Real-time and near real-time ZTD from a local network of low-cost dual-frequency GNSS receivers.

The dynamics of water vapor distribution in the troposphere, measured with Global Navigation Satellite Systems (GNSS), is a subject of weather research and climate studies. With GNSS, remote sensing of the troposphere in Europe is performed continuously and operationally under the E-GVAP (http://egvap.dmi.dk/) program with more than 2000 permanent stations. These data are one of the assimilation system component of mesoscale weather prediction models (10 km scale) for many nations across Europe. However, advancing precise local forecasts for severe weather requires high resolution models and observing system.&#160; &#160;Further densification of the tracking network, e.g. in urban or mountain areas, will be costly when considering geodetic-grade equipment. However, the rapid development of GNSS-based applications results in a dynamic release of mass-market GNSS receivers. It has been demonstrated that post-processing of GPS-data from a dual-frequency low-cost receiver allows retrieving ZTD with high accuracy. Although low-cost receivers are a promising solution to the problem of densifying GNSS networks for water vapor monitoring, there are still some technological limitations and they require further development and calibration.We have developed a low-cost GNSS station, dedicated to real-time GNSS meteorology, which provides GPS, GLONASS and Galileo dual-frequency observations either in RINEX v3.04 format or via RTCM v3.3 stream, with either Ethernet or GSM data transmission. The first two units are deployed in a close vicinity of permanent station WROC, which belongs to the International GNSS Service (IGS) network. Therefore, we compare results from real-time and near real-time processing of GNSS observations from a low-cost unit with IGS Final products. We also investigate the impact of replacing a standard patch antenna with an inexpensive survey-grade antenna. Finally, we deploy a local network of low-cost receivers in and around the city of Wroclaw, Poland, in order to analyze the dynamics of troposphere delay at a very high spatial resolution.As a measure of accuracy, we use the standard deviation of ZTD differences between estimated ZTD and IGS Final product. For the near real-time mode, that accuracy is 5&#160;mm and 6 mm, for single- (L1) and dual-frequency (L1/L5,E5b) solution, respectively. Lower accuracy of the dual-frequency relative solution we justify by the missing antenna phase center correction model for L5 and E5b frequencies. With the real-time Precise Point Positioning technique, we estimate ZTD with the accuracy of 7.5 &#8211; 8.6 mm. After antenna replacement, the accuracy is improved almost by a factor of 2 (to 4.1 mm), which is close to the 3.1&#160;mm accuracy which we obtain in real-time using data from the WROC station.

Download Full-text

Potential of Cost-Efficient Single Frequency GNSS Receivers for Water Vapor Monitoring

Remote Sensing ◽

10.3390/rs10091493 ◽

2018 ◽

Vol 10 (9) ◽

pp. 1493 ◽

Cited By ~ 10

Author(s):

Andreas Krietemeyer ◽

Marie-claire ten Veldhuis ◽

Hans van der Marel ◽

Eugenio Realini ◽

Nick van de Giesen

Keyword(s):

Water Vapor ◽

Low Cost ◽

Global Navigation Satellite Systems ◽

Single Frequency ◽

Small Scale ◽

Reference Network ◽

Tropospheric Delay ◽

Dual Frequency ◽

Gnss Receivers ◽

Cost Efficient

Dual-frequency Global Navigation Satellite Systems (GNSSs) enable the estimation of Zenith Tropospheric Delay (ZTD) which can be converted to Precipitable Water Vapor (PWV). The density of existing GNSS monitoring networks is insufficient to capture small-scale water vapor variations that are especially important for extreme weather forecasting. A densification with geodetic-grade dual-frequency receivers is not economically feasible. Cost-efficient single-frequency receivers offer a possible alternative. This paper studies the feasibility of using low-cost receivers to increase the density of GNSS networks for retrieval of PWV. We processed one year of GNSS data from an IGS station and two co-located single-frequency stations. Additionally, in another experiment, the Radio Frequency (RF) signal from a geodetic-grade dual-frequency antenna was split to a geodetic receiver and two low-cost receivers. To process the single-frequency observations in Precise Point Positioning (PPP) mode, we apply the Satellite-specific Epoch-differenced Ionospheric Delay (SEID) model using two different reference network configurations of 50–80 km and 200–300 km mean station distances, respectively. Our research setup can distinguish between the antenna, ionospheric interpolation, and software-related impacts on the quality of PWV retrievals. The study shows that single-frequency GNSS receivers can achieve a quality similar to that of geodetic receivers in terms of RMSE for ZTD estimations. We demonstrate that modeling of the ionosphere and the antenna type are the main sources influencing the ZTD precision.

