Search Results (8)

Radiative transfer models (RTMs) are often used to retrieve biophysical parameters from earth observation data. RTMs with multi-temporal and realistic forest representations enable radiative transfer (RT) modeling for real-world dynamic processes. To achieve more realistic RT modeling for dynamic forest processes, this study presents the 3D-explicit reconstruction of a typical temperate deciduous forest in 2015 and 2022. We demonstrate for the first time the potential use of bitemporal 3D-explicit RT modeling from terrestrial laser scanning on the forward modeling and quantitative interpretation of: (1) remote sensing (RS) observations of leaf area index (LAI), fraction of absorbed photosynthetically active radiation (FAPAR), and canopy light extinction, and (2) the impact of canopy gap dynamics on light availability of explicit locations. Results showed that, compared to the 2015 scene, the hemispherical-directional reflectance factor (HDRF) of the 2022 forest scene relatively decreased by 3.8% and the leaf FAPAR relatively increased by 5.4%. At explicit locations where canopy gaps significantly changed between the 2015 scene and the 2022 scene, only under diffuse light did the branch damage and closing gap significantly impact ground light availability. This study provides the first bitemporal RT comparison based on the 3D RT modeling, which uses one of the most realistic bitemporal forest scenes as the structural input. This bitemporal 3D-explicit forest RT modeling allows spatially explicit modeling over time under fully controlled experimental conditions in one of the most realistic virtual environments, thus delivering a powerful tool for studying canopy light regimes as impacted by dynamics in forest structure and developing RS inversion schemes on forest structural changes. Full article

This paper aims to assess the relationship between the surface reflectance derived from ground based and aircraft measurements. The parameters of the Rahman–Pinty–Verstraete (RPV) and Ross Thick-LiSparse (RTLS) kernel based bi-directional reflectance distribution functions (BRDF), have been derived using actual measurements of the hemispherical-directional reflectance factor (HDRF), collected during different campaigns over the Railroad Valley Playa. The effect of the atmosphere, including that of the diffuse radiation on bi-directional reflectance factor (BRF) parameter retrievals, assessed using 6S model simulations, was negligible for the low turbidity conditions of the site under investigation (${\tau }_{550}\le 0.05$). It was also shown that the effects of the diffuse radiation on RPV spectral parameters retrieval is linear for the isotropic parameter ${\rho }_0$ and the scattering parameter $\mathrm{\Theta }$, and can be described with a second order polynomial for the k-Minnaert parameter. In order to overcome the lack of temporal collocations between aircraft and in-situ measurements, Monte Carlo 3-D radiative transfer simulations mimicking in-situ and remote sensing techniques were performed on a synthetic parametric meshed scene defined by merging Landsat and Multianglhe Imaging Spectroradiometer (MISR) remote sensing reflectance data. We simulated directional reflectance measurements made at different heights for PARABOLA and CAR, and analyzed them according to practices adopted for real measurements, consisting of the inversion of BRF functions and the calculation of the bi-hemispherical reflectance (BHR). The difference of retrievals against the known benchmarks of kernel parameters and BHR is presented. We associated an uncertainty of up to 2% with the retrieval of area averaged BHR, independently of flight altitudes and the BRF model used for the inversion. As expected, the local nature of PARABOLA data is revealed by the difference of the anisotropic kernel parameters with the corresponding parameters retrieved from aircraft loops. The uncertainty of the resultant BHR fell within $\pm 3\%$. Full article

Radio frequency communication technology has not only greatly improved public network service, but also developed a new technological route for indoor navigation service. However, there is a gap between the precision and accuracy of indoor navigation services provided by indoor navigation service and the expectation of the public. This study proposed a method for constructing a hybrid dual frequency received signal strength indicator (HDRF-RSSI) fingerprint library, which is different from the traditional RSSI fingerprint library constructing method in indoor space using 2.4G radio frequency (RF) under the same Wi-Fi infrastructure condition. The proposed method combined 2.4G RF and 5G RF on the same access point (AP) device to construct a HDRF-RSSI fingerprint library, thereby doubling the fingerprint dimension of each reference point (RP). Experimental results show that the feature discriminability of HDRF-RSSI fingerprinting is 18.1% higher than 2.4G RF RSSI fingerprinting. Moreover, the hybrid radio frequency fingerprinting model, training loss function, and location evaluation algorithm based on the machine learning method were designed, so as to avoid limitation that transmission point (TP) and AP must be visible in the positioning method. In order to verify the effect of the proposed HDRF-RSSI fingerprint library construction method and the location evaluation algorithm, dual RF RSSI fingerprint data was collected to construct a fingerprint library in the experimental scene, which was trained using the proposed method. Several comparative experiments were designed to compare the positioning performance indicators such as precision and accuracy. Experimental results demonstrate that compared with the existing machine learning method based on Wi-Fi 2.4G RF RSSI fingerprint, the machine learning method combining Wi-Fi 5G RF RSSI vector and the original 2.4G RF RSSI vector can effectively improve the precision and accuracy of indoor positioning of the smart phone. Full article

