Search

Crop statistics are crucial for developing a demand-based export and import strategy to ensure a country's sustainable food security. Remote sensing efficiently generates essential crop statistics, while ground-based supplementary sensor data offers sufficient information for crop delineation. This study explored the multispectral satellite imagery using in-situ ground-based hyperspectral reflectance phenology information as training data to delineate wheat from other competitive winter crops in Northwestern Bangladesh as a case study. Wheat spectral signatures were primarily obtained through a hand-held Spectroradiometer at various phenological stages, aligned with Sentinel-2 data availability. Five vegetation indices (VIs), namely Normalized Difference Vegetation Index (NDVI), Red-edge NDVI (RENDVI), Enhanced Vegetation Index (EVI), Greenness Chromatic Coordinate (GCC) and Soil-Adjusted Vegetation Index (SAVI), were derived from Spectroradiometer-data across six wheat growth stages: seedling, tillering, booting, flowering, grain development, and maturity. Maximum and minimum threshold values for the VIs at those six growth stages were determined from regression analysis of the values collected from Spectroradiometer and Sentinel-2. A rule-based classification technique was then used to categorize Sentinel-2 for wheat crop delineation based on those threshold values. The results revealed that maps based on NDVI, EVI, and SAVI showed overall accuracies of 83.33%, 85.18%, and 81.48%, respectively. These accuracies were found to be statistically acceptable (p < 0.05) outcomes. A positive agreement was observed when comparing the remotely sensed area at the union (4th tier administrative level) with the officially reported data of Bangladesh. This innovative method has the potential to be extended for developing phenology and area delineation for other major crops locally and globally. Highlights: A phenology-based algorithm was applied for delineating winter wheat. The algorithm is developed by combining Sentinel-2 images and Spectroradiometer data. Vegetative indices of wheat exhibited a strong relationship between two sensors' data. Accuracy assessment and validation of the produced maps demonstrated significant results. The method has the potential to be extended to area mapping for other crops locally and globally. [ABSTRACT FROM AUTHOR]

This study analyzed the ground conditions that allowed some extreme wildfires in 2017 and 2023 to take such proportions and burn around 750,000 ha across Central Chile. Using publicly available satellite data, we examined the relationship between the burned areas from the Moderate Resolution Imaging Spectroradiometers (MODIS) and their antecedent soil moisture from the Soil Moisture Active Passive (SMAP) mission. We found that a small number of fires were responsible for disproportionately large burned areas and that these megafires (i.e., >10,000 ha) were more likely to exhibit relatively drier conditions in the months and days prior. Based on this, we tested various thresholds in low antecedent soil moisture to identify areas more prone to megafires. By differentiating the moisture conditions below and above 0.14 m3/m3, we were able to map all of the 2017 megafires, at least in part. Our classification balanced the success and errors in prediction, yielding 54.1% recall and 75.9% precision (well above the 56.3% baseline). For 2023, the burned areas could not be classified as accurately, due to differences in pre-fire conditions. Overall, our research provided new insights into the link between satellite-based soil moisture and extreme wildfire events. Among other things, this study demonstrated that certain critical thresholds in SMAP had predictive skill to identify conditions more conducive to megafires. Ultimately, this work can be expanded to other parts of the world in support of enhanced wildfire mitigation and management. [ABSTRACT FROM AUTHOR]

The scattering channel of a spectroradiometer, as a commonly used optical parameter measuring device, can measure irradiance in all directions of the sky. To improve the calibration accuracy and efficiency, this paper proposes a spectral radiometer scattering channel calibration method based on direct solar radiation intensity. The direct solar radiation channel of the spectral radiometer can measure the solar radiation transmitted through the atmosphere in real-time and atmospheric transmittance. Combined with the solar radiation intensity at the top of the atmosphere and the optical component parameters of the instrument, the calibration value of the scattering channel of the full band can be obtain. The calibration values obtained by separately calibrating the integrating sphere and the transfer calibration are applied to calculate the all-sky background radiation. The deviation of the transfer calibration from the integrating sphere calibration is calculated and found to have an average deviation of less than 5%. By comparing the spectral radiation calculated using two calibration methods when fixed-point observation is used, it is found that the average deviation is less than 5%. The above comparison shows that the transfer calibration has good calibration accuracy and will be used in devices that measure both direct solar light and atmospheric scattered light. [ABSTRACT FROM AUTHOR]

Abstract Crop statistics are crucial for developing a demand-based export and import strategy to ensure a country’s sustainable food security. Remote sensing efficiently generates essential crop statistics, while ground-based supplementary sensor data offers sufficient information for crop delineation. This study explored the multispectral satellite imagery using in-situ ground-based hyperspectral reflectance phenology information as training data to delineate wheat from other competitive winter crops in Northwestern Bangladesh as a case study. Wheat spectral signatures were primarily obtained through a hand-held Spectroradiometer at various phenological stages, aligned with Sentinel-2 data availability. Five vegetation indices (VIs), namely Normalized Difference Vegetation Index (NDVI), Red-edge NDVI (RENDVI), Enhanced Vegetation Index (EVI), Greenness Chromatic Coordinate (GCC) and Soil-Adjusted Vegetation Index (SAVI), were derived from Spectroradiometer-data across six wheat growth stages: seedling, tillering, booting, flowering, grain development, and maturity. Maximum and minimum threshold values for the VIs at those six growth stages were determined from regression analysis of the values collected from Spectroradiometer and Sentinel-2. A rule-based classification technique was then used to categorize Sentinel-2 for wheat crop delineation based on those threshold values. The results revealed that maps based on NDVI, EVI, and SAVI showed overall accuracies of 83.33%, 85.18%, and 81.48%, respectively. These accuracies were found to be statistically acceptable (p

Floods are major hazard in Mzuzu City, Malawi. This study applied geospatial and hydrological modeling techniques to map flood incidences and hazard in the city. Multi-sensor [Sentinel 1, Sentinel 2, and Moderate Resolution Imaging Spectroradiometer (MODIS)] Normalized Difference Vegetation Index (NDVI) datasets were used to determine the spatio-temporal variation of flood inundation. Ground control points collected using a participatory GIS mapping approach were used to validate the identified flood hazard areas. A Binary Logistic Regression (BLR) model was used to determine and predict the spatial variation of flood hazard as a function of selected environmental factors. The Hydrologic Engineering Center's Hydrologic Modeling System (HEC-HMS) was used to quantify the peak flow and runoff contribution needed for flood in the city. The runoff and peak flow from the HEC-HMS model were subjected to extreme value frequency analysis using the Gumbel Distribution approach before input into the Hydrologic Engineering Center River Analysis System (RAS) (HEC-RAS). The HEC-RAS model was then applied to map flood inundated areas producing flood extents maps for 100, 50, 20, and 10-year return periods, with rain-gauge and Climate Prediction Center MORPHed precipitation (CMORPH) satellite-based rainfall inputs. Results revealed that selected MODIS and Sentinel datasets were effective in delineating the spatial distribution of flood events. Distance from the river network and urban drainage are the most significant factors (p < 0.05) influencing flooding. Consequently, a relatively higher flood hazard probability and/susceptibility was noted in the south-eastern and western-most regions of the study area. The HEC-HMS model calibration (validation) showed satisfactory performance metrics of 0.7 (0.6) and similarly, the HEC-RAS model significantly performed satisfactorily as well (p < 0.05). We conclude that bias corrected satellite rainfall estimates and hydrological modeling tools can be used for flood inundation simulation especially in areas with scarce or poorly designed rain gauges such as Mzuzu City as well as those affected by climate change. These findings have important implications in informing and/updating designs of flood early warning systems and impacts mitigation plans and strategies in developing cities such as Mzuzu. [ABSTRACT FROM AUTHOR]

