Development of Willow Tree Yield-Mapping Technology

With today’s environmental challenges, developing sustainable energy sources is crucial. From this perspective, woody biomass has been, and continues to be, a significant research interest. The goal of this research was to develop new technology for mapping willow tree yield grown in a short-rotation forestry (SRF) system. The system gathered the physical characteristics of willow trees on-the-go, while the trees were being harvested. Features assessed include the number of trees harvested and their diameter. To complete this task, a machine-vision system featuring an RGB-D stereovision camera was built. The system tagged these data with the corresponding geographical coordinates using a Global Navigation Satellite System (GNSS) receiver. The proposed yield-mapping system showed promising detection results considering the complex background and variable light conditions encountered in the outdoors. Of the 40 randomly selected and manually observed trees in a row, 36 were successfully detected, yielding a 90% detection rate. The correctly detected tree rate of all trees within the scenes was actually 71.8% since the system tended to be sensitive to branches, thus, falsely detecting them as trees. Manual validation of the diameter estimation function showed a poor coefficient of determination and a root mean square error (RMSE) of 10.7 mm.

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Unsupervised Human Detection with an Embedded Vision System on a Fully Autonomous UAV for Search and Rescue Operations

Sensors ◽

10.3390/s19163542 ◽

2019 ◽

Vol 19 (16) ◽

pp. 3542 ◽

Cited By ~ 15

Author(s):

Eleftherios Lygouras ◽

Nicholas Santavas ◽

Anastasios Taitzoglou ◽

Konstantinos Tarchanidis ◽

Athanasios Mitropoulos ◽

...

Keyword(s):

Embedded System ◽

Emergency Services ◽

Vision System ◽

Open Water ◽

Satellite System ◽

Search And Rescue ◽

Human Detection ◽

Primary Role ◽

Wide Range ◽

Global Navigation Satellite

Unmanned aerial vehicles (UAVs) play a primary role in a plethora of technical and scientific fields owing to their wide range of applications. In particular, the provision of emergency services during the occurrence of a crisis event is a vital application domain where such aerial robots can contribute, sending out valuable assistance to both distressed humans and rescue teams. Bearing in mind that time constraints constitute a crucial parameter in search and rescue (SAR) missions, the punctual and precise detection of humans in peril is of paramount importance. The paper in hand deals with real-time human detection onboard a fully autonomous rescue UAV. Using deep learning techniques, the implemented embedded system was capable of detecting open water swimmers. This allowed the UAV to provide assistance accurately in a fully unsupervised manner, thus enhancing first responder operational capabilities. The novelty of the proposed system is the combination of global navigation satellite system (GNSS) techniques and computer vision algorithms for both precise human detection and rescue apparatus release. Details about hardware configuration as well as the system’s performance evaluation are fully discussed.

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An Introduction to the EUMETSAT Polar system

Bulletin of the American Meteorological Society ◽

10.1175/bams-88-7-1085 ◽

2007 ◽

Vol 88 (7) ◽

pp. 1085-1096 ◽

Cited By ~ 96

Author(s):

K. Dieter Klaes ◽

Marc Cohen ◽

Yves Buhler ◽

Peter Schlüssel ◽

Rosemary Munro ◽

...

Keyword(s):

