Background Reflectance Research Articles

Retrieval of seasonal dynamics of forest understory reflectance from semiarid to boreal forests using MODIS BRDF data

AbstractSpatial and temporal patterns of forest background (understory) reflectance are crucial for retrieving biophysical parameters of forest canopies (overstory) and subsequently for ecosystem modeling. In this communication, we retrieved seasonal courses of understory normalized difference vegetation index (NDVI) from multiangular Moderate Resolution Imaging Spectroradiometer bidirectional reflectance distribution function (MODIS BRDF)/albedo data. We compared satellite‐based seasonal courses of understory NDVI to understory NDVI values measured in different types of forests distributed along a wide latitudinal gradient (65.12°N–31.35°N). Our results indicated that the retrieval method performs well particularly over open forests of different types. We also demonstrated the limitations of the method for closed canopies, where the understory signal retrieval is much attenuated.

Meet the Flexperts! How to bring in expert contributions around the contract in support of commercial interests

The purpose of this paper is to highlight difficulties currently facing cross-disciplinary experts attempting to collaborate around commercial contracts in large businesses, and to suggest a means of addressing this in order to ease the process and enhance the client experience. The paper tells the story of a deal in short chapters, intercut with background explanations and reflections on the challenges and the solutions. This unusual approach in an academic essay allows the author to share a vision within a little-known commercial sector – reinsurance – which serves as a paradigm for complex cross-border contracting. This vision intends to provoke thinking and does not have the ambition of proving one approach over another. The author’s recommendation is an investment in a backbone technology allowing knowledge sharing, and a change in mindset which the author refers to as ‘Flexpertise’ to align the views of individuals to the view of the company.

ADAPTIVE OPTICS IMAGING OF FOVEAL SPARING IN GEOGRAPHIC ATROPHY SECONDARY TO AGE-RELATED MACULAR DEGENERATION.

To describe adaptive optics (AO) imaging of foveal sparing in geographic atrophy (GA) secondary to age-related macular degeneration. Flood-illumination AO infrared (IR) fundus images were obtained in four consecutive patients with GA using an AO retinal camera (rtx1; Imagine Eyes). Adaptive optics IR images were overlaid with confocal scanning laser ophthalmoscope near-IR autofluorescence images to allow direct correlation of en face AO features with areas of foveal sparing. Adaptive optics appearance of GA and foveal sparing, preservation of functional photoreceptors, and cone densities in areas of foveal sparing were investigated. In 5 eyes of 4 patients (all female; mean age 74.2 ± 11.9 years), a total of 5 images, sized 4° × 4°, of foveal sparing visualized on confocal scanning laser ophthalmoscope near-IR autofluorescence were investigated by AO imaging. En face AO images revealed GA as regions of inhomogeneous hyperreflectivity with irregularly dispersed hyporeflective clumps. By direct comparison with adjacent regions of GA, foveal sparing appeared as well-demarcated areas of reduced reflectivity with less hyporeflective clumps (mean 14.2 vs. 3.2; P = 0.03). Of note, in these areas, en face AO IR images revealed cone photoreceptors as hyperreflective dots over the background reflectivity (mean cone density 3,271 ± 1,109 cones per square millimeter). Microperimetry demonstrated residual function in areas of foveal sparing detected by confocal scanning laser ophthalmoscope near-IR autofluorescence. Adaptive optics allows the appreciation of differences in reflectivity between regions of GA and foveal sparing. Preservation of functional cone photoreceptors was demonstrated on en face AO IR images in areas of foveal sparing detected by confocal scanning laser ophthalmoscope near-IR autofluorescence.