Download Full-text

Research and Development of Real-time High-precision GNSS Receivers: A Feasible Application for Surveying and Mapping in Vietnam

Inżynieria Mineralna ◽

10.29227/im-2021-02-36 ◽

2021 ◽

Vol 1 (2) ◽

Author(s):

Cong Khai PHAM ◽

Gia Trong NGUYEN ◽

Van Hai NGUYEN ◽

Trong Xuan TRAN

Keyword(s):

Real Time ◽

Low Cost ◽

Satellite System ◽

Dual Frequency ◽

Standard Format ◽

Gnss Receiver ◽

Programming Tool ◽

Standard Design ◽

Gnss Receivers ◽

Surveying And Mapping

In recent years, the Global Navigation Satellite System (GNSS) has been widely applied insurveying and mapping. Currently, in Vietnam, dual-frequency GNSS receivers are quite extensivelyapplied with the real-time kinematic (RTK) measurement technique using a continuously operatingreference station network. However, high-accuracy GNSS receivers are often expensive, sometimes notmeeting the needs of users for specific applications. This research develops two types of low-cost highprecisionGNSS receivers for RTK positioning for different purposes. First, the millimeter precisionGNSS receiver used in real-time displacement monitoring is based on Trimble's BD970 mainboardtechnology and some other modules. These components are interconnected according to a standarddesign scheme and assembled in an enclosure to form a GNSS receiver. In addition, a GNSS datatransmission in the National Marine Electronics Association standard format by Networked Transport ofRadio Technical Commission for Maritime Services via Internet Protocol (NTRIP) has beendesigned and developed. The GNSS receiver after development is loaded with program code written inthe C# programming language, using the Arduino programming tool. Second, the GNSS receivers havethe centimeter accuracy for RTK positioning used in surveying and mapping based on U-blox'smainboard technology and some other modules. These modules are also connected together according toa standard design scheme and assembled in an enclosure to form a complete GNSS receiver. Theevaluation results show that the designed and developed GNSS receivers completely meet therequirements of surveying and mapping in coal mines in Vietnam, such as real-time monitoring oflandslides, surveying and topographical mapping and other surveying works to serve the mining process.

Download Full-text

HGPT2: An ERA5-Based Global Model to Estimate Relative Humidity

Remote Sensing ◽

10.3390/rs13112179 ◽

2021 ◽

Vol 13 (11) ◽

pp. 2179

Author(s):

Pedro Mateus ◽

Virgílio B. Mendes ◽

Sandra M. Plecha

Keyword(s):

Water Vapor ◽

Relative Humidity ◽

Real Time ◽

Prediction Models ◽

Weather Prediction ◽

Precipitable Water ◽

Precipitable Water Vapor ◽

Global Navigation Satellite Systems ◽

International Gnss Service ◽

Weighted Mean Temperature

The neutral atmospheric delay is one of the major error sources in Space Geodesy techniques such as Global Navigation Satellite Systems (GNSS), and its modeling for high accuracy applications can be challenging. Improving the modeling of the atmospheric delays (hydrostatic and non-hydrostatic) also leads to a more accurate and precise precipitable water vapor estimation (PWV), mostly in real-time applications, where models play an important role, since numerical weather prediction models cannot be used for real-time processing or forecasting. This study developed an improved version of the Hourly Global Pressure and Temperature (HGPT) model, the HGPT2. It is based on 20 years of ERA5 reanalysis data at full spatial (0.25° × 0.25°) and temporal resolution (1-h). Apart from surface air temperature, surface pressure, zenith hydrostatic delay, and weighted mean temperature, the updated model also provides information regarding the relative humidity, zenith non-hydrostatic delay, and precipitable water vapor. The HGPT2 is based on the time-segmentation concept and uses the annual, semi-annual, and quarterly periodicities to calculate the relative humidity anywhere on the Earth’s surface. Data from 282 moisture sensors located close to GNSS stations during 1 year (2020) were used to assess the model coefficients. The HGPT2 meteorological parameters were used to process 35 GNSS sites belonging to the International GNSS Service (IGS) using the GAMIT/GLOBK software package. Results show a decreased root-mean-square error (RMSE) and bias values relative to the most used zenith delay models, with a significant impact on the height component. The HGPT2 was developed to be applied in the most diverse areas that can significantly benefit from an ERA5 full-resolution model.