High Resolution ◽

New Technology ◽

Satellite System ◽

Infrared Observation ◽

Polar System ◽

Microwave Sounding Unit ◽

Atmospheric Sounding ◽

Core Components ◽

Microwave Sounding ◽

Global Navigation Satellite

The European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT) Polar System is the European contribution to the European–U.S. operational polar meteorological satellite system (Initial Joint Polar System). It serves the midmorning (a.m.) orbit 0930 Local Solar Time (LST) descending node. The EUMETSAT satellites of this new polar system are the Meteorological Operational Satellite (Metop) satellites, jointly developed with ESA. Three Metop satellites are foreseen for at least 14 years of operation from 2006 onward and will support operational meteorology and climate monitoring. The Metop Programme includes the development of some instruments, such as the Global Ozone Monitoring Experiment, Advanced Scatterometer, and the Global Navigation Satellite System (GNSS) Receiver for Atmospheric Sounding, which are advanced instruments of recent successful research missions. Core components of the Metop payload, common with the payload on the U.S. satellites, are the Advanced Very High Resolution Radiometer and the Advanced Television Infrared Observation Satellite (TIROS) Operational Vertical Sounder (ATOVS) package, composed of the High Resolution Infrared Radiation Sounder (HIRS), Advanced Microwave Sounding Unit A (AMSU-A), and Microwave Humidity Sounder (MHS). They provide continuity to the NOAA-K, -L, -M satellite series (in orbit known as NOAA-15, -16 and -17). MHS is a EUMETSAT development and replaces the AMSU-B instrument in the ATOVS suite. The Infrared Atmospheric Sounding Interferometer (IASI) instrument, developed by the Centre National d'Etudes Spatiales, provides hyperspectral resolution infrared sounding capabilities and represents new technology in operational satellite remote sensing.

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Rice Height Monitoring between Different Estimation Models Using UAV Photogrammetry and Multispectral Technology

Remote Sensing ◽

10.3390/rs14010078 ◽

2021 ◽

Vol 14 (1) ◽

pp. 78

Author(s):

Wenyi Lu ◽

Tsuyoshi Okayama ◽

Masakazu Komatsuzaki

Keyword(s):

Point Cloud ◽

Vegetation Index ◽

Satellite System ◽

Coefficient Of Determination ◽

Crop Height ◽

Gnss Receiver ◽

Vegetation Fraction ◽

Spad Value ◽

Digital Terrain ◽

Global Navigation Satellite

Unmanned aerial vehicle (UAV) photogrammetry was used to monitor crop height in a flooded paddy field. Three multi-rotor UAVs were utilized to conduct flight missions in order to capture RGB (RedGreenBlue) and multispectral images, and these images were analyzed using several different models to provide the best results. Two image sets taken by two UAVs, mounted with RGB cameras of the same resolution and Global Navigation Satellite System (GNSS) receivers of different accuracies, were applied to perform photogrammetry. Two methods were then proposed for creating crop height models (CHMs), one of which was denoted as the M1 method and was based on the Digital Surface Point Cloud (DSPC) and the Digital Terrain Point Cloud (DSPT). The other was denoted as the M2 method and was based on the DSPC and a bathymetric sensor. An image set taken by another UAV mounted with a multispectral camera was used for multispectral-based photogrammetry. A Normal Differential Vegetation Index (NDVI) and a Vegetation Fraction (VF) were then extracted. A new method based on multiple linear regression (MLR) combining the NDVI, the VF, and a Soil Plant Analysis Development (SPAD) value for estimating the measured height (MH) of rice was then proposed and denoted as the M3 method. The results show that the M1 method, the UAV with a GNSS receiver with a higher accuracy, obtained more reliable estimations, while the M2 method, the UAV with a GNSS receiver of moderate accuracy, was actually slightly better. The effect on the performance of CHMs created by the M1 and M2 methods is more negligible in different plots with different treatments; however, remarkably, the more uniform the distribution of vegetation over the water surface, the better the performance. The M3 method, which was created using only a SPAD value and a canopy NDVI value, showed the highest coefficient of determination (R2) for overall MH estimation, 0.838, compared with other combinations.

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New Dynamic Positioning Reference System Concepts Enabled by Autonomy

Marine Technology Society Journal ◽

10.4031/mtsj.52.5.6 ◽

2018 ◽

Vol 52 (5) ◽

pp. 27-30

Author(s):

Arne Rinnan

Keyword(s):