Sensitivity analysis of retrieving fraction of absorbed photosynthetically active radiation (FPAR) using remote sensing data

The fraction of absorbed photosynthetically active radiation (FPAR) is a key biophysical variable for vegetation productivity estimation, vegetation growth condition monitoring, and climate change analysis. The object of this study is to conduct a comprehensive sensitivity analysis on the contributing factors of FPAR variation, in order to reveal the impacts of the interference factors on FPAR estimation using remote sensing and to improve the accuracy of the model. The analysis was conducted based on a coupled leaf-canopy–atmosphere radiative transfer model and a global sensitivity analysis algorithm. Due to the impact of diffuse FPAR on the variation of FPAR, we also analyzed the determinant factors of diffuse FPAR. The results showed that leaf area index (LAI) and the average leaf inclination angle (ALA) are two important canopy structural parameters determining FPAR variability, especially before canopy closure. FPAR was found to be affected differently by these two variables with canopy development. Canopy background reflectance has a great impact on FPAR estimation at low LAI values (LAI<1.0). For the effects of leaf biochemical variables, the contribution of leaf chlorophyll concentration (LCC) to FPAR variability is negligible at the early vegetative growth stage, but becomes dominant starting from the exuberant growth periods, with the contribution increasing consistently with LAI. For the external factors, solar zenith angle (SZA) and aerosol optical depth (AOD) are two important driving factors significantly influencing FPAR by changing the optical path length and the proportion of the diffuse photosynthetically active radiation (PAR). SZA influences both FPAR and diffuse FPAR throughout the growing period, while, AOD is the most important determinant factor for diffuse FPAR variation. When LAI is low, the impact of canopy background reflectance on the diffuse FPAR cannot be ignored. The analysis also revealed that the diffuse FPAR variation significantly influences on the vegetation productivity estimation. In summary, this study shows that the variation of FPAR is affected by different factors in different ways. It provides a comprehensive understanding of the contributing factors to FPAR variability including the diffuse FPAR, which could be potentially useful in developing FPAR retrieval algorithm from remote sensing data.

临近空间高空气球地基探测能力分析

Radiance model of detection system was built based on background radiation and radiation of high altitude balloon. the radiometric signal electrons in focal plane array produced by high attitude balloon in near space and background radiation were calculated precisely by considering the effects of atmosphere transmission, optical system imaging, detector and detector sampling. then signal-to-noise ratio was deduced for high attitude balloon in near space. an atmospheric modeling tool, modtran, was used to model radiance of self-emission, specular background reflection and diffuse background reflection. radiation characteristic of balloon in complex atmospheric and the influence on optic-electronic equipment's snr of specular reflectivity, diffuse reflectivity and integration time were analyzed. the research results indicate that the visible-near infrared ray (vis-nir) (0.6~2.4) detector can be used to detect balloon in sunshine and the long wave infrared ray (lwir) (8~12) detector can be used to detect balloon in complex atmospheric. with the integral time of 0.25s, the specular reflectivity of 0.32 and the diffuse reflectivtiy of 0.68, or the integral time of 1s, the specular reflectivity of 0.43 and the diffuse reflectivtiy of 0.57, detection of high altitude balloon can easily been achieved. © 2016, science press. all right reserved.

Landsat 8 OLI image based terrestrial water extraction from heterogeneous backgrounds using a reflectance homogenization approach

Abstract Surface waters are fundamental resources for terrestrial life, yet they are not free of both natural and anthropogenic influences at global-scale. An accurate and robust method to extract water bodies is critical to effectively manage these irreplaceable resources. Conventional methods are frequently limited in terms of the uncertainty related to the coarse resolution and regional reflectance heterogeneity of satellite images. The fuzzy clustering method (FCM) considering local spatial information has a proven capability to compensate for these limitations. Nevertheless, this technique is highly sensitive to immense false signals in original satellite images. Therefore, a systematic surface water extraction method by taking advantage of the complementarity between a water index (WI) and a modified FCM (WIMFCM) was designed in this study to improve the water extraction accuracy, the rationale of which is a background reflectance bias correction. Applications were performed to sixteen test sites varying from coasts to inland waters to comprehensively evaluate the reliability of the WIMFCM using the Landsat-8 Operational Land Imager (OLI) images. Results showed the WIMFCM improved the accuracy of water extraction in comparison to alternative methods in terms of kappa coefficients (KCs) and total classification errors (TEs). Overall, the mean KC of the WIMFCM was 0.94 and its mean TE was 11.39%, compared with original WI (KC = 0.89, TE = 19.84%) and a support vector machine (SVM) method (KC = 0.89, TE = 22.39%). In addition, a seasonal analysis revealed the WIMFCM could maintain consistent reliability throughout the year, demonstrating its potential for accurate dynamic water monitoring associated with seasonal water probability mask. Additional tests using Moderate-Resolution Imaging Spectroradiometer (MODIS) data revealed the WIMFCM could be extended to large-scale regions, as well as be used in near-real time surface water body extraction. The findings of this study offer a new method to improve target detection accuracy under reflectance heterogeneous environments.