In this work, we present and describe a spectral library (SL) with 15 vascular plant species from Montesinho Natural Park (MNP), a protected area in Northeast Portugal. We selected species from the vascular plants that are characteristic of the habitats in the MNP, based on their prevalence, and also included one invasive species: Alnus glutinosa (L.) Gaertn, Castanea sativa Mill., Cistus ladanifer L., Crataegus monogyna Jacq., Frangula alnus Mill., Fraxinus angustifolia Vahl, Quercus pyrenaica Willd., Quercus rotundifolia Lam., Trifolium repens L., Arbutus unedo L., Dactylis glomerata L., Genista falcata Brot., Cytisus multiflorus (L'Hér.) Sweet, Erica arborea L., and Acacia dealbata Link. We collected spectra (300–2500 nm) from five records per leaf and leaf side, which resulted in 538 spectra compiled in the SL. Additionally, we computed five vegetation indices from spectral data and analysed them to highlight specific characteristics and differences among the sampled species. We detail the data repository information and its organisation for a better understanding of the data and to facilitate its use. The SL structure can add valuable information about the selected plant species in MNP, contributing to conservation purposes. This plant species SL is publicly available in Zenodo platform. [ABSTRACT FROM AUTHOR]

Underwater spectral detection plays an important role in the study of the underwater environment, ecology, oceanography, and environmental monitoring. A kind of underwater spectral radiometer that can observe the distribution of underwater spectral radiation bidirectionally has been developed. The flat-field concave holographic grating is used as the only optical component, the optical design parameters are optimized, and the system is miniaturized. The mechanism of stray light generation in the spectrometer is studied, and a method of suppressing stray light is proposed and simulated. The level of stray light in the system is suppressed to the order of 10−4, the signal-to-noise ratio of the system is improved, and the ability to detect weak light is enhanced. The wavelength calibration experiment was completed, and the experimental results show that the wavelength resolution of the underwater spectral radiometer is better than 3 nm. Finally, the quantitative relationship between spectral irradiance and digital output is obtained through radiation in the calibration of the system. [ABSTRACT FROM AUTHOR]

Early detection and monitoring of the internal aspects of Bactrocera zonata infestation in fruits and vegetables are important for sustainable agriculture. The present study depends on the non-destructive detection of B. zonata damage in peach fruits using a high-resolution spectroradiometer to characterize the spectral reflectance pattern of peach fruits in healthy and infested fruits with different pest stages, including egg stage and larval instars. Additionally, five vegetation indices were used to detect infestation. Laboratory trials were carried out to investigate the entomopathogenic nematodes (EPNs) pathogenicity, gamma-irradiated and unirradiated Steinernema carpocapsae, and Heterorhabditis bacteriophora against B. zonata larvae and pupae. The spectral reflectance pattern of healthy peach fruit samples was higher than that of all infested samples. The peak level of light reflection for a peach fruit in a healthy state was observed at 750 nm. Conversely, at 1050 nm, the reflectance was low, and it reached its minimum level at 2150 nm for infested peach fruit. Green spectral zones achieved the highest level of discrimination between healthy and infested peach fruit. There was no noticeable distinction between the blue and SWIR-1 zones. However, SWIR-2, red, and NIR spectral zones exhibited a significant difference as they could differentiate between healthy and infested peach fruit. The normalized pigment chlorophyll index (NPCI) was the best plant index employed in pest identification. As the concentration of EPNs increased, the proportion of mortality additionally increased. Furthermore, this study revealed that irradiation of S. carpocapsae juveniles boosted their pathogenicity toward larvae. The LC50 value decreased from 569.39 infective juveniles (IJs)/larva to 433.43 IJs/larva. There was no significant difference in pupae. However, irradiation of H. bacteriophora juveniles negatively impacted larvae, increasing the LC50 value from 1608.04 IJs/ larvae to 2295.73 IJs/larvae by 1.4 fold. Additionally, it significantly affected pupae, as it caused the lowest LC50 value of 402.66 IJs/pupae. The results of this study confirmed hyperspectral data’s utility in the early prediction of fruit infestation and differentiated between different stages of B. zonata infestation. Similarly, applying irradiation to EPNs significantly impacts the control of B. zonata. [ABSTRACT FROM AUTHOR]

The results of the development and field testing of a compact high-speed deck spectroradiometer for remote sensing reflectance measurements are presented. Validation using data obtained with hydrooptical equipment showed that the new device makes it possible to measure data on remote sensing reflectance with an accuracy sufficient for calculating bio-optical characteristics. Based on the data obtained during field tests of the new device, processed using regional algorithms, the values of the bio-optical characteristics of the Kara and Black seas surface waters were quantitatively assessed. [ABSTRACT FROM AUTHOR]

Frequent fungicide applications are required to manage grapevine powdery mildew (Erysiphe necator). However, this practice is costly and has led to widespread fungicide resistance. A method of monitoring in-field fungicide efficacy could help growers maximize spray-interval length, thereby reducing costs and the rate of fungicide resistance emergence. The goal of this study was to evaluate if hyperspectral sensing in the visible to shortwave infrared range (400 to 2,400 nm) can quantify foliar fungicide efficacy on grape leaves. Commercial formulations of metrafenone, Bacillus mycoides isolate J (BmJ), and sulfur were applied on Chardonnay grapevines in vineyard or greenhouse settings. Foliar reflectance was measured with handheld hyperspectral spectroradiometers at multiple days post-application. Fungicide efficacy was estimated as a proxy for fungicide residue and disease control measured with the Blackbird microscopy imaging robot. Treatments could be differentiated from the untreated control with an accuracy of 73.06% for metrafenone, 67.76% for BmJ, and 94.10% for sulfur. The change in spectral reflectance was moderately correlated with the cube root of the area under the disease progress curve for metrafenone- and sulfur-treated samples (R2 = 0.38 and 0.36, respectively) and with sulfur residue (R2 = 0.42). BmJ treatment impacted foliar physiology by enhancing the leaf mass/area and reducing the nitrogen and total phenolic content as estimated from spectral reflectance. The results suggest that hyperspectral sensing can be used to monitor in-situ fungicide efficacy, and the prediction accuracy depends on the fungicide and the time point measured. The ability to monitor in-situ fungicide efficacy could facilitate more strategic fungicide applications and promote sustainable grapevine protection. [ABSTRACT FROM AUTHOR]

To improve the accuracy of infrared radiation characteristics measurement in the aviation field, an infrared Fourier transform imaging spectrometer based on a double-swing solid angle reflector was designed. This imaging spectrometer operates in the 3–5 μm wavelength range and has a field of view of 1.7° × 1.7°. This article presents a comprehensive analysis of the system's stray light and also studies the impact of external stray light on the imaging quality, along with the influence of internal stray light on the interference effects and the spectral resolution. It also present the design of a hood that suppresses the point source transmittance of the external stray light down to the order of 10−4. Based on this, we propose a method that incorporates the introduction of wedge and inclination angles. Additionally, a numerical range is provided for the addition of these angles on the beam splitter mirror and compensation plate. This ensures the effective suppression of any internal stray light. This study fills the gap in the knowledge about Fourier transform imaging spectrometers operating in the mid-infrared band for aviation applications, and proposes a suppression method suitable for interference systems, which is also suitable for Fourier transform imaging spectrometers based on other types of interferometers. This study broadens the application field of Fourier transform imaging spectrometers in stray light, and has great significance to promote the development of Fourier transform imaging spectrometer. [ABSTRACT FROM AUTHOR]

