Variations In Reflectance Research Articles

NDVI or PPI: A (Quick) Comparison for Vegetation Dynamics Monitoring in Mountainous Area

Cold ecosystems are experiencing a warming rate that is twice as fast as the global average and are particularly vulnerable to the consequences of climate change. In mountain ecosystems, it is particularly important to monitor vegetation to understand ecosystem dynamics, biodiversity conservation, and the resilience of these fragile ecosystems to global change. Hence, we used satellite data acquired by Sentinel-2 to perform a comparative assessment of the Normalized Difference Vegetation Index (NDVI) and the Plant Phenology Index (PPI) in mountainous regions (canton of Valais-Switzerland in the European Alps) for monitoring vegetation dynamics of four types: deciduous trees, coniferous trees, grasslands, and shrublands. Results indicate that the NDVI is particularly noisy in the seasonal cycle at the beginning/end of the snow season and for coniferous trees, which is consistent with its known snow sensitivity issue and difficulties in retrieving signal variation in dense and evergreen vegetation. The PPI seems to deal with these problems but tends to overestimate peak values, which could be attributed to its logarithmic formula and derived high sensitivity to variations in near-infrared (NIR) and red reflectance during the peak growing season. Concerning seasonal parameters retrieval, we find close concordance in the results for the start of season (SOS) and end of season (EOS) between indices, except for coniferous trees. Peak of season (POS) results exhibit important differences between the indices. Our findings suggest that PPI is a robust remote sensed index for vegetation monitoring in seasonal snow-covered and complex mountain environments.

Direct extraction of optical constants of organic semiconductors in ultrastrongly coupled microcavities and their application in antireflection design for polariton devices

The strongly bound Frenkel excitons in organic semiconductors enable strong or even ultrastrong exciton-photon coupling in room-temperature cavities, with the resulting polariton states typically resolved through reflectance measurements. This paper demonstrates that the distinct features of exciton and polariton modes in the reflectance spectra of strongly/ultrastrongly coupled organic microcavities can be effectively utilized to extract the optical constants and physical thickness of the embedded organic semiconductor. We investigate metal-clad microcavities based on two prototype conjugated polymers, poly[2-methoxy-5-(3,7-dimethyloctyloxy)-1,4-phenylenevinylene] (MDMO-PPV) and poly(3-hexylthiophene) (P3HT), both exhibiting ultrastrong coupling characteristics. The (n,k) spectra and thickness of these polymer films are determined by fitting the normal incidence reflectance spectra of organic microcavities, using Kramers-Kronig transformation and transfer-matrix calculations with varying optical and thickness parameters. We also examine the individual effects of the main fitting parameters on the spectrum, establishing a close correlation with the underlying polariton properties. Moreover, we analyze the optical admittance at exciton and polariton modes to understand reflectance variations with different parameters, which facilitates precise control of optical properties at specific modes through cavity design. Finally, using the extracted optical constants of MDMO-PPV and P3HT, we propose optimized microcavity designs that exhibit antireflection at the lower polariton mode for potential luminescence and photodetection device applications.

Experimental study of type-I crack propagation in rock monitored by fiber Bragg grating

The occurrence of rock mass engineering disasters can be reduced significantly by obtaining the key information in the process of rock internal fracture accumulation and evolution through advanced monitoring means and taking certain preventive measures. Through fiber Bragg grating monitoring tests of the type-I crack propagation in rock, the spectral characteristics of the fiber Bragg grating in the process of rock failure were analyzed, the bandwidth expansion was extracted to characterize the local tensile strain during the crack propagation process, and the damage variable based on the bandwidth expansion was calculated to describe the type-I crack propagation process. The research results showed the following: (1) The fiber Bragg grating generated a non-uniform local tensile strain during type-I crack propagation. The bandwidth expansion of the wave spectrum was positively correlated with the local tensile strain. The change in the characteristics of the wave spectrum could provide the local real strain in the process of crack propagation. (2) During the steady propagation of the type-I crack, the bandwidth increased obviously, while the number of acoustic emission events was relatively small, and most of them were in the process zone. The gentle increase in the bandwidth corresponded to the unstable growth stage of the type-I crack, which could be used as a precursor of rock sample instability. During loading, the maximum tensile strain of the type-I crack was 6 %, while the maximum shear strain reached 1.8 %, primarily attributed to tensile failure. The average value of fracture toughness KIC, based on the equivalent linear elastic fracture mechanics model, was determined to be 1.21 MPa·m1/2, and the average value of fracture energy Gf was calculated as 57.7 N/m. The variation of peak reflectivity in fiber Bragg grating was associated with the closure of pre-existing defects and the propagation of microcracks in rocks, resulting in unstable shear strain at crack extension sites. (3) The damage variable D defined by the bandwidth broadening began to become concentrated and accumulated in the crack steady growth stage, and it increased slowly in the crack intensification and evolution stage. The grating was sensitive to changes when it was pasted to the surface at 90°, but it could easily fracture or become unable to capture spectral signals in time. Based on a comprehensive comparison, the monitoring effect was the best when the grating was pasted at 60° relative to the crack.

