Determination of Concrete Properties Using … · Determination of Concrete Properties Using Hyperspectral Imaging Technology: A ... The spectral signature is a unique spectral reflectance

Hyperspectral remote sensing images were used todevelop a method of oil-gas exploration (Tian, 2012). Theresearcher, (Tian, 2012), found that the oil-gas reservoirscan be detected directly by the absorption bands near1730 nm in hyperspectral images. In addition, hediscovered that thin oil silk of microseepage could beextracted using spectral angle matching of alterationmineral. Hyperspectral images include large data sets, butinterpreting them requires an understanding of exactlywhat properties of materials that we are trying tomeasure and how they relate to the measurementsactually made by the hyperspectral sensor (camera).Therefore, the purpose of this paper is to provide anintroduction to the fundamental concepts in the field ofhyperspectral imaging and review some applications ofhyperspectral imaging technology in determining concreteproperties.

2.0 Basic Principles of Spectral Imagery

2.1 Electromagnetic Spectrum

The electromagnetic spectrum is the entire range ofelectromagnetic radiation extending in frequency fromhigh‑energy waves (10²¹ Hz) to low‑energy waves (10⁵ Hz).The electromagnetic spectrum is divided into five majortypes of radiation. As shown in Figure (1), these includeradio waves (including microwaves, FM, TV, Shortwave, andAM), light (including ultraviolet, visible, and infrared), heatradiation, X-rays, and gamma rays. Your eye can detect onlypart of the light spectrum (BBC, 2006). The visible light ofthe electromagnetic radiation which is near the center ofthe spectrum extends from 400 nm to 700 nm. It is only avery small part of the overall range of wavelengths inthe spectrum. While, the other electromagnetic radiationwhich range from shortest wavelengths (10-¹⁴) m (gammarays) to longest wavelengths (10⁴) m (AM radio waves)span a wider range of wavelengths than does visiblelight. For instance, the infrared range includes a broadrange of wavelengths. Infrared range includes a broadrange of wavelengths. It begins just above the longestwaves in the visible portion (red) and extends up to thewavelength range that is used for communication.Infrared wavelengths range from about 700 nm up to1 mm. The part of the range closest to the visiblespectrum is called near infrared and the longerwavelength part is called far infrared (Space ComputerCorporation, 2007).

Science Journal of Civil Engineering & Architecture Published ByISSN: 2276-6332 Science Journal Publicationhttp://www.sjpub.org/sjcea.html International Open Access Publisher© Author(s) 2013. CC Attribution 3.0 License.

Research Article Volume 2013, Article ID sjcea-102, 11 Pages, 2013. doi: 10.7237/sjcea/102

Determination of Concrete Properties Using Hyperspectral Imaging Technology: AReview

Alaa Shaban

PhD Candidate in Civil Engineering, Florida Institute of Technology, Melbourne, FL 32901, USA

Accepted 22th May, 2013

Abstract

The strength and durability of concrete are the mostessential parameters for determining structuralperformance of any concrete structure. Thus, there hasbeen always a need to develop an appropriate test methodto evaluate and identify concrete properties in variousstructural members. In recent years, several researchershave strived to exploit hyperspectral technology as a nondestructive test method for assessing properties ofconcrete structures in-situ. In this test method, thereflectance radiations across the visible near-infrared andshortwave-infrared (VI-NIR & SWIR) in the regionbetween (350 - 2500) nm were utilized as an approach topredict unknown concrete properties. The application ofhyperspectral measurements are becoming moresignificant for the cost effective coverage of large concreteareas and can provide accurate predictions of concreteproperties relatively quickly compared to traditionalfield sampling and subsequent experimental testsunder laboratory conditions. This paper presents thefundamental elements of hyperspectral technology anddiscusses the possibility of utilizing hyperspectral imagingsensors for detecting characteristics of concrete structuresin-situ.

Keywords: Hypespectral, Spectrometer, Concrete, Reflectance,Imaging Spectroscopy, Spectral Signature

1.0 Introduction

Hyperspectral imaging is a relatively new technology thathas been utilized by researchers and scientists for severalapplications, including mineral identification, vegetationclassification, land cover exploration, atmosphericmonitoring, and target detection. All of these applicationsdepend on a material having a spectral (Finger-Print) thatcan be collected as a set of images for measurementpurposes.

