A Correction Method of Height Variation Error Based on One SNR Arc Applied in GNSS–IR Sea-Level Retrieval

Sea-level monitoring is important for the safety of coastal cities and analysis of ocean and climate. Sea levels can be estimated based using the global navigation satellite system–interferometry reflectometry (GNSS–IR). The frequency in a signal-to-noise ratio (SNR) arc has been found to be related to the height between the GNSS antenna and reflecting surface, which is called reflector height (RH, h). The height variation of the reflecting surface causes an error, and this error is the most significant error in the GNSS–IR sea-level retrieval. The key to the correction of height variation error lies in the determination of the RH variation rate ḣ. The classical correction method determines ḣ based on tide analysis of a coarse RH series over a longer time period. Therefore, ḣ inherits errors in coarse RH series, which contains significant bias during a storm surge, and correcting this requires data accumulation. This study proposes a correction method of height variation error based on just one SNR arc based on wavelet analysis and least-square estimation. First, using wavelet analysis, instantaneous frequencies are extracted in one SNR arc; these frequencies are then converted to RH series. Second, using least-square estimation, h and ḣ are conjointly solved based on the RH series from wavelet analysis. Data of GNSS site HKQT located in Hong Kong, China, during a period of time that includes Typhoon Hato were used. The root-mean-square errors (RMSEs) of retrievals were 21.5 cm for L1, 9.5 cm for L2P, 9.3 cm for L2C, and 7.6 cm for L5 of GPS; 16.8 cm for L1C, 14.1 cm for L1P, 12.6 cm for L2C, and 10.7 cm for L2P of GLONASS; 15.7 cm for L1, 11.2 cm for L5, 12.2 cm for L7, and 9.6 cm for L8 of Galileo. Results showed this method can correct the height variation error based on just one SNR arc, can avoid the inheritance of errors, and can be used during periods of storm surge.

Testing the Height Variation Hypothesis with the R rasterdiv Package for Tree Species Diversity Estimation

Forest biodiversity is a key element to support ecosystem functions. Measuring biodiversity is a necessary step to identify critical issues and to choose interventions to be applied in order to protect it. Remote sensing provides consistent quality and standardized data, which can be used to estimate different aspects of biodiversity. The Height Variation Hypothesis (HVH) represents an indirect method for estimating species diversity in forest ecosystems from the LiDAR data, and it assumes that the higher the variation in tree height (height heterogeneity, HH), calculated through the ’Canopy Height Model’ (CHM) metric, the more complex the overall structure of the forest and the higher the tree species diversity. To date, the HVH has been tested exclusively with CHM data, assessing the HH only with a single heterogeneity index (the Rao’s Q index) without making use of any moving windows (MW) approach. In this study, the HVH has been tested in an alpine coniferous forest situated in the municipality of San Genesio/Jenesien (eastern Italian Alps) at 1100 m, characterized by the presence of 11 different tree species (mainly Pinus sylvestris, Larix decidua, Picea abies followed by Betula alba and Corylus avellana). The HH has been estimated through different heterogeneity measures described in the new R rasterdiv package using, besides the CHM, also other LiDAR metrics (as the percentile or the standard deviation of the height distribution) at various spatial resolutions and MWs (ALS LiDAR data with mean point cloud density of 2.9 point/m2). For each combination of parameters, and for all the considered plots, linear regressions between the Shannon’s H′ (used as tree species diversity index based on field data) and the HH have been derived. The results showed that the Rao’s Q index (singularly and through a multidimensional approach) performed generally better than the other heterogeneity indices in the assessment of the HH. The CHM and the LiDAR metrics related to the upper quantile point cloud distribution at fine resolution (2.5 m, 5 m) have shown the most important results for the assessment of the HH. The size of the used MW did not influence the general outcomes but instead, it increased when compared to the results found in the literature, where the HVH was tested without MW approach. The outcomes of this study underline that the HVH, calculated with certain heterogeneity indices and LiDAR data, can be considered a useful tool for assessing tree species diversity in considered forest ecosystems. The general results highlight the strength and importance of LiDAR data in assessing the height heterogeneity and the related biodiversity in forest ecosystems.

