scholarly journals Geostatistical Modelling and Mapping of the Concentration of Gaseous Pollutants

2018 ◽  
Vol 2 (2) ◽  
pp. 219-232
Author(s):  
J. S. Okpoko ◽  
H. A. P. Audu
Keyword(s):  
Root Mean Square ◽  
Gas Flow ◽  
Fine Particulate Matter ◽  
Satellite System ◽  
Gaseous Pollutants ◽  
Mean Square ◽  
Kriging Method ◽  
Geospatial Modelling ◽  
Gis Environment ◽  
Global Navigation Satellite

In this study, the prediction of the concentration of gaseous pollutants around Ughelli West gas flow station in Delta State of Nigeria was carried out using Geostatistical technique in GIS environment. Since air pollutants negatively affect quality of air, lives and the environment, there is therefore the need to frequently monitor air quality, have thorough understanding of the pollutants’ concentration and their spatial distribution in an environment. The gaseous pollutants data of volatile organic compounds (VOCs), methane (CH4), nitrogen dioxide (NO2), sulphur dioxide (SO2) and ozone (O3), were obtained using Multi-parameter gas monitor while that of fine particulate matter (PM2.5) was obtained with SPM meter for a period of three months. Thermo Anemometer was used to obtain the values of wind speed, ambient temperature, atmospheric pressure and relative humidity. Artificial Neural Network designer software (Pythia) was used to validate the acquired field data; predict the concentration of the gaseous pollutants at selected distances from the flow station. The geospatial coordinates of the flow station were obtained using Global Navigation Satellite System (GNSS) receivers; the geospatial modelling and analysis were performed with ArcGIS software and ordinary kriging method of Geostatistical techniques. The results of the maximum concentration for the gaseous pollutants in the study area were 28.17 µg/m3, 19.44 µg/m3, 0.37 µg/m3, 49.81 µg/m3, 0.061 µg/m3 and 0.047µg/m3 for VOCs, CH4, NO2, PM2.5, O3 and SO2 respectively. The root mean square error for the concentration of the gaseous pollutants, ozone and sulphur (IV) oxide in the study area were 0.01618 and 0.008417 indicating a good interpolation model, while their root mean square standard errors, which show the reliability of the predicted values, were 0.70513551 and 0.8459251 respectively. These results conform with the report of other researchers that a better kriging method yields a smaller root mean square and a standard root mean square closer to one. The developed prediction maps for the gaseous pollutants in this study revealed that the study area will experience lower concentration of gaseous pollutants at a distance of 400 m and above.

scholarly journals Utilization of Quasi-Zenith Satellite System for Navigation of a Robot Combine Harvester

Agronomy ◽  
2021 ◽  
Vol 11 (3) ◽  
pp. 483
Author(s):  
Kannapat Udompant ◽  
Ricardo Ospina ◽  
Yong-Joo Kim ◽  
Noboru Noguchi
Keyword(s):  
Root Mean Square ◽  
Satellite System ◽  
Mean Square ◽  
Activation Time ◽  
Lateral Deviation ◽  
Clock Analysis ◽  
Combine Harvester ◽  
Positioning Technique ◽  
Global Navigation Satellite ◽  
Static Conditions

The purpose of this study is to evaluate the performance of a robot combine harvester by comparing the Centimeter Level Augmentation Service (CLAS) and the Multi-Global Navigation Satellite System (GNSS) Advanced Demonstration tool for Orbit and Clock Analysis (MADOCA) from the Quasi-Zenith Satellite System (QZSS) by using the Real Time Kinematic (RTK) positioning technique as a reference. The first section of this study evaluates the availability and the precision under static conditions by measuring the activation time, the reconnection time, and obtaining a Twice Distance Root Mean Square (2DRMS) of 0.04 m and 0.10 m, a Circular Error Probability (CEP) of 0.03 m and 0.08 m, and a Root Mean Square Error (RMSE) of 0.57 m and 0.54 m for the CLAS and MADOCA, respectively. The second section evaluates the accuracy under dynamic conditions by using a GNSS navigation-based combine harvester running in an experimental field. The results show that the RMSE of the lateral deviation is between 0.04 m and 0.69 m for MADOCA and between 0.03 m and 0.31 m for CLAS; which suggest that the CLAS positioning augmentation system can be utilized for the robot combine harvester if the user considers these accuracy and dynamic characteristics.

scholarly journals Global Mean Sea Surface Height Estimated from Spaceborne Cyclone-GNSS Reflectometry

