Derivation of an urban materials spectral library through emittance and reflectance spectroscopy

Kotthaus, Simone; Smith, Thomas E. L.; Wooster, Martin J.; Grimmond, Sue

doi:10.1016/j.isprsjprs.2014.05.005

Cited by 164 publications

(131 citation statements)

References 58 publications

Supporting

Mentioning

104

Contrasting

Unclassified

Order By: Relevance

“…Air temperature-humidity values were obtained by means of a pocket thermo-hygrometer. When the analyzed site was accessible (case studies 1, 2 and 3) experimental laboratory emissivity tests were performed on the rock samples, according to the FLIR systems recommendations [65] and the work of [66], showing a good accordance with bibliographic data [67,68]. Some of the research activities were performed in order to support local authorities in the framework of the post-hydrogeological disaster activities led by the Italian National Department of Civil Protection.…”

Section: Methodsmentioning

confidence: 99%

“…While the last variables are easily obtainable in the field (by means of a thermo hygrometer and a distometer) emissivity can vary according to several factors: (i) the material surface roughness (the greater the roughness compared to the size of the incident wavelength, the greater the absorption and emission); (ii) the moisture content (the more moisture contained within an object, the greater its ability to absorb and emit); (iii) the viewing angle from which the object is surveyed [89][90][91][92][93]. In most applications, the emissivity of an object is based on values found in tables and literature (in many cases also the camera firmware has its own emissivity table) [67,68]. However, when reasonably precise material emissivity values are needed it is possible to use an empirically developed approach to obtain them [65,66].…”

Section: Irt Surveying Technical and Logistical Contraintsmentioning

confidence: 99%

See 1 more Smart Citation

Landslide Mapping and Characterization through Infrared Thermography (IRT): Suggestions for a Methodological Approach from Some Case Studies

et al. 2017

View full text Add to dashboard Cite

Abstract:In this paper, the potential of Infrared Thermography (IRT) as a novel operational tool for landslide surveying, mapping and characterization was tested and demonstrated in different case studies, by analyzing various types of instability processes (rock slide/fall, roto-translational slide-flow). In particular, IRT was applied, both from terrestrial and airborne platforms, in an integrated methodology with other geomatcs methods, such as terrestrial laser scanning (TLS) and global positioning systems (GPS), for the detection and mapping of landslides' potentially hazardous structural and morphological features (structural discontinuities and open fractures, scarps, seepage and moisture zones, landslide drainage network and ponds). Depending on the study areas' hazard context, the collected remotely sensed data were validated through field inspections, with the purpose of studying and verifying the causes of mass movements. The challenge of this work is to go beyond the current state of the art of IRT in landslide studies, with the aim of improving and extending the investigative capacity of the analyzed technique, in the framework of a growing demand for effective Civil Protection procedures in landslide geo-hydrological disaster managing activities. The proposed methodology proved to be an effective tool for landslide analysis, especially in the field of emergency management, when it is often necessary to gather all the required information in dangerous environments as fast as possible, to be used for the planning of mitigation measures and the evaluation of hazardous scenarios. Advantages and limitations of the proposed method in the field of the explored applications were evaluated, as well as general operative recommendations and future perspectives.

show abstract

Section: Methodsmentioning

confidence: 99%

Section: Irt Surveying Technical and Logistical Contraintsmentioning

confidence: 99%

Landslide Mapping and Characterization through Infrared Thermography (IRT): Suggestions for a Methodological Approach from Some Case Studies

et al. 2017

View full text Add to dashboard Cite

show abstract

“…If the surface is a grey body, knowledge of the surface emissivity ε and incoming longwave radiation is required to translate T B into T 0 . The surface emissivity varies widely with materials in urban systems (Kotthaus et al, 2014) as does incoming longwave radiation on different facets as not only sky radiation, but also emittance from neighbouring facets is intercepted. Differences in emissivities in urban systems can cause differences of up to 7 K between T B and T 0 (Voogt and Oke, 1997).…”

Section: Introductionmentioning

confidence: 99%

The effect of radiometer placement and view on inferred directional and hemispheric radiometric temperatures of an urban canopy

