Multisensoral remote sensing for the microclimatic characterisation and 
classification of urban structures

Bechtel, Benjamin

doi:10.1127/1432-8364/2011/0090

Item

ITEM ACTIONSEXPORT

Add to Basket

Local TagsRelease HistoryDetailsSummary

Released

Journal Article

Multisensoral remote sensing for the microclimatic characterisation and classification of urban structures

MPS-Authors

There are no MPG-Authors in the publication available

External Resource

No external resources are shared

Fulltext (restricted access)

There are currently no full texts shared for your IP range.

Fulltext (public)

There are no public fulltexts stored in PuRe

Supplementary Material (public)

There is no public supplementary material available

Citation

Bechtel, B. (2011). Multisensoral remote sensing for the microclimatic characterisation and classification of urban structures. Photogrammetrie Fernerkundung Geoinformation, (5), 325-338. doi:10.1127/1432-8364/2011/0090.

Cite as: https://hdl.handle.net/11858/00-001M-0000-0015-8882-0

Abstract

Multisensoral remote sensing for the microclimatic characterisation and classification of urban structures. Remote sensing can play an important role for the microclimatic characterisation of urban structures. Against the background of relevant climatic properties of urban surfaces (i.e. thermal and aerodynamic) new surface parameters from different datasets for the comprehensive urban climatologic characterisation are developed for the case of Hamburg. The annual cycle of surface temperatures in multitemporal Landsat data is approximated by a sine function. The extracted parameters "Mean Annual Surface Temperature" (MAST) and "Yearly Amplitude of Surface Temperature" (YAST) show substantial distinctions between urban structures and are strongly correlated with a long-term urban heat island (UHI) pattern derived from floristic proxy data. The frequency distribution of heights from an interferometric SAR digital height model (IFSAR-DHM) from Intermap Technologies shows a clear correspondence with the surface roughness. Eventually, it is shown, that the new parameters are suitable for the classification of urban micro-climatic structures.