2020 ◽  
Vol 12 (3) ◽  
pp. 356 ◽  
Author(s):  
Hui Qiu ◽  
Shuanggen Jin
Keyword(s):  
Root Mean Square Error ◽  
Mean Square Error ◽  
Correlation Coefficient ◽  
Root Mean Square ◽  
Absolute Error ◽  
Satellite System ◽  
Sea Surface Height ◽  
Sea Surface ◽  
Mean Square ◽  
Mean Sea Surface

Mean sea surface height (MSSH) is an important parameter, which plays an important role in the analysis of the geoid gap and the prediction of ocean dynamics. Traditional measurement methods, such as the buoy and ship survey, have a small cover area, sparse data, and high cost. Recently, the Global Navigation Satellite System-Reflectometry (GNSS-R) and the spaceborne Cyclone Global Navigation Satellite System (CYGNSS) mission, which were launched on 15 December 2016, have provided a new opportunity to estimate MSSH with all-weather, global coverage, high spatial-temporal resolution, rich signal sources, and strong concealability. In this paper, the global MSSH was estimated by using the relationship between the waveform characteristics of the delay waveform (DM) obtained by the delay Doppler map (DDM) of CYGNSS data, which was validated by satellite altimetry. Compared with the altimetry CNES_CLS2015 product provided by AVISO, the mean absolute error was 1.33 m, the root mean square error was 2.26 m, and the correlation coefficient was 0.97. Compared with the sea surface height model DTU10, the mean absolute error was 1.20 m, the root mean square error was 2.15 m, and the correlation coefficient was 0.97. Furthermore, the sea surface height obtained from CYGNSS was consistent with Jason-2′s results by the average absolute error of 2.63 m, a root mean square error ( RMSE ) of 3.56 m and, a correlation coefficient ( R ) of 0.95.

KONTRIBUSI GLOBAL NAVIGATION SATELLITE SYSTEM PADA PENENTUAN TITIK KONTROL UDARA DI METODE FOTOGRAMETRI UNMANNED AERIAL VEHICLE UNTUK PEMETAAN SKALA BESAR DI INDONESIA

2021 ◽  
pp. 867
Author(s):  
Irwan Gumilar ◽  
Deni Suwardhi ◽  
Irfan Budaya ◽  
Brian Bramanto ◽  
Kamal Nur Fauzan
Keyword(s):  
Unmanned Aerial Vehicle ◽  
Global Navigation Satellite System ◽  
Satellite System ◽  
Navigation Satellite ◽  
Mean Square ◽  
Post Processing ◽  
Check Points ◽  
Aerial Vehicle ◽  
Global Navigation ◽  
Global Navigation Satellite

Indonesia saat ini sedang melakukan pemetaan skala besar secara masif. Salah satu metode yang digunakan pada pemetaan skala besar tersebut adalah dengan menggunakan teknik fotogrametri berbasiskan Unmanned Aerial Vehicle (UAV). Saat ini, metode penentuan titik kontrol udara dengan menggunakan Global Navigation Satellite System (GNSS) banyak dilakukan untuk memimalisir jumlah titik kontrol tanah tanpa mengurangi kualitas dari produk fotogrameteri yang dihasilkan. Penelitian ini bertujuan untuk menganalisa kontribusi sistem GNSS pada penentuan titik kontrol udara untuk metode fotogrametri berbasiskan UAV. Pengukuran GNSS frekuensi ganda pada sistem UAV di wilayah Jatinangor, Bandung dan Panglipuran Bali digunakan pada penelitian ini. Panjang baseline antara titik kontrol dan rover berkisar antara 350 hingga 900 m. Penentuan posisi titik kontrol udara berbasiskan GNSS menggunakan metode Post Processing Kinematic (PPK) dengan teknik pemecahan ambiguitas fase LAMBDA Fix and Hold. Pengolahan data GNSS dilakukan dengan menggunakan beberapa kombinasi frekuensi dan sistem GNSS. Evaluasi ketelitian hasil perataan berkas menggunakan titik kontrol udara pada setiap kombinasi frekuensi dan sistem GNSS dilakukan dengan memperhatikan nilai Root Mean Square Error (RMSE) pada 20 titik cek tanah atau Independent Check Points (ICP). Berdasarkan hasil tersebut, kombinasi gelombang L1 dan L2 menggunakan sistem GPS dan BeiDou idealnya digunakan untuk pemetaan skala besar menggunakan fotogrametri UAV. Selain itu, kombinasi data GPS dan Beidou frekuensi ganda memiliki tingkat ketelitian titik kontrol udara yang terbaik dibandingkan kombinasi yang lainnya. Selain itu, kombinasi GPS dan BeiDou menggunakan hanya gelombang L1 memiliki tingkat ketelitian yang sama dibandingkan dengan GPS menggunakan gelombang L1 dan L2.