Reference System ◽

Oil And Gas ◽

High Reliability ◽

New Technology ◽

Satellite System ◽

Dynamic Positioning ◽

Reference Systems ◽

Trade Offs ◽

Global Navigation Satellite ◽

High Level

AbstractA certain level of autonomy is already present in dynamic positioning (DP), and DP requirements have been a driving force in the development of a diversity of high-reliability reference systems. Today, there is a strong drive for autonomous concepts and solutions in several market niches (e.g., short sea shipping and ocean-based aquaculture). At the same time, the market downturn in traditional oil and gas leads to a reduced implementation of new reference system solutions. A development toward higher levels of autonomy in novel operations drives the development from traditional reference systems toward solutions capable of proximity awareness and connectivity. The existing reference system technologies comprise a good platform for this development, but new technology elements like new sensor fusion concepts, machine learning, artificial intelligence, and extended connectivity are evolving. The article presents ongoing developments within microwave, laser, Global Navigation Satellite System (GNSS), and inertial-based reference systems and discusses likely future developments. Connectivity will be a native feature of future reference systems and is also discussed. The article is focusing on the drivers behind these developments and some of the related challenges from a high-level perspective. Current development is running at a much higher pace than legislation and regulation can adapt. Some input to regulation challenges and trade-offs are outlined.

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The characteristics of transforming coordinates from the geocentric system WGS-84 for the Mercator projection under low latitudes conditions

Geodesy and Cartography ◽

10.22389/0016-7126-2018-940-10-2-6 ◽

2018 ◽

Vol 940 (10) ◽

pp. 2-6

Author(s):

J.A. Younes ◽

M.G. Mustafin

Keyword(s):

Coordinate System ◽

Satellite System ◽

Programming Algorithm ◽

Low Latitude ◽

Model Calculations ◽

Mercator Projection ◽

Low Latitudes ◽

Rectangular Coordinates ◽

Global Navigation Satellite ◽

Coordination Methods

The issue of calculating the plane rectangular coordinates using the data obtained by the satellite observations during the creation of the geodetic networks is discussed in the article. The peculiarity of these works is in conversion of the coordinates into the Mercator projection, while the plane coordinate system on the base of Gauss-Kruger projection is used in Russia. When using the technology of global navigation satellite system, this task is relevant for any point (area) of the Earth due to a fundamentally different approach in determining the coordinates. The fact is that satellite determinations are much more precise than the ground coordination methods (triangulation and others). In addition, the conversion to the zonal coordinate system is associated with errors; the value at present can prove to be completely critical. The expediency of using the Mercator projection in the topographic and geodetic works production at low latitudes is shown numerically on the basis of model calculations. To convert the coordinates from the geocentric system with the Mercator projection, a programming algorithm which is widely used in Russia was chosen. For its application under low-latitude conditions, the modification of known formulas to be used in Saudi Arabia is implemented.

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Detecting Apples in the Wild: Potential for Harvest Quantity Estimation

Sustainability ◽

10.3390/su13148054 ◽

2021 ◽

Vol 13 (14) ◽

pp. 8054

Author(s):

Artur Janowski ◽

Rafał Kaźmierczak ◽

Cezary Kowalczyk ◽

Jakub Szulwic

Keyword(s):

Image Analysis ◽

Pilot Study ◽

Production Management ◽

Satellite System ◽

Morphological Operations ◽

Computational Performance ◽

Analysis Methods ◽

Manual Counting ◽

In The Wild ◽

Global Navigation Satellite

Knowing the exact number of fruits and trees helps farmers to make better decisions in their orchard production management. The current practice of crop estimation practice often involves manual counting of fruits (before harvesting), which is an extremely time-consuming and costly process. Additionally, this is not practicable for large orchards. Thanks to the changes that have taken place in recent years in the field of image analysis methods and computational performance, it is possible to create solutions for automatic fruit counting based on registered digital images. The pilot study aims to confirm the state of knowledge in the use of three methods (You Only Look Once—YOLO, Viola–Jones—a method based on the synergy of morphological operations of digital imagesand Hough transformation) of image recognition for apple detecting and counting. The study compared the results of three image analysis methods that can be used for counting apple fruits. They were validated, and their results allowed the recommendation of a method based on the YOLO algorithm for the proposed solution. It was based on the use of mass accessible devices (smartphones equipped with a camera with the required accuracy of image acquisition and accurate Global Navigation Satellite System (GNSS) positioning) for orchard owners to count growing apples. In our pilot study, three methods of counting apples were tested to create an automatic system for estimating apple yields in orchards. The test orchard is located at the University of Warmia and Mazury in Olsztyn. The tests were carried out on four trees located in different parts of the orchard. For the tests used, the dataset contained 1102 apple images and 3800 background images without fruits.