Inter- and intra-annual variations of clumping index derived from the MODIS BRDF product

Clumping index quantifies the level of foliage aggregation, relative to a random distribution, and is a key structural parameter of plant canopies and is widely used in ecological and meteorological models. In this study, the inter- and intra-annual variations in clumping index values, derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) BRDF product, are investigated at six forest sites, including conifer forests, a mixed deciduous forest and an oak-savanna system. We find that the clumping index displays large seasonal variation, particularly for the deciduous sites, with the magnitude in clumping index values at each site comparable on an intra-annual basis, and the seasonality of clumping index well captured after noise removal. For broadleaved and mixed forest sites, minimum clumping index values are usually found during the season when leaf area index is at its maximum. The magnitude of MODIS clumping index is validated by ground data collected from 17 sites. Validation shows that the MODIS clumping index can explain 75% of variance in measured values (bias=0.03 and rmse=0.08), although with a narrower amplitude in variation. This study suggests that the MODIS BRDF product has the potential to produce good seasonal trajectories of clumping index values, but with an improved estimation of background reflectance.

MISR empirical stray light corrections in high-contrast scenes

Abstract. We diagnose the potential causes for the Multi-angle Imaging SpectroRadiometer's (MISR) persistent high aerosol optical depth (AOD) bias at low AOD with the aid of coincident MODerate-resolution Imaging Spectroradiometer (MODIS) imagery from NASA's Terra satellite. Stray light in the MISR instrument is responsible for a large portion of the high AOD bias in high-contrast scenes, such as broken-cloud scenes that are quite common over ocean. Discrepancies among MODIS and MISR nadir-viewing blue, green, red, and near-infrared images are used to optimize seven parameters individually for each wavelength, along with a background reflectance modulation term that is modeled separately, to represent the observed features. Independent surface-based AOD measurements from the AErosol RObotic NETwork (AERONET) and the Marine Aerosol Network (MAN) are compared with MISR research aerosol retrieval algorithm (RA) AOD retrievals for 1118 coincidences to validate the corrections when applied to the nadir and off-nadir cameras. With these corrections, plus the baseline RA corrections and enhanced cloud screening applied, the median AOD bias for all data in the mid-visible (green, 558 nm) band decreases from 0.006 (0.020 for the MISR standard algorithm (SA)) to 0.000, and the RMSE decreases by 5 % (27 % compared to the SA). For AOD558 nm &lt; 0.10, which includes about half the validation data, 68th percentile absolute AOD558 nm errors for the RA have dropped from 0.022 (0.034 for the SA) to &lt; 0.02 (~ 0.018).

