Underlying Surface Reflectance Research Articles

Research on the outdoor thermal comfort of children in Hangzhou and Its influence on the underlying surface reflectance.

The outdoor thermal comfort (OTC) of children is more specific than that of adults, and the complex influence of outdoor activity spaces on children's thermal comfort warrants further investigation. To investigate the outdoor thermal comfort baseline (OTCB) of children in Hangzhou and explore the thermal impact of outdoor surfaces on children, a survey was conducted in six typical outdoor activity spaces in Hangzhou, China, during spring and summer utilizing physical measurements, questionnaire surveys, and the universal thermal climate index (UTCI). This study analyzed the differences in thermal perception among children in Hangzhou in different seasons, their OTCB, and the impact of surface reflectance (Rs) on children's OTC. The results indicated the following: 1) In spring, children in Hangzhou generally felt comfortable, but their discomfort with heat noticeably increased in summer. 2) The neutral UTCIs (NUTCIs) for Hangzhou children were 11.6°C (spring) and 27.7°C (summer), and the NUTCI ranges (NUTCIRs) were 9.7-17.5°C (spring) and 25.7-30.0°C (summer); additionally, the thermal acceptability ranges (TARs) were 13.2-25.2°C (spring) and 11.8-34.8°C (summer). 3) A high Rs made children feel more uncomfortable with heat, which was primarily due to the space's total shortwave and longwave radiation, which peaked between 14:00 and 15:00. 4) Based on the research findings, corresponding bioclimatic design strategies were proposed. Recommendations include using high Rs underlays with shading, composite underlays, or the future adoption of thermochromic coatings. Keeping permeable underlays moist is essential for activating their cooling mechanisms. Fundamental safety measures are imperative. This study provides valuable data for urban planners and landscape designers to create public spaces suitable for children's outdoor activities, contributing to a harmonious and unified living environment.

Validation of GRASP algorithm product from POLDER/PARASOL data and assessment of multi-angular polarimetry potential for aerosol monitoring

Validation of GRASP algorithm product from POLDER/PARASOL data and assessment of multi-angular polarimetry potential for aerosol monitoring

Reconstructing Cloud Contaminated Pixels Using Spatiotemporal Covariance Functions and Multitemporal Hyperspectral Imagery

One of the major challenges in optical-based remote sensing is the presence of clouds, which imposes a hard constraint on the use of multispectral or hyperspectral satellite imagery for earth observation. While some studies have used interpolation models to remove cloud affected data, relatively few aim at restoration via the use of multi-temporal reference images. This paper proposes not only the use of image time-series, but also the implementation of a geostatistical model that considers the spatiotemporal correlation between them to fill the cloud-related gaps. Using Hyperion hyperspectral images, we demonstrate a capacity to reconstruct cloud-affected pixels and predict their underlying surface reflectance values. To do this, cloudy pixels were masked and a parametric family of non-separable covariance functions was automated fitted, using a composite likelihood estimator. A subset of cloud-free pixels per scene was used to perform a kriging interpolation and to predict the spectral reflectance per each cloud-affected pixel. The approach was evaluated using a benchmark dataset of cloud-free pixels, with a synthetic cloud superimposed upon these data. An overall root mean square error (RMSE) of between 0.5% and 16% of the reflectance was achieved, representing a relative root mean square error (rRMSE) of between 0.2% and 7.5%. The spectral similarity between the predicted and reference reflectance signatures was described by a mean spectral angle (MSA) of between 1° and 11°, demonstrating the spatial and spectral coherence of predictions. The approach provides an efficient spatiotemporal interpolation framework for cloud removal, gap-filling, and denoising in remotely sensed datasets.

The VIS-SWIR spectrum of skylight polarization.

The skylight degree of linear polarization (DoLP) was previously shown to vary primarily with aerosol optical depth and underlying surface reflectance for visible-to-near-infrared (VNIR) wavelengths. This paper extends the study of skylight polarization to 2.5μm in the short-wave infrared (SWIR). A successive-orders-of-scattering radiative transfer code was used to model skylight polarization with measured inputs that included aerosol properties retrieved from a ground-based solar radiometer (extrapolated into the SWIR) and spectral surface reflectance from a handheld spectrometer. The modeled DoLP depended heavily on the aerosol size distribution at SWIR wavelengths and on the aerosol optical depth at VNIR wavelengths. Once the aerosol optical depth became greater than the Rayleigh optical depth, the predicted polarization deviated significantly from Rayleigh scattering theory. The SWIR polarization spectrum generally decreased at wavelengths beyond 1μm at a rate dependent on the aerosol size distribution. The surface reflectance affected the polarization in the same manner throughout the visible (VIS)-SWIR spectrum, with higher reflectance decreasing the skylight polarization. Validation measurements of SWIR skylight polarization in a 1.5-1.8μm band are also shown. These measurements were made on clean and smoky days using a SWIR imaging polarimeter. In both simulations and measurements, the SWIR skylight polarization was greater in the smoky atmosphere than in the clean atmosphere.

Retrieving near‐global aerosol loading over land and ocean from AVHRR

AbstractThe spaceborne advanced very high resolution radiometer (AVHRR) sensor data record is approaching 40 years, providing a crucial asset for studying long‐term trends of aerosol properties regionally and globally. However, due to limitations of its channels' information content, aerosol optical depth (AOD) data from AVHRR over land are still largely lacking. In this paper, we describe a new physics‐based algorithm to retrieve aerosol loading over both land and ocean from AVHRR for the first time. The over‐land algorithm is an extension of our Sea‐viewing Wide Field‐of‐view Sensor and Moderate Resolution Imaging Spectroradiometer (MODIS) Deep Blue algorithm, while a simplified version of our Satellite Ocean Aerosol Retrieval algorithm is used over ocean. We compare retrieved AVHRR AOD with that from MODIS on a daily and seasonal basis and find, in general, good agreement between the two. For the satellites with equatorial crossing times within 2 h of solar noon, the spatial coverage of the AVHRR aerosol product is comparable to that of MODIS, except over very bright arid regions (such as the Sahara), where the underlying surface reflectance at 630 nm reaches the critical surface reflectance. Based upon comparisons of the AVHRR AOD against Aerosol Robotic Network data, preliminary results indicate that the expected error confidence interval envelope is around ±(0.03 + 15%) over ocean and ±(0.05 + 25%) over land for this first version of the AVHRR aerosol products. Consequently, these new AVHRR aerosol products can contribute important building blocks for constructing a consistent long‐term data record for climate studies.

Comprehensive tool for calculation of radiative fluxes: illustration of shortwave aerosol radiative effect sensitivities to the details in aerosol and underlying surface characteristics

Abstract. The evaluation of aerosol radiative effect on broadband hemispherical solar flux is often performed using simplified spectral and directional scattering characteristics of atmospheric aerosol and underlying surface reflectance. In this study we present a rigorous yet fast computational tool that accurately accounts for detailed variability of both spectral and angular scattering properties of aerosol and surface reflectance in calculation of direct aerosol radiative effect. The tool is developed as part of the GRASP (Generalized Retrieval of Aerosol and Surface Properties) project. We use the tool to evaluate instantaneous and daily average radiative efficiencies (radiative effect per unit aerosol optical thickness) of several key atmospheric aerosol models over different surface types. We then examine the differences due to neglect of surface reflectance anisotropy, nonsphericity of aerosol particle shape and accounting only for aerosol angular scattering asymmetry instead of using full phase function. For example, it is shown that neglecting aerosol particle nonsphericity causes mainly overestimation of the aerosol cooling effect and that magnitude of this overestimate changes significantly as a function of solar zenith angle (SZA) if the asymmetry parameter is used instead of detailed phase function. It was also found that the nonspherical–spherical differences in the calculated aerosol radiative effect are not modified significantly if detailed BRDF (bidirectional reflectance distribution function) is used instead of Lambertian approximation of surface reflectance. Additionally, calculations show that usage of only angular scattering asymmetry, even for the case of spherical aerosols, modifies the dependence of instantaneous aerosol radiative effect on SZA. This effect can be canceled for daily average values, but only if sun reaches the zenith; otherwise a systematic bias remains. Since the daily average radiative effect is obtained by integration over a range of SZAs, the errors vary with latitude and season. In summary, the present analysis showed that use of simplified assumptions causes systematic biases, rather than random uncertainties, in calculation of both instantaneous and daily average aerosol radiative effect. Finally, we illustrate application of the rigorous aerosol radiative effect calculations performed as part of GRASP aerosol retrieval from real POLDER/PARASOL satellite observations.

