Effect of climate change on seasonal water use efficiency in subalpine <Emphasis Type="Italic">Abies fabri</Emphasis>

Abies fabri is a typical subalpine dark coniferous forest in southwestern China. Air temperature increases more at high elevation areas than that at low elevation areas in mountainous regions, and climate change ratio is also uneven in different seasons. Carbon gain and the response of water use efficiency (WUE) to annual and seasonal increases in temperature with or without CO₂ fertilization were simulated in Abies fabri using the atmospheric-vegetation interaction model (AVIM2). Four future climate scenarios (RCP2.6, RCP4.5, RCP6.0 and RCP8.5) from the Coupled Model Intercomparison Project Phase 5 (CMIP5) were selectively investigated. The results showed that warmer temperatures have negative effects on gross primary production (GPP) and net primary production (NPP) in growing seasons and positive effects in dormant seasons due to the variation in the leaf area index. Warmer temperatures tend to generate lower canopy WUE and higher ecosystem WUE in Abies fabri. However, warmer temperature together with rising CO₂ concentrations significantly increase the GPP and NPP in both growing and dormant seasons and enhance WUE in annual and dormant seasons because of the higher leaf area index (LAI) and soil temperature. The comparison of the simulated results with and without CO₂ fertilization shows that CO₂ has the potential to partially alleviate the adverse effects of climate warming on carbon gain and WUE in subalpine coniferous forests.     

The Bayesian detection of discontinuities in a polynomial regression and its application to the cycle-slip problem

This paper deals with the problem of detecting and correcting cycle-slips in Global Navigation Satellite System (GNSS) phase data by exploiting the Bayesian theory. The method is here applied to undifferenced observations, because repairing cycle-slips already at this stage could be a useful pre-processing tool, especially for a network of permanent GNSS stations. If a dual frequency receiver is available, the cycle-slips can be easily detected by combining two phase observations or phase and range observations from a single satellite to a single receiver. These combinations, expressed in a distance unit form, are completely free from the geometry and depend only on the ionospheric effect, on the electronic biases and on the initial integer ambiguities; since these terms are expected to be smooth in time, at least in a short period, a cycle-slip in one or both the two carriers can be modelled as a discontinuity in a polynomial regression. The proposed method consists in applying the Bayesian theory to compute the marginal posterior distribution of the discontinuity epoch and to detect it as a maximum a posteriori (MAP) in a very accurate way. Concerning the cycle-slip correction, a couple of simultaneous integer slips in the two carriers is chosen by maximazing the conditional posterior distribution of the discontinuity amplitude given the detected epoch. Numerical experiments on simulated and real data show that the discontinuities with an amplitude 2 or 3 times larger than the noise standard deviation are successfully identified. This means that the Bayesian approach is able to detect and correct cycle-slips using undifferenced GNSS observations even if the slip occurs by one cycle. A comparison with the scientific software BERNESE 5.0 confirms the good performance of the proposed method, especially when data sampled at high frequency (e.g. every 1 s or every 5 s) are available.     

A Combined Biophysical and Economic GIS Framework to Assess Sugarcane Cropping Potential in Brazil

Recently, the increasing demand for biofuels triggered a new phase for the sugar‐alcohol sector. In Brazil, as well as in other tropical countries, this process raised worries regarding the possible direct and indirect effects of the crop's expansion on the conversion of native vegetation coverings. Therefore, the modeling of spatial‐economic surfaces, representing the potential rent variation in its spatial component, for economic activities, may be a useful tool in the decision‐making process. Hence, here we propose and present the results of a combined framework composed of two modules using the modeling platform Dinamica EGO. The first module simulates sugarcane's growth, calculating the daily response of the crop to environmental conditions during the stages of the plant's development. The second module estimates rents for sugarcane cultivation in Brazil, identifying areas where this activity would bring higher economic return, looking at simulated productivity, production costs and selling prices in a way that is spatially explicit for Brazil. Two different scenarios for production costs were tested, and results ranged from negative values to maxima of R$/ha 929 and R$/ha 1176 for standard and efficient costs of production, respectively. The model successfully indicated non‐profitable and profitable areas, and regions where high expected economic return overlaps endangered ecosystems.     