Influence of Tissue Fluorescence Measurement and Imaging by Auto-Fluorescence of Substrata

Polymers, glass and fiber reinforced materials are increasingly being used in photophysical devices. The inherent fluorescence of devices made of these materials may itself become important during fluorescence detection. It may interfere with or even negate the low fluorescence signals emitted from fluorophores molecules of interest especially when the fluorophores exist in microvolume samples. Such effects are significant when tissue micro-sections placed on substrata of high background fluorescence. Using different excitation wavelengths, fluorescence spectral and imaging studies were carried out to examine the effect of background fluorescence of microslides made of various substrata such as glass, polycarbonate and aluminium on autofluorescence of tissue sections. With decreasing wavelength of excitation, all substrata showed increased autofluorescence. Glass showed least inherent fluorescence and aluminium showed more reflectance than autofluorescence. After continuous exposure to blue and UV light, all substrata showed irreversible decreased autofluorescence. During spectrofluorimetric studies, a definite blue shift was observed in the autofluorescence of tissue sections placed on microslides made of each of the materials. This suggests an interference of tissue autofluorescence by background fluorescence emitted by the substratum. This may lead to false positive or negative reporting of the fluorophores, particularly important while analyzing micro-sections of biological samples. Microscopic imaging did not show any background fluorescence for glass substratum with blue light. However, with UV light, glass also showed background fluorescence during imaging. Other substrata showed strong background fluorescence or reflectance with both blue and UV light. This study has the potential for accurate quantification of fluorescence spectral and decay and improved fluorescence imaging using the photobleaching effect.

Modified vegetation indices for estimating crop fraction of absorbed photosynthetically active radiation

The fraction of absorbed photosynthetically active radiation (FPAR) is an important biophysical parameter of vegetation. It is often estimated using vegetation indices (VIs) derived from remote-sensing data, such as the normalized difference VI (NDVI). Ideally a linear relationship is used for the estimation; however, most conventional VIs are affected by canopy background reflectance and their sensitivity to FPAR declines at high biomass. In this study, a multiplier, the ratio of the green to the red reflectance, was introduced to improve the linear relationship between VIs and crop FPAR. Three widely used VIs – NDVI, the green normalized difference VI (GNDVI), and the renormalized difference VI (RDVI) – were modified this way and were called modified NDVI (MNDVI), modified GNDVI (MGNDVI), and modified RDVI (MRDVI), respectively. A sensitivity study was applied to analyse the correlation between the three modified indices and the leaf area index (LAI) using the reflectance data simulated by the combined PROSPECT leaf optical properties model and SAIL canopy bidirectional reflectance model (PROSAIL model). The results revealed that these new indices reduced the saturation trend at high LAI and achieved better linearity with crop LAI at low-to-medium biomass when compared with their corresponding original versions. This has also been validated using in situ FPAR measurements over wheat and maize crops. In particular, estimation using MNDVI achieved a coefficient of determination (R2) of 0.97 for wheat and 0.86 for maize compared to 0.90 and 0.82 for NDVI, respectively, while MGNDVI achieved 0.97 for wheat and 0.88 for maize, compared to 0.90 and 0.81 for GNDVI, respectively. Algorithms based on the VIs when applied to both wheat and maize showed that MNDVI and MGNDVI achieved a better linearity relationship with FPAR (R2 = 0.92), in comparison with NDVI (R2 = 0.85) and GNDVI (R2 = 0.82). The study demonstrated that applying the green to red reflectance ratio can improve the accuracy of FPAR estimation.

Cowbird responses to aircraft with lights tuned to their eyes: Implications for bird–aircraft collisions

ABSTRACT Collisions between birds and aircraft (bird strikes) are expensive, risk human lives, and increase bird mortality. Aircraft lighting has been proposed as a potential means of enhancing avian responses to aircraft. Determining the optimal changes to lighting to reduce bird strikes is a complicated problem because avian visual systems differ markedly from that of humans. Icteridae, including Brown-headed Cowbirds (Molothrus ater; hereafter “cowbirds”), are involved in bird strikes, have a well-described visual system, and respond to approaching vehicles and lights. Our goal was to assess cowbirds' responses to a remote-controlled (RC) aircraft fitted with lights tuned to the cowbird eye. On the basis of perceptual modeling (i.e. visual physiology, object and background reflectance, and ambient light conditions), we found that 470-nm lights (“blue” portion of the human spectrum) would be the most conspicuous wavelength for cowbirds. We used field experiments to examine cowbird response to 470-nm lig...

