scholarly journals Identification and Characterization of an Anomaly in Two-Dimensional Video Disdrometer Data

Atmosphere ◽  
2018 ◽  
Vol 9 (8) ◽  
pp. 315 ◽  
Author(s):  
Michael Larsen ◽  
Michael Schönhuber
Keyword(s):  
Ground Truth ◽  
Rain Event ◽  
Two Dimensional ◽  
Data Set ◽  
Sample Area ◽  
Precipitation Gauge ◽  
Rain Rates ◽  
Quantitative Impact ◽  
Rainfall Retrieval

The two-dimensional video distrometer (2DVD) is a well known ground based point-monitoring precipitation gauge, often used as a ground truth instrument to validate radar or satellite rainfall retrieval algorithms. This instrument records a number of variables for each detected hydrometeor, including the detected position within the sample area of the instrument. Careful analyses of real 2DVD data reveal an artifact—there are time periods where hydrometeor detections within parts of the sample area are artificially enhanced or diminished. Here, we (i) illustrate this anomaly with an exemplary 2DVD data set, (ii) describe the origin of this anomaly, (iii) develop and present an algorithm to help flag data potentially partially corrupted by this anomaly, and (iv) explore the prevalence and quantitative impact of this anomaly. Although the anomaly is seen in every major rain event studied and by every 2DVD the authors have examined, the anomaly artificially induces less than 3% of all detected drops and typically alters estimates of rain rates and accumulations by less than 2%.

scholarly journals A geostatistical approach to multisensor rain field reconstruction and downscaling

2001 ◽  
Vol 5 (2) ◽  
pp. 201-213 ◽  
Author(s):  
P. Fiorucci ◽  
P. La Barbera ◽  
L.G. Lanza ◽  
R. Minciardi
Keyword(s):  
Large Scale ◽  
A Priori ◽  
Grid Cell ◽  
Ground Truth ◽  
Rain Gauge ◽  
Rain Event ◽  
Data Set ◽  
Field Reconstruction ◽  
Geostatistical Approach ◽  
A Posteriori Estimates

Abstract. A rain field reconstruction and downscaling methodology is presented, which allows suitable integration of large scale rainfall information and rain-gauge measurements at the ground. The former data set is assumed to provide probabilistic indicators that are used to infer the parameters of the probability density function of the stochastic rain process at each pixel site. Rain-gauge measurements are assumed as the ground truth and used to constrain the reconstructed rain field to the associated point values. Downscaling is performed by assuming the a posteriori estimates of the rain figures at each grid cell as the a priori large-scale conditioning values for reconstruction of the rain field at finer scale. The case study of an intense rain event recently observed in northern Italy is presented and results are discussed with reference to the modelling capabilities of the proposed methodology. Keywords: Reconstruction, downscaling, remote sensing, geostatistics, Meteosat

Characterization of compounds in crude oils by gas purge micro-syringe extraction coupled to comprehensive two-dimensional gas chromatography

2014 ◽  
Vol 32 (10) ◽  
pp. 1144
Author(s):  
Ting TONG ◽  
Wanfeng ZHANG ◽  
Donghao LI ◽  
Jinhua ZHAO ◽  
Zhenyang CHANG ◽  
...  
Keyword(s):  
Gas Chromatography ◽  
Crude Oils ◽  
Two Dimensional ◽  
Gas Purge

scholarly journals Fig Plant Segmentation from Aerial Images Using a Deep Convolutional Encoder-Decoder Network

2019 ◽  
Vol 11 (10) ◽  
pp. 1157 ◽  
Author(s):  
Jorge Fuentes-Pacheco ◽  
Juan Torres-Olivares ◽  
Edgar Roman-Rangel ◽  
Salvador Cervantes ◽  
Porfirio Juarez-Lopez ◽  
...  
Keyword(s):  
Precision Agriculture ◽  
Image Data ◽  
Ground Truth ◽  
Aerial Images ◽  
Aerial Image ◽  
Data Set ◽  
Visual Appearance ◽  
Aerial Robots ◽  
Lighting Conditions ◽  
Convolutional Encoder

