scholarly journals Detecting Unknown Artificial Urban Surface Materials Based on Spectral Dissimilarity Analysis

Sensors ◽  
2017 ◽  
Vol 17 (8) ◽  
pp. 1826 ◽  
Author(s):  
Marianne Jilge ◽  
Uta Heiden ◽  
Martin Habermeyer ◽  
André Mende ◽  
Carsten Juergens
Keyword(s):  
Urban Surface ◽  
Surface Materials

scholarly journals Temperature Reduction in Urban Surface Materials through Tree Shading Depends on Surface Type Not Tree Species

Forests ◽  
2020 ◽  
Vol 11 (11) ◽  
pp. 1141
Author(s):  
Kaluarachichi T.U.N. ◽  
Tjoelker M.G. ◽  
Pfautsch S.
Keyword(s):  
Urban Space ◽  
Tree Species ◽  
Austral Summer ◽  
Bare Soil ◽  
Urban Surface ◽  
Surface Material ◽  
Free Standing ◽  
Area Index ◽  
Surface Temperatures ◽  
Surface Materials

Trees play a vital role in urban cooling. The present study tested if key canopy characteristics related to tree shade could be used to predict the cooling potential across a range of urban surface materials. During the austral summer of 2018–2019, tree and canopy characteristics of 471 free-standing trees from 13 species were recorded across Greater Sydney, Australia. Stem girth and tree height, as well as leaf area index and ground-projected crown area was measured for every tree. Surface temperatures were recorded between noon (daylight saving time) and 3:00 p.m. under the canopy of each tree in the shade and in full sun to calculate the temperature differential between adjacent sunlit and shaded surfaces (∆Ts). The limited control over environmental parameters was addressed by using a large number of randomly selected trees and measurement points of surface temperatures. Analyses revealed that no systematic relationship existed among canopy characteristics and ∆Ts for any surface material. However, highly significant differences (p < 0.001) in ∆Ts existed among surface materials. The largest cooling potential of tree shade was found by shading bark mulch (∆Ts = −24.8 °C ± 7.1), followed by bare soil (∆Ts = −22.1 °C ± 5.5), bitumen (∆Ts = −20.9 °C ± 5.8), grass (∆Ts = −18.5 °C ± 4.8) and concrete pavers (∆Ts = −17.5 °C ± 6.0). The results indicate that surface material, but not the tree species, matters for shade cooling of common urban surfaces. Shading bark mulch, bare soil or bitumen will provide the largest reductions in surface temperature, which in turn results in effective mitigation of radiant heat. This refined understanding of the capacity of trees to reduce thermal loads in urban space can increase the effectiveness of urban cooling strategies.

scholarly journals THERMAL PROPERTIES OF URBAN SURFACE MATERIALS

1984 ◽  
Vol 57 (9) ◽  
pp. 639-651 ◽  
Author(s):  
Ken-ichi NARITA ◽  
Takeshi SEKINE ◽  
Toshikazu TOKUOKA
Keyword(s):  
Thermal Properties ◽  
Urban Surface ◽  
Surface Materials

scholarly journals Capability of Remote Sensing Images to Distinguish the Urban Surface Materials: A Case Study of Venice City

2021 ◽  
Vol 13 (19) ◽  
pp. 3959
Author(s):  
Rosa Maria Cavalli
Keyword(s):  
Remote Sensing ◽  
Spatial Resolution ◽  
Spectral Range ◽  
Spectral Resolution ◽  
Urban Areas ◽  
Spectral Characteristics ◽  
Urban Surface ◽  
Remote Sensing Images ◽  
Surface Materials ◽  
The Impact

Many countries share an effort to understand the impact of growing urban areas on the environment. Spatial, spectral, and temporal resolutions of remote sensing images offer unique access to this information. Nevertheless, their use is limited because urban surface materials exhibit a great diversity of types and are not well spatially and spectrally distinguishable. This work aims to quantify the effect of these spatial and spectral characteristics of urban surface materials on their retrieval from images. To avoid other sources of error, synthetic images of the historical center of Venice were analyzed. A hyperspectral library, which characterizes the main materials of Venice city and knowledge of the city, allowed to create a starting image at a spatial resolution of 30 cm and spectral resolution of 3 nm and with a spectral range of 365–2500 nm, which was spatially and spectrally resampled to match the characteristics of most remote sensing sensors. Linear spectral mixture analysis was applied to every resampled image to evaluate and compare their capabilities to distinguish urban surface materials. In short, the capability depends mainly on spatial resolution, secondarily on spectral range and mixed pixel percentage, and lastly on spectral resolution; impervious surfaces are more distinguishable than pervious surfaces. This analysis of capability behavior is very important to select more suitable remote sensing images and/or to decide the complementarity use of different data.

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