Synthesizing a realistic seismic training data set incorporating prior geologic patterns and seismic imaging features for supervised convolutional neural network-based intracratonic strike-slip fault detection

Intracratonic strike-slip faults play a vital role in hydrocarbon migration and accumulation, making their accurate detection crucial for subsurface structure interpretation and reservoir characterization. Although numerous approaches have been developed for automatic fault interpretation, they are still unable to fully recognize intracratonic strike-slip faults with subtle reflection variations in seismic images. We develop a supervised convolutional neural network (CNN) to automatically and precisely delineate these faults in 3D seismic images. The primary obstacle in using a CNN for this task is the lack of diverse seismic training samples and corresponding high-quality labels. To address this, we develop an efficient two-step workflow for automatically generating a tremendous amount of 3D seismic training sample pairs: (1) guided by the prior geologic structure patterns of the study area, we use parameterized vector fields to simulate various velocity models with accurate fault labels incorporating realistic intracratonic strike-slip faulting features, such as the transtensional, transpressional, and strike-slip translational types and (2) following seismic imaging laws, we synthesize seismic training samples from simulated velocity models through the point-spread function-based convolution method. One synthetic and two field examples demonstrate that the CNN trained with this seismic data set containing prior geologic patterns and seismic imaging features outperforms the conventional fault detection approaches in accurately and continuously delineating intracratonic strike-slip faults.

Separating Surface Reflectance from Volume Reflectance in Medical Hyperspectral Imaging.

Hyperspectral imaging has shown great promise for diagnostic applications, particularly in cancer surgery. However, non-bulk tissue-related spectral variations complicate the data analysis. Common techniques, such as standard normal variate normalization, often lead to a loss of amplitude and scattering information. This study investigates a novel approach to address these spectral variations in hyperspectral images of optical phantoms and excised human breast tissue. Our method separates surface and volume reflectance, hypothesizing that spectral variability arises from significant variations in surface reflectance across pixels. An illumination setup was developed to measure samples with a hyperspectral camera from different axial positions but with identical zenith angles. This configuration, combined with a novel data analysis approach, allows for the estimation and separation of surface reflectance for each direction and volume reflectance across all directions. Validated with optical phantoms, our method achieved an 83% reduction in spectral variability. Its functionality was further demonstrated in excised human breast tissue. Our method effectively addresses variations caused by surface reflectance or glare while conserving surface reflectance information, which may enhance sample analysis and evaluation. It benefits samples with unknown refractive index spectra and can be easily adapted and applied across a wide range of fields where hyperspectral imaging is used.

Rapid characterization of soil horizons for different soil series utilizing Vis-NIR spectral information

The visible-near infrared (Vis-NIR) reflectance technique is a powerful tool, particularly for obtaining faster information about soil texture, organic matter, and calcium carbonate content. However, there is limited research on the characterization of soil horizons using Vis-NIR data in profiles of different soil series. This study investigated the relationship between soil properties and spectral reflectance (Vis-NIR) in eight soil profiles with varying genetic properties from Harran Plain, Türkiye, focusing on variations within profiles (A, B, and C horizons) and across different soil series. A total of 36 soil samples were collected from the A, B, and C horizons, and spectral reflectance was measured along with calcium carbonate, organic matter, and particle size distribution. High variability was observed in calcium carbonate (11.58–52.50%) and organic matter content (0.60–3.71%), reflecting complex soil composition influenced by parent material and land management. Distinct reflectance patterns were observed within profiles, reflecting variations in soil composition. Ap horizons with higher organic matter content often exhibited lower reflectance (visible region). Clay content influenced NIR reflectance, with higher absorption in clay-rich profiles. The Kaynakli series (Fine-loamy, mixed, mesic Typic Calcixerepts) showed differentiation in reflectance between A and B horizons after 700 nm due to horizon formation and clay/carbonate accumulation. Increasing calcium carbonate content in Ck horizons led to higher reflectance compared to other layers. Confirmed that Vis-NIR reflectance could explain a significant portion of the variance in soil properties (A: 87.7%, B: 88.3%, and C: 90.6%). PCA results supported the notion that spectral signatures captured by Vis-NIR reflectance measurements are indicative of inherent differences between A, B, and C horizons. This study contributes to the growing body of knowledge on the application of Vis-NIR spectroscopy for soil assessment and monitoring. However, future research should focus on understanding spectral reflectance variations under diverse soil and environmental conditions.