scholarly journals Mapping The Distribution of Iron Content in Nickel Laterite Deposits Using Indicator Kriging and Ordinary Kriging Interpolation Method

PROMINE ◽  
2021 ◽  
Vol 9 (1) ◽  
pp. 29-36
Author(s):  
Hendro Purnomo
Keyword(s):  
Root Mean Square ◽  
Iron Content ◽  
Ordinary Kriging ◽  
Interpolation Method ◽  
Indicator Kriging ◽  
Kriging Interpolation ◽  
Mean Square ◽  
Kriging Method ◽  
Nickel Laterite ◽  
Kriging Interpolation Method

Beside containing nickel (Ni), nickel laterite deposits also contain other elements, including iron (Fe) which have varying levels in each layer. In this study, the distribution of Fe content in the limonite layers was carried out using the indicator kriging method to analyze the probability distribution of iron levels and ordinary kriging to analyze the variability of iron levels spatially. Fitting the variogram was undertaken by using spherical, exponential and gaussian models. The selection of the best variogram model was carried out based on the smallest root mean square error (RMSE) value, while the estimation of resource potential was calculated by the polygon extended area method. The results of the interpolation show that the distribution of iron anomaly occupies ± 83,3% of the research area with a potential resource of ±64.522.110 ton of iron. The evaluation of the interpolation results base on the root mean square standardized prediction error (RMSP) indicates that the estimation results of iron content using the ordinary kriging method are underestimated.

scholarly journals Assessment of Dual Frequency GNSS Observations from a Xiaomi Mi 8 Android Smartphone and Positioning Performance Analysis

Electronics ◽  
2019 ◽  
Vol 8 (1) ◽  
pp. 91 ◽  
Author(s):  
Umberto Robustelli ◽  
Valerio Baiocchi ◽  
Giovanni Pugliano
Keyword(s):  
Root Mean Square Error ◽  
Mean Square Error ◽  
Global Navigation Satellite System ◽  
Carrier Phase ◽  
Single Point ◽  
Satellite System ◽  
Navigation Satellite ◽  
Mean Square ◽  
Dual Frequency ◽  
Global Navigation Satellite

On May 2018 the world’s first dual-frequency Global Navigation Satellite System (GNSS) smartphone produced by Xiaomi equipped with a Broadcom BCM47755 chip was launched. It is able to receive L1/E1/ and L5/E5 signals from GPS, Galileo, Beidou, and GLONASS (GLObal NAvigation Satellite System) satellites. The main aim of this work is to achieve the phone’s position by using multi-constellation, dual frequency pseudorange and carrier phase raw data collected from the smartphone. Furthermore, the availability of dual frequency raw data allows to assess the multipath performance of the device. The smartphone’s performance is compared with that of a geodetic receiver. The experiments were conducted in two different scenarios to test the smartphone under different multipath conditions. Smartphone measurements showed a lower C/N0 and higher multipath compared with those of the geodetic receiver. This produced negative effects on single-point positioning as showed by high root mean square error (RMS). The best positioning accuracy for single point was obtained with the E5 measurements with a DRMS (horizontal root mean square error) of 4.57 m. For E1/L1 frequency, the 2DRMS was 5.36 m. However, the Xiaomi Mi 8, thanks to the absence of the duty cycle, provided carrier phase measurements used for a static single frequency relative positioning with an achieved 2DRMS of 1.02 and 1.95 m in low and high multipath sites, respectively.

CFD Model Validation for a Benchmark Data of Texas A&M 1/16th Scaled VHTR Upper Plenum

2020 ◽  
Author(s):  
Prasad Vegendla ◽  
Rui Hu ◽  
Ling Zou
Keyword(s):  
High Temperature ◽  
Root Mean Square ◽  
Reynolds Stress ◽  
Gas Flow ◽  
Independent Study ◽  
Mean Square ◽  
Reactor Performance ◽  
Mean Velocity ◽  
Benchmark Data ◽  
Cfd Models

Abstract In High Temperature Gas-cooled Reactors (HTGR), gas flow patterns are very complex and reduced order models (1D or 2D) may be too simplified to predict accurate reactor performance. 3D Computational Fluid Dynamics (CFD) models can help provide the detailed information needed to optimize the reactor thermal performance. The main objective of this work is to validate the CFD models with data of a 1/16th scaled Very High Temperature Reactor (VHTR) upper plenum measured at Texas A&M University. In this paper, the flow characteristics of a single isothermal jet discharging into the upper plenum was investigated using Nek5000 Large-Eddy Simulation (LES) CFD tool. Several numerical simulations were performed for various jet Reynolds numbers ranging from 3,413 to 12,819. Grid independent study was performed. The numerical results of mean velocity, root-mean-square fluctuating velocity, and Reynolds stress were validated with the benchmark data. Good agreement was obtained between simulated and measured data for axial mean velocities, except near the upper plenum hemisphere. The maximum predicted errors for axial mean velocities at various normalized coolant channel diameter heights of 1, 5 and 10 are 1.56%, 1.88% and 3.82%, respectively. Also, the predicted root-mean-square fluctuating velocity and Reynolds stress are qualitatively agreed with the experimental data.