Precise photorealistic visualization for restoration of historic buildings based on tacheometry data

This paper puts forward a 3D reconstruction methodology applied to the restoration of historic buildings taking advantage of the speed, range and accuracy of a total geodetic station. The measurements representing geo-referenced points produced an interactive and photorealistic geometric mesh of a monument named ‘Neoria.’ ‘Neoria’ is a Venetian building located by the old harbor at Chania, Crete, Greece. The integration of tacheometry acquisition and computer graphics puts forward a novel integrated software framework for the accurate 3D reconstruction of a historical building. The main technical challenge of this work was the production of a precise 3D mesh based on a sufficient number of tacheometry measurements acquired fast and at low cost, employing a combination of surface reconstruction and processing methods. A fully interactive application based on game engine technologies was developed. The user can visualize and walk through the monument and the area around it as well as photorealistically view it at different times of day and night. Advanced interactive functionalities are offered to the user in relation to identifying restoration areas and visualizing the outcome of such works. The user could visualize the coordinates of the points measured, calculate distances and navigate through the complete 3D mesh of the monument. The geographical data are stored in a database connected with the application. Features referencing and associating the database with the monument are developed. The goal was to utilize a small number of acquired data points and present a fully interactive visualization of a geo-referenced 3D model.     

3D-Monitoring Big Geo Data on a seaport infrastructure based on FIWARE

Many organizations of all kinds are using new technologies to assist the acquisition and analysis of data. Seaports are a good example of this trend. Seaports generate data regarding the management of marine traffic and other elements, as well as environmental conditions given by meteorological sensors and buoys. However, this enormous amount of data, also known as Big Data, is useless without a proper system to organize, analyze and visualize it. SmartPort is an online platform for the visualization and management of a seaport data that has been built as a GIS application. This work offers a Rich Internet Application that allows the user to visualize and manage the different sources of information produced in a port environment. The Big Data management is based on the FIWARE platform, as well as “The Internet of Things” solutions for the data acquisition. At the same time, Glob3 Mobile (G3M) framework has been used for the development of map requirements. In this way, SmartPort supports 3D visualization of the ports scenery and its data sources.     

Image-aided platform orientation determination with a GNSS/low-cost IMU system using robust-adaptive Kalman filter

The availability of miniaturized sensors with enhanced capabilities, new methods for image processing, and easy access to small and low-weight airborne platforms for data acquisition, including unmanned vehicles, opens new possibilities for geodetic navigation applications and developing new developments in sensor fusion. In this context, the development of efficient methods, based on low-cost sensors, to extract precise georeferenced information from digital cameras is of utmost interest. We present a method to improve the performance of the integration of GNSS/low-cost IMU by exploiting the orientation changes retrieved from digital images. In this work, a robust-adaptive Kalman filter is also introduced to further improve the performance of the method deployed. The adaptive factor and the robust factor accomplished are determined by innovation information and the threshold value of orientation changes between consecutive images. Results from airborne tests used to assess the performance of the method are presented. The results show that using a non-metric camera, the Euler angle estimation accuracy of the GNSS/low-cost IMU integration can be improved to be close to 0.5 degree and an additional improvement, which can reach 59%, can be achieved after using the robust-adaptive Kalman filter.     

Analysis of estimated satellite clock biases and their effects on precise point positioning

This study provides a systemic analysis to identify the biases in estimated satellite clocks and illustrates their effects in precise point positioning (PPP). First, the precise satellite clock estimation method considering pseudorange and carrier phase hardware delays is derived. Two methods for satellite clock estimation are compared, and their equivalency is discussed. The results show that apart from the well-known constant code hardware biases, the time-variant phase hardware biases are also absorbed by the estimated clocks. Also, the satellite clocks contain biases caused by modeling errors. To analyze the effects of these biases, they are grouped into initial clock biases (ICBs) and time-dependent biases (TDBs). Then, a detailed analysis of the impact of the biases on PPP-based troposphere and coordinate estimates is conducted. The experimental analysis demonstrates that TDBs affect positioning and tropospheric estimates, and their impacts are more significant in the static mode. The ICBs affect coordinate accuracy, zenith total delay mean bias, and its standard deviations only at the millimeter level for kinematic and static PPP, which is negligible. However, the ICBs affect the convergence period for both static and real kinematic PPP, and the magnitude of their impact largely depends on data quality. Note that satellites clocks are generally estimated with the P1/P2 and L1/L2 ionospheric-free combinations, and that hardware-specific parts of ICBs and TDBs cancel if users employ the same type of observables as the clock providers. Otherwise, the effects of biases cannot be ignored, especially for triple-frequency applications. Also, modeling-specific parts of ICBs and TDBs are significant in real-time clocks, which also affect user applications. Our conclusion is applicable for understanding the effects of these biases.     