A coating design to rule them all: asymmetric Fabry-Perot resonators with diverse optical response based on Au films with high-temperature sensitivity.

Thermal annealing of thin metal films induces morphology changes that have a dramatic effect in the optical properties. Here we propose an asymmetric Fabry-Perot resonator consisting of a top metal film, a dielectric spacer, and a bottom metal mirror that can display a diverse infrared response. Thermally induced morphology changes result in large reflectivity variations within a limited temperature range following the top film transition between conductive, highly lossy, and transparent regimes. This behavior arises from the combination of the top film properties with interference effects in the multilayer. Furthermore, the proposed structure holds promise for potential sensing applications, as its optical response displays four times larger temperature sensitivity than a single film.

Parcel level temporal variance of remotely sensed spectral reflectance predicts plant diversity

Over the last two decades, considerable research has built on remote sensing of spectral diversity to assess plant diversity. The spectral variation hypothesis (SVH) proposes that spatial variation in reflectance data of an area is positively associated with plant diversity. While the SVH has exhibited validity in dense forests, it performs poorly in highly fragmented and temporally dynamic agricultural landscapes covered mainly by grasslands. Such underperformance can be attributed to the mosaic-like spatial structure of human-dominated landscapes with fields in varying phenological and management stages. Therefore, we argued for re-evaluating SVH’s flawed window-based spatial analysis and underutilized temporal component. In particular, we captured the spatial and temporal variation in reflectance and assessed the relationships between spatial and temporal components of spectral diversity and plant diversity at the parcel level as a unit that relates to management patterns. Our investigation spanned three grasslands on two continents covering a wide spectrum of agricultural usage intensities. To calculate different components of spectral diversity, we used multi-temporal spaceborne Sentinel-2 data. We showed that plant diversity was negatively associated with the temporal component of spectral diversity across all sites. In contrast, the spatial component of spectral diversity was related to plant diversity in sites with larger parcels. Our findings highlighted that in agricultural landscapes, the temporal component of spectral diversity drives the spectral diversity-plant diversity associations. Consequently, our results offer a novel perspective for remote sensing of plant diversity globally.

Design of optically pumped ultrahigh-performance terahertz sensors based on graphene metamaterials

The surface conductivity of graphene can be precisely adjusted to approach the sigma-near-zero (SNZ) point by manipulating the quasi-Fermi level via optical pumping. This capability holds great promise for advanced graphene metamaterials-based terahertz (THz) sensors. In this study, we present a rational approach for designing two distinct types of patterned graphene THz sensors, each tailored to specific requirements regarding the quasi-Fermi level, resonance frequency, and Q-factor. The first sensor type operates in transmission mode and is well-suited for analytes with refractive indices ranging from 1 to 2. With a fixed analyte thickness of 40 nm, it achieves a frequency sensitivity of 1.036 THz/RIU, a Q-factor between 230 and 360, and a figure of merit (FOM) ranging from 51/RIU to 74/RIU. The second sensor type operates in reflection mode and is optimized for detecting biomolecules with refractive indices between 1.5 and 1.7. It exhibits a significant frequency shift of approximately 0.16 THz and a reflectance variation as high as 0.941 when the bio-analyte thickness is 100 nm. Numerical simulations of the sensing performances confirm the potential of these designed sensors for applications in detecting thin dielectric films and biosensing.