The present study highlights delineation of the distribution of understorey invasive plant species (IPS) in Mudumalai Tiger Reserve (MTR), Western Ghats, India using very high resolution airborne imaging spectroscopy images by evaluating the performance of a Multiple Endmember Spectral Mixture Analysis (MESMA). Lantana camara L. and Chromolaena odorata (L.) R.M.King & H.Rob. have imposed a serious threat to natural ecosystems in MTR by altering the ecosystem processes. The Airborne Visible-Infrared Imaging Spectrometer-Next Generation (AVIRIS-NG) based analysis delineated the distribution of understorey IPS, viz., L. camara and C. odorata in MTR, with an overall accuracy of 87 % (k = 0.84) and 84 % (k = 0.8), respectively, with minimal root-mean-square error (RMSE) of MESMA classification (0.001 to 0.0025). In MTR, both the IPS were distributed in large parts and in association with all dominant canopy tree species barring Eucalyptus species. L. camara was majorly found in the southern parts of central MTR with 'high' to 'very high' presence covering 23.09 % and 11.51 % of the total area of central MTR, respectively, in association with Terminalia anogeissiana Gere & Boatwr. and Tectona grandis L.f. Whereas, C. odorata was dominantly found with high (18.11 % area of central MTR) to very high (11.85 % area of central MTR) intensity in the south and southeastern parts within the vicinity of T. anogeissiana and Terminalia elliptica Willd. The study highlights the utilization of high spectral agility in mapping of understorey IPS through spectral differentiation of the patchy distribution of IPS and its intermixing with other local species may be helpful in ecological restoration, conservation of biodiversity, and provisioning long-term management of ecosystem services in highly invaded tropical forests. [ABSTRACT FROM AUTHOR]

Mediterranean Fruit Fly, Ceratitis capitata (Diptera: Tephritidae) is regarded as an important pest of orange (Citrus). Early detection of pest infestations enables the optimal application of preventative and control measures. This study was carried out under laboratory conditions, in order to predict and monitor orange pest infestations. Consequently, the scope was to find a remote sensing application that can help in the prediction of Mediterranean Fruit Fly infestation in oranges with the least loss in production. Spectroscopic and thermal imaging techniques were investigated, as effective tools in determination of pest infestation and damage in orange fruits. According to the findings, the optimum spectral zones that can be used to discriminate and differentiate between healthy (non-infected) orange fruit and infected ones were red and near infrared bands. Six vegetation indices were calculated to analyze the Field Spectral measurements. By calculating the NPCI (Normalized Pigment Chlorophyll Index), it was found that NPCI values for infected orange fruits were higher in comparison to healthy ones. Thermal imaging showed that the infected orange fruit temperatures were on average 0.8 °C higher than that of healthy fruits. As the maximum temperature differential (MTD) between healthy and infected fruits were 23.7–24.5 °C, respectively. These spectral reflectance curves were useful for researchers working on Site-specific crop management, as they can use remote sensing to detect individual fruit infections. Also, this technique should be used as a powerful and non-destructive method for assistance in agriculture.

Precise spectral ultraviolet (UV) measurements are needed to ensure human protection as well as to support scientific research. Quantifying the uncertainty of the UV spectra recorded is crucial to evaluate the quality of the measurements which is needed, in turn, for the assessment of their reliability. However, for double‐monochromator spectroradiometers, the analytical derivation of this uncertainty is a challenging task due to the difficulties involved in propagating individual uncertainties. Under these circumstances, a Monte Carlo simulation is a reliable alternative as it does not require the calculation of partial derivatives and considers both nonlinear effects and correlations in the data. In the present study, the uncertainty of the spectral UV irradiance measured by a Brewer MKIII spectrophotometer is evaluated using a Monte Carlo approach. This instrument belongs to the National Institute of Aerospace Technology and has successfully participated in several international campaigns, which ensures its precise calibration. The average expanded uncertainty (k = 2) of the global UV irradiance measured by this instrument varies between 10% at 300 nm and 7% at 363 nm. At shorter wavelengths, it increases sharply due to thermal and electronic noise as well as wavelength misalignment. The results indicate that a Brewer spectrophotometer is suitable for climatological studies and model validation. Nevertheless, a substantial reduction of these uncertainties might be required for accurately detecting long‐term UV trends. Although the study focused on a Brewer spectrometer, the methodology used for the uncertainty analysis is general and can be adapted to most UV spectroradiometers. Plain Language Summary: The solar ultraviolet (UV) spectrum covers the wavelength range from 100 to 400 nm. Although it represents less than 10% of the total radiation reaching the earth's surface, it is of great importance as it can be harmful to humans, aquatic, and terrestrial ecosystems. To study its effects, high‐quality measurements are needed. To determine the quality of the irradiance recorded its uncertainty must be first evaluated. Most techniques used for uncertainty estimation rely on the calculation of partial derivatives, which are difficult to obtain for most instruments measuring UV irradiance. The reason for this is that the mathematical expression relating some uncertainty sources and the measured irradiance is complex, with unknown correlations between the different uncertainty sources. To solve this problem, the Monte Carlo technique was used instead of the analytical one. The Monte Carlo approach is easier to implement and needs no calculation of partial derivatives. The method was implemented for a Brewer spectrometer, one of the preferred devices to measure UV irradiance. The results indicate that the Brewer is suitable for model validation, but a substantial reduction of its uncertainty might be needed to accurately detect spectral UV trends. Key Points: A Monte Carlo technique has been implemented to obtain the uncertainty of the spectral ultraviolet recorded by a Brewer MKIII spectrometerThe methodology used for the uncertainty propagation is general and can be adapted to most spectroradiometers used in ultraviolet (UV) researchBrewer spectrometers are suitable for model and satellite validation but might be limited in the determination of spectral UV trends [ABSTRACT FROM AUTHOR]

To retrieve columnar aerosol properties from sun-photometers both irradiance and radiance calibration factors are needed. For the irradiance the solar calibration constant, V0, that is the instrument counts for a direct normal solar flux extrapolated to the top of the atmosphere, must be determined. The solid view angle, SVA, is the measure of the field of view of the instrument, and it is important for obtaining the Radiance from sky diffuse irradiance measurements. Each of the three sun-photometers networks considered in the present study (SKYNET, AERONET, WMO-GAW) adopts different protocols of calibration and we evaluated the performance of the on-site calibration procedures, applied to SKYNET PREDE-POM instruments, during intercomparison campaigns and laboratory calibrations held in the framework of the Metrology for Aerosol Optical Properties (MAPP) EMPIR project. The on-site calibration, performed as frequently as possible (rather monthly) to monitor change of the machine condition, allow operators to track and evaluate the calibration status on a continuous basis considerably reducing the data gaps incurred by the periodical shipments for performing centralized calibrations. The performance of the on-site calibration procedures for V0 was very good in sites with low turbidity, showing an agreement with a reference calibration between 0.5% and 1.5% depending on wavelengths. In the urban area the agreement decreases between 1.7% and 2.5%. For the SVA the difference varied from a minimum of 0.03 % to a maximum of 3.46%. [ABSTRACT FROM AUTHOR]

Background: Advancements in field spectrometry have the potential to increase understanding of crop growth and development in response to hot and dry environments. However, as with any instrument used for scientific advancement, it is important to continue developing and optimizing data collection protocols to promote efficiency, safety, and data quality. The goal of this study was to develop a novel data collection method, involving a proximal sensing cart with onboard cooling equipment, to improve deployments of a field spectroradiometer in a hot and dry environment. Advantages and disadvantages of the new method were compared with the traditional backpack approach and other approaches reported in literature. Results: The novel method prevented the spectroradiometer from overheating and nearly eliminated the need to halt data collection for battery changes. It also enabled data collection from a significantly larger field area and from more field plots as compared to the traditional backpack method. Use of a custom cooling box to stabilize operating temperatures for the field spectroradiometer also improved stability of white panel data both within and among collections despite outside air temperatures in excess of 30°C. Conclusions: As compared to traditional data collection approaches for measuring spectral reflectance of field crops in a hot and dry environment, use of a proximal sensing cart with a customized equipment cooling box improved spectroradiometer performance, increased practicality of equipment transport, and reduced operator safety concerns. [ABSTRACT FROM AUTHOR]