Workspace Analysis of a Mobile Manipulator with Obstacle Avoidance in 3D Printing Tasks

The knowledge of the workspace for a robotic system on construction sites represents an essential resource to ensure the work progress, guarantee the safety of the construction tasks, and avoid robot damage. Despite the dramatic development of 3D printing technologies with robotic systems in recent years, these are still several challenges to consider, such as the size of the printing profile and obstacles in the construction site. This work presents the results from evaluating the workspace of a mobile manipulator in 3D printing tasks on construction sites. The methodology analyses the printing workspace based on the workspace of the mobile manipulator, considering fixed obstacles and possible collisions between the robot and obstacles during 3D printing tasks. The results showed that the shape of the printing profile defined as a building element changes the shape of the printing workspace. Furthermore, the obstacles in the construction site and height variation of the printing profile cause changes in the displacement of the robotic platform and values of rotation of its joints, which also modify the shape of the printing workspace.

Exploring potential applications of optical lattice clocks in a plate subduction zone

Optical clocks improved the accuracy of state-of-the-art cesium clocks by more than two orders of magnitude and enabled frequency comparison with a fractional uncertainty of one part in 1018. Gravitational redshift of two such clocks allows determining their height difference with an uncertainty of 1 cm. In Europe, chronometric leveling has been extensively conducted for unifying the height reference systems. Temporal response of the leveling, which affords monitoring a cm height variation within hours of averaging time, may offer new opportunities to explore seismology and volcanology. Superb stability of optical lattice clocks will be best used for such applications. This article outlines the prospects of chronometric leveling in Japan. Combining optical lattice clocks with an existing observation network of GNSS, crustal deformations may be monitored with unprecedented accuracy in the future.

Pemanfaatan Kulit Buah Kakao sebagai Media Adsorpsi Logam Besi (Fe) dan Mangan (Mn) pada Air Sumur

This study aims to determine the percentage reduction in iron (Fe2+) and manganese (Mn2+) content in well water using carbon from cocoa peel as an adsorption media with media height variation. The results of this study indicate that well water sample contains iron (Fe2+) levels of 1.39 mg/L and manganese (Mn2+) of 0.76 mg/L. After filtration with 60 minutes contact using carbon of cocoa peel as an adsorption media without activation, iron content and manganese content in well water decreased. The percentage reduction of iron (Fe2+) content in media height 70 cm, 80 cm and 90 cm were 76.98%, 84.17% and 98.21%. Meanwhile, the percentage in manganese (Mn2+) content at 70 cm media height was 98,93% and archived an optimum reduction at 80 cm and 90 cm media height which is 99.79% with 60 minute contact time.

Retrieval of Stratospheric HNO3 and HCl Based on Ground-Based High-Resolution Fourier Transform Spectroscopy

Vertical profiles and stratospheric HNO3 and HCl columns are retrieved by ground-based high resolution Fourier transform infrared spectroscopy (FTIR) remote sensing measurements at the Hefei site in China. The time series of stratospheric HNO3 and HCl columns from January 2017 to December 2019 showed similar annual variation trends, with an annually decreasing rate of (−9.45 ± 1.20)% yr−1 and (−7.04 ± 0.81)% yr−1 for stratospheric HNO3 and HCl, respectively. The seasonal amplitudes of stratospheric HNO3 and HCl are 2.67 × 1015 molec cm−2 and 4.76 × 1014 molec cm−2 respectively, both reaching their maximum in March and their minimum in September, due to the tropopause height variation. Further, HNO3 and HCl data were used to compare with Microwave Limb Sounder (MLS) satellite data. MLS satellite data showed similar seasonal variations and annual rates with FTIR data, and the stratospheric HNO3 and HCl columns of the two datasets have correlation coefficients (r) of 0.87 and 0.88, respectively. The mean bias between satellite and FTIR data of stratospheric HNO3 and HCl columns are (−8.58 ± 12.22)% and (4.58 ± 13.09)%, respectively.