Solar Tracking Control Algorithm Based on Artificial Intelligence Applied to Large-Scale Bifacial Photovoltaic Power Plants

The transition to a low-carbon economy is one of the main challenges of our time. In this context, solar energy, along with many other technologies, has been developed to optimize performance. For example, solar trackers follow the sun’s path to increase the generation capacity of photovoltaic plants. However, several factors need consideration to further optimize this process. Important variables include the distance between panels, surface reflectivity, bifacial panels, and climate variations throughout the day. Thus, this paper proposes an artificial intelligence-based algorithm for solar trackers that takes all these factors into account—mainly weather variations and the distance between solar panels. The methodology can be replicated anywhere in the world, and its effectiveness has been validated in a real solar plant with bifacial panels located in northeastern Brazil. The algorithm achieved gains of up to 7.83% on a cloudy day and obtained an average energy gain of approximately 1.2% when compared to a commercial solar tracker algorithm.

Factors determining tropical upper-level cloud radiative effect in the radiative-convective equilibrium framework

Investigation of the major factors determining tropical upper-level cloud radiative effect (TUCRE) is crucial for understanding cloud feedback mechanisms. We examined the TUCRE inferred from the outputs of historical runs and AMIP runs from CMIP6 models employing a radiative-convective equilibrium (RCE). In this study, we incorporated the RCE model configurations of atmospheric dynamics and thermodynamics from the climate models, while simplifying the intricate systems. Using the RCE model, we adjusted the global mean surface temperature to achieve energy balance, considering variations in tropical cloud fraction, regional reflectivity, and emission temperature corresponding to each climate model. Subsequently, TUCRE was calculated as a unit of K/%, representing the change in global mean surface temperature (K) in response to an increment in the tropical upper-level clouds (%). Our RCE model simulation indicates that the major factors determining the TUCRE are the emission temperatures of tropical moist-cloudy and moist-clear regions, as well as the fraction of tropical upper-level clouds. The higher determination coefficients between TUCRE and both the emission temperature of tropical moist regions and the upper-level cloud fraction are attributable to their contribution to the trapping effect on the outgoing longwave radiations, which predominantly determines TUCRE. Consequently, the results of this study underscore the importance of accurately representing the upper-level cloud fraction and emission temperature in tropical moist regions to enhance the representation of TUCRE in climate models.

Insights into the structural and optical properties of (Cu,Ag)2ZnSnSe4 thin films: Role of pre-annealing and selenization times

The present study investigates the properties of Cu2ZnSnSe4 (CZTSe) absorber layers with silver substitution, scrutinizing how their characteristics improve by varying the pre-annealing and selenization times. The X-ray diffraction (XRD) analysis confirms the presence of tetragonal structured (Cu,Ag)2ZnSnSe4 (CAZTSe) thin films and reveals a peak shift towards lower angles, indicating silver substitution in place of copper within the kesterite lattice. Raman peaks observed at 195 cm−1, 172 cm−1, and 233 cm−1 further support these findings. Particularly, the CAZTSe thin film subjected to a 30-min pre-annealing at 275 °C, followed by a 2-min selenization at 450 °C, exhibits a compact surface morphology. Additionally, Secondary ion mass spectrometry (SIMS) analysis demonstrates a uniform elemental profile throughout the depth of the film. The optical analysis reveals variations in transmittance (T%), reflectance (R%), extinction coefficient (k), and refractive index (n) over a wavelength range of 400–2000 nm. The described CAZTSe thin film possesses a band gap of 1.06 eV. Furthermore, the electrical analysis reveals the highest carrier concentration of 1.12 × 1016 cm−3, a maximum mobility of 260 cm2/(Vs)−1, and the lowest resistivity of 2.15 Ωcm among these CAZTSe thin films.

P‐181: Enhancing the Bragg‐Reflection by Blending Ag Nanoparticles in Polymer Stabilized Cholesteric Liquid Crystals

The coupling between the incident light and the highly reflective nanoparticles is believed to potentially raise the reflective intensity of PSCLCs by creating a channel that causes the incident light to reach the helical CLCs and reflect outward. Therefore, in this research Ag nanoparticles were blended into polymer stabilized cholesteric liquid crystals (PSCLCs) to enhance their reflective intensity. A small amount of blending Ag nanoparticles (less than 1.0 wt%) in PSCLCs that investigated with 1wt% ‐ 3wt% RM 257 polymerization effectively leads to an increase of the reflective intensity of up to 17%, but has little effect on their thermally induced dynamical reflection variations. These results indicate that the blending of Ag nanoparticles in PSCLCs is an adequate method for the investigation of highly reflective PSCLCs.

