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All-Sky 1 km MODIS Land Surface Temperature Reconstruction Considering Cloud Effects Based on Machine Learning
No full textOpen AccessArticle
All-Sky 1 km MODIS Land Surface Temperature Reconstruction Considering Cloud Effects Based on Machine Learning
by Dongjin ChoORCID,Dukwon Bae,Cheolhee YooORCID,Jungho Im *ORCID,Yeonsu LeeORCID andSiwoo LeeORCID
Department of Urban and Environmental Engineering, Ulsan National Institute of Science and Technology (UNIST), Ulsan 44919, Korea
*
Author to whom correspondence should be addressed.
Academic Editor: Anand Inamdar
Remote Sens. 2022, 14(8), 1815; https://doi.org/10.3390/rs14081815
Received: 9 February 2022 / Revised: 5 April 2022 / Accepted: 7 April 2022 / Published: 9 April 2022
(This article belongs to the Special Issue Land Surface Temperature Estimation Using Remote Sensing)
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Abstract
A high spatio-temporal resolution land surface temperature (LST) is necessary for various research fields because LST plays a crucial role in the energy exchange between the atmosphere and the ground surface. The moderate-resolution imaging spectroradiometer (MODIS) LST has been widely used, but it is not available under cloudy conditions. This study proposed a novel approach for reconstructing all-sky 1 km MODIS LST in South Korea during the summer seasons using various data sources, considering the cloud effects on LST. In South Korea, a Local Data Assimilation and Prediction System (LDAPS) with a relatively high spatial resolution of 1.5 km has been operated since 2013. The LDAPS model???s analysis data, binary MODIS cloud cover, and auxiliary data were used as input variables, while MODIS LST and cloudy-sky in situ LST were used together as target variables based on the light gradient boosting machine (LightGBM) approach. As a result of spatial five-fold cross-validation using MODIS LST, the proposed model had a coefficient of determination (R2) of 0.89???0.91 with a root mean square error (RMSE) of 1.11???1.39 ??C during the daytime, and an R2 of 0.96???0.97 with an RMSE of 0.59???0.60 ??C at nighttime. In addition, the reconstructed LST under the cloud was evaluated using leave-one-station-out cross-validation (LOSOCV) using 22 weather stations. From the LOSOCV results under cloudy conditions, the proposed LightGBM model had an R2 of 0.55???0.63 with an RMSE of 2.41???3.00 ??C during the daytime, and an R2 of 0.70???0.74 with an RMSE of 1.31???1.36 ??C at nighttime. These results indicated that the reconstructed LST has higher accuracy than the LDAPS model. This study also demonstrated that cloud cover information improved the cloudy-sky LST estimation accuracy by adequately reflecting the heterogeneity of the relationship between LST and input variables under clear and cloudy skies. The reconstructed all-sky LST can be used in a variety of research applications including weather monitoring and forecasting
Optimal Band Selection for Airborne Hyperspectral Imagery to Retrieve a Wide Range of Cyanobacterial Pigment Concentration Using a Data-Driven Approach
Get PDFUnderstanding the concentration and distribution of cyanobacteria blooms is an important aspect of managing water quality problems and protecting aquatic ecosystems. Airborne hyperspectral imagery (HSI)-which has high temporal, spatial, and spectral resolutions-is widely used to remotely sense cyanobacteria bloom, and it provides the distribution of the bloom over a wide area. In this study, we determined the input spectral bands that were relevant in effectively estimating the main two pigments (PC, Phycocyanin; Chl-a, Chlorophyll-a) of cyanobacteria by applying data-driven algorithms to HSI and then evaluating the change in the spatio-temporal distribution of cyanobacteria. The input variables for the algorithms consisted of reflectance band ratios associated with the optical properties of PC and Chl-a, which were calculated by the selected hyperspectral bands using a feature selection method. The selected input variable was composed of six reflectance bands (465.7-589.6, 603.6-631.8, 641.2-655.35, 664.8-679.0, 698.0-712.3, and 731.4-784.1 nm). The artificial neural network showed the best results for the estimation of the two pigments with average coefficients of determination 0.80 and 0.74. This study proposes relevant input spectral information and an algorithm that can effectively detect the occurrence of cyanobacteria in the weir pool along the Geum river, South Korea. The algorithm is expected to help establish a preemptive response to the formation of cyanobacterial blooms, and to contribute to the preparation of suitable water quality management plans for freshwater environments