Accuracy assessment of Terra-MODIS aerosol optical depth retrievals

Moderate Resolution Imaging Spectroradiometer (MODIS) aerosol products have been widely used to address environment and climate change subjects with daily global coverage. Aerosol optical depth (AOD) is retrieved by different algorithms based on the pixel surface, determining between land and ocean. MODIS-Terra and Global Aerosol Robotic Network (AERONET) products can be obtained from the Multi-sensor Aerosol Products Sampling System (MAPSS) for coastal regions during 2000-2010. Using data collected from 83 coastal stations worldwide from AERONET from 2000-2010, accuracy assessments are made for coastal aerosol optical depth (AOD) retrieved from MODIS aboard the Terra satellite. AOD retrieved from MODIS at 0.55μm wavelength has been compared With the AERONET derived AOD, because it is reliable with the major wavelength used by many chemistry transport and climate models as well as previous MODIS validation studies. After removing retrievals with quality flags below1 for Ocean algorithm and below 3 for Land algorithm, The accuracy of AOD retrieved from MODIS Dark Target Ocean algorithms (correlation coefficient R2 is 0.844 and a regression equation of τM = 0.91·τA + 0.02 (where subscripts M and A represent MODIS and AERONET respectively), is the greater than the MODIS Dark Target Land algorithms (correlation coefficient R2 is 0.764 and τM = 0.95·τA + 0.03) and the Deep Blue algorithm (correlation coefficient R2 is 0.652 and τM = 0.81·τA + 0.04). The reasons of the retrieval error in AOD are found to be the various underlying surface reflectance. Therefore, the aerosol models and underlying surface reflectance are the dominant factors which influence the accuracy of MODIS retrieval performance. Generally the MODIS Land algorithm implements better than the Ocean algorithm for coastal sites.

Effects of surface reflectance on skylight polarization measurements at the Mauna Loa Observatory

An all-sky imaging polarimeter was deployed in summer 2008 to the Mauna Loa Observatory in Hawaii to study clear-sky atmospheric skylight polarization. The imager operates in five wavebands in the visible and near infrared spectrum and has a fisheye lens for all-sky viewing. This paper describes the deployment and presents comparisons of the degree of skylight polarization observed to similar data observed by Coulson with a principal-plane scanning polarimeter in the late 1970s. In general, the results compared favorably to those of Coulson. In addition, we present quantitative results correlating a variation of the maximum degree of polarization over a range of 70-85% to fluctuation in underlying surface reflectance and upwelling radiance data from the GOES satellite.

Effect of Thin Cirrus Clouds on Dust Optical Depth Retrievals From MODIS Observations

The effect of thin cirrus clouds in retrieving the dust optical depth from MODIS observations is investigated by using a simplified aerosol retrieval algorithm based on the principles of the Deep Blue aerosol property retrieval method. Specifically, the errors of the retrieved dust optical depth due to thin cirrus contamination are quantified through the comparison of two retrievals by assuming dust-only atmospheres and the counterparts with overlapping mineral dust and thin cirrus clouds. To account for the effect of the polarization state of radiation field on radiance simulation, a vector radiative transfer model is used to generate the lookup tables. In the forward radiative transfer simulations involved in generating the lookup tables, the Rayleigh scattering by atmospheric gaseous molecules and the reflection of the surface assumed to be Lambertian are fully taken into account. Additionally, the spheroid model is utilized to account for the nonsphericity of dust particles in computing their optical properties. For simplicity, the single-scattering albedo, scattering phase matrix, and optical depth are specified a priori for thin cirrus clouds assumed to consist of droxtal ice crystals. The present results indicate that the errors in the retrieved dust optical depths due to the contamination of thin cirrus clouds depend on the scattering angle, underlying surface reflectance, and dust optical depth. Under heavy dusty conditions, the absolute errors are comparable to the predescribed optical depths of thin cirrus clouds.

Retrieval of aerosol optical thickness over land using the ATSR‐2 Dual‐Look Satellite Radiometer

We present a new method of retrieving aerosol optical thickness over land that takes advantage of the dual look capability of the ATSR‐2 instrument. Unlike some methods, the approach does not require dense dark vegetation to be located, nor is it dependent upon invariant targets, nor does it assume that the underlying surface reflectance is purely Lambertian. It makes use of a new surface approximation that exploits the property of the surface which is least variable with wavelength to allow atmospheric parameters to be retrieved and, consequently, is applicable over virtually any land surface. The method is tested using simulated ATSR‐2 measurements based upon a radiative transfer model coupled with a surface bidirectional model that includes the hot‐spot effect, and is shown to be robust to the effects of differing underlying canopy types. At high optical depths, the retrieval process achieves a mean error in optical thickness of less than 2.5%, depending on surface type, with a maximum absolute error (for the same data sets) of 5% while at low optical depths errors are of the order of 5%. The effects of systematic error in the simulated radiances are also shown. The method may be readily extended to other multiple look satellite radiometers.