The results of the development and field testing of a compact high-speed deck spectroradiometer for remote sensing reflectance measurements are presented. Validation using data obtained with hydrooptical equipment showed that the new device makes it possible to measure data on remote sensing reflectance with an accuracy sufficient for calculating bio-optical characteristics. Based on the data obtained during field tests of the new device, processed using regional algorithms, the values of the bio-optical characteristics of the Kara and Black seas surface waters were quantitatively assessed. [ABSTRACT FROM AUTHOR]

Over the last 15 years, new important developments occurred in the reference method and use of optical sensors dedicated to in-season potato crop nitrogen (N) status (CNS) monitoring. The reference method is based on N nutrition index (NNI) defined as the ratio of critical N concentration (%Nc) and actual plant N concentration (%N) during the growing season, %Nc being deduced from the critical N dilution curve (CNDC) in total crop biomass. New statistical insights on the 11 different existing potato CNDCs worldwide, considered as site- and time-specific because they are built on specific combinations of potato cultivars (G), environment (E) and crop management practices (M), led to the assumption that it could be possible to derive more generic CNDCs providing large sets of data (pairs of biomass and plant N% assessments) from different G×E×M situations. Practical application of the reference method for CNS assessment is labour intensive and time consuming due to plant sampling and laboratory analysis for N content. However, a more generic NNI reference method is valuable to define threshold or critical values of plant N-related biophysical or biochemical variables (BVs) that can be retrieved from optical sensor readings and used as quick indicators for CNS assessment. Optical sensors are classically used to measure leaf or canopy transmittance, reflectance and chlorophyll fluorescence of visible (VIS) and near-infrared (NIR) wavelengths of the electromagnetic spectrum and related to leaf chlorophyll content (LCC) demonstrated as strongly correlated to leaf N content (LNC). Optical sensors applied at the leaf level are mainly handheld devices based on transmittance and chlorophyll fluorescence and have specific advantages and weaknesses that are extensively described to derive BVs and to assess potato CNS. Their main application is dedicated for CNS assessment at small field scale showing low within-field variability. Reflectance-based, remotely sensed optical devices are applied at canopy level from different ground-based, airborne or spaceborne platforms. Ground-based and airborne approaches, combined with different reflectance data analysis and processing mathematical and statistical methods (vegetation indices, chemometrics, machine learning) or physically-based approach such as inversion of radiative transfer models, allowed reliable retrieve of N-related BVs for CNS assessment such as LCC, canopy chlorophyll content (CCC), leaf area index (LAI) or others BVs. Remote sensing from spaceborne platforms, with the recent and forthcoming launches of satellite missions equipped with multispectral and hyperspectral sensors and with enhanced spatial, temporal, spectral and radiometric resolutions in the VIS and NIR regions but also shortwave infrared (SWIR) region allowing to consider plant N related to leaf proteins, have opened new avenues for real-time and reliable CNS monitoring at field and within-field scale over large territories and based on the setup of generic N-related BVs across different growing conditions and multiple G×E×M scenarios. [ABSTRACT FROM AUTHOR]

This review was carried out to understand the retrieval of aerosol optical depth (AOD) datasets for estimating particle concentration and its influence on ambient air and surroundings by various models. Several studies have evaluated particle (PM10 and PM2.5) concentration profiles present in the lowest layers of the atmosphere by using AOD datasets. This study aimed at identifying consistent and precise particle estimation by various datasets retrieved by satellite‐based models for the ground‐level PM concentration. Extremities of satellite sensor data, like specific capabilities, as well as a few drawbacks are presented. Multi‐angle imaging spectroradiometer (MISR), visible infrared imaging radiometer suite (VIIRS) datasets, mixed‐effect model (MEM), and geographically weighted regression (GWR) models outperformed to estimate AOD and PM in comparison with the moderate resolution imaging spectroradiometer (MODIS) and other datasets. The improvised algorithms with higher resolution in the upcoming research would provide an even better estimation for AOD and PM. [ABSTRACT FROM AUTHOR]

Mediterranean Fruit Fly, Ceratitis capitata (Diptera: Tephritidae) is regarded as an important pest of orange (Citrus). Early detection of pest infestations enables the optimal application of preventative and control measures. This study was carried out under laboratory conditions, in order to predict and monitor orange pest infestations. Consequently, the scope was to find a remote sensing application that can help in the prediction of Mediterranean Fruit Fly infestation in oranges with the least loss in production. Spectroscopic and thermal imaging techniques were investigated, as effective tools in determination of pest infestation and damage in orange fruits. According to the findings, the optimum spectral zones that can be used to discriminate and differentiate between healthy (non-infected) orange fruit and infected ones were red and near infrared bands. Six vegetation indices were calculated to analyze the Field Spectral measurements. By calculating the NPCI (Normalized Pigment Chlorophyll Index), it was found that NPCI values for infected orange fruits were higher in comparison to healthy ones. Thermal imaging showed that the infected orange fruit temperatures were on average 0.8 °C higher than that of healthy fruits. As the maximum temperature differential (MTD) between healthy and infected fruits were 23.7–24.5 °C, respectively. These spectral reflectance curves were useful for researchers working on Site-specific crop management, as they can use remote sensing to detect individual fruit infections. Also, this technique should be used as a powerful and non-destructive method for assistance in agriculture. [ABSTRACT FROM AUTHOR]

Interpersonal violence is a rising issue in global society and new approaches are being sought to combat the problem. Within this context, expanding forensic techniques to better document violent crime scenes is critical for improving and acquiring legal evidence, such as proving or tracing contact between victims and suspects. This project aims to demonstrate the potential for forensic investigations in the context of interpersonal violence using a field-based reflective spectroscopy approach. For this, a common cosmetic, Wet'N'Wild "Color Icon" blush in the shade "Pearlescent Pink", was mineralogically characterized using transmission electron microscopy and powder X-ray diffraction and subsequently investigated via reflective spectroscopy on a variety of common substrates. Differing amounts of the cosmetic product, ranging from 0.001 g to 0.075 g, were applied to a variety of substrates using a simple push method to simulate forcible contact and material transfer. Substrates included a pine wood block; (calcareous) sand from Tulum, Mexico; Ottawa sand; tile; Pergo wood; linoleum; closet material; carpets; and fabrics. The reflective spectra of cosmetic–substrate combinations were measured via an ASD FieldSpec 4 Hi-Res spectroradiometer. The Wet'N'Wild cosmetic was reliably detected on various substrates relevant to crime scenes. Minor amounts (as low as 0.02 mg/mm2) could be detected, and average limits of detection of 0.03 mg/mm2) were achieved; however, a calcareous sand (Tulum) had a high level of detection (>0.38 mg/mm2), suggesting that further investigation is needed for more complex sand substrates. The use of the ASD spectroradiometer as a forensic tool within the context of crime scene documentation shows promise. Future work should expand the characterization of cosmetic materials across a broad range of substrates and consider systematic studies of specific population groups. Furthermore, combining this approach with hyperspectral imaging at crime scenes is a promising future direction for crime scene documentation. This work therefore demonstrates a novel method for investigating cosmetics within the context of interpersonal violence and provides a foundation for future laboratory and field work using the ASD FieldSpec 4 and hyperspectral imaging systems. [ABSTRACT FROM AUTHOR]

The use of tanning devices in Spain is regulated by the Royal Decree 1002/2002, which is based on the European standard EN60335-2-27. The European standard establishes that the total unweighted irradiance between 200 and 280 nm must not exceed 0.003 Wm−2, a requirement that the Spanish regulation modified to 0.03 Wm−2 from 250 to 295 nm. With these differences, the compliance consideration of an artificial tanning device can vary. Spectral irradiance measurements of 41 tanning devices performed with a high-resolution spectroradiometer were analyzed. None of the tanning devices had irradiances higher than 0.003 Wm−2 between 250 (the shortest wavelength measured by the spectroradiometer) and 280 nm, but the limit required by Spanish regulation was exceeded by 11 devices, of which one would have been considered compliant according to the European standard since the effective irradiance was lower than 0.3 Wm−2. Beyond noting the differences that can occur in sunbed inspections according to the established criteria, this work has shown the differences in the spectral and total values of devices in use in Spain, validating the need for periodic inspections. [ABSTRACT FROM AUTHOR]