Simple and Reliable Position Sense Assessment Under Different External Torques: Toward Developing a Post-Stroke Proprioception Evaluation Device
Get PDFEvaluation of position sense post-stroke is essential for rehabilitation. Position sense may be an output of a process needing position information, external torque, and the sense of effort. Even for healthy individuals, it is unclear whether external torque affects position sense. Thus, evaluation of position sense under different external torques in clinical settings is strongly needed. However, simple devices for measuring position sense under different external torques in clinical settings are lacking. Technologically advanced devices that may evaluate the elbow position sense under different torques were reported to be infeasible clinically because of device complexity and the need for technical experts when analyzing data. To address the unmet need, in this study, a simple and light elbow position sense measurement device was developed that allows clinicians to measure elbow position sense under different external torques in the form of position matching error objectively without any technical difficulties. The feasibility of the device, including intra-session intra-rater reliability and test-retest reliability over two consecutive days, was verified to be clinically applicable using tests with 25 healthy subjects. Thanks to its ease of use, high reliability, and ease of data analysis, it is expected that the device can help to evaluate the position sense post-stroke comprehensively
Asymmetric Iris Structures for Dual-Polarization Waveguide Slot Arrays for E-Band Wireless Backhaul Systems
No full textThis article proposes a design of waveguide slot arrays with asymmetric iris to achieve broadband properties with high polarization isolation for E-band wireless backhaul systems. The proposed subarray of 2 x 2 radiating slots is excited by two-layered feeding networks carrying two orthogonal waves, and the asymmetric iris is inserted at the intersection where the waves merge. For verification, a prototype with 16 x 16 radiating slots is fabricated, and its antenna characteristics are measured in an anechoic chamber. The fabricated antenna has a bandwidth of 13 GHz at Port 1 and 10.5 GHz at Port 2 for voltage standing wave ratio (VSWR) <= 2.6, and the isolation between two ports is greater than 30 till within the target frequency bands. The average bore-sight gains of the two ports are 30.85 and 31.67 dBi, and the half-power beamwidths are 3.5 degrees and 3.25 degrees. We also fabricate another prototype with 64 x 64 radiating slots for a field test. The proposed prototype is capable of maintaining the received power to he greater than 15 dB for an effective isotropic radiated power of 40.7 dBm at 25 m, which demonstrates that the proposed antenna is suitable to replace current parabolic dish antennas with a reduced profile
Extracellular Vesicle Uptake Assay via Confocal Microscope Imaging Analysis
No full textThere is a need for practical assays to visualize and quantify the cells' extracellular vesicle (EV) uptake. EV uptake plays a role in intercellular communication in various research fields; cancer biology, neuroscience, and drug delivery. Many EV uptake assays have been reported in the literature; however, there is a lack of practical, detailed experimental methodology. EV uptake can be assessed by fluorescently labeling EVs to detect their location within cells. Distinguishing between internalized EVs in cells and the superficial EVs on cells is difficult, yet critical, to accurately determine the EV uptake. Therefore, an assay that efficiently quantifies EV uptake through three-dimensional (3D) fluorescence confocal microscopy is proposed in this work. Fluorescently labeled EVs were prepared using a nano-filtration-based microfluidic device, visualized by 3D confocal microscopy, and then analyzed through advanced image-processing software. The protocol provides a robust methodology for analyzing EVs on a cellular level and a practical approach for efficient analysis
Multichannel convolution neural network for gas mixture classification
