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A Framework for the Long-term Monitoring of Urban Green Volume Based on Multi-temporal and Multi-sensoral Remote Sensing Data

  • Annett FrickEmail author
  • Steffen Tervooren
Article
  • 12 Downloads

Abstract

Green urban infrastructure is of key importance for many aspects of urban life and urban planning. Valid and comprehensive databases with very high spatial and temporal resolution are needed to monitor changes and to detect negative trends. This paper presents an approach to assess urban indicators such as green volume and soil sealing with very high accuracy and based on a wide range of different sensors (aerial stereo images, QuickBird, WorldView 2 and 3, Sentinel 2, HRSC, LIDAR). A framework using regression tree methods was developed and successfully applied in a case study (the city of Potsdam, Germany) resulting in a long time series dating back 25 years. The methodology offers the opportunity to analyze urban development in detail and to understand the functional relationships of urban planning processes. Demands for effective climate change adaptation, especially in terms of reducing heat stress, can thus be better defined.

Keywords

Urban green volume Remote sensing Monitoring Stereo matching 

Notes

Funding

The authors thank the city of Potsdam for financing the study.

Compliance with Ethical Standards

We comply with ethical standards.

Conflict of Interest

The authors declare that they have no conflict of interest.

Ethical Approval

Our research did not involve human participants.

Informed Consent

Our research did not involve human participants.

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.LUP GmbHPotsdamGermany
  2. 2.State Capital Potsdam, Environment and NaturePotsdamGermany

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