Crop segmentation is an important task in Precision Agriculture, where the use of aerial robots with an on-board camera has contributed to the development of new solution alternatives. We address the problem of fig plant segmentation in top-view RGB (Red-Green-Blue) images of a crop grown under open-field difficult circumstances of complex lighting conditions and non-ideal crop maintenance practices defined by local farmers. We present a Convolutional Neural Network (CNN) with an encoder-decoder architecture that classifies each pixel as crop or non-crop using only raw colour images as input. Our approach achieves a mean accuracy of 93.85% despite the complexity of the background and a highly variable visual appearance of the leaves. We make available our CNN code to the research community, as well as the aerial image data set and a hand-made ground truth segmentation with pixel precision to facilitate the comparison among different algorithms.

scholarly journals Terahertz characterization of two-dimensional low-conductive layers enabled by metal gratings

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Prashanth Gopalan ◽  
Yunshan Wang ◽  
Berardi Sensale-Rodriguez
Keyword(s):  
Optical Transmission ◽  
Terahertz Spectroscopy ◽  
Design Guidelines ◽  
Two Dimensional ◽  
Highly Sensitive ◽  
Transmission Measurements ◽  
Metal Gratings ◽  
Low Sensitivity ◽  
Non Destructive

AbstractWhile terahertz spectroscopy can provide valuable information regarding the charge transport properties in semiconductors, its application for the characterization of low-conductive two-dimensional layers, i.e., σs <  < 1 mS, remains elusive. This is primarily due to the low sensitivity of direct transmission measurements to such small sheet conductivity levels. In this work, we discuss harnessing the extraordinary optical transmission through gratings consisting of metallic stripes to characterize such low-conductive two-dimensional layers. We analyze the geometric tradeoffs in these structures and provide physical insights, ultimately leading to general design guidelines for experiments enabling non-contact, non-destructive, highly sensitive characterization of such layers.

scholarly journals Prediction of Wide Range Two-Dimensional Refractivity Using an IDW Interpolation Method from High-Altitude Refractivity Data of Multiple Meteorological Observatories

2021 ◽  
Vol 11 (4) ◽  
pp. 1431
Author(s):  
Sungsik Wang ◽  
Tae Heung Lim ◽  
Kyoungsoo Oh ◽  
Chulhun Seo ◽  
Hosung Choo
Keyword(s):  
High Altitude ◽  
Korean Peninsula ◽  
Interpolation Method ◽  
Atmospheric Condition ◽  
Propagation Path ◽  
Two Dimensional ◽  
Data Set ◽  
Wide Range ◽  
Atmospheric Data ◽  
Terrain Surface

This article proposes a method for the prediction of wide range two-dimensional refractivity for synthetic aperture radar (SAR) applications, using an inverse distance weighted (IDW) interpolation of high-altitude radio refractivity data from multiple meteorological observatories. The radio refractivity is extracted from an atmospheric data set of twenty meteorological observatories around the Korean Peninsula along a given altitude. Then, from the sparse refractive data, the two-dimensional regional radio refractivity of the entire Korean Peninsula is derived using the IDW interpolation, in consideration of the curvature of the Earth. The refractivities of the four seasons in 2019 are derived at the locations of seven meteorological observatories within the Korean Peninsula, using the refractivity data from the other nineteen observatories. The atmospheric refractivities on 15 February 2019 are then evaluated across the entire Korean Peninsula, using the atmospheric data collected from the twenty meteorological observatories. We found that the proposed IDW interpolation has the lowest average, the lowest average root-mean-square error (RMSE) of ∇M (gradient of M), and more continuous results than other methods. To compare the resulting IDW refractivity interpolation for airborne SAR applications, all the propagation path losses across Pohang and Heuksando are obtained using the standard atmospheric condition of ∇M = 118 and the observation-based interpolated atmospheric conditions on 15 February 2019. On the terrain surface ranging from 90 km to 190 km, the average path losses in the standard and derived conditions are 179.7 dB and 182.1 dB, respectively. Finally, based on the air-to-ground scenario in the SAR application, two-dimensional illuminated field intensities on the terrain surface are illustrated.

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