Shallow and coastal waters are often rich in nutrients (eutrophic), biologically productive, turbid from runoff, and located where the atmosphere above can be more aerosol-laden than over open-ocean waters due to proximity to aerosol sources on land. Although the NASA Earth Observing System's Multi-angle Imaging SpectroRadiometer (MISR) on board the Terra satellite has been monitoring global aerosols for over 23 years, the current operational retrieval algorithm (V23) is not applied over waters less than 50 m in depth or within 5 km of land, designated as "shallow water." This is due to the simplicity of the Dark Water algorithm, applied operationally over deep waters, which assumes the surface is essentially black in the primarily used red and near-infrared spectral bands. In this work, we describe the implementation and validation of a "Shallow Water" aerosol retrieval algorithm for MISR, which takes advantage of all four available spectral bands and includes a Lambertian surface reflectivity term to account for water-leaving radiance. This algorithm compares well to independent, surface-based observations and demonstrates better performance over shallow waters than the operational Dark Water retrieval algorithm. Globally, aerosol retrievals over shallow waters increase the total number of MISR over-water measurements by more than 7 %, including new retrievals made over some of the most biologically productive parts of the ocean. [ABSTRACT FROM AUTHOR]

Remote and proximal sensing platforms at the service of precision olive growing are bringing new development possibilities to the sector. A proximal sensing platform is close to the vegetation, while a remote sensing platform, such as unmanned aerial vehicle (UAV), is more distant but has the advantage of rapidity to investigate plots. The study aims to compare multispectral and hyperspectral data acquired with remote and proximal sensing platforms. The comparison between the two sensors aims at understanding the different responses their use can provide on a crop, such as olive trees having a complex canopy. The multispectral data were acquired with a DJI multispectral camera mounted on the UAV Phantom 4. Hyperspectral acquisitions were carried out with a FieldSpec® HandHeld 2™ Spectroradiometer in the canopy portions exposed to South, East, West, and North. The multispectral images were processed with Geographic Information System software to extrapolate spectral information for each cardinal direction's exposure. The three main Vegetation indices were used: normalized difference vegetation index (NDVI), normalized difference red-edge index (NDRE), and modified soil adjusted vegetation index (MSAVI). Multispectral data could describe the total variability of the whole plot differentiating each single plant status. Hyperspectral data were able to describe vegetation conditions more accurately; they appeared to be related to the cardinal exposure. MSAVI, NDVI, and NDRE showed correlation r =0.63**, 0.69**, and 0.74**, respectively, between multispectral and hyperspectral data. South and West exposures showed the best correlations with both platforms. [ABSTRACT FROM AUTHOR]

Spectroradiometric measurements of direct solar irradiance traceable to the SI were performed by three spectroradiometer systems during a 3-week campaign in September 2022 at the Izaña Atmospheric Observatory (IZO) located on the island of Tenerife, Canary Islands, Spain. The spectroradiometers provided direct spectral irradiance measurements in the spectral ranges 300 to 550 nm (QASUME), 550 to 1700 nm (QASUME-IR), 300 to 2150 nm (BiTec Sensor, BTS), and 316 to 1030 nm (Precision Solar Spectroradiometer, PSR), with relative standard uncertainties of 0.7 %, 0.9 %, and 1 % for QASUME/QASUME-IR, the PSR, and the BTS respectively. The calibration of QASUME and QASUME-IR was validated prior to this campaign at Physikalisch-Technische Bundesanstalt (PTB) by measuring the spectral irradiance from two spectral irradiance sources, the high-temperature blackbody BB3200pg as a national primary standard and the tuneable laser facility TULIP. The top-of-atmosphere (ToA) solar irradiance spectra from the spectroradiometers were retrieved from direct solar irradiance measurements using zero-air-mass extrapolation during cloud-free conditions, which were then compared to the TSIS-1 Hybrid Solar Reference Spectrum (HSRS). These ToA solar spectra agreed to within 1 % for spectral ranges longer than 400 nm (for QASUME also at shorter wavelengths) in the spectral regions free of significant trace gas absorption and were well within the combined uncertainties over the full investigated spectral range. Using the results from the comparison with QASUME, the relative standard uncertainty of the TSIS-1 HSRS ToA solar spectrum in the spectral range 308 to 400 nm could be reduced from its nominal 1.3 % to 0.8 %, representing the relative standard uncertainty of the QASUME ToA solar spectrum in this spectral range. The spectral aerosol optical depth (AOD) retrieved from the solar irradiance measurements of these spectroradiometers using the TSIS-1 HSRS as the reference ToA solar spectrum agreed to within 0.01 in optical depth in nearly all common spectral channels of two narrowband filter radiometers belonging to the Global Atmosphere Watch Precision Filter Radiometer (GAW-PFR) network and Aerosol Robotic Network (AERONET). This study shows that it is now possible to retrieve spectral AOD over the extended spectral range from 300 to 1700 nm using solar irradiance measurements traceable to the SI using laboratory-calibrated spectroradiometers with similar quality to that from traditional Langley-based calibrated instruments. The main improvement to previous investigations is the recent availability of the high-spectral-resolution TSIS-1 HSRS with very low uncertainties, which provides the top-of-atmosphere reference for the spectral atmospheric transmission measurements obtained from ground-based solar irradiance measurements. [ABSTRACT FROM AUTHOR]

The adoption of photovoltaic (PV) modules for clean electricity relies on accurate measurements of their performance, which are essential for estimating their energy production potential. Herein, the calibration chain of PV cells and modules, with particular emphasis on primary reference cell calibrations, is discussed. Also, herein, the direct sunlight method the group has developed for these calibrations is presented and critical improvements and upgrades that lead to calibration uncertainty as low as 0.45% are discussed. The ultimate motivation behind this work is to provide low‐uncertainty performance measurements of PV modules, and lowering the calibration uncertainty of primary reference cells is a key first step toward achieving this goal. As the use of solar electricity continues to grow, the demand for primary reference cell calibrations inevitably increases beyond what the small handful of primary calibration laboratories can provide today. Therefore, this work can serve as a useful guide for implementing primary PV reference cell calibrations using the outdoor method, as well as outlining the critical elements required to make these calibrations highly accurate. [ABSTRACT FROM AUTHOR]

In this work, we present and describe a spectral library (SL) with 15 vascular plant species from Montesinho Natural Park (MNP), a protected area in Northeast Portugal. We selected species from the vascular plants that are characteristic of the habitats in the MNP, based on their prevalence, and also included one invasive species: Alnus glutinosa (L.) Gaertn, Castanea sativa Mill., Cistus ladanifer L., Crataegus monogyna Jacq., Frangula alnus Mill., Fraxinus angustifolia Vahl, Quercus pyrenaica Willd., Quercus rotundifolia Lam., Trifolium repens L., Arbutus unedo L., Dactylis glomerata L., Genista falcata Brot., Cytisus multiflorus (L’Hér.) Sweet, Erica arborea L., and Acacia dealbata Link. We collected spectra (300–2500 nm) from five records per leaf and leaf side, which resulted in 538 spectra compiled in the SL. Additionally, we computed five vegetation indices from spectral data and analysed them to highlight specific characteristics and differences among the sampled species. We detail the data repository information and its organisation for a better understanding of the data and to facilitate its use. The SL structure can add valuable information about the selected plant species in MNP, contributing to conservation purposes. This plant species SL is publicly available in Zenodo platform.