A UAV–RTK Lidar System for Wave and Tide Measurements in Coastal Zones

2018 ◽  
Vol 35 (8) ◽  
pp. 1557-1570 ◽  
Author(s):  
Zhi-Cheng Huang ◽  
Cheng-Yang Yeh ◽  
Kuo-Hsin Tseng ◽  
Wen-Yang Hsu
Keyword(s):  
Root Mean Square ◽  
Low Cost ◽  
Surface Displacement ◽  
Ground Truth ◽  
Satellite System ◽  
Mean Square ◽  
Coastal Zones ◽  
Lidar System ◽  
Tidal Elevation ◽  
Mean Square Errors

AbstractA lightweight and low-cost unmanned aerial vehicle (UAV) system for coastal wave and tide measurements is developed. This system is based on an assembly of a multirotor UAV, a robotic lidar, an altitude and heading reference system (AHRS), and a real-time kinematic (RTK) Global Navigation Satellite System (GNSS). A great advantage of the system is that it can be operated at low altitude in a few meters; the accuracy and spatial resolution can therefore be increased. When the system was moved up and down in 2–12 m, the root-mean-square error (RMSE) was approximately 5 cm compared to the ground truth value measured by a manual RTK GNSS. The system was operated in a hover mode to measure the tide and waves in the field. The results of using the UAV–RTK lidar system were consistent with those of in situ measurements using a pressure sensor. The root-mean-square errors between the two techniques for measurements of tidal elevation, significant wave height, and wave period were 4.9 cm, 4.8 cm, and 0.028 s, respectively. This finding suggests the system could be applied to measure instantaneous sea surface displacement. The system provides the potential for using a low-cost, extremely portable, and efficient tool for monitoring wave properties, topographic changes, and water-level gradients in coastal zones.

scholarly journals Ecogeomorphological Transformations of Aeolian Form—The Case of a Parabolic Dune, Poland

2021 ◽  
Vol 13 (19) ◽  
pp. 3937
Author(s):  
Roksana Zarychta ◽  
Adrian Zarychta ◽  
Katarzyna Bzdęga
Keyword(s):  
Image Fusion ◽  
Root Mean Square ◽  
Near Infrared ◽  
Health Condition ◽  
Global Navigation Satellite Systems ◽  
Anthropogenic Activity ◽  
Mean Square ◽  
Satellite Systems ◽  
Asymmetric Shape ◽  
Global Navigation Satellite

The range of natural environmental degradation caused by anthropogenic activity may include geomorphological forms such as dunes resulting from the build-up activity of the wind. In effect, such environmental transformation affects changes connected not only with their relief, but also with the presence and health of diverse plant and animal inhabitants. The subject of the survey was a parabolic dune with asymmetric shape, the sand of which was subjected to exploitation over many years. Terrain data acquired by means of GNSS (Global Navigation Satellite Systems) served to elaborate the present relief of the surveyed dune and to reconstruct its primary relief. These were mainly places where the impacts of human activities were recorded. For this purpose, ordinary kriging (OK) estimation was performed. Simultaneously, satellite data and UAV (Unmanned Aerial Vehicle) imaging were acquired, and subjected to image fusion in order to acquire near infrared bands (NIR), red, green, blue in high spatial resolution. These in turn were applied so as to estimate the condition of the vegetation overplanting the dune and surrounding terrain. The correctness of the modelling was verified by cross-validation (CV), which disclosed low error values. Such values in present and primary relief were, respectively, mean error (ME) at −0.009 and −0.014, root mean square error (RMSE) at 0.564 and 0.304 and root mean square standardised error (RMSSE) at 0.999 and 1.077. Image fusion, with use of pansharpening allowed a colour-infrared composition (CIR) and a Modified Chlorophyll Absorption in Reflectance Index 1 (MCARI1) to be obtained. Their analysis disclosed that vegetation on the dune is characterised by worse health condition as compared with the surrounding area thereof. The proposed approach enabled the environmental condition of the surveyed dune to be analysed, and thereby it allows for a determination of the consequences of further uncontrolled sand recovery without taking into account the historical cartographic materials customarily considered to be the main source of information.

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