An overview of a land evaluation in the context of ecosystem services

The environment is changing quickly and it is ever more burdened in connection with the greater needs of human society. This fact has increased efforts to improve the management of land and natural resources and the necessity to evaluate them. Land valuations become more important as the land consumption increases. Soil needs to be evaluated in the whole context of how its quality is affected and the values it provides. The concept of ecosystem services offers this holistic view. This paper defines ecosystem services (ES), the various linkages between soil properties, their functions and benefits, the assessment of soil quality using indicators and then briefly mentions EU environmental assessment methods and terms used in the context of ES. The article also mentions frameworks with which to assess and evaluate the soil quality that can be divided into two groups. The first group is comprised of a framework of indicators that describe the current state of the soil system assessment for evaluating the quality of the agricultural land. This is based on a detailed measurement of the terrain, a statistical analysis of soil databases or processing the status of specific threats to the soil. The second group is comprised of a framework of indicators focused on changes in the soil quality and applied soil management. These frameworks deal with the productivity of the soil in various systems of farming, compare agricultural systems or discuss the advantages of soil biota as indicators of soil quality in detail. Many of the designs of the soil quality indicators focus on the soil management in the context of a single discipline such as agriculture or water pollution. There are concepts for considering the soil quality in regional planning.

First SIMO Harmonic Radar Based on the SFCW Concept and the HR Transfer Function

This paper presents a new SIMO radar system based on a harmonic radar (HR) stepped frequency continuous wave (SFCW) architecture. Simple tags that can be electronically individually activated and deactivated via a DC control voltage were developed and combined to form an MO array field. This HR operates in the entire 2.45 GHz ISM band for transmitting the illumination signal and receives at twice the stimulus frequency and bandwidth centered around 4.9 GHz. This paper presents the development, the basic theory of a HR system for the characterization of objects placed into the propagation path in-between the radar and the reflectors (similar to a free-space measurement with a network analyzer) as well as first measurements performed by the system. Further detailed measurement series will be made available later on to other researchers to develop AI and machine learning based signal processing routines or synthetic aperture radar algorithms for imaging, object recognition, and feature extraction. For this purpose, the necessary information is published in this paper. It is explained in detail why this SIMO-HR can be an attractive solution augmenting or replacing existing systems for radar measurements in production technology for material under test measurements and as a simplified MIMO system. The novel HR transfer function, which is a basis for researchers and developers for material characterization or imaging algorithms, is introduced and metrologically verified in a well traceable coaxial setup.

High-frequency observation during sand and dust storms at the Qingtu Lake Observatory

Partially due to global climate change, sand and dust storms (SDSs) have occurred more and more frequently, yet a detailed measurement of SDS events at different heights is still lacking. Here we provide a high-frequency observation from the Qingtu Lake Observation Array (QLOA), China. The wind and dust information were measured simultaneously at different wall-normal heights during the SDS process. The datasets span the period from 17 March to 9 June 2016. The wind speed and direction are recorded by a sonic anemometer with a sampling frequency of 50 Hz, while particulate matter with a diameter of 10 µm or less (PM10) is sampled simultaneously by a dust monitor with a sampling frequency of 1 Hz. The wall-normal array had 11 sonic anemometers and monitors spaced logarithmically from z=0.9 to 30 m, where the spacing is about 2 m between the sonic anemometer and dust monitor at the same height. Based on its nonstationary feature, an SDS event can be divided into three stages, i.e., ascending, stabilizing and descending stages, in which the dynamic mechanism of the wind and dust fields might be different. This is preliminarily characterized by the classical Fourier power analysis. Temporal evolution of the scaling exponent from Fourier power analysis suggests a value slightly below the classical Kolmogorov value of -5/3 for the three-dimensional homogeneous and isotropic turbulence. During the stabilizing stage, the collected PM10 shows a very intermittent pattern, which can be further linked with the burst events in the turbulent atmospheric boundary layer. This dataset is valuable for a better understanding of SDS dynamics and is publicly available in a Zenodo repository at https://doi.org/10.5281/zenodo.5034196 (Li et al., 2021a).

Uncertainty quantification for aerodynamic pressure probes, using adaptive quasi-Monte Carlo

In the present study, an adaptive randomized Quasi Monte Carlo methodology is presented, combining Stein’s two-stage adaptive scheme and Low Discrepancy Sobol sequences. The method is used for the propagation and calculation of uncertainties related to aerodynamic pneumatic probes and high frequency fast response aerodynamic probes (FRAP). The proposed methodology allows the fast and accurate, in a probabilistic sense, calculation of uncertainties, ensuring that the total number of Monte Carlo (MC) trials is kept low based on the desired numerical accuracy. Thus, this method is well-suited for aerodynamic pressure probes, where multiple points are evaluated in their calibration space. Complete and detailed measurement models are presented for both a pneumatic probe and FRAP. The models are segregated in sub-problems allowing the evaluation and inspection of intermediate steps of MC in a transparent manner, also enabling the calculation of the relative contributions of the elemental uncertainties on the measured quantities. Various, commonly used sampling techniques for MC simulation and different adaptive MC schemes are compared, using both theoretical toy distributions and actual examples from aerodynamic probes' measurement models. The robustness of Stein's two-stage scheme is demonstrated even in cases when signiffcant deviation from normality is observed in the underlying distribution of the output of the MC. With regards to FRAP, two issues related to piezo-resistive sensors are addressed, namely temperature dependent pressure hysteresis and temporal sensor drift, and their uncertainties are accounted for in the measurement model. These effects are the most dominant factors, affecting all flow quantities' uncertainties, with signiffcance that varies mainly with Mach and operating temperature. This work highlights the need to construct accurate and detailed measurement models for aerodynamic probes, that otherwise will result in signiffcant underestimation (in most cases in excess of 50%) of the final uncertainties.

Pengukuran Karakteristik Lahan Berbasis Internet of Things

Climate change is one of the factors that affect crop production, so it is necessary to implement strategies and technologies to maintain the availability of cereal crops in Indonesia. It is necessary to prepare the land for the early planting process and monitoring plant growth in order to produce maximum crops. Utilization of the Internet of Things (IoