scholarly journals Three-Dimensional Cloud Structure Reconstruction from the Directional Polarimetric Camera

2019 ◽  
Vol 11 (24) ◽  
pp. 2894 ◽  
Author(s):  
Haixiao Yu ◽  
Jinji Ma ◽  
Safura Ahmad ◽  
Erchang Sun ◽  
Chao Li ◽  
...  

Clouds affect radiation transmission through the atmosphere, which impacts the Earth’ s energy balance and climate. Currently, the study of clouds is mostly based on a two-dimensional (2-D) plane rather than a three-dimensional (3-D) space. However, 3-D cloud reconstruction is playing an important role not only in a radiation transmission calculation but in forecasting climate change as well. Currently, the study of clouds is mostly based on 2-D single angle satellite observation data while the importance of a 3-D structure of clouds in atmospheric radiation transmission is ignored. 3-D structure reconstruction would improve the radiation transmission accuracy of the cloudy atmosphere based on multi-angle observations data. Characterizing the 3-D structure of clouds is crucial for an extensive study of this complex intermediate medium in the atmosphere. In addition, it is also a great carrier for visualization of its parameters. Special attributes and the shape of clouds can be clearly illustrated in a 3-D cloud while these are difficult to describe in a 2-D plane. It provides a more intuitive expression for the study of complex cloud systems. In order to reconstruct a 3-D cloud structure, we develop and explore a ray casting algorithm applied to data from the Directional Polarimetric Camera (DPC), which is onboard the GF-5 satellite. In this paper, we use DPC with characteristics of imaging multiple angles of the same target, and characterize observations of clouds from different angles in 3-D space. This feature allows us to reconstruct 3-D clouds from different angles of observations. In terms of verification, we use cloud profile data provided by the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) to compare with the results of reconstructed 3-D clouds based on DPC data. This shows that the reconstruction method has good accuracy and effectiveness. This 3-D cloud reconstruction method would lay a scientific reference for future analysis on the role of clouds in the atmosphere and for the construction of 3-D structures of aerosols.

2018 ◽  
Vol 90 (10) ◽  
pp. 1577-1592 ◽  
Author(s):  
Oscar Björnham ◽  
Håkan Grahn ◽  
Niklas Brännström

AbstractStand-off detection of airborne chemical compounds has proven to be a useful method that is gaining popularity following technical progress. There are obvious advantages compared to in situ measurements when it comes to the security aspect and the ability to measure at locations otherwise hard to reach. However, an inherent limitation in many of the stand-off detection techniques lies in the fact that the measured signal from a chemical depends nonlinearly on the distance to the detector. Furthermore, the measured signal describes the summation of the responses from all chemicals spatially distributed in the line of sight of the instrument. In other words, the three dimensional extension of the chemical plume is converted into a two-dimensional image. Not only is important geometric information per se lost in this process, but the measured signal strength itself depends on the unknown plume distribution which implies that the interpretation of the observation data suffers from significant uncertainty. In this paper we investigate different and novel approaches to reconstruct the original three-dimensional distribution and concentration of the plume by implementation of atmospheric dispersion models and numerical retrieval methods. In particular our method does not require a priori assumptions on the three-dimensional distribution of the plume. We also strongly advocate the use of proper constraints to avoid unphysical solutions being derived (or post-process ‘adjustments’ to correct unphysical solutions). By applying such a reconstruction method, both improved and additional information is obtained from the original observation data, providing important intelligence to the analysts and decision makers.


Author(s):  
Liang Zhao ◽  
Chang-Hua Li ◽  
Fa-Ning Dang ◽  
Chu-Jun Li ◽  
Zhong-Xing Duan

The research of the mechanical properties of concrete, a kind of heterogeneous composite material, was previously established on basis of the mathematical model of random aggregate, which is used to study and analyze the mesoscopic damage mechanism of concrete. Although the shape and distribution of aggregate in the model built by this method are closer to the real structure of concrete, there is still a big difference between them and the real concrete specimen. In order to solve the problem of large amount of redundant computation in the CT reconstruction of full size cube space, a fast reconstruction method based on ray-casting algorithm is proposed. First, a method integrating the new bounding box technology with the plane intersection algorithm clusters were adopted to cut the body data and ray-casting effectively, and then, the polygon scanning and conversion was utilized to reduce the number of cast rays, finally, the adaptive sampling method was used to avoid repeatedly sampling same voxel so that the reconstruction efficiency of whole algorithm and the feasibility of numerical calculation can be enhanced. The experimental results demonstrate that the proposed algorithm can greatly improve the 3D rendering speed of concrete CT without affecting the image quality. It provides a more effective and reliable approach for correctly analyzing the mesoscopic damage mechanism and mechanical characteristics of concrete.