Reviewing Space-Borne GNSS-Reflectometry for Detecting Freeze/Thaw Conditions of Near-Surface Soils

GNSS-Reflectometry, a technique that harnesses the power of microwave remote sensing, is poised to revolutionize our ability to detect and monitor near-surface soil freeze/thaw processes. This technique’s theoretical underpinnings are deeply rooted in the comprehensive explanation of the Zhang–Zhao dielectric constant model, which provides crucial insights into the behavior of frozen and thawed soils. The model elucidates how the dielectric properties of soil change as it transitions between frozen and thawed states, offering a scientific basis for understanding reflectivity variations. Furthermore, the theoretical framework includes a set of formulas that are instrumental in calculating reflectivity at Lower Right (LR) polarization and in deriving Dual-Polarization Differential Observables (DDMs). These calculations are pivotal for interpreting the signals captured by GNSS-R sensors, allowing for the detection of subtle changes in the soil’s surface conditions. The evolution of GNSS-R as a tool for detecting freeze/thaw phenomena has been substantiated through qualitative analyses involving multiple satellite missions, such as SMAP-R, TDS-1, and CYGNSS. These analyses have provided empirical evidence of the technique’s effectiveness, illustrating its capacity to capture the dynamics of soil freezing and thawing processes. In addition to these qualitative assessments, the application of a discriminant retrieval algorithm using data from CYGNSS and F3E GNOS-R has further solidified the technique’s potential. This algorithm contributes to refining the accuracy of freeze/thaw detection by distinguishing between frozen and thawed soil states with greater precision. The deployment of space-borne GNSS-R for monitoring near-surface freeze/thaw cycles has yielded commendable results, exhibiting robust consistency and delivering relatively precise retrieval outcomes. These achievements stand as testaments to the technique’s viability and its growing significance in the field of remote sensing. However, it is imperative to recognize and actively address certain limitations that have been highlighted in this review. These limitations serve as critical focal points for future research endeavors, directing the efforts toward enhancing the technique’s overall performance and applicability. Addressing these challenges will be essential for leveraging the full potential of GNSS-R to advance our understanding and management of near-surface soil freeze/thaw processes.

Transient reflectance of silicon carbide during laser-induced phase separation

Laser irradiation can induce local modulations of functional material properties, such as a decreased resistivity or a variation in reflectance. Recent studies investigated the laser-induced phase separation of 4 H-SiC into carbon and silicon on top of regrown SiC to customize its electrical conductivity for the application in electronic devices. To understand the physical processes leading to the laser-induced phase separation, time-resolved pump-probe measurements represent a suitable tool. This study advances the state of the art by characterizing the transient reflectance changes in 4 H-SiC upon irradiation by spatially resolved pump-probe reflectometry. Since the laser heating alters the reflectance of the sample, the spatially resolved measurement enables to observe the heat conduction from the irradiated to the non-irradiated areas, which sustains for several milliseconds. Numerical simulations of the temperature evolution reveal a restricted one-dimensional heat conduction into depth due to the broad lateral extent of the irradiated area. The associated sustained increased temperature within the irradiated area most certainly abets the feasibility of the phase separation. These findings offer practical insights for optimizing the applied laser parameters to tailor the material properties via phase separation.

Linking aerial hyperspectral data to canopy tree biodiversity: An examination of the spectral variation hypothesis

AbstractImaging spectroscopy is emerging as a leading remote sensing method for quantifying plant biodiversity. The spectral variation hypothesis predicts that variation in plant hyperspectral reflectance is related to variation in taxonomic and functional identity. While most studies report some correlation between spectral and field‐based (i.e., taxonomic and functional) expressions of biodiversity, the observed strength of association is highly variable, and the utility in applying spectral community properties to examine environmental drivers of communities remains unknown. We linked hyperspectral data acquired by airborne imaging spectrometers with precisely geolocated field plots to examine the spectral variation hypothesis along a temperate‐to‐boreal forest gradient in southern Québec, Canada. First, we examine the degree of association between spectral and field‐based dimensions of canopy tree composition and diversity. Second, we ask whether the relationships between field‐based community properties and the environment are reproduced when using spectral community properties. We found support for the spectral variation hypothesis with the strength of association generally greater for the functional than taxonomic dimension, but the strength of relationships was highly variable and dependent on the choice of method or metric used to quantify spectral and field‐based community properties. Using a multivariate approach (comparisons of separate ordinations), spectral composition was moderately well correlated with field‐based composition; however, the degree of association increased when univariately relating the main axes of compositional variation. Spectral diversity was most tightly associated with functional diversity metrics that quantify functional richness and divergence. For predicting canopy tree composition and diversity using environmental variables, the same qualitative conclusions emerge when hyperspectral or field‐based data are used. Spatial patterns of canopy tree community properties were strongly related to the turnover from temperate‐to‐boreal communities, with most variation explained by elevation. Spectral composition and diversity provide a straightforward way to quantify plant biodiversity across large spatial extents without the need for a priori field observations. While commonly framed as a potential tool for biodiversity monitoring, we show that spectral community properties can be applied more widely to assess the environmental drivers of biodiversity, thereby helping to advance our understanding of the drivers of biogeographical patterns of plant communities.