Estimation of seasonal dynamics of understory NDVI in northern forests using MODIS BRDF data: Semi-empirical versus physically-based approach

The spatial and temporal patterns of the forest background reflectance are critically important for retrieving the biophysical parameters of the forest canopy (overstory) and for ecosystem modeling. In this short communication paper, we retrieved the seasonal courses of understory Normalized Difference Vegetation Index (NDVI) from MODIS BRDF data using the semi-empirical and physically-based approach. We compared the satellite-based understory NDVI series to seasonal courses of understory NDVI measured in the forests for three full growing seasons in boreal and hemiboreal sites in Northern Europe. Our results indicated both semi-empirical and physically-based approaches using MODIS BRDF data do have a potential to track seasonal changes in understory NDVI. Differences in the performance between of the two retrieval methods can be expected within the boreal zone depending on the level of forest fragmentation.

Retrieving Leaf Area Index from Remotely Sensed Data Using Advanced Statistical Approaches

Mapping and monitoring leaf area index (LAI) is critical to model surface energy balance, evapotranspiration, and vegetation productivity. Remote sensing helps in rapid collection of LAI on individual fields over large areas, in a time and cost-effective manner using empirical regression between LAI and spectral vegetation indices (SVI). However, these relationships may be ineffective when sun-surface sensor geometry, background reflectance and atmosphereinduced variations on canopy reflectance are larger than variations in the canopy itself. This requires development of superior and region-specific LAI-SVI models. In recent years, statistical learning methods such as support vector machines (SVM) and relevant vector machines (RVM) have been successful over the ordinary least square (OLS) regression models for complex processes. The objective of this study is to develop and compare OLS, SVM, and RVMbased reflectance models to estimate LAI for major summer crops in the Texas High Plains. The LAI was measured in 47 randomly selected commercial fields in Moore and Ochiltree counties. Data collection was made to coincide with Landsat 5 satellite overpasses on the study area. Numerous derivations of SVIs were examined for estimating LAI using OLS, SVM, and RVM models. Analysis of the results indicated that the SVI-LAI models based on the ratio of TM bands 4 and 3, and normalized difference vegetation index (NDVI) are most sensitive to LAI. The R2 values for selected models varied from 0.79 to 0.96 with the SVM model producing the best results. However, accuracy of reported LAI models needs further evaluation that accounts for in-field spatial variability in the LAI for wider applicability.

304 赤外線サーモグラフィ法における放射率角度依存性を考慮した背景反射の補正

304 赤外線サーモグラフィ法における放射率角度依存性を考慮した背景反射の補正

Asymmetric photonic resonances in GaN slab waveguide for mid infrared selective filters.

We demonstrate a spectrally selective reflector that exploits asymmetric photonic resonances of a 1D photonic crystal. The proposed spectrally selective reflector has a very simple structure - essentially just a single high-index slab of GaN, properly perforated, and supported by a transparent sapphire substrate. With the proper 1D array design, nearly 100% reflection is achieved with a narrow spectral width between 10 cm⁻¹ - 18 cm⁻¹, while the background reflection remains low across the entire mid-IR range. The reflection peak can be tuned over a large wavelength span based on physical parameters. Resonant transmission dips in the experimentally measured spectra corroborate the device theory and simulation, exhibiting the narrowband low-background mid-IR reflection as predicted.

A gestalt account of lightness illusions.

Illusions of lightness offer valuable clues to how lightness values are computed by the visual system. The traditional domain of lightness illusions must be expanded to include failures of constancy, as there is no distinction between these categories. Just as lightness is (relatively) constant in the face of changes in illumination level, so it is equally constant in the face of changes in background reflectance. Simultaneous lightness contrast, the most familiar lightness illusion, is fairly weak, and represents a failure of background-independent lightness constancy. It is argued that a combination of the highest-luminance rule of anchoring plus the Kardos idea of codetermination can account for most lightness illusions. Kardos suggested that the lightness value of a target surface is partly determined relative to the field of illumination (or framework) in which it is embedded, and partly relative to the neighboring field of illumination. Although Kardos did not apply his principle of codetermination to failures of background-independent constancy such as the simultaneous contrast illusion, this can be done rather easily by defining a framework as a perceptual group instead of identifying it strictly with an objective field of illumination.