BackgroundAdvancements in field spectrometry have the potential to increase understanding of crop growth and development in response to hot and dry environments. However, as with any instrument used for scientific advancement, it is important to continue developing and optimizing data collection protocols to promote efficiency, safety, and data quality. The goal of this study was to develop a novel data collection method, involving a proximal sensing cart with onboard cooling equipment, to improve deployments of a field spectroradiometer in a hot and dry environment. Advantages and disadvantages of the new method were compared with the traditional backpack approach and other approaches reported in literature.ResultsThe novel method prevented the spectroradiometer from overheating and nearly eliminated the need to halt data collection for battery changes. It also enabled data collection from a significantly larger field area and from more field plots as compared to the traditional backpack method. Use of a custom cooling box to stabilize operating temperatures for the field spectroradiometer also improved stability of white panel data both within and among collections despite outside air temperatures in excess of 30°C.ConclusionsAs compared to traditional data collection approaches for measuring spectral reflectance of field crops in a hot and dry environment, use of a proximal sensing cart with a customized equipment cooling box improved spectroradiometer performance, increased practicality of equipment transport, and reduced operator safety concerns.

Objective: To investigate the effect of cross‐polarization filters on the colors of shade tabs obtained with a digital single‐lens reflex (DSLR) camera, macrolens, and a ring flash. Materials and Methods: Digital images of four shade tables (1M1, 3L2.5, 3R2.5, and 5M3) from the VITA Toothguide 3D‐Master shade guide were taken using a DSLR camera, 100 mm macrolens, and ring flash with two different cross‐polarizing filters (Polar_eyes and Filtropolar), and without (Nonpolarizer; n = 7). The CIE L*a*b* color coordinates of digital images were calculated and remeasured with a spectroradiometer (SR). The color differences (ΔE00) between the SR and digital images were calculated and analyzed with the two‐way analysis of variance (ANOVA) and Tukey HSD test (α = 0.05). Results: ΔE00 values of all test groups were higher than the clinically acceptable threshold (∆E00 > 1.80). While the ∆E00 values of Filtropolar (6.19 ± 0.44) and Polar_eyes (7.82 ± 0.23) groups were significantly higher than the Nonpolarizer (4.69 ± 0.32) for the 1M1 shade tab, ∆E00 value of Polar_eyes (6.23 ± 0.34) was significantly lower than Nonpolarizer (10.71 ± 0.48) group for 5M3 shade tab (p < 0.05). Conclusion: The color‐matching results of tested digital photography techniques with and without cross‐polarization were unacceptable, compared to a spectroradiometer. While digital photography with Polar_eyes cross‐polarizing filter has closer results to the reference device for the low‐in‐value shade table (5M3), for the high‐in‐value shade table (1M1), improved results were obtained without a cross‐polarizing filter. Clinical Significance: The cross‐polarization filters are increasingly used in dentistry for tooth color communication with digital photography techniques. However, the digital photography techniques with‐without cross‐polarization filterers should be improved to obtain clinically acceptable color‐matching results. [ABSTRACT FROM AUTHOR]

The Peak Design Ltd hyperspectral radiometer (HSR1) was tested at the Atmospheric Radiation Measurement User Facility (ARM) Southern Great Plains (SGP) site in Lamont, Oklahoma for two months from May to July 2022. The HSR1 is a prototype instrument that measures total and diffuse spectral irradiance from 360 to 1100 nm with a spectral resolution of 3 nm. The HSR1 spectral irradiance measurements are compared to nearby collocated spectral radiometers including two multifilter rotating shadowband radiometers (MFRSR) and a shortwave array spectroradiometer—hemispheric (SASHe). The total spectral irradiances at 500 nm for the HSR1 compared to the MFRSRs have a mean (relative) difference of 0.01 W m-2 nm-1 (1–2 %). The HSR1 mean diffuse spectral irradiance at 500 nm is smaller than the MFRSRs by 0.03–0.04 (10 %) W m-2 nm-1. The HSR1 clear-sky aerosol optical depth (AOD) is also retrieved by considering Langley regressions and compared to collocated instruments such as the Cimel sunphotometer (CSPHOT), MFRSRs, and SASHe. The mean HSR1 spectral AOD at 500 nm is larger than the CSPHOT by 0.010 (8 %) and larger than the MFRSRs by 0.007–0.017 (6–18 %). In general, good agreement between the HSR1 and other instruments is found in terms of the spectral total irradiance, diffuse irradiance, and AODs at 500 nm. The HSR1 quantities are also compared at other wavelengths to the collocated instruments, where similar agreement is found for the spectral irradiances, although relatively larger disagreement is found at higher wavelengths, especially for spectral AODs. [ABSTRACT FROM AUTHOR]

We report an all-fiber, near-infrared laser heterodyne radiometer (LHR) that uses two distributed feedback (DFB) diode lasers as local oscillators. This scheme allows the retrieval of the column abundances of multiple atmospheric gases of CH4, CO2, and H2O. To improve the detection efficiency, we operated the two DFB diode lasers emitting at 1653 and 1568 nm simultaneously within one scanning cycle. The duration of one scanning cycle was experimentally determined to be 2 s. An atmospheric transmission spectrum of multi-gas was observed within 20 s after averaging ten times. This approach has simplified the sensing system and reduced the probability of being affected by the rapid and random fluctuation of solar radiation due to clouds. We regulated the laser power, and hence, the amplitudes of background heterodyne signals excited by the two local oscillators, to accurately measure the transmission spectrum of each gas species. The results of the sun-tracking observations of this LHR sensor show good agreement with the data taken simultaneously by the GOSAT satellite. [ABSTRACT FROM AUTHOR]

Remote and proximal sensing platforms at the service of precision olive growing are bringing new development possibilities to the sector. A proximal sensing platform is close to the vegetation, while a remote sensing platform, such as unmanned aerial vehicle (UAV), is more distant but has the advantage of rapidity to investigate plots. The study aims to compare multispectral and hyperspectral data acquired with remote and proximal sensing platforms. The comparison between the two sensors aims at understanding the different responses their use can provide on a crop, such as olive trees having a complex canopy. The multispectral data were acquired with a DJI multispectral camera mounted on the UAV Phantom 4. Hyperspectral acquisitions were carried out with a FieldSpec® HandHeld 2™ Spectroradiometer in the canopy portions exposed to South, East, West, and North. The multispectral images were processed with Geographic Information System software to extrapolate spectral information for each cardinal direction’s exposure. The three main Vegetation indices were used: normalized difference vegetation index (NDVI), normalized difference red-edge index (NDRE), and modified soil adjusted vegetation index (MSAVI). Multispectral data could describe the total variability of the whole plot differentiating each single plant status. Hyperspectral data were able to describe vegetation conditions more accurately; they appeared to be related to the cardinal exposure. MSAVI, NDVI, and NDRE showed correlation r =0.63**, 0.69**, and 0.74**, respectively, between multispectral and hyperspectral data. South and West exposures showed the best correlations with both platforms.

Maintaining rich biodiversity and being a habitat and resource for humans, tropical forests are one of the most important global biomes. These forest ecosystems have been experiencing a host of unregulated anthropogenic activities including illegal tourism, and shifting cultivation. The presence of human-habitats in the restricted zones of forest ecosystems is a direct indicator of the human activities that may accelerate deterioration of forest quality by area and tree species composition. Remote sensing data have been extensively used for mapping forest types, and biophysical characterization at various spatial scales. Several remote sensing datasets from multispectral, hyperspectral and LIDAR sensors are available for developing and validating a host of methodologies for remote sensing application in forestry. However, quantifying the quality of forest stands and detecting potential threats from the sporadic and small-scale human activities requires sub-pixel level remote sensing data analysis methods such as, spectral mixture modelling. Generally, most of the studies employ pixel-level supervised learning-based analysis techniques to detect infrastructure and settlements. However, if the settlements are smaller than the ground sampling distance and are under the canopy, pixel-based techniques are not suitable. Reinvigorated with progressive availability of hyperspectral imagery, spectral mixture modelling based sub-pixel image analysis is gaining prominence in the contemporary remote sensing application development. However, there is a paucity of high-resolution hyperspectral imagery and associated ground truth spectral measurements for assessing various methodological approaches on studies related to anthropogenic activities and forest disturbance. Most of the studies have relied upon simulating and synthesising the hyperspectral imagery and its associated ground truth spectra for implementation of methods and algorithms. This article presents a distinct dataset of high-resolution hyperspectral imagery and associated ground truth spectra of various vegetable crops acquired over a tropical forest ecosystem. The dataset is valuable for research on developing new discrimination models of forest and cultivated vegetation, classification methods, spectral matching analysis techniques, and sub-pixel target detection methods.