Download Full-text

Developing Relative Humidity and Temperature Corrections for Low-Cost Sensors Using Machine Learning

Sensors ◽

10.3390/s21103338 ◽

2021 ◽

Vol 21 (10) ◽

pp. 3338

Author(s):

Ivan Vajs ◽

Dejan Drajic ◽

Nenad Gligoric ◽

Ilija Radovanovic ◽

Ivan Popovic

Keyword(s):

Machine Learning ◽

Air Quality ◽

Relative Humidity ◽

Low Cost ◽

Quality Monitoring ◽

Air Quality Monitoring ◽

Lower Accuracy ◽

Wide Range ◽

The Impact ◽

Monitoring Stations

Existing government air quality monitoring networks consist of static measurement stations, which are highly reliable and accurately measure a wide range of air pollutants, but they are very large, expensive and require significant amounts of maintenance. As a promising solution, low-cost sensors are being introduced as complementary, air quality monitoring stations. These sensors are, however, not reliable due to the lower accuracy, short life cycle and corresponding calibration issues. Recent studies have shown that low-cost sensors are affected by relative humidity and temperature. In this paper, we explore methods to additionally improve the calibration algorithms with the aim to increase the measurement accuracy considering the impact of temperature and humidity on the readings, by using machine learning. A detailed comparative analysis of linear regression, artificial neural network and random forest algorithms are presented, analyzing their performance on the measurements of CO, NO2 and PM10 particles, with promising results and an achieved R2 of 0.93–0.97, 0.82–0.94 and 0.73–0.89 dependent on the observed period of the year, respectively, for each pollutant. A comprehensive analysis and recommendations on how low-cost sensors could be used as complementary monitoring stations to the reference ones, to increase spatial and temporal measurement resolution, is provided.

Download Full-text

Reducing the Influence of Environmental Factors on Performance of a Diffusion-Based Personal Exposure Kit

Sensors ◽

10.3390/s21144637 ◽

2021 ◽

Vol 21 (14) ◽

pp. 4637

Author(s):

Huixin Zong ◽

Peter Brimblecombe ◽

Li Sun ◽

Peng Wei ◽

Kin-Fai Ho ◽

...

Keyword(s):

Exposure Assessment ◽

Real Time ◽

Low Cost ◽

Personal Exposure ◽

Sensor Technology ◽

Heterogeneous Environments ◽

Mathematical Algorithms ◽

Personal Exposure Assessment ◽

Address System ◽

The Impact

Sensor technology has enabled the development of portable low-cost monitoring kits that might supplement many applications in conventional monitoring stations. Despite the sensitivity of electrochemical gas sensors to environmental change, they are increasingly important in monitoring polluted microenvironments. The performance of a compact diffusion-based Personal Exposure Kit (PEK) was assessed for real-time gaseous pollutant measurement (CO, O3, and NO2) under typical environmental conditions encountered in the subtropical city of Hong Kong. A dynamic baseline tracking method and a range of calibration protocols to address system performance were explored under practical scenarios to assess the performance of the PEK in reducing the impact of rapid changes in the ambient environment in personal exposure assessment applications. The results show that the accuracy and stability of the ppb level gas measurement is enhanced even in heterogeneous environments, thus avoiding the need for data post-processing with mathematical algorithms, such as multi-linear regression. This establishes the potential for use in personal exposure monitoring, which has been difficult in the past, and for reporting more accurate and reliable data in real-time to support personal exposure assessment and portable air quality monitoring applications.