Temperature dependence of optical properties for thermoplastic composite prepreg during laser in-situ consolidation

The optical properties of the thermoplastic prepreg play a critical role in influencing heating efficiency during the in-situ consolidation process. This study investigates the temperature-dependent reflectance of the prepreg during laser heating. A reflectance testing device is developed based on an in-situ heating system, and the reflectance of carbon fiber/PEEK prepreg is studied from 20 to 500 °C. Through a comparative analysis, the reflectance of pure PEEK films and carbon fibers are individually examined within the same temperature range. The variation in reflectance at different temperatures is explained according to the classical electromagnetic theory. Furthermore, the effect of fiber density on the reflectance of thermoplastic prepreg is explored, and the results indicate that the reflectance of the prepreg decreases from 15.65 % to 11.80 % as the temperature rises from 20 °C to 500 °C, which can be primarily attributed to the decline in carbon fiber reflectance with increasing temperature.

Assessment of the spectral misalignment effect (SMILE) on EarthCARE's Multi-Spectral Imager aerosol and cloud property retrievals

Abstract. The Multi-Spectral Imager (MSI) on board the Earth Cloud, Aerosol and Radiation Explorer (EarthCARE) will provide horizontal information about aerosols and clouds. These measurements are needed to extend vertical cloud and aerosol property information, which is obtained from EarthCARE's active sensors, in order to obtain a full three-dimensional view of cloud and aerosol conditions. Mesoscale weather systems, in particular, will be characterized. The discovery of a non-compliance of the MSI visible–near-infrared–shortwave infrared (VNS) camera’s visible (VIS) and shortwave infrared (SWIR1) channels regarding a spectral central wavelength (CWVL) shift across-track of up to 14 nm (VIS) and 20 nm (SWIR1) led to the need for an analysis regarding its impact on MSI Level-2A aerosol and cloud products. A significant influence of the spectral misalignment effect (SMILE) on MSI retrievals is identified due to the spectral variation in gas absorption, surface reflectance, and aerosol and cloud properties within the spectral ranges of these MSI bands. For example, the VIS channel is positioned in close proximity to the red edge of green vegetation and is impacted by residual absorption of water vapor and ozone. Small central wavelength variations introduce uncertainties due to the rapid change in surface reflectance for conditions with low optical thickness. The present central wavelength shift in the VIS towards shorter wavelengths than at nadir introduces a relative error in transmission of up to 3.3 % due to the increasing influence of water vapor and ozone absorption. We found relative errors in the top-of-atmosphere (TOA) signal due to the SMILE of up to 30 % for low optical thickness over a land surface in that band. Since the magnitude of the impact strongly depends on the underlying surface and atmospheric conditions, we conclude that accounting for the SMILE in Level-2 retrievals or correcting the Level-1 signal will improve MSI aerosol and cloud product quality.

Seasonal and altitudinal variation in dorsal skin reflectance and thermic rates in a high-altitude montane lizard.