A novel moisture adjusted vegetation index (MAVI) to reduce background reflectance and topographical effects on LAI retrieval.

A new moisture adjusted vegetation index (MAVI) is proposed using the red, near infrared, and shortwave infrared (SWIR) reflectance in band-ratio form in this paper. The effectiveness of MAVI in retrieving leaf area index (LAI) is investigated using Landsat-5 data and field LAI measurements in two forest and two grassland areas. The ability of MAVI to retrieve forest LAI under different background conditions is further evaluated using canopy reflectance of Jack Pine and Black Spruce forests simulated by the 4-Scale model. Compared with several commonly used two-band vegetation index, such as normalized difference vegetation index, soil adjusted vegetation index, modified soil adjusted vegetation index, optimized soil adjusted vegetation index, MAVI is a better predictor of LAI, on average, which can explain 70% of variations of LAI in the four study areas. Similar to other SWIR-related three-band vegetation index, such as modified normalized difference vegetation index (MNDVI) and reduced simple ratio (RSR), MAVI is able to reduce the background reflectance effects on forest canopy LAI retrieval. MAVI is more suitable for retrieving LAI than RSR and MNDVI, because it avoids the difficulty in properly determining the maximum and minimum SWIR values required in RSR and MNDVI, which improves the robustness of MAVI in retrieving LAI of different land cover types. Moreover, MAVI is expressed as ratios between different spectral bands, greatly reducing the noise caused by topographical variations, which makes it more suitable for applications in mountainous area.

Colour in a new light: a spectral perspective on the quantitative genetics of carotenoid colouration

Summary Carotenoid‐based colours are model traits for research on animal signalling and sexual selection but, whereas the consequences of variable expression have been extensively studied, its causes are rarely quantified. This issue is complicated by the composite nature of carotenoid‐based colour patches, which combine pigments and a reflective background. Ultimately, the evolution of such colours will be determined by the processes that govern variable expression of these mechanisms. We present a novel approach to assessing the quantitative genetics of colour expression, in which reflectance spectra are analysed directly, thereby avoiding the data loss and inherent subjectivity of summary colour variables. Further, the influence of the component mechanisms can be distinguished in spectral analyses due to their contrasting wavelength‐dependencies. Using data from a 6‐year study of carotenoid‐based plumage reflectance in wild great tits (Parus major), we employ a multi‐parallel ‘animal modelling’ approach to estimate sources of variance for narrow (2 nm) wavebands across the visible spectrum. Moderate heritability estimates were limited to the violet‐blue region of the spectrum, diagnostic of the carotenoid content of plumage being heritable. The natal environment effect was limited entirely to the violet‐blue, again indicating that it relates to variation in carotenoid content of feathers. Other wavelengths were sensitive to annual and permanent environmental variation but only marginally influenced by additive genetic variation. Hence, background reflectance is the component that is more sensitive to the environment. Analysing reflectance spectra directly provided an objective perspective of the dynamics of colour expression that is not apparent when relying on summary colour scores. In this case, our results suggest that carotenoid deposition may be an effective target of selection and hence could explain the important role carotenoids frequently play in intraspecific signalling.

