City development in China


The city of Suqian lies in the Jiangsu Province, East China, and is a typical example of the rapid urban development and growth in that country. Suqian’s development can be traced back to ancient times when it served as a transportation hub along the Grand Canal, connecting northern and southern China. Over the centuries, it evolved into a regional centre for trade and commerce.

In recent decades, Suqian has experienced an economic boom, which is reflected in the satellite images. The GDP grew from 1 billion Euro in 2000 to over 30 billion Euro in 2020. This growth has been driven by investments in industry, agriculture, and technology, with annual export values exceeding 20 billion Euro. The city’s strategic location, excellent infrastructure, and business-friendly policies have attracted over 10,000 domestic and international enterprises.

Suqian has committed itself to sustainable development and green initiatives, including the establishment of over 800 square kilometres of forest coverage and the adoption of renewable energy sources, meeting 30% of its energy needs. Urban planning efforts have already resulted in a reduction in pollution levels and an increase in green spaces.

Diagram: Population development in Suqian.


  • Satellite Map:
    • Looking at the satellite image map, click on the layer selector icon in the upper right and compare the satellite images from 1987, 1999, 2010, and 2023 by switching them on and off.
    • Try to estimate the area of the city in 1987 and in 2023, respectively.
    • By which factor has the area increased?
    • How does this relate with the population increase during this time span? What can this tell about changes in the economic structure (think about industrial halls, which cover large areas without increasing the population)?
    • Green areas in the satellite images are covered with vegetation. What types of vegetated areas do you expect in this environment (e.g. pastures, crop fields, …)?
  • EO Browser:
    • Open the EO Browser.
    • Find the most recent Sentinel-2 dataset covering the area displayed in the satellite map.
    • Select a true colour representation
    • Can you identify additional, recent changes in the area?
    • Select a false colour infrared representation. Can you identify the the most intensely vegetated areas (represented by bright red colours)? Think about agricultural land in the region.

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