No full textConcomitant with people beginning to understand their legal rights or entitlement to complain, complaints of offensive odors and smell pollution have increased significantly. Consequently, monitoring gases and identifying their types and causes in real time has become a critical issue in the modern world. In particular, toxic gases that may be generated at industrial sites or odors in daily life consist of hybrid gases made up of various chemicals. Understanding the types and characteristics of these mixed gases is an important issue in many areas. However, mixed gas classification is challenging because the gas sensor arrays for mixed gases must process complex nonlinear high-dimensional data. In addition, obtaining sufficient training data is expensive. To overcome these challenges, this paper proposes a novel method for mixed gas classification based on analogous image representations with multiple sensor-specific channels and a convolutional neural network (CNN) classifier. The proposed method maps a gas sensor array into a multichannel image with data augmentation, and then utilizes a CNN for feature extraction from such images. The proposed method was validated using public mixture gas data from the UCI machine learning repository and real laboratory experiments. The experimental results indicate that it outperforms the existing classification approaches in terms of the balanced accuracy and weighted F1 scores. Additionally, we evaluated the performance of the proposed method in various experimental settings in terms of data representation, data augmentation, and parameter initialization, so that practitioners can easily apply it to artificial olfactory systems
Non-Fused Polymerized Small Molecular Acceptors for Efficient All-Polymer Solar Cells
No full textThe development of polymer acceptors is critical to promote the power conversion efficiencies (PCEs) of all-polymer solar cells (all-PSCs). Herein, two novel polymer acceptors (PBTz-TT and PFBTz-TT) derived from non-fused small molecules, which possess synthetic simplicity, narrow optical bandgap, and high absorption coefficients, are reported for the first time. The all-PSCs are fabricated by a layer-by-layer deposition technique with PBDB-T as donor, and the device performance is improved by the synergistic effect of solvent additive and thermal annealing. As a result, the all-PSCs offer PCEs of 10.14% and 6.85% for PFBTz-TT and PBTz-TT, respectively. Further morphological and electrical characterizations unveil that the higher device performance of PFBTz-TT originates from more efficient exciton separation and charge transport as a result of more ordered polymer packing in solid state. Herein, it is demonstrated that polymerizing non-fused small molecular acceptors is an effective strategy to develop polymer acceptors for high-performance all-PSCs
GFDM-Based Asynchronous Grant-Free Multiple-Access
No full textFor next-generation Internet-of-Things (IoT) networks, asynchronous instant transmission has attracted increasing research interest with the expectation of achieving near-zero latency without excessive initiation procedure. However, in an asynchronous multiple-access scenario, there exist significant inter-carrier interference between sub-carriers allocated to different users. To suppress out-of-band emission (OOBE) of each sub-carrier, a new generalized frequency division multiplexing (GFDM) has been proposed, which has lower OOBE than the conventional orthogonal frequency division multiplexing (OFDM). In this paper, by using GFDM, two types of receivers are proposed with the aim of reducing latency and improving throughput: a GFDM-based minimum mean square error (MMSE) receiver and a GFDM-based MMSE-successive interference cancellation (SIC) receiver. Then, we develop a lightweight scheme using an epsilon-conservative rate control with GFDM-based MMSE receivers and also invent a performance-focused scheme using an advanced rate control with GFDM-based MMSE-SIC receivers. In particular, the latter scheme provides higher throughput with limited increase in computational load of user equipments. Numerical results show that with a high successful transmission probability higher than 99 %, the performance-focused scheme and the lightweight scheme achieve up to 85 % and up to 70 % higher throughput compared to the conventional OFDM-based asynchronous multiple-access scheme, respectively. Furthermore, since our proposal does not require any centralized user scheduling or initiation procedure, it presents a significant reduction in latency compared to the existing low-latency technologies