2018 ◽  
Vol 10 (11) ◽  
pp. 1858 ◽  
Author(s):  
Byungsuk Lee ◽  
Larry Di Girolamo ◽  
Guangyu Zhao ◽  
Yizhe Zhan

Characterizing 3-D structure of clouds is needed for a more complete understanding of the Earth’s radiative and latent heat fluxes. Here we develop and explore a ray casting algorithm applied to data from the Multi-angle Imaging SpectroRadiometer (MISR) onboard the Terra satellite, in order to reconstruct 3-D cloud volumes of observed clouds. The ray casting algorithm is first applied to geometrically simple synthetic clouds to show that, under the assumption of perfect, clear-conservative cloud masks, the reconstruction method yields overestimation in the volume whose magnitude depends on the cloud geometry and the resolution of the reconstruction grid relative to the image pixel resolution. The method is then applied to two hand-picked MISR scenes, fully accounting for MISR’s viewing geometry for reconstructions over the Earth’s ellipsoidal surface. The MISR Radiometric Camera-by-camera Cloud Mask (RCCM) at 1.1-km resolution and the custom cloud mask at 275-m resolution independently derived from MISR’s red, green, and blue channels are used as input cloud masks. A wind correction method, termed cloud spreading, is applied to the cloud masks to offset potential cloud movements over short time intervals between the camera views of a scene. The MISR cloud-top height product is used as a constraint to reduce the overestimation at the cloud top. The results for the two selected scenes show that the wind correction using the cloud spreading method increases the reconstructed volume up to 4.7 times greater than without the wind correction, and that the reconstructed volume generated from the RCCM is up to 3.5 times greater than that from the higher-resolution custom cloud mask. Recommendations for improving the presented cloud volume reconstructions, as well as possible future passive remote sensing satellite missions, are discussed.


Author(s):  
Byungsuk Lee ◽  
Larry Di Girolamo ◽  
Guangyu Zhao ◽  
Yizhe Zhan

Abstract: Characterization the 3-D structure of clouds is needed for a more complete understanding of the Earth's radiative and latent heat fluxes. Here we develop and explore a “ray casting” algorithm applied to the Multi-angle Imaging SpectroRadiometer (MISR) on board the Terra satellite, to reconstruct 3-D cloud volumes for observed clouds. The ray casting algorithm is first applied to geometrically simple synthetic clouds to show that, under the assumption of perfect, clear-conservative cloud masks, the reconstruction method yields overestimation whose magnitude depends on the cloud geometry and the resolution of the reconstruction grid relative to the image pixel resolution. The method is then applied to two select MISR scenes, fully accounting for MISR’s viewing geometry for reconstructions over the Earth’s ellipsoidal surface. The MISR Radiometric Camera-by-camera Cloud Masks at 1.1 km resolution and custom cloud masks at 275 m resolution independently derived from MISR RGB channels are used as input cloud masks. A wind correction method, termed “cloud spreading”, is devised and applied to the cloud masks to offset potential cloud movements over short time intervals (around 7 minutes at maximum) between the cameras. The MISR cloud top height product is used as a constraint to reduce the overestimation at the cloud top. The reconstruction results show that their uncertainty is significant when the wind correction is applied, and that they have more refined structures when the input cloud mask has a higher resolution. Recommendations for improving the presented cloud volume reconstructions as well as for future passive remote sensing satellite missions are discussed.


2017 ◽  
Vol 17 (13) ◽  
pp. 8599-8618 ◽  
Author(s):  
Andrew T. Prata ◽  
Stuart A. Young ◽  
Steven T. Siems ◽  
Michael J. Manton

Abstract. We apply a two-way transmittance constraint to nighttime CALIOP (Cloud-Aerosol Lidar with Orthogonal Polarization) observations of volcanic aerosol layers to retrieve estimates of the particulate lidar ratio (Sp) at 532 nm. This technique is applied to three volcanic eruption case studies that were found to have injected aerosols directly into the stratosphere. Numerous lidar observations permitted characterization of the optical and geometric properties of the volcanic aerosol layers over a time period of 1–2 weeks. For the volcanic ash-rich layers produced by the Puyehue-Cordón Caulle eruption (June 2011), we obtain mean and median particulate lidar ratios of 69 ± 13 sr and 67 sr, respectively. For the sulfate-rich aerosol layers produced by Kasatochi (August 2008) and Sarychev Peak (June 2009), the means of the retrieved lidar ratios were 66 ± 19 sr (median 60 sr) and 63 ± 14 sr (median 59 sr), respectively. The 532 nm layer-integrated particulate depolarization ratios (δp) observed for the Puyehue layers (δp = 0.33 ± 0.03) were much larger than those found for the volcanic aerosol layers produced by the Kasatochi (δp = 0.09 ± 0.03) and Sarychev (δp = 0.05 ± 0.04) eruptions. However, for the Sarychev layers we observe an exponential decay (e-folding time of 3.6 days) in δp with time from 0.27 to 0.03. Similar decreases in the layer-integrated attenuated colour ratios with time were observed for the Sarychev case. In general, the Puyehue layers exhibited larger colour ratios (χ′ = 0.53 ± 0.07) than what was observed for the Kasatochi (χ′ = 0.35 ± 0.07) and Sarychev (χ′ = 0.32 ± 0.07) layers, indicating that the Puyehue layers were generally composed of larger particles. These observations are particularly relevant to the new stratospheric aerosol subtyping classification scheme, which has been incorporated into version 4 of the level 2 CALIPSO (Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation) data products.


