Urban Areas

Image: New York (USA), DESIS / ISS RGB (639 nm, 550 nm, 470 nm)
Source: DLR/Teledyne Brown

The world is currently experiencing rapid urbanization and an increase in the number of megacities, particularly in developing countries. According to the United Nations Development Program, urban population growth will continue over the next decades, though at decreasing growth rates (UN, 2022). The process of urbanization always results in changes in land use and cover and causes serious problems, such as environmental pollution, destruction of ecosystems, and waste disposal.

Reliable surface material indicators are needed for urban climate studies and other approaches that require knowledge on the biophysical properties of urban land cover. Remote sensing data is used more and more to study the urban climate at meso and macro scales. Especially physical properties of urban areas, such as reflection, absorption, emissivity, specific heat capacity, but also height and spatial arrangement of urban objects, are needed to parameterize climate models. the synergistic use of hyperspectral, thermal, and optical data with advanced data analysis techniques may result in enhanced socioeconomic and environmental indicators to model urban dynamics and their social and environmental consequences.

Accordingly, main scientific tasks related to urban areas include:

  • Mapping and monitoring of urbanization and its dynamics with high spectral detail worldwide;
  • Development of comprehensive urban spectral libraries for universal urban land-cover mapping based on EnMAP data;
  • Development and improvement of classification algorithms to quantify urban land cover, including classes that are spectrally ambiguous in multispectral data;
  • Investigation of new concepts for information extraction based on spectral mixtures;
  • Application and extension of the V-I-S concept to produce biophysical surface maps with respect to the needs of urban environmental process models, e.g., on urban climate and hydrology; and
  • Mapping of the abundance of hazardous materials such as asbestos, e.g., in the context of risk analyses.
This website doesn't support
Internet Explorer

please open using Chrome, Firefox or Safari or another modern browser