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GPS-BDS-Galileo double-differenced stochastic model refinement based on least-squares variance component estimation

Journal of Navigation ◽

10.1017/s0373463321000564 ◽

2021 ◽

pp. 1-16

Author(s):

Hong Hu ◽

Xuefeng Xie ◽

Jingxiang Gao ◽

Shuanggen Jin ◽

Peng Jiang

Keyword(s):

Stochastic Model ◽

Least Squares ◽

Stochastic Models ◽

Variance Component ◽

Satellite System ◽

Variance Component Estimation ◽

Short Baseline ◽

Component Estimation ◽

Zero Baseline ◽

Global Navigation Satellite

Abstract Stochastic models are essential for precise navigation and positioning of the global navigation satellite system (GNSS). A stochastic model can influence the resolution of ambiguity, which is a key step in GNSS positioning. Most of the existing multi-GNSS stochastic models are based on the GPS empirical model, while differences in the precision of observations among different systems are not considered. In this paper, three refined stochastic models, namely the variance components between systems (RSM1), the variances of different types of observations (RSM2) and the variances of observations for each satellite (RSM3) are proposed based on the least-squares variance component estimation (LS-VCE). Zero-baseline and short-baseline GNSS experimental data were used to verify the proposed three refined stochastic models. The results show that, compared with the traditional elevation-dependent model (EDM), though the proposed models do not significantly improve the ambiguity resolution success rate, the positioning precision of the three proposed models has been improved. RSM3, which is more realistic for the data itself, performs the best, and the precision at elevation mask angles 20°, 30°, 40°, 50° can be improved by 4⋅6%, 7⋅6%, 13⋅2%, 73⋅0% for L1-B1-E1 and 1⋅1%, 4⋅8%, 16⋅3%, 64⋅5% for L2-B2-E5a, respectively.

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Investigation of Pre-Earthquake Ionospheric and Atmospheric Disturbances for Three Large Earthquakes in Mexico

Geosciences ◽

10.3390/geosciences11010016 ◽

2020 ◽

Vol 11 (1) ◽

pp. 16

Author(s):

Christina Oikonomou ◽

Haris Haralambous ◽

Sergey Pulinets ◽

Aakriti Khadka ◽

Shukra R. Paudel ◽

...

Keyword(s):

Chemical Potential ◽

Atmospheric Model ◽

Satellite System ◽

Seismic Events ◽

Electron Content ◽

Total Electron ◽

Atmospheric Disturbances ◽

Global Ionospheric Maps ◽

Global Navigation Satellite ◽

Large Earthquakes

The purpose of the present study is to investigate simultaneously pre-earthquake ionospheric and atmospheric disturbances by the application of different methodologies, with the ultimate aim to detect their possible link with the impending seismic event. Three large earthquakes in Mexico are selected (8.2 Mw, 7.1 Mw and 6.6 Mw during 8 and 19 September 2017 and 21 January 2016 respectively), while ionospheric variations during the entire year 2017 prior to 37 earthquakes are also examined. In particular, Total Electron Content (TEC) retrieved from Global Navigation Satellite System (GNSS) networks and Atmospheric Chemical Potential (ACP) variations extracted from an atmospheric model are analyzed by performing statistical and spectral analysis on TEC measurements with the aid of Global Ionospheric Maps (GIMs), Ionospheric Precursor Mask (IPM) methodology and time series and regional maps of ACP. It is found that both large and short scale ionospheric anomalies occurring from few hours to a few days prior to the seismic events may be linked to the forthcoming events and most of them are nearly concurrent with atmospheric anomalies happening during the same day. This analysis also highlights that even in low-latitude areas it is possible to discern pre-earthquake ionospheric disturbances possibly linked with the imminent seismic events.