Download Full-text

Positioning Evaluation of Single and Dual-Frequency Low-Cost GNSS Receivers Signals Using PPP and Static Relative Methods in Urban Areas

Applied Sciences ◽

10.3390/app112210642 ◽

2021 ◽

Vol 11 (22) ◽

pp. 10642

Author(s):

Rosendo Romero-Andrade ◽

Manuel E. Trejo-Soto ◽

Alejandro Vega-Ayala ◽

Daniel Hernández-Andrade ◽

Jesús R. Vázquez-Ontiveros ◽

...

Keyword(s):

Urban Areas ◽

Precise Point Positioning ◽

Low Cost ◽

Observation Data ◽

Dual Frequency ◽

Positional Accuracy ◽

Gnss Receivers ◽

Point Positioning ◽

Error Circle ◽

Vertical Positioning

A positional accuracy obtained by the Precise Point Positioning and static relative methods was compared and analyzed. Test data was collected using low-cost GNSS receivers of single- and dual-frequency in urban areas. The data was analyzed for quality using the TEQC program to determine the degree of affectation of the signal in the urban area. Low-cost GNSS receivers were found to be sensitive to the multipath effect, which impacts positioning. The horizontal and vertical accuracy was evaluated with respect to Mexican regulations for the GNSS establishment criteria. Probable Error Circle (CEP) and Vertical Positioning Accuracy (EPV) were performed on low cost GNSS receiver observation data. The results show that low-cost dual-frequency GNSS receivers can be used in urban areas. The precision was obtained in the order of 0.013 m in the static relative method. The results obtained are comparable to a geodetic receiver in a geodetic baseline of <20 km. The study does not recommend using single and dual frequencies low cost GNSS receivers based on results obtained by the Precise Point Positioning (PPP) method in urban areas. The inclusion of the GGM10 model reduces the vertical precision obtained by using low cost GNSS receivers in both methods, conforming to the regulations only in the horizontal component.

Download Full-text

IMPROVING UAV TELEMETRY POSITIONING FOR DIRECT PHOTOGRAMMETRY

ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences ◽

10.5194/isprs-archives-xliii-b2-2021-61-2021 ◽

2021 ◽

Vol XLIII-B2-2021 ◽

pp. 61-68

Author(s):

L. Rossi ◽

F. Ioli ◽

E. Capizzi ◽

L. Pinto ◽

M. Reguzzoni

Keyword(s):

Low Cost ◽

Three Dimensional ◽

Control Points ◽

Three Dimensional Model ◽

Commercial Software ◽

Ground Control Points ◽

Lower Accuracy ◽

Least Squares Adjustment ◽

Gnss Receivers

Abstract. A fundamental step of UAV photogrammetric processes is to collect Ground Control Points (GCPs) by means of geodetic-quality GNSS receivers or total stations, thus obtaining an absolutely oriented model with a centimetric accuracy. This procedure is usually time-consuming, expensive and potentially dangerous for operators who sometimes need to reach inaccessible areas. UAVs equipped with low-cost GNSS/IMU sensors can provide information about position and attitude of the images. This telemetry information is not enough for a photogrammetric restitution with a centimetric accuracy, but it can be usefully exploited when a lower accuracy is required. The algorithm proposed in this paper aims at improving the quality of this information, in order to introduce it into a direct-photogrammetric process, without collecting GCPs. In particular, the estimation of an optimal trajectory is obtained by combining the camera positions derived from UAV telemetry and from the relative orientation of the acquired images, by means of a least squares adjustment. Then, the resulting trajectory is used as a direct observation of the camera positions into a commercial software, thus replacing the information of GCPs. The algorithm has been tested on different datasets, comparing the classical photogrammetric solution (with GCPs) with the proposed one. These case-studies showed that using the improved trajectory as input to the commercial software (without GCPs) the reconstruction of the three-dimensional model can be improved with respect to the solution computed by using the UAV raw telemetry only.