The prefix (hyper) in hyperspectral means "over", andindicates to a vast number of measured spectral bands ofelectromagnetic radiation. Hyperspectral images arespectrally over determined, which implies that theyprovide extensive spectral information to detect andidentify spectrally a wide variety of materials (Shippert,2012). For instance, hyperspectral imaging technology hasbeen used by agricultural engineers, (Detar et al, 2008), todetect in-field distribution of soil properties with airbonehyperspectral measurements of bare fields.

Corresponding Author: Alaa ShabanPhD Candidate in Civil Engineering, Florida Institute of Technology, Melbourne, FL 32901, USA Email:[email protected]

mailto:[email protected]

2.2 Spectral Signature

When electromagnetic radiation hits an object, thewavelengths may be reflected, absorbed or transmittedthrough the object. The following schematic, Figure (2),depicts these three processes. In fact, reflection,absorption and transmission electromagnetic radiationsthrough objects depend mainly on physical properties andchemical composition of the objects and wavelengths ofthe radiations. So, for any given material, the amount ofelectromagnetic radiation that is reflected, emitted,transmitted or absorbed varies with the wavelength of theradiation. If the percentage of reflection or emissivity for agiven material is plotted across a range of wavelengths,the resulting curve is referred to as a spectral signature

for that material (Vagni, 2007). The spectral signature is aunique spectral reflectance of an object that can be usedto identify and discriminate different types of materials.As an example, Figure (3) shows the reflectance spectra(i.e. the percentage of reflected electromagnetic radiation)measured by laboratory spectrometer for four materials:granite, concrete, asphalt and basalt. Each object’sreflectance is plotted on the chart as a function ofwavelength; such a chart is known as a spectral signature.Field and laboratory spectrometers usually measurereflectance at many narrow, closely spaced wavelengthbands, so that the resulting spectra appear to becontinuous curves.

Science Journal of Civil Engineering & Architecture (ISSN: 2276-6332) page 2

,

Fig. (1): Electromagnetic Spectrum

(Adapted: Space Computer Corporation, 2007)

Fig. (2): a. Reflection b. Absorption c. Transmission

(Adapted: Space computer Corporation, 2007)

a b c

How to Cite this Article: Alaa Shaban "Determination of Concrete Properties Using Hyperspectral Imaging Technology: A Review" Science Journal of CivilEngineering and Architecture, Volume 2013, Article ID sjcea-102, 11 Pages, 2013. doi: 10.7237/sjcea/102

Page 3 Science Journal of Civil Engineering & Architecture (ISSN: 2276-6332)

Fig. (3): Reflectance spectra measured by laboratory spectrometers for four materials:granite, concrete, asphalt & basalt

(Adapted: Randall, 2012)

2.3 Hyperspectral Data

Most conventional multispectral imagers measure reflectedenergy from a surface at a few wide wavelength bandsseparated by segments where no measurements are taken.Typically, multispectral imagers yield between 3 and 10different band measurements in each pixel of their images.On the other hand, hyperspectral imagers measure reflectedradiation at a series of narrow and contiguous wavelengthbands. Hyperspectral images can include more than 200 ofnarrow contiguous spectrum bands. Therefore, this type ofdetailed pixel spectrum can provide more information about

Fig. (4): Reflectance spectra of the four materials; on the left: as they would appear to themultispectral sensor; on the right as they would appear to the hyperspectral sensor

(Adapted: Shippert, 2004)

surface than is available in traditional multispectral pixelspectrum (Shippert, 2004). Also, hyperspectral data sets allowan almost complete reconstruction of the spectralsignature: the retrieved spectrum for each pixel appearsvery much like the spectrum that would be measured in aspectroscopy laboratory. This concept is illustrated in theFigure (4), which typifies the reflectance spectra of fivematerials as they would appear to a multispectral sensorand to hyperspectral sensor.

