Discussion on effect of material on UV reflection and its disinfection with focus on Japanese Stucco for interior wall

Research has previously shown that ultraviolet light C (UV-C) can inactivate unexpected infection. However, this type of potential disinfection is dramatically reduced for the shadow area such as under desk or medical equipment. Because the UV-C reflectance ratio is low on the general wall surfaces. We compared Stucco against the other materials to investigate whether we could improve disinfection for the shadow area. The reflectance ratios of UV-C irradiation of each material were examined, with particular attention to the rates for the author’s Modified Stucco. To evaluate the disinfection effects of the UV-C reflective lighting, colonies of E. coli and of Staphylococcus hominis were cultured in an agar media and counted over a certain time period after applying UV-C irradiation from a sterilizing lamp onto the investigation materials. The author’s Modified Stucco, produced reflectance ratios that was 11 times that of white wallpaper. This demonstrated that the UV-C reflected on the Stucco wall having optimum components and their compositions inhibited the number of E. coli and S. hominis, resulting in significantly disinfection effects on white wallpapers. The space with Modified Stucco and then irradiated by a UV-C may give a strong disinfection effect.

Use of spectral information for red scale pest control

Decreasing the use of pesticides is one of the main goals of current agriculture, which requires fast, precise and continuous assessments of crop pests. Citrus pests cause a lot of damage worldwide and the techniques to evaluate them are mainly based on manual, time-consuming readings of insects stuck on traps spread over the crops. This is the case of red scale insects, whose control is notably challenging due to their small size and high reproduction rate. Hence, in this work, we carry out a spectral characterization of this insect in the visible range through spectrometric devices, microscopy and hyperspectral imaging technology to analyze the feasibility of using this information as a means of automatically identifying specimens belonging to this species in this era of precision agriculture. The results obtained show that spectral reflectance differences between red scales and other insects can be recorded at long (red) wavelengths and that red scales are morphologically different, i.e., smaller and more rounded. A reflectance ratio computed from spectral images taken at 774 nm and 410 nm is proposed as a new approach for automated discrimination of red scales from other insects.

An Algorithm for the Retrieval of High Temporal-Spatial Resolution Shortwave Albedo from Landsat-8 Surface Reflectance and MODIS BRDF

Variations in surface physicochemical properties and spatial structures can prominently transform surface albedo which conversely influence surface energy balances and global climate, making it crucial to continuously monitor and quantify surface dynamics at fine scales. Here, we made two improvements to propose an algorithm for the simultaneous retrieval of 30-m Landsat albedo, based on the coupling of Landsat-8 and MODIS BRDF. First, two kinds of prior knowledge were added to disaggregate BRDF, including the Anisotropic Flat Index (AFX) and the Albedo-to-Nadir reflectance ratio (AN ratio), from MODIS scales into Landsat scales. Second, a simplified data fusion method was used to simulate albedo for the same, subsequent, or antecedent dates. Finally, we validated the reliability and correlations of the algorithm at six sites of the Surface Radiation (SURFRAD) budget network and intercompared the results with another algorithm called the ‘concurrent approach’. The results showed that the proposed algorithm had favorable usability and robustness, with a root mean square error (RMSE) of 0.015 (8%) and a mean bias of −0.005; while the concurrent approach had a RMSE of 0.026 (14%) and a mean bias of −0.018. The results emphasized that the proposed algorithm has captured subtle changes in albedo over a 16-day period.

A Dual-Channel Aerosol Optical Depth Retrieval Algorithm Incorporating the BRDF Effect from AVHRR over Eastern Asia

A NOAA/AVHRR dual-channel method over land is proposed to simultaneously retrieve aerosol optical depth (AOD) at 0.55 μm, and surface reflectance at 0.63 and 0.85 μm. Compared with previous well-established one-channel retrieval algorithms, this algorithm takes advantage of the surface reflectance ratio between 0.63 and 0.85 μm in an attempt to account for the effect induced by the surface bidirectional reflectance distribution function (BRDF). This effect cannot be negligible due to the orbit drift and phasing running of NOAA satellites, both of which potentially cause large solar angular variation. Meanwhile, the observation posture change of AVHRR would cause large sensor angular variation in time series measurements. The used surface reflectance ratio based on dual channels at 0.63 and 0.85 μm is found more reasonable to be assumed as unchanged during a certain period of time, compared to the traditional ratio when addressing the BRDF issue. AOD retrievals have been carried out over Eastern Asia. Validation against aerosol robotic network (AERONET) measurements shows that up to 83% of AOD validation collocations are within error lines (±0.15 ± 0.15τ, τ is AOD) with an R of 0.88 and an root mean square error (RMSE) of 0.15. The dual-channel algorithm taking into account the surface BRDF effect is proved outperforming the conventional 0.63 μm-channel method. It indicates that our algorithm has the potential to be applied to the retrieval of long series of AOD, especially to the AOD retrieval of the sensors which lack a shortwave infrared channel required in the MODerate resolution Imaging Spectroradiometer (MODIS) dark target AOD algorithm.