Download Full-text

A comparison between the GNSS tomography technique and the WRF model in retrieving 3D wet refractivity field in Hong Kong

10.5194/angeo-2018-84 ◽

2018 ◽

Author(s):

Zhaohui Xiong ◽

Bao Zhang ◽

Yibin Yao

Keyword(s):

Hong Kong ◽

Water Vapor ◽

Weather Prediction ◽

Wrf Model ◽

Vertical Direction ◽

Lower Troposphere ◽

Reanalysis Data ◽

Radiosonde Data ◽

Rainy Period ◽

Lower Accuracy

Abstract. Water vapor plays an important role in various scales of weather processes. However, there are limited means to monitor its 3-dimensional (3D) dynamical changes. The Numerical Weather Prediction (NWP) model and the Global Navigation Satellite System (GNSS) tomography technique are two of the limited means. Here, we conduct an interesting comparison between the GNSS tomography technique and the Weather Research and Forecasting (WRF) model (a representative of the NWP models) in retrieving Wet Refractivity (WR) in Hong Kong area during a rainy period and a rainless period. The GNSS tomography technique is used to retrieve WR from the GNSS slant wet delay. The WRF Data Assimilation (WRFDA) model is used to assimilate GNSS Zenith Tropospheric Delay (ZTD) to improve the background data. The WRF model is used to generate reanalysis data using the WRFDA output as the initial values. The radiosonde data are used to validate the WR derived from the GNSS tomography and the reanalysis data. The Root Mean Square (RMS) of the tomographic WR, the reanalysis WR that assimilate GNSS ZTD, and the reanalysis WR that without assimilating GNSS ZTD are 6.50 mm/km, 4.31 mm/km and 4.15 mm/km in the rainy period. The RMS becomes 7.02 mm/km, 7.26 mm/km and 6.35 mm/km in the rainless period. The lower accuracy in the rainless period is mainy due to the sharp variation of WR in the vertical direction. The results also show that assimilating GNSS ZTD into the WRFDA model only slightly improves the accuracy of the reanalysis WR and that the reanalysis WR is better than the tomographic WR in most cases. However, in a special experimental period when the water vapor is highly concentrated in the lower troposphere, the tomographic WR outperforms the reanalysis WR in the lower troposphere. When we assimilate the tomographic WR in the lower troposphere into the WRFDA model, the reanalysis WR is improved.

Download Full-text

Statistical post-processing of ensemble forecasts of the height of new snow

Nonlinear Processes in Geophysics ◽

10.5194/npg-26-339-2019 ◽

2019 ◽

Vol 26 (3) ◽

pp. 339-357 ◽

Cited By ~ 2

Author(s):

Jari-Pekka Nousu ◽

Matthieu Lafaysse ◽

Matthieu Vernay ◽

Joseph Bellier ◽

Guillaume Evin ◽

...

Keyword(s):

Real Time ◽

Spatial Scales ◽

Weather Prediction ◽

Evaluation Criteria ◽

Training Dataset ◽

Post Processing ◽

Probabilistic Forecasting ◽

Ensemble Forecasts ◽

Heterogeneous Model ◽

The Impact

Abstract. Forecasting the height of new snow (HN) is crucial for avalanche hazard forecasting, road viability, ski resort management and tourism attractiveness. Météo-France operates the PEARP-S2M probabilistic forecasting system, including 35 members of the PEARP Numerical Weather Prediction system, where the SAFRAN downscaling tool refines the elevation resolution and the Crocus snowpack model represents the main physical processes in the snowpack. It provides better HN forecasts than direct NWP diagnostics but exhibits significant biases and underdispersion. We applied a statistical post-processing to these ensemble forecasts, based on non-homogeneous regression with a censored shifted Gamma distribution. Observations come from manual measurements of 24 h HN in the French Alps and Pyrenees. The calibration is tested at the station scale and the massif scale (i.e. aggregating different stations over areas of 1000 km2). Compared to the raw forecasts, similar improvements are obtained for both spatial scales. Therefore, the post-processing can be applied at any point of the massifs. Two training datasets are tested: (1) a 22-year homogeneous reforecast for which the NWP model resolution and physical options are identical to the operational system but without the same initial perturbations; (2) 3-year real-time forecasts with a heterogeneous model configuration but the same perturbation methods. The impact of the training dataset depends on lead time and on the evaluation criteria. The long-term reforecast improves the reliability of severe snowfall but leads to overdispersion due to the discrepancy in real-time perturbations. Thus, the development of reliable automatic forecasting products of HN needs long reforecasts as homogeneous as possible with the operational systems.

Download Full-text