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Estimation of fractional cycle bias for GPS/BDS-2/Galileo based on international GNSS monitoring and assessment system observations using the uncombined PPP model

Satellite Navigation ◽

10.1186/s43020-021-00039-x ◽

2021 ◽

Vol 2 (1) ◽

Author(s):

Jin Wang ◽

Qin Zhang ◽

Guanwen Huang

Keyword(s):

Estimation Method ◽

Satellite Orbit ◽

Satellite System ◽

Assessment System ◽

Navigation Satellite ◽

Dual Frequency ◽

Fractional Cycle Bias ◽

The Stability ◽

High Consistency ◽

Global Navigation Satellite

AbstractThe Fractional Cycle Bias (FCB) product is crucial for the Ambiguity Resolution (AR) in Precise Point Positioning (PPP). Different from the traditional method using the ionospheric-free ambiguity which is formed by the Wide Lane (WL) and Narrow Lane (NL) combinations, the uncombined PPP model is flexible and effective to generate the FCB products. This study presents the FCB estimation method based on the multi-Global Navigation Satellite System (GNSS) precise satellite orbit and clock corrections from the international GNSS Monitoring and Assessment System (iGMAS) observations using the uncombined PPP model. The dual-frequency raw ambiguities are combined by the integer coefficients (4,− 3) and (1,− 1) to directly estimate the FCBs. The details of FCB estimation are described with the Global Positioning System (GPS), BeiDou-2 Navigation Satellite System (BDS-2) and Galileo Navigation Satellite System (Galileo). For the estimated FCBs, the Root Mean Squares (RMSs) of the posterior residuals are smaller than 0.1 cycles, which indicates a high consistency for the float ambiguities. The stability of the WL FCBs series is better than 0.02 cycles for the three GNSS systems, while the STandard Deviation (STD) of the NL FCBs for BDS-2 is larger than 0.139 cycles. The combined FCBs have better stability than the raw series. With the multi-GNSS FCB products, the PPP AR for GPS/BDS-2/Galileo is demonstrated using the raw observations. For hourly static positioning results, the performance of the PPP AR with the three-system observations is improved by 42.6%, but only 13.1% for kinematic positioning results. The results indicate that precise and reliable positioning can be achieved with the PPP AR of GPS/BDS-2/Galileo, supported by multi-GNSS satellite orbit, clock, and FCB products based on iGMAS.

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Improving DGNSS Performance through the Use of Network RTK Corrections

Remote Sensing ◽

10.3390/rs13091621 ◽

2021 ◽

Vol 13 (9) ◽

pp. 1621

Author(s):

Duojie Weng ◽

Shengyue Ji ◽

Yangwei Lu ◽

Wu Chen ◽

Zhihua Li

Keyword(s):

Carrier Phase ◽

Local Area ◽

Satellite System ◽

High Accuracy ◽

Single Frequency ◽

Baseline Length ◽

Low Latitude ◽

Phase Measurements ◽

Network Rtk ◽

Global Navigation Satellite

The differential global navigation satellite system (DGNSS) is an enhancement system that is widely used to improve the accuracy of single-frequency receivers. However, distance-dependent errors are not considered in conventional DGNSS, and DGNSS accuracy decreases when baseline length increases. In network real-time kinematic (RTK) positioning, distance-dependent errors are accurately modelled to enable ambiguity resolution on the user side, and standard Radio Technical Commission for Maritime Services (RTCM) formats have also been developed to describe the spatial characteristics of distance-dependent errors. However, the network RTK service was mainly developed for carrier-phase measurements on professional user receivers. The purpose of this study was to modify the local-area DGNSS through the use of network RTK corrections. Distance-dependent errors can be reduced, and accuracy for a longer baseline length can be improved. The results in the low-latitude areas showed that the accuracy of the modified DGNSS could be improved by more than 50% for a 17.9 km baseline during solar active years. The method in this paper extends the use of available network RTK corrections with high accuracy to normal local-area DGNSS applications.

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