The potential health risks for communities that surround railyards have largely been understudied. Mastery and quality of life (QoL) have been associated with self-reported health status in the general population, but few studies have explored this variable among highly vulnerable low-income groups exposed to harmful air pollutants. This study investigates the relationship between self-reported health status and correlates of Heart Disease Risk Factors (HDRF) and Respiratory Illness (RI) with mastery and QoL acting as potential protective buffers. This cross-sectional study of 684 residents residing near a Southern California railyard attempts to address this limitation. Results from three separate hierarchal linear regressions showed that those who reported being diagnosed with at least one type of HDRF and/or RI reported lower perceived health status. For those that lived further from the railyard, mastery and QoL predicted modest increases in perceived health status. Results suggest that mastery and QoL may be helpful as tools in developing interventions but should not solely be used to assess risk and health outcomes as perceived health status may not measure actual health status. Full article

This technical note presents the first Sentinel-2 data service platform for obtaining atmospherically-corrected images and generating the corresponding value-added products for any land surface on Earth. Using the European Space Agency’s (ESA) Sen2Cor algorithm, the platform processes ESA’s Level-1C top-of-atmosphere reflectance to atmospherically-corrected bottom-of-atmosphere (BoA) reflectance (Level-2A). The processing runs on-demand, with a global coverage, on the Earth Observation Data Centre (EODC), which is a public-private collaborative IT infrastructure in Vienna (Austria) for archiving, processing, and distributing Earth observation (EO) data. Using the data service platform, users can submit processing requests and access the results via a user-friendly web page or using a dedicated application programming interface (API). Building on the processed Level-2A data, the platform also creates value-added products with a particular focus on agricultural vegetation monitoring, such as leaf area index (LAI) and broadband hemispherical-directional reflectance factor (HDRF). An analysis of the performance of the data service platform, along with processing capacity, is presented. Some preliminary consistency checks of the algorithm implementation are included to demonstrate the expected product quality. In particular, Sentinel-2 data were compared to atmospherically-corrected Landsat-8 data for six test sites achieving a R² = 0.90 and Root Mean Square Error (RMSE) = 0.031. LAI was validated for one test site using ground estimations. Results show a very good agreement (R² = 0.83) and a RMSE of 0.32 m²/m² (12% of mean value). Full article

The broadband albedo values retrieved from satellite sensors are usually compared directly to ground measurements. Some authors have noted the necessity of high spatial resolution albedo estimates to fill the gap between ground measurements and satellite retrievals. In this respect, hyperspectral airborne data with high spatial resolution is a powerful tool. Here, a new operational method for the calculation of airborne broadband apparent albedo over the spectral range of 350–2500 nm is presented. This new method uses the Hemispherical Directional Reflectance Factor (HDRF) as a proxy for the narrowband albedo, assuming a Lambertian approximation. The broadband apparent albedo obtained is compared to that estimated using theapparent albedo equation devised for the Moderate Resolution Imaging Spectroradiometer (MODIS). Airborne data were collected using the Airborne Hyperspectral Scanner (AHS). Field data were acquired at three sites: a camelina field, a green grass field, and a vineyard. The HDRF can be used to approximate the narrowband albedo for all View Zenith Angle (VZA) values for flights parallel to the solar principal plane (SPP); for flights orthogonal to the SPP, discrepancies are observed when the VZA approaches −45°. Root Mean Square Error (RMSE) values in the range 0.009–0.018 were obtained using the new method, improving upon previous results over the same area (RMSEs of 0.01–0.03). The relative error in the albedo estimation using the new method is 12% for −36.2° < VZA < 40.8° in the case of flights parallel to the SPP and less than 15% for −13° < VZA < 45° and 45% for VZA = −45° for flights orthogonal to the SPP. The good performance of the new method lies in the use of the at-surface solar irradiance and the proposed integration method. Full article

This article presents and technically describes a new field spectro-goniometer system for the ground-based characterization of the surface reflectance anisotropy under natural illumination conditions developed at the Alfred Wegener Institute (AWI). The spectro-goniometer consists of a Manual Transportable Instrument platform for ground-based Spectro-directional observations (ManTIS), and a hyperspectral sensor system. The presented measurement strategy shows that the AWI ManTIS field spectro-goniometer can deliver high quality hemispherical conical reflectance factor (HCRF) measurements with a pointing accuracy of ±6 cm within the constant observation center. The sampling of a ManTIS hemisphere (up to 30° viewing zenith, 360° viewing azimuth) needs approx. 18 min. The developed data processing chain in combination with the software used for the semi-automatic control provides a reliable method to reduce temporal effects during the measurements. The presented visualization and analysis approaches of the HCRF data of an Arctic low growing vegetation showcase prove the high quality of spectro-goniometer measurements. The patented low-cost and lightweight ManTIS instrument platform can be customized for various research needs and is available for purchase. Full article

The design, operation, and properties of the Finnish Geodetic Institute Field Goniospectrometer (FIGIFIGO) are presented. FIGIFIGO is a portable instrument for the measurement of surface Bidirectional Reflectance Factor (BRF) for samples with diameters of 10 – 50 cm. A set of polarising optics enable the measurement of linearly polarised BRF over the full solar spectrum (350 – 2,500 nm). FIGIFIGO is designed mainly for field operation using sunlight, but operation in a laboratory environment is also possible. The acquired BRF have an accuracy of 1 – 5% depending on wavelength, sample properties, and measurement conditions. The angles are registered at accuracies better than 2°. During 2004 – 2008, FIGIFIGO has been used in the measurement of over 150 samples, all around northern Europe. The samples concentrate mostly on boreal forest understorey, snow, urban surfaces, and reflectance calibration surfaces. Full article