Cyanobacterial blooms impact aquatic environments and human health. Cyanobacterial biomass is usually estimated using traditional time-consuming and costly field sampling techniques. A remote sensing approach is time and cost efficient and feasible for repetitive monitoring. In this work, we test the potential of various algorithms to retrieve phycocyanin concentration in a Mediterranean lake. Field Spectro radiometric measurements and sampling were performed during 2016 and 2017. The results obtained prove that various ratio models can be used for the estimation of phycocyanin, with the model “R(700)/R(600)” being the best (R2 = 0.716). This research highlights the potential of cyanobacteria mapping using various available satellites.

Retrieval of the cloud thermodynamic phase (CP) is essential for satellite remote sensing and downstream applications. However, there is still a lack of efficient nighttime CP data products. A transfer‐learning‐based deep learning model, transfer‐learning‐ResUnet, is proposed to retrieve the nighttime CP of Himawari‐8 from thermal infrared channels. Cloud products of Himawari‐8 and Moderate‐resolution Imaging Spectroradiometers were selected as labels during training. A benchmark obtained by the Cloud‐Aerosol Lidar and Infrared Pathfinder Satellite Observations confirmed the accuracy of the CP retrieval. During three independent months, the daytime and nighttime retrieval accuracy of the CP was 0.867 and 0.816, respectively, which was superior to that of the Himawari‐8 operational product in the daytime (0.788). Plain Language Summary: Clouds are essential for modulating global weather and climate systems and are routinely monitored by weather satellites such as Himawari‐8, a geostationary Earth‐observing satellite operated by the Japan Meteorological Agency. The cloud thermodynamic phase (CP) product is the main Level 2 product of Himawari‐8 and contains cloud properties. However, Himawari‐8 lacks a nighttime CP product, owing to its retrieval algorithm. Deep learning (DL) has proven to be effective in remote sensing. Among the various deep‐learning model structures, the fusion model of ResNet‐34 and Unet has the most accurate retrieval. Taking this model structure as the basis, the transfer‐learning‐ResUnet was established to improve the retrieval accuracy by integrating the Himawari‐8 and Moderate‐resolution Imaging Spectroradiometers cloud products as labels through a transfer‐learning method. To validate the nighttime CP retrieved by the model, data products obtained by Cloud‐Aerosol Lidar and Infrared Pathfinder Satellite Observations were used. During three independent months, the daytime and nighttime retrieval accuracy of CP retrieval was 0.867 and 0.816, respectively, which were higher than that of Himawari‐8 operational product in the daytime (0.788). Key Points: The cloud thermodynamic phase obtained from Himawari‐8 is essential, but there is no accurate nighttime productA transfer‐learning‐based method provides rapidly obtained and accurate products, with an accuracy higher than that of Himawari‐8 productsIndependent comparisons with Cloud‐Aerosol Lidar and Infrared Pathfinder Satellite Observations and Moderate‐resolution Imaging Spectroradiometers show that the retrieval results are reliable for both daytime and nighttime [ABSTRACT FROM AUTHOR]

Spectroradiometric measurements of direct solar irradiance traceable to the SI were performed by three spectroradiometer systems during a three week campaign in September 2022 at the Izaña Atmospheric Observatory (IZO) located on the island of Tenerife, Canary Islands, Spain. The spectroradiometers provided direct spectral irradiance measurements in the spectral range 300 nm to 550 nm (QASUME), 550 nm to 1700 nm (QASUME-IR), 300 nm to 2150 nm (BTS), and 316 nm to 1030 nm (PSR), with relative standard uncertainties of 0.7%, 0.9% and 1% for QASUME/QASUME-IR, PSR, and BTS respectively. The calibration of QASUME and QASUME-IR was validated prior to this campaign at the PTB by measuring the spectral irradiance from two spectral irradiance sources, the high temperature blackbody BB3200pg as national primary standard and the tuneable laser facility TULIP. The Top of Atmosphere (ToA) solar irradiance spectra from the spectroradiometers were retrieved from direct solar irradiance measurements using zero airmass extrapolation during cloudfree conditions which were then compared to the TSIS-1 HSRS solar spectrum. These ToA solar spectra agreed to within 1% for the spectral range longer than 400 nm (for QASUME also at shorter wavelengths) in the spectral regions free of significant trace gas absorption and well within the combined uncertainties over the full investigated spectral range. Using the results from the comparison with QASUME, the relative standard uncertainty of the TSIS-1 HSRS ToA solar spectrum in the spectral range 308 nm to 400 nm could be reduced from its nominal 1.3% to 0.8%, representing the relative standard uncertainty of the QASUME ToA solar spectrum in this spectral range. The spectral Aerosol Optical Depth (AOD) retrieved from the solar irradiance measurements of these spectroradiometers using TSIS-1 HSRS as the reference ToA solar spectrum agreed to within 0.01 in optical depth in nearly all common spectral channels of two narowband filter radiometers belonging to the GAWPFR and AERONET networks. This study shows that it is now possible to retrieve spectral AOD over the extended spectral range from 300 nm to 1700 nm using solar irradiance measurements traceable to the SI using laboratory calibrated spectroradiometers with similar qual20 ity as from traditional Langley-based calibrated instruments. The main improvement to previous investigations is the recent availability of the high spectral resolution TSIS-1 HSRS solar spectrum with very low uncertainties which provides the Top of Atmosphere reference for the spectral atmospheric transmission measurements obtained from ground based solar irradiance measurements. [ABSTRACT FROM AUTHOR]

This study presents a new total column ozone (TCO) retrieval from the Koherent system, developed at the Physikalisch-Meteorologisches Observatorium Davos, World Radiation Center (PMOD/WRC). The instrument is based on a small, cost-effective, robust, low-maintenance and state-of-the-art-technology array spectroradiometer. It consists of a BTS-2048-UV-S-F array spectroradiometer from Gigahertz-Optik GmbH, coupled with an optical fibre to a lens-based telescope mounted on a sun tracker for measuring direct UV irradiance in the ultraviolet wavelength band between 305 to 345 nm. Two different algorithms are developed for retrieving TCO from these spectral measurements: (1) TCO retrieved by a least-squares-fit algorithm (LSF) and (2) a custom-double-ratio (CDR) technique using four specifically selected wavelengths from the spectral measurements. The double-ratio technique is analogous to the retrieval algorithm applied for the Dobson instruments and the Brewer instruments but is adopted here for TCO retrieval with Koherent. The instrument was calibrated in two different ways: (a) absolute calibration of the spectra using the portable reference for ultraviolet radiation QASUME for the LSF retrieval and (b) relative calibration of the extraterrestrial constant (ETC) of the CDR retrieval by minimising the slope between air mass and the relative differences of TCO from QASUME and Koherent. This adjustment of the ETC allows the instrument to be calibrated with standard TCO reference instruments during calibration campaigns, such as a double-monochromator Brewer. A 2-year comparison in Davos, Switzerland, between Koherent and the Brewer 156 (double monochromator) shows that TCO derived from Koherent and the Brewer 156 agree, on average, over the entire period within 0.7 % for all retrievals in terms of offset. The performance in terms of slant path depends on the selected retrieval and the applied corrections. The stray-light-corrected LSF retrieval exhibits a smaller slant path dependency than the CDR retrieval and performs almost as well as a double-monochromator system. The slant path dependency of the CDR is comparable to the slant path dependency of a single Brewer monochromator. The combination of both retrievals leads to performance with an offset close to zero compared to Brewer 156, a seasonal amplitude of the relative difference of 0.08 % and a slant path dependency of maximum 1.64 %, which is similar to other standard TCO instruments such as single Brewer or Dobson. Applying the double-ratio technique by selecting the wavelengths and slit functions from Brewer and Dobson, respectively, allows for the determination of the effective ozone temperature with an uncertainty of 3 K in terms of daily averages. With the improved TCO retrieval, Koherent serves as a new low-maintenance instrument which could also be used to monitor TCO at remote sites. The TCO retrieval presented here may be applied to other array-based spectroradiometers, providing direct spectral measurements in the ultraviolet wavelength band. [ABSTRACT FROM AUTHOR]

