksheets for the students. These worksheets consist of a series of tasks preceded by instructional videos. This combination ensures that students are guided step-by-step through the material and learn in an interactive way.

For teachers, there is an extensive manual available. This manual provides substantive support and contains practical tips and advice to avoid common pitfalls. The aim is to provide you extra support, so that you can effectively guide your students through the project.

Additionally, there is a technical manual included in the project materials. This manual contains detailed installation instructions for QGIS and directions for preparing PCs for use. This ensures that both students and teachers can get started on the tasks without technical issues.

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Data

The project provides satellite imagery and socio-economic data for the city of Atlanta and for Toronto:

1. Landsat-8 Land Surface Temperature (LST)
    
   This data is derived from the Landsat-8 satellite, which captures thermal infrared radiation to compute the land surface temperature. LST data is crucial for analyzing microclimates within cities, understanding urban heat islands, and assessing the effects of vegetation on temperature regulation. The spatial resolution of 60m of Landsat-8 LST data enables detailed study of temperature over large areas, providing insights into temperature variations across different urban and rural landscapes.
2. Sentinel-2 optical data
   
   Sentinel-2 provides 10m resolution optical images in multiple spectral bands. This data is instrumental for vegetation mapping, land cover classification, and monitoring environmental changes. The multispectral capabilities of Sentinel-2 are particularly valuable for distinguishing between different types of vegetation and assessing vegetation density and health. This can be correlated with urban planning and environmental assessments.
3. Census Tracts with Associated Socio-Economic Data
   
   The project datasets also include demographic and economic data at the level of census tracts, which are small subdivisions of a county or equivalent entity. Census data typically encompasses information such as population density, income level, educational attainment, and employment statistics. Such data is essential for understanding the social fabric of the areas under study and can be used to analyze correlations between socio-economic factors and environmental data like vegetation cover and land surface temperature.

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Downloads

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Contact

If you need more information, you can contact info@green-in-the-city.be.

This workshop is designed and curated by

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