Application of Reflectance Ratios on High-Resolution Satellite Imagery to Remotely Identify Eucalypt Vegetation

The scale and accessibility of passive global surveillance have rapidly increased over time. This provides an opportunity to calibrate the performance of models, algorithms, and reflectance ratios between remote-sensing devices. Here, we test the sensitivity and specificity of the Eucalypt chlorophyll-a reflectance ratio (ECARR) and Eucalypt chlorophyll-b reflectance ratio (ECBRR) to remotely identify eucalypt vegetation in Queensland, Australia. We compare the reflectance ratio values from Sentinel-2 and Planet imagery across four sites of known vegetation composition. All imagery was transformed to reflectance values, and Planet imagery was additionally scaled to harmonize across Planet scenes. ECARR can identify eucalypt vegetation remotely with high sensitivity but shows low specificity and is impacted by the density of the vegetation. ECBRR reflectance ratios show similar sensitivity and specificity when identifying eucalypt vegetation but with values an order of magnitude smaller than ECARR. We find that ECARR was better at identifying eucalypt vegetation in the Sentinel-2 imagery than Planet imagery. ECARR can serve as a general chlorophyll indicator but is not a specific index to identify Eucalyptus vegetation with certainty.

Application of Reflectance Ratios on High-Resolution Satellite Imagery to Remotely Identify Eucalypt Vegetation

The scale and accessibility of passive global surveillance have rapidly increased over time. This provides an opportunity to calibrate the performance of models, algorithms, and reflectance ratios between remote sensing devices. Here we test the sensitivity and specificity of Eucalypt chlorophyll-a reflectance ratio (ECARR) and Eucalypt chlorophyll-b reflectance ratio (ECBRR) to remotely identify eucalypt vegetation in Queensland, Australia. We compare reflectance ratio values from Sentinel-2 and Planet imagery across four sites of known vegetation composition. All imagery was transformed to reflectance values and Planet imagery was additionally scaled to harmonize across Planet Scenes. ECARR can identify eucalypt vegetation remotely with high sensitivity, but shows low specificity and is impacted by the density of the vegetation. ECBRR reflectance ratios show similar sensitivity and specificity when identifying eucalypt vegetation but with values an order of magnitude smaller than ECARR. We find that ECARR was better at identifying eucalypt vegetation in the Sentinel-2 imagery than Planet imagery. ECARR can serve as a general chlorophyll indicator but is not a specific index to identify Eucalyptus vegetation with certainty.

Investigations of Al2O3–Nb2O5 bi-layer Bragg reflector investigations for blue and green lights

At first, the single-layer Al2O3 and Nb2O5 films were deposited to find their refractive indices. After the indices of the single-layer Al2O3 and Nb2O5 films were measured, the thickness of 1/4 wavelength ([Formula: see text] for each layer of the Al2O3–Nb2O5 bi-layer Bragg reflectors of blue (450-nm) and green (550-nm) lights could be obtained. E-beam was used to deposit the bi-layer Al2O3–Nb2O films (called as one period) with two, four, and six periods on glass substrates to fabricate the Bragg reflectors of blue and green lights. The measured results had proven that the reflectance ratio increased and the bandwidth and full-width at half-depth (FWHD) decreased with the increase of number of periods. The measured results had also proven that as the designed central wavelength increased (changed from blue to green light) and same periods were deposited, the reflectance ratio decreased and the bandwidth and FWHD values increased.

IDENTIFYING THE EUTROPHICATION STATUS OF SHALLOW WATERS BASED ON THE ESTIMATED TROPHIC STATE INDEX FROM SATELLITE DATA

Remote sensing techniques have been widely used to measure the qualitative parameters of waterbodies. This work identifies the eutrophication status of 6 small and shallow lakes, including Hoan Kiem, Ba Mau, Bay Mau, Dam Tri, Truc Bach and Hai Ba Trung, in the Hanoiurban area using an empirical model developed from the in situ trophic state index (TSI) and Landsat 8 satellite data acquired on 21 September 2016 and 10 December 2016. The strong correlation between TSI values and the reflectance ratio of Landsat 8 band 3 versus band 2 (R2 = 0.69) allowed the quantification of the TSI by an exponential function (MSE = 0.04). Validation of the model for other water samples collected on the dates shows a high accuracy (R2 = 0.85; MSE = 0.4). Maps of TSI over the 6 lakes on the two dates surveyed clarified the eutrophication status of these lakes in autumn 2016 and demonstrate the trend in identifying the distribution of TSI from space. Study methods and data stated in this study confirm the high applicability of Landsat 8 satellite data for monitoring shallow lake eutrophication status.