On the accuracy of the GPS L2 observable for ionospheric monitoring

The introduction of the unencrypted global positioning system (GPS) L2 civil (L2C) signal has the potential to improve measurements made with the L2 frequency, an important observable in GPS-based ionospheric research and monitoring. Recent work has shown significant differences between the legacy L2P(Y) and L2C-derived total electron content rate of change index (ROTI). This difference is observed between L2P(Y) and L2C-derived ROTI with certain receiver models and between zero-baseline receiver pairs. We discuss the likely cause for these differences: L1-aided tracking used to track both the L2P(Y) and L2C signals. We also present L2C data that are confirmed to be from tracking independent of L1. Using the ionospheric-free linear combination, we show that the independently tracked carrier phase dynamics are significantly more accurate than the L1-aided observables. This result is confirmed by comparing the behavior of the L2C and L2P(Y) carrier phase observables upon a sudden antenna rotation.     

A new evil waveforms evaluating method for new BDS navigation signals

With the advent of new global navigation satellite systems (GNSSs) and new signals, GNSS users will rely more on them to obtain higher-accuracy positioning. Evil waveform monitoring and assessment are of great importance for GNSS to achieve its positioning, velocity, and timing service with high accuracy. However, the advent of new navigation signals introduces the necessity to extend the traditional analyzing techniques already accepted for binary phase-shift keying modulation to new techniques. First, the well-known second-order step thread model adopted by the International Civil Aviation Organization is introduced. Then the extended new general thread models are developed for the new binary offset carrier modulated signals. However, no research has been done on navigation signal waveform symmetry yet. Simulation results showed that, waveform asymmetry may also cause tracking errors, range biases, and position errors in GNSS receivers. It is thus imperative that the asymmetry be quantified to enable the design of appropriate error budgets and mitigation strategies for various application fields. A novel evil waveform analysis method, called waveform rising and falling edge symmetry (WRaFES) method, is proposed. Based on this WRaFES method, the correlation metrics are provided to detect asymmetric correlation peaks distorted by received signal asymmetry. Then the statistical properties of the proposed methods are analyzed, and a proper deformation detection threshold is calculated. Finally, both simulation results and experimentally measured results of Beidou navigation satellite system (BDS) M1-S B1Cd signal are given, which show the effectiveness and robustness of the proposed thread models.     

Beidou satellite maneuver thrust force estimation for precise orbit determination

Beidou satellites, especially geostationary earth orbit (GEO) and inclined geosynchronous orbit (IGSO) satellites, need to be frequently maneuvered to keep them in position due to various perturbations. The satellite ephemerides are not available during such maneuver periods. Precise estimation of thrust forces acting on satellites would provide continuous ephemerides during maneuver periods and could significantly improve orbit accuracy immediately after the maneuver. This would increase satellite usability for both real-time and post-processing applications. Using 1 year of observations from the Multi-GNSS Experiment network (MGEX), we estimate the precise maneuver periods for all Beidou satellites and the thrust forces. On average, GEO and IGSO satellites in the Beidou constellation are maneuvered 12 and 2 times, respectively, each year. For GEO satellites, the maneuvers are mainly in-plane, while out-of-plane maneuvers are observed for IGSO satellites and a small number of GEO satellites. In most cases, the Beidou satellite maneuver periods last 15–25 min, but can be as much as 2 h for the few out-of-plane maneuvers of GEO satellites. The thrust forces acting on Beidou satellites are normally in the order of 0.1–0.7 mm/s². This can cause changes in velocity of GEO/IGSO satellites in the order of several decimeters per second. In the extreme cases of GEO out-of-plane maneuvers, very large cross-track velocity changes are observed, namely 28 m/s, induced by 5.4 mm/s² thrust forces. Also, we demonstrate that by applying the estimated thrust forces in orbit integration, the orbit errors can be estimated at decimeter level in along- and cross-track directions during normal maneuver periods, and 1–2 m in all the orbital directions for the enormous GEO out-of-plane maneuver.