Light is one of the most important factors for photosynthetic organisms to grow. Historically, the amount of light in plant sciences has been referred to as light intensity, irradiance, photosynthetic active radiation, photon flux, photon flux density, etc. On occasion, all these terms are used interchangeably, yet they refer to different physical units and each metric offers distinct information. Even for experts in the fields of plant photobiology, the use of these terms is confusing, and there is a loose implementation of each concept. This makes the use of radiometric units even more confusing to non-experts when looking for ways to measure light, since they could easily feel overwhelmed by the specialized literature. The use of scientific concepts must be accurate, as ambiguity in the use of radiometric quantities can lead to inconsistencies in analysis, thus decreasing the comparability between experiments and to the formulation of incorrect experimental designs. In this review, we provide a simple yet comprehensive view of the use of radiometric quantities in an effort to clarify their meaning and applications. To facilitate understanding, we adopt a minimum amount of mathematical expressions and provide a historical summary of the use of radiometry (with emphasis on plant sciences), examples of uses, and a review of the available instrumentation for radiometric measurements. [ABSTRACT FROM AUTHOR]

A laser correlation study of irradiation damage is carried out on the basis of anodized functional films with the aim of improving the stray light absorptivity in the framework of high-energy laser systems and reducing the contamination of the system after irradiation damage. An experimental study is performed to investigate the effect of different laser characteristics (wavelength, spot diameter, energy and incident angle) on the damage of functional films. On this basis, the damage evolution process was analyzed using ABAQUS secondary development and was in good agreement with the experimental results. In addition, the damage mechanism of the film system is discussed. This study can provide guidance for the optimization of the functional film system, as well as a reference for the design of the main optical path of the high-energy laser system. [ABSTRACT FROM AUTHOR]

Hyperspectral remote sensing is a useful technique for detecting spatio-temporal changes in crop morphological and physiological health. In order to identify the pestsensitive bands for rice leaf folder (RLF), the groundbased hyperspectral data were recorded at varying damage levels. The first- and second-order derivatives were correlated with correlation coefficient r and per cent leaf damage. The common region identified were recognized as sensitive regions (508-529, 671-680, 721-759, 779-786 and 804-820 nm). The absorption dips were also found using Sensitivity and Continuum Removal Analysis. Combining all, a total of nine spectral bands (518, 549, 661, 674, 678, 731, 789, 816 and 898 nm) were identified as pest-sensitive bands for RLF. The feature-selection method was employed using RELIEFF algorithm to find out the band combinations and bands 518, 661 and 731 nm yielded maximum accuracy of 81.67%. [ABSTRACT FROM AUTHOR]

Array spectroradiometers are increasingly being used to measure natural and artificial optical radiation because of their many advantages compared to traditional instruments. This study aims to thoroughly characterise a commercially available, cost-effective array device (AvaSpec ULS2048-LTEC) and compare its measurements of global solar irradiance in the 290–1100 nm wavelength range with those collected during three short-term field campaigns from more advanced, or specifically designed instruments. Moreover, the AvaSpec observations were compared with the output of a radiative transfer model. The results show that, despite its conceptually simple instrumental design, the AvaSpec can provide measurements of nearly comparable quality to those from reference instruments (e.g., UV index and global horizontal irradiance generally within ±5%) if all corrections are performed. These preliminary observations will be the basis of a long-term series at the Aosta–Saint-Christophe observatory, which can be employed to study solar energy production, biological effects and atmospheric composition changes in the Alpine environment. All procedures, including the encountered issues and proposed solutions, are described in detail. [ABSTRACT FROM AUTHOR]

Monitoring grape nutrient status, from flowering to veraison, is important for viticulturists when implementing vineyard management strategies, in order to produce quality wines. However, traditional methods for measuring nutrient elements incur high labour costs. The aim of this study is to explore the potential of predicting grapevine leaf blade nutrient concentration based on hyperspectral data. Leaf blades were collected at two Pinot Noir commercial vineyards at Martinborough, New Zealand. The leaf blade spectral data were obtained with a handheld spectroradiometer, to evaluate surface reflectance and derivative spectra in the spectrum range between 400 and 2400 nm. Afterwards, leaf blades nutrient concentrations (N, P, K, Ca, and Mg) were measured, and their relationships with the hyperspectral data were modelled by machine learning models; partial least squares regression (PLSR), random forest regression (RFR), and support vector regression (SVR) were used. Pearson correlation and recursive feature elimination, based on cross-validation, were used as feature selection methods for RFR and SVR, to improve the model's performance. The variable importance score of PLSR, and permutation variable importance of RFR and SVR, were used to determine the most sensitive wavelengths, or spectral regions related to each biochemical variable. The results showed that the best predictive performance for leaf blade N concentration was based on PLSR to raw reflectance data (R2 = 0.66; RMSE = 0.15%). The combination of support vector regression with the Pearson correlation selected method and second derivative reflectance provided a high accuracy for K and Ca modelling (R2 = 0.7; RMSE = 0.06%; R2 = 0.62; RMSE = 0.11%, respectively). However, the modelling performance for P and Mg, by different feature groups and variable selection methods, was poor (R2 = 0.15; RMSE = 0.02%; R2 = 0.43; RMSE = 0.43%, respectively). Thus, a larger dataset is needed for improving the prediction of P and Mg. The results indicated that for Pinot Noir leaf blades, raw reflectance data had potential for the prediction of N concentration, while the second-derivative spectra were more suitable to predict K and Ca. This study led to the provision of rapid and non-destructive measurements of grapevine leaf nutrient status. [ABSTRACT FROM AUTHOR]

Grapevine virus-associated disease such as grapevine leafroll disease (GLD) affects grapevine health worldwide. Current diagnostic methods are either highly costly (laboratory-based diagnostics) or can be unreliable (visual assessments). Hyperspectral sensing technology is capable of measuring leaf reflectance spectra that can be used for the non-destructive and rapid detection of plant diseases. The present study used proximal hyperspectral sensing to detect virus infection in Pinot Noir (red-berried winegrape cultivar) and Chardonnay (white-berried winegrape cultivar) grapevines. Spectral data were collected throughout the grape growing season at six timepoints per cultivar. Partial least squares-discriminant analysis (PLS-DA) was used to build a predictive model of the presence or absence of GLD. The temporal change of canopy spectral reflectance showed that the harvest timepoint had the best prediction result. Prediction accuracies of 96% and 76% were achieved for Pinot Noir and Chardonnay, respectively. Our results provide valuable information on the optimal time for GLD detection. This hyperspectral method can also be deployed on mobile platforms including ground-based vehicles and unmanned aerial vehicles (UAV) for large-scale disease surveillance in vineyards. [ABSTRACT FROM AUTHOR]