Author(s):  
Bert Ph. M. Menco ◽  
Ido F. Menco ◽  
Frans L.T. Verdonk

Previously we presented an extensive study of the distributions of intramembranous particles of structures in apical surfaces of nasal olfactory and respiratory epithelia of the Sprague-Dawley rat. For the same structures these distributions were compared in samples which were i) chemically fixed and cryo-protected with glycerol before cryo-fixation, after excision, and ii)ultra-rapidly frozen by means of the slam-freezing method. Since a three-dimensional presentation markedly improves visualization of structural features micrographs were presented as stereopairs. Two exposures were made by tiling the sample stage of the electron microscope 6° in either direction with an eucentric goniometer. The negatives (Agfa Pan 25 Professional) were reversed with Kodak Technical Pan Film 2415 developed in D76 1:1. The prints were made from these reversed negatives. As an example tight-junctional features of an olfactory supporting cell in a region where this cell conjoined with two other cells are presented (Fig. 1).


Author(s):  
Neng-Yu Zhang ◽  
Terence Wagenknecht ◽  
Michael Radermacher ◽  
Tom Obrig ◽  
Joachim Frank

We have reconstructed the 40S ribosomal subunit at a resolution of 4 nm using the single-exposure pseudo-conical reconstruction method of Radermacher et al.Small (40S) ribosomal subunits were Isolated from rabbit reticulocytes, applied to grids and negatively stained (0.5% uranyl acetate) in a manner that “sandwiches” the specimen between two layers of carbon. Regions of the grid exhibiting uniform and thick staining were identified and photographed twice (magnification 49,000X). The first micrograph was always taken with the specimen tilted by 50° and the second was of the Identical area untilted (Fig. 1). For each of the micrographs the specimen was subjected to an electron dose of 2000-3000 el/nm2.Three hundred thirty particles appearing in the L view (defined in [4]) were selected from both tilted- and untilted-specimen micrographs. The untilted particles were aligned and their rotational alignment produced the azimuthal angles of the tilted particles in the conical tilt series.


2020 ◽  
Vol 12 (23) ◽  
pp. 3946
Author(s):  
Pasquale Sellitto ◽  
Silvia Bucci ◽  
Bernard Legras

Clouds in the tropics have an important role in the energy budget, atmospheric circulation, humidity, and composition of the tropical-to-global upper-troposphere–lower-stratosphere. Due to its non-sun-synchronous orbit, the Cloud–Aerosol Transport System (CATS) onboard the International Space Station (ISS) provided novel information on clouds from space in terms of overpass time in the period of 2015–2017. In this paper, we provide a seasonally resolved comparison of CATS characterization of high clouds (between 13 and 18 km altitude) in the tropics with well-established CALIPSO (Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observation) data, both in terms of clouds’ occurrence and cloud optical properties (optical depth). Despite the fact that cloud statistics for CATS and CALIOP are generated using intrinsically different local overpass times, the characterization of high clouds occurrence and optical properties in the tropics with the two instruments is very similar. Observations from CATS underestimate clouds occurrence (up to 80%, at 18 km) and overestimate the occurrence of very thick clouds (up to 100% for optically very thick clouds, at 18 km) at higher altitudes. Thus, the description of stratospheric overshoots with CATS and CALIOP might be different. While this study hints at the consistency of CATS and CALIOP clouds characterizaton, the small differences highlighted in this work should be taken into account when using CATS for estimating cloud properties and their variability in the tropics.


Sensors ◽  
2021 ◽  
Vol 21 (10) ◽  
pp. 3493
Author(s):  
Gahyeon Lim ◽  
Nakju Doh

Remarkable progress in the development of modeling methods for indoor spaces has been made in recent years with a focus on the reconstruction of complex environments, such as multi-room and multi-level buildings. Existing methods represent indoor structure models as a combination of several sub-spaces, which are constructed by room segmentation or horizontal slicing approach that divide the multi-room or multi-level building environments into several segments. In this study, we propose an automatic reconstruction method of multi-level indoor spaces with unique models, including inter-room and inter-floor connections from point cloud and trajectory. We construct structural points from registered point cloud and extract piece-wise planar segments from the structural points. Then, a three-dimensional space decomposition is conducted and water-tight meshes are generated with energy minimization using graph cut algorithm. The data term of the energy function is expressed as a difference in visibility between each decomposed space and trajectory. The proposed method allows modeling of indoor spaces in complex environments, such as multi-room, room-less, and multi-level buildings. The performance of the proposed approach is evaluated for seven indoor space datasets.


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