Temperature is one of the most important factors in the life histories of ectotherms, as body temperature has an undeniable effect on growth, activity, and reproduction. Lizards have a wide variety of strategies to acquire and maintain body temperature in an optimal range. The "Thermal Melanism Hypothesis" proposes that individuals with lower skin reflectance can heat up faster as a result of absorbing more solar radiation compared to lighter conspecifics. Therefore, having a darker coloration might be advantageous in cold habitats. Dorsal skin reflectance has been found to change rapidly with body temperature in several lizard species, and it can also vary over longer, seasonal time scales. These variations may be important in thermoregulation, especially in lizards that inhabit areas with a large temperature variation during the year. Here, we study how dorsal reflectance fluctuates with body temperature and varies among seasons. We compared dorsal skin reflectance at three body temperature treatments, and measured thermal rates (i.e., heat and cool rate, thermic lapse, and net heat gain) by elevation (2500-4100m) and seasons (spring, summer, and autumn) in the mesquite lizard, Sceloporus grammicus. Our results show that lizards were darker at high elevations and during the months with the lowest environmental temperatures. The rate of obtaining and retaining heat also varied during the year and was highest during the reproductive season. Our results indicate that the variation of dorsal skin reflectance and thermal rates follows a complex pattern in lizard populations and is affected by both elevation and season.

First retrieval of daily 160 m aerosol optical depth over urban areas using Gaofen-1/6 synergistic observations: Algorithm development and validation

The satellite-based aerosol optical depth (AOD), which can provide continuous spatial observations of aerosol loadings, is widely adopted to estimate atmospheric environmental quality and evaluate its risk for human health. However, current satellite-retrieved AOD products characterized by a comparatively coarse spatial resolution (≥1 km) can hardly analyze the structure of atmospheric pollution or its correlation with urban landscapes over populated urban areas. Existed studies have tried to address this deficiency by retrieving high-resolution AOD using Landsat images, whose long revisit period (16 days nominally), however, largely limits its applications related to urban air pollution research. To achieve both high spatial resolution and expected revisit period from satellite observation, in this study, a comprehensive AOD retrieval framework is developed for Wide-Field-of-View (WFV) satellite sensors to yield a daily AOD dataset over urban areas with 160 m spatial resolution, based on the Gaofen-1 and Gaofen-6 synergistic observations. To address the crucial challenge that the high spatial resolution and complex urban landscape both contribute a dramatic variation of land surface bidirectional reflectance, a Simulated-Annealing-coupled Semiempirical Modified Rahman-Pinty-Verstraete (SAS-MRPV) scheme is proposed to model and estimate the land surface reflectance (LSR) in the AOD retrieval framework, where the SAS-MRPV scheme is implemented using simulated annealing iteration initialized by the bidirectional reflectance distribution function (BRDF) products from the Moderate Resolution Imaging Spectrometer (MODIS) as a priori knowledge. The validation results demonstrate that the Gaofen WFV AOD retrievals exhibit good agreement with the ground-based AErosol RObotic NETwork (AERONET) and SONET (Sun-sky radiometer Observation NETwork) AOD, demonstrating the correlation coefficient and the expected error (EE)±(0.05 + 0.15AODAERONET/SONET) ratio respectively reaching up to 0.97 and over 80 %, and only slight bias fluctuations are found under different land cover types, aerosol loading, and seasonal conditions. Moreover, the validation results of Gaofen WFV AOD retrievals, with LSR estimated based on the SAS-MRPV scheme, the MODIS BRDF Products, and the Minimum Reflectance Technique (MRT) method, demonstrate better accuracy and completeness of AOD retrievals using the SAS-MPRV scheme over both natural and impervious land surfaces, indicating the stability and reliability of proposed SAS-MRPV LSR determination scheme in WFV AOD retrieval. In addition to that, the error analyses and quality control results demonstrate that the SAS-MRPV scheme is effective and necessary to guarantee the reliability and accuracy of land surface bidirectional reflectance estimation by identifying and excluding the land surface pixels unsuitable for LSR modeling, which mitigates the uncertainty and yield better accuracy in the final WFV AOD products. Furthermore, the inter-comparison between WFV-derived AOD against the operational MODIS Deep Blue (10 km), Dark Target (3 km), and Multi-Angle Implementation of Atmospheric Correction (MAIAC, 1 km) AOD products demonstrates that the 160 m WFV AOD retrievals, on the basis of obtaining similar aerosol overall descriptions as MODIS AOD retrievals, possess the capability to characterize the spatial distribution of atmospheric pollution at a finer scale with smoother variation under both clean and polluted conditions. With outstanding accuracy and reliable performance, the developed comprehensive high-resolution AOD retrieval framework exhibits substantial potential for operational AOD retrieval of Gaofen WFV satellite observations, which could be directly applied to other urban areas supporting further studies related to air pollution emission management and health risk assessment at extra-fine spatial scale.