Wavelength (micrometer)

Ref

lect

ance

(%

)


Science Journal of Civil Engineering & Architecture (ISSN: 2276-6332) Page 4

It is important to underline that, although mosthyperspectral sensors measure hundreds of wavelengthbands, it is not the number of measured wavelengths thatdefines a sensor as hyperspectral. Rather it is thenarrowness and contiguous nature of the measurements.Hyperspectral imagery provides an opportunity for moredetailed image analysis. Using hyperspectral data, spectrallysimilar (but unique) materials can be identified anddistinguished and sub-pixel scale information can beextracted (Andreoli et al, 2007).

2.4 Spectral Libraries

Several spectral libraries include wide collections ofreflectance spectra of different types of materials. These highquality libraries provide valuable information for manyinvestigators who collect spectral libraries for materials intheir sites as part of every project, to facilitate analysis ofmultispectral or hyperspectral imagery from those sites. Thefollowing libraries are the most trusted and comprehensivemass spectral libraries in the world that use foridentification and quantification hyperspectral images:

● ASTER Spectral Library: This library has beendeveloped by NASA as part of the AdvancedSpaceborne Thermal Emission Reflection Radiometer(ASTER) imaging instrument program. ASTER whichwas first released in 1998 contains a compilation ofover 2400 spectra of natural and manmade materials.Many of the spectra cover the entire wavelength regionfrom 0.4 to 14 μm (Baldridge et al, 2009).

Fig. (5): The Concept of Imaging Spectroscopy

(Adapted: Shaw & Burke, 2003)

● USGS Spectral Library : This library has been developedby United States Geological Survey. This digital spectrallibrary which covers the wavelength range from ultravioletto far infrared parts of electromagnetic spectrum provides asource of reference spectra that can be used to supportimaging spectroscopy studies of the Earth and planets(Ranadall, 2012).

3.0 Hyperspectral Sensor

3.1 Imaging Spectroscopy

Imaging spectroscopy is a simultaneous acquisition ofimages in many relatively narrow and contiguous spectralbands, encompassing the visible, the near-infrared (NIR) andshortwave infrared (SWIR) regions of electromagneticspectrum. Consequently, applying this concept results inquantitative and qualitative characterization of both thesurface and the atmosphere, using geometrically coherentspectro-radiometric measurements that can be used toidentify and map individual materials (Michael et al, 2006).

The schematic illustration of the imaging spectroscopyconcept is shown in Figure (5). As shown in this figure, anairborne or spaceborne imaging sensor simultaneouslysamples multiple spectral wavebands over a large area in aground-based scene. After appropriate processing, spectralinformation in the resulting images provides a completereflectance spectrum for every pixel in the imagingspectrometer scene, which can be interpreted to identify anddetect the materials present in the scene. The graphs in theFigure (5) clarify the spectral variation in reflectance forsoil, water, and vegetation.



3.2 Imaging Spectrometer

An imaging spectrometer, spectroradiometer, is aninstrument used in the field of imaging spectroscopy toacquire spectral measurements of a light reflected from anobject. An optical dispersing element such as refractingprism in the spectrometer splits this light into many narrow,adjacent wavelength bands and the energy in each band ismeasured by a separate detectors. By using detectionsystem, spectrometers can make spectral measurements ofbands as narrow as 0.01 micrometers over a widewavelength range, typically at least 350 to 2400 nm (visiblethrough middle infrared wavelength ranges) (Randall,2012).

Data from imaging spectrometers are usually reported inunits of reflectance. As stated previously, reflectance is aphysical property of an object's surface. It is defined as thepercentage of total amount of radiation reflected by asurface to the total amount of electromagnetic radiationincident on the surface. Reflectance can be presented ina variety of ways depending upon the direction of incidentradiation and it characteristics and the type ofspectrometer. The two most common types of reflectanceused in remote sensing include directional-hemisphericalreflectance and bi-directional reflectance. Directional-hemispherical reflectance is typically determined in thelaboratory by utilizing a collimated beam as the directional

Table 1: Ground Based / Hand Held Systems (Adapted from: Vagni, 2007)

NameManufacturer Country Number of Bands Spectral Range

(µm) Spectral

GALAAD(Prototype)

ATIS(France) / 7.0 – 14.0 Double grating

with needle mask

CTHIS LWIR SSC(USA) 40 6.5 – 11.0 Rotating prism

CTHIS MWIR SSC(USA)

62 2.7 – 5.0Rotating prism

ImSpector N10 Spectral ImagingLtd. (Finland)

Spectral resol. 5.0nm 0.7 – 1.0 Prism-Grating-

Prism(PGP)

ImSpector N17 Spectral ImagingLtd. (Finland)

Spectral resol. 10nm 0.9 – 1.75 Prism-Grating-

Prism(PGP)

Orion IR Imager(SWIR, MWIR,LWIR models)

CEDIP(France)

4 or 6per model

SWIR, MWIRLWIR Filter wheel

Sherlock LWIRPacific Advanced

Technology(USA)

Spectral resol.3 nm at

λ = 3.0μm8.0 – 10.5 Image Multi-

Spectral Sensing

Sherlock MWIRPacific Advanced

Technology(USA)

Spectral resol.33 nm atλ = 3.0μm

3.0 – 5.0 Image Multi-Spectral Sensing

source, and an integrating sphere to take reflected radiationat all possible view geometries. Contrary, Bidirectionalreflectance is usually determined in the field by mostimaging spectrometers. In this case, reflected energy ismeasured from specific points of incidence (Dar & Martin,2004). As stated previously, laboratory-based instrumentstypically measure directional-hemispherical reflectance toinvestigate material properties based on the interaction ofelectromagnetic radiation with matter. These instrumentshave the advantage of providing controlled conditions andthe highest quality reflectance. While, field instruments areused to capture the real-world effects of surface particles.The performance of these instruments depends on manyfactors such the weight of the instrument, its durability, scantime, software and environmental circumstance (John et al,2008).

According to the development in hyperspectral imagingtechnology, many different types of hyperspectral sensorshave been developed recently. There are two main types ofsystems that take images: airborne/spaceborne systemand ground system. In this investigation, we are moreinterested in ground systems. Table (1) lists the currentground based hyperspectral sensors and their principlecharacteristics.


imaging systems, which are outdoors, typically rely onnatural illumination comes from the sun, while laboratorysystems are usually used in conjunction with several laserillumination sources, artificial illumination. These sourceshave significant influence on accuracy of spectral reflectancemeasured at hyperspectral sensors. For instance, Dimillumination can affect the reflectance properties of objectsin a scene, and introduce shadowing within the scene.Generally, laboratory and field tests have shown thatutilizing an active source of illumination drastically reducesshadowing. Moreover, active illumination enables a sensorto operate day or night; even under adverse weatherconditions when solar illumination is greatly reduced(Nischan et al, 2003).

● Illumination Geometry

The amount of electromagnetic radiations reflected oremitted form a surface depends on the amount of lightenergy illuminating the surface, which in turn dependsupon the angle of incidence. This angle can be defined asthe angle between a light ray and a line perpendicular tothe reflecting surface at the point of incidence, as shownFigure (6), illumination difference can arise from alteringincidence angles. Specifically, the energy received at eachwavelength (Eg) varies as the cosine of the angle ofincidence (θ): Eg = Eo x cos θ, where Eo is the amount ofincoming energy. In addition, if the object’s surface is notflat, the energy received also varies instantaneously acrossa scene because of differences in slope angle and direction(Randall, 2012).


3.3 Practical Considerations

There are many practical issues that must be considered inthe design and implementation of in-situ hyperspectralmeasurements. These issues which have a potential effecton the accuracy of resultant spectral data include thefollowing:

● Atmospheric effect

The reflected radiations while traveling from the object’ssurface to a sensor interact with the atmosphere, throughabsorption and diffusion process. Subsequently, thecontaminated reflectance received at the sensor may bemore or less than that due to reflectance from surfacealone. Typically, the incident radiation on the surface-sensor ray path is subjected to the following:

1) Absorption by well-mixed gases such as (oxygen-O,methane-CH, and carbon dioxide-CO)

2) Absorption by water vapor3) Scattering gas by molecules and particulates4 ) Scattering and absorption by aerosols and

hydrometeors

Therefore, a series of atmospheric correction algorithmshave been developed to retrieve accurate surfacereflectance and to minimize the atmospheric effects (Griffin& Burke, 2003).

● Illumination source

Illumination source that use in hyperspectral measurementscan be classified into two main categories: naturalillumination & artificial illumination. In-situ, field spectral

Fig. (6): The effect of illumination geometry

(Adapted: Randall, 2012)



4.0 Hyperspectral Applications for Detecting ConcreteProperties

Modern architecture and construction nearly always includeconcrete in some form and to some extent. Concrete is usedin buildings, foundation, bridges, retaining walls, roads andin many other applications. Concrete structures must bestrong enough to withstand the structural and service loadswhich will be applied to them, as well as must be durable toresist severe environmental conditions to which they areintended.

The compressive strength of concrete is the most commonperformance measure used by engineers as a basis forquality control to assure that structural requirements aremet. This parameter is widely determined by compressiontest of the standard specimens (cube or cylinder). The testprocedure is relatively easy to perform in terms of sampling,preparation of specimens and the determination of strength;however it is not intended for determining the in-situstrength of the concrete since it makes no allowance for theeffects of placing, compaction, or curing. Therefore, severalnon-destructive tests including ultrasonic testing,radiographic testing and rebound hammer testing have beendeveloped to assess and evaluate concrete properties in-situ.Ideally, these methods don't impair the function of thestructure and permit re-testing at the same locations toevaluate changes in properties with time.

Recently, several researchers indicate that the concept ofhyperspectral technology also might be utilized as a nondestructive test for monitoring concrete structures. Ifspectral characteristics according to concrete conditions canbe understood, hyperspectral imagery may be applied as auseful instrument for surveying the current state for anumber of concrete structures.

4.1 Spectral Reflectance of Concrete

Spectral reflectance measurements provide valuableinformation on the characteristics of many objects. In fact,each kind of object has its own specific reflectability: type ofthe spectral curves and different values of spectralreflectance coefficients in the different bands. Thesecharacteristics are determined by the physical and chemicalproperties of the objects (Karavanova, 2001). For concretethe most important properties that influence the level ofreflectance are: components of concrete mixture, hardnessof concrete surface, maturity or (aging) of concrete andhydration process in concrete matrix. For instance, alaboratory investigation which was carried out by (Marceau& Vangeem, 2008), showed that the solar reflectance of thecementitious materials has more effect on the solarreflectance of concrete than the other constituents. The solarreflectance of the fine aggregate has a small effect on thesolar reflectance of the concrete, but the solar reflectance ofthe coarse aggregate does not have a significant effect.Moreover, the investigators reported that concretereflectance increased with progress of hydration processand stabilized at 6 weeks of age, with an average increase ofabout 8%. (Anna & Eyal, 2011) have utilized reflectancespectroscopy as a tool to assess the quality of concrete in-situ. In this work, more than 3000 concrete samples were

spectrally measured after applying several treatments.It was concluded that the spectral reflectance is closelyrelated to the hardness of concrete surface. In anotherstudy, (Nurul & Helmi, 2011) found that the spectral signaturesof older concrete samples comparatively different fromthe new samples. The results reveal that the reflectance ofold type of concrete samples is high with the increasingreflectance toward longer wavelength. While, spectralreflectance of new samples is slightly low.

4.2 Concrete Spectroscopy

Recently, several studies have explored new spectraltechniques which have utilized the reflected radiation ofconcrete (Sridhar et al, 2008; Anna & Eyal, 2011; Cavalli et al, 2011;Lee et al, 2012; Anna & Eyal, 2012). As a result of theseinvestigations, the reflectance radiations across the VIS-NIR and SWIR in the region between (350-2500) nm areoften considered a useful region with which to predictunknown concrete properties. Such techniques arebecoming more significant for the cost effective coverage oflarge concrete areas and can provide accurate predictionsof concrete properties relatively quickly compared totraditional field sampling and subsequent experimental testsunder laboratory conditions.

Generally, there are many types of imaging spectrometers,with many possible variations and modifications that canimprove the quality of retrieved surface reflectance andidentifying chemical and physical properties of concrete.These types include (GER-2600, GER-3700, FieldSpec³Pro-FRQ, FieldSpec⁴Pro‑FR…etc); however the (FieldSpec⁴Pro‑FRQ) is the most widely used among many researchers inthis field.

FieldSpec⁴Pro‑FRQ instrument characteristics aredemonstrated in Table (2). The instrument uses threeintegrated detectors. In the VNIR (350-1050 nm), thespectral sampling interval of each channel is 1.4 nm,however the spectral resolution (FWHM) is approximately3 nm at around 700. The sampling interval for the SWIRregions (900–1850 and 1700–2500) is 2 nm, with spectralresolution varying between 10 - 12 nm. The spectralinformation from the three detectors is subsequentlycorrected within software for baseline electrical signal(dark current), and then interpolated to a (1 nm)sampling interval over the wavelength range. TheFieldSpec⁴Pro‑FRQ, as illustrated in Figure (7), collectslight passively by means of a fiber optic cable. Longer cableresults in a loss of signal strength, especially beyond 2000nm. Thus, the standard fiber optic cable length of theFieldSpec⁴Pro‑ FRQ is typically 1 m (ASDinc , 2013).

4.3 Identification of Concrete Properties from SpectralData

Using reflectance spectroscopic methods, several directand indirect concrete properties, can be extracted simplyvia spectra data analysis. Despite the importance of thistechnology, knowledge concerning the spectralcharacteristics of man-made surface such as concrete isscarce, and little research has focused on this field. Theliterature about these applications would be presented in



Table 2: FieldSpec4Pro-FRQ Technical Specifications (Adapted from: ASD, 2013)

Spectral Range 350 -2500 nm

Spectral Resolution3 nm @ 700 nm

10 nm @ 1400/2100 nm

Sampling interval1.4 nm @ 350–1050 nm

2 nm @ 1000–2500 nm

Scanning time 100 milliseconds

Detectors

§ VNIR detector (350-1000 nm): 512 element silicon array§ SWIR 1 detector (1000-1800 nm): Graded Index InGaAs

§ Photodiode, TE Cooled§ SWIR 2 detector (1800-2500 nm): Graded Index InGaAs

§ Photodiode, TE Cooled

Noise Equivalent Radiance § VNIR 1.0 X10-9 W/cm2/nm/sr @ 700 nm§ SWIR 1 1.2 X10-9 W/cm2/nm/sr @ 1400 nm§ SWIR 2 1.9 X10-9 W/cm2/nm/sr @ 2100 nm

Input Optional narrower field of view fiber optics available.

Weight 5.44 kg (12 Ibs)

Calibration Wavelength, reflectance, radiance*, irradiance*. All calibrationsare NIST traceable (*radiometric calibrations are optional).

Fiber-optic cable Standard ASD fiber optic cable is 1 m in length. SSD’s ASD hasa 5 m fiber optic cable.

Fig. (7): FieldSpc4Pro-Spectrometer

(Adapted: ASD, 2013)



Fig. (8): Spectrum of Normal Concrete Fig. (9): Spectrum of Degraded Concrete

(Adapted form: Jun et al, 2001)

(Anna & Eyal, 2012) presented a study to assess the in-situstrength of high performance concrete using diffusereflectance spectroscopy. In this study, 77 highperformance concrete samples were spectrally measured,analyzed and simultaneously tested for compressivestrength. The results of this work demonstrated that thespectral measurement in the VNIR-SWIR (visible nearinfrared & short wave infrared) spectral region (400-2500) nm provides significant and accurate informationon concrete’s status and physical strength. Further, in-situvalidation was performed in this investigation whichexhibited that the spectral imagery acquired by spectralcamera in the field can be used as a useful tool for real-time strength assessment of concrete structures.

The exploitation of hyperspectral technology for assessingthe conservation status of infrastructures, such asreinforced concrete structures, roads, buildings .…etc wasstudied by (Cavalli et al, 2011). In this study, hyperspectralmeasurements were carried out on a reinforced concretebeam that was subjected to different loading factors toforce a formation of a clear cracking within the concretebeam. The researchers have utilized a processingtechnique, RX algorithm, to analyze hyperspectral dataacquired by hyperspectral scanner from concrete beam.The results indicate that the fractures are well detected bythe RX algorithm even though other anomalies are visible.Figure (10) illustrates the good performance ofhyperspectral technology in solving and detecting surfacecrack by using RX method.

An investigation was implemented by (Sridhar et al, 2008) toidentify unique spectral characteristics of concrete underdifferent construction practices. A total of 32 concreteblocks of identical shape and size (20×20×6) cm³ wereprepared and subjected to eight different processes. The

(Jun et al, 2001) have utilized hyperspectral imagery toidentify degradation of concrete structures due toexposure to various aggressive environments, includingcarbon dioxide, sodium chloride and sulfuric acid. Theresults of this study indicate that the spectrumcharacteristics of degraded concrete are stronglyinfluenced by spectrum chemical materials that aregenerated during degradation process. Figures (8) & (9)exhibit a significant difference in spectrum between intactconcrete and degraded concrete by carbon dioxide.Moreover, the investigators have developed a formula,equation No.1, to estimate degradation depth caused bycarbon dioxide from spectral reflectance of concretesurface.

Another study was implemented by (Lee et al, 2012) toextract spectral reflectance characteristics of concrete. Inthis investigation, the spectral information of eightconcrete specimens with different strength at 27 daymaterial age was measured. As a result of thesemeasurements, spectral characteristics of specimens wereshown almost similarly on the whole; however theyappeared different aspect according to the strength in therange of 1950 to 2350 nm. Also, the researchers, (Lee et al,2012), extended their investigations to include realconcrete structures such as concrete slab of DaejongchumBridge and decks surface of Yangbuk Bridge. The results ofthis extension exhibited that the spectral characteristics ofactual concrete show similar pattern with those of interiorexperiment.



Fig. (10): RX Image shows structural cracks within concrete surface

(Adapted form: Cavalli et al, 2011)

different treatments were TC (control), TNC (no cure), TCL

(cool cure), TH (heat cure), THW (high water content), THC

(half cement), TG (gravel used as coarse aggregate) andTL (limestone used as fine aggregate). The results of thisinvestigation clearly demonstrate that the spectralabsorption features around 450, 1380 and 1850 nm alteraccordingly with alteration in the characteristics ofconcrete. Also, the TNC and TCL treated concrete blocks canbe differentiated from other concrete blocks based on thefollowing spectral ratio indices, R600/R450, R1380/R1440,R1850/R1950 and R2150/R880. However, the spectral ratioR600/R450 can differentiate the TC, TG and TL treatedconcrete blocks, which were considered to have betterconcrete quality from the rest of the concrete treatments.

Spectral reflectance of concrete surfaces has been studiedpreviously to monitor aging of concrete sidewalks by(Herold et al, 2004). Spectral data analyses indicate that thenew concrete sidewalks exhibit higher spectral reflectancethan older sidewalks. The investigators attributed thisbehavior to the continued oxidation of concrete surfaces,as well as accumulation of dust and dirt that decreases thebrightness of concrete surfaces. On the other hand, theresults of this study demonstrate that concrete sidewalkshave stronger SWIR absorption features. This observationcan be ascribed that calcium carbonate in concrete matrixhave a significant absorption feature at 2300 nm for calciteand at 2370 nm from dolomite.

5.0 Summary & Conclusions

This paper has provided a brief overview of someimportant aspects of hyperspectral imaging technology.Then, it has discussed the important radiometric andspectral concepts, with a focus on how they apply toconcrete structures. The fundamental findings of thispaper are summarized as following:

1. Hyperspectral imaging technology has the ability tomeasure an intrinsic property of material; its spectralsignature. As a consequence, hyperspectral technologycan be used to identify and discriminate differenttypes of materials.

2. The amount of electromagnetic radiation reflected oremitted from a surface is affected by several factorsincluding; source of illumination, atmospherictransmission, sampling strategy, timing of dataacquisition and viewing geometry.

3. Hyperspectral imagery provides opportunities toextract more detailed information than is possibleusing traditional multispectral imagery.

4. Spectral libraries are a collection of the spectralsignatures of the target materials. They require the in-situ collection and laboratory spectroscopic analysis ofthe investigated samples.

5. The impact of deterioration factors on concretesurfaces can be diagnosed and measured by means ofhyperspectral imaging.

6. Reflectance spectroscopy can be used as a nondestructive cost-effective approach to determineconcrete strength in-situ.

7. Reflectance radiations across the VIS-NIR and SWIR inthe region between (350-2500) nm are oftenconsidered a useful region with which to predictunknown concrete properties.

8. Field portable spectrometer can be utilized as in-situtool for engineers to monitor and evaluate status ofdifferent concrete structures.



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