2015

View full text Add to dashboard Cite

Abstract. Any radiometer at a fixed location has a biased view when observing a convoluted, three-dimensional surface such as an urban canopy. The goal of this contribution is to determine the bias of various sensors views observing a simple urban residential neighbourhood (nadir, oblique, hemispherical) over a 24 hour cycle under clear weather conditions. The error in measuring a longwave radiation flux density (L) and/or inferring surface temperatures (T 0 ) is quantified for different times over a diurnal cycle. Panoramic time-sequential thermography (PTST) data were recorded by a thermal camera on a hydraulic mast above a residential canyon in Vancouver, BC. The data set resolved sub-facet temperature variability of all representative urban facets in a 360• swath repetitively over a 24-hour cycle. This data set is used along with computer graphics and vision techniques to project measured fields of L for a given time and pixel onto texture sheets of a three-dimensional urban surface model at a resolution of centimetres. The resulting data set attributes L of each pixel on the texture sheets to different urban facets and associates facet location, azimuth, slope, material, and sky view factor. The texture sheets of L are used to calculate the complete surface temperature (T 0,C ) and to simulate the radiation in the field of view (FOV) of narrow and hemispheric radiometers observing the same urban surface (in absence of emissivity and atmospheric effects). The simulated directional (T 0,d ) and hemispheric (T 0,h ) radiometric temperatures inferred from various biased views are compared to T 0,C . For a range of simulated off-nadir (φ) and azimuth ( ) angles, T 0,d (φ, ) and T 0,C differ between −2.6 and +2.9 K over the course of the day. The effects of effective anisotropy are highest in the daytime, particularly around sunrise and sunset when different views can lead to differences in T 0,d (φ, ) that are as high as 3.5 K. For a sensor with a narrow FOV in the nadir of the urban surface, T 0,d (φ = 0) differs from T 0,C by +1.9 K (day) and by −1.6 K (night).Simulations of the FOV of hemispherical, downwardfacing pyrgeometers at 270 positions show considerable variations in the measured L and inferred hemispherical radiometeric temperature T 0,h as a function of both horizontal placement and height. The root mean squared error (RMSE) between different horizontal positions in retrieving outgoing longwave emittance L ↑ decreased exponentially with height, and was 11.2, 6.3 and 2.0 W m −2 at 2, 3, and 5 times the mean building height z b . Generally, above 3.5 z b the horizontal positional error is less than the typical accuracy of common pyrgeometers. The average T 0,h over 24 h determined from the hemispherical radiometer sufficiently above an urban surface is in close agreement with the average T 0,C . However, over the course of the day, the difference between T 0,h and T 0,C shows an RMSE of 1.7 K (9.4 W m −2 ) because the relative contributions of facets within the projected FOV of a pyrgeometer do not co...

show abstract

“…1.1.3 Weather models Very fine knowledge concerning urban land cover (in terms of materials, perviousness and vegetation) are required by micro weather (wind, temperature, ...) model simulators (Heldens et al, 2011, Heldens et al, 2010, Kotthaus et al, 2014.…”

Section: Some Needs For Urban Materials Mapsmentioning

confidence: 99%

Spectral Band Selection for Urban Material Classification Using Hyperspectral Libraries

Bris¹,

Chehata²,

Briottet³

et al. 2016

ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci.

View full text Add to dashboard Cite

ABSTRACT:In urban areas, information concerning very high resolution land cover and especially material maps are necessary for several city modelling or monitoring applications. That is to say, knowledge concerning the roofing materials or the different kinds of ground areas is required. Airborne remote sensing techniques appear to be convenient for providing such information at a large scale. However, results obtained using most traditional processing methods based on usual red-green-blue-near infrared multispectral images remain limited for such applications. A possible way to improve classification results is to enhance the imagery spectral resolution using superspectral or hyperspectral sensors. In this study, it is intended to design a superspectral sensor dedicated to urban materials classification and this work particularly focused on the selection of the optimal spectral band subsets for such sensor. First, reflectance spectral signatures of urban materials were collected from 7 spectral libraires. Then, spectral optimization was performed using this data set. The band selection workflow included two steps, optimising first the number of spectral bands using an incremental method and then examining several possible optimised band subsets using a stochastic algorithm. The same wrapper relevance criterion relying on a confidence measure of Random Forests classifier was used at both steps. To cope with the limited number of available spectra for several classes, additional synthetic spectra were generated from the collection of reference spectra: intra-class variability was simulated by multiplying reference spectra by a random coefficient. At the end, selected band subsets were evaluated considering the classification quality reached using a rbf svm classifier. It was confirmed that a limited band subset was sufficient to classify common urban materials. The important contribution of bands from the Short Wave Infra-Red (SWIR) spectral domain (1000 -2400 nm) to material classification was also shown.

show abstract

Derivation of an urban materials spectral library through emittance and reflectance spectroscopy

Cited by 164 publications

References 58 publications

Landslide Mapping and Characterization through Infrared Thermography (IRT): Suggestions for a Methodological Approach from Some Case Studies

Landslide Mapping and Characterization through Infrared Thermography (IRT): Suggestions for a Methodological Approach from Some Case Studies

The effect of radiometer placement and view on inferred directional and hemispheric radiometric temperatures of an urban canopy

Spectral Band Selection for Urban Material Classification Using Hyperspectral Libraries

Contact Info

Product

Resources

About