Mapping global seasonal forest background reflectivity with Multi‐angle Imaging Spectroradiometer data

AbstractForest background reflectivities with seasonal and spatial variations are critically important in the estimation of canopy biophysical parameters of the forest canopy. In this paper, seasonal background reflectivity for global forested areas was mapped at 1.1 km resolution using four‐scale model and Multi‐angle Imaging Spectroradiometer data of the nadir and 45° forward directions. The largest seasonal variation of forest background reflectivities was observed in middle and high latitudes of Northern Hemisphere. The background reflectivity differs between deciduous broadleaf forest and coniferous forest in the near‐infrared band and varies with increasing canopy leaf area index. The partial validation of forest background reflectivity with adjacent grassland in the Northern Hemisphere and the comparison of understory leaf area index on leaf appearance day for larch forest in North Asia both indicate the relative reliability of results. The nearly 70% spatial coverage of retrieval with high‐quality flags makes it eligible for applications over global coniferous and deciduous broadleaf forest areas.

Raman Line Broadening with Graphene Coated Broad-Band Nano-Antennas

: Raman spectroscopy is a well-established tool providing for molecular fingerprints. Here we examine the Raman signal of graphene coated nano-antennas. The antennas studied were in the shape of bow-tie and diamond. Substantial signal amplification and line broadening have been observed signifying the nonlinear interaction between the antenna gain profile and the Raman line. Summary: Surface enhanced Raman scattering (SERS) [1] is a major spectroscopic tool for an efficient molecular identification down to the level of a few molecules [2,3]. Driven by the notion of localized electric field intensities, research turned to aggregates of metal particles and then to the more structured nano-optical antennas [4-6]. Yet, most antennas used so far were narrow band; covering mostly the laser frequency. Enhancement of the Raman signal has been further hindered by uncertainties in analyte concentration and location relative to the antenna. Here we examined a new antenna type, the diamond-shape antenna (D-ant) [7] with a bandwidth capable of accommodating both the pump laser and scattered Raman frequencies. The role of the antenna at resonance becomes two-fold: enhancing the absorption of the pump laser frequency and imposing unique conditions for plasmonic scattering of the Raman signal at the far-field. By using graphene [8] as a test film we eliminated much of the uncertainty in molecule’s location and concentration, thus enabling better comparative studies. Fig. 1 is a scanning electron microscope (SEM) image of our graphene-coated antennas. The metal layout included markers, which exhibited photoluminescence (PL) when illuminated by the 633 nm HeNe laser. The PL signal of gold was small when illuminated with the 785 nm laser and thus, mostly the antennas glow was accentuated near resonance. The background reflection has substantially elevated near resonance: this occurred because of antenna’s reflectivity and antenna’s directivity.The Raman signal from a graphene coated diamond antenna exhibited a substantial enhancement and line broadening, associated which every Raman line. The broadening becomes smaller as the Raman shift becomes larger. It was as-if the enhancement and line broadening mapped the gain-profile of the diamond shaped antenna.If we zoom at the 1300 cm-1graphene line we may observe an enhancement factor of ca 70 and line broadening by a factor of almost 5.In summary, diamond shape antennas exhibited substantial signal enhancement and line broadening compared to bow-tie antennas with similar dimensions.1. M. Fleischmann, P. J. Hendra, A. J. McQuillan, Chem. Phys. Letters 26 163-166 (1974).2. S. Nie and S. R. Emory, Science 275, 1102-1105 (1997).3. K. Kneipp et al, Phys. Rev. Letts, 78, 1667-1671 (1997).4. P. J. Schuck, D. P. Fromm, A. Sundaramurthy, G. S. Kino, and W. E. Moerner, , Phys. Rev. Lett. 2005, 94 (1), No. 017402-4.5. Katherine A. Willets and Richard P. Van Duyne, Annual Review of Physical Chemistry, 58: 267-297 (2007) DOI: 10.1146/annurev.physchem.58.032806.1046076. Jon A. Schuller, Edward S. Barnard, Wenshan Cai, Young Chul Jun, Justin S. White and Mark l. Brongersma, Nature Materials 9, 193-204 (2010). DOI: 10.1038/nmat2630.7. Nan Ni and H. Grebel, IEEE Antennas and Wireless Propagation Letters 5 (4), pp. 127-129 (2006).8. A. K. Geim, Science, 324 (5934), 1530-1534 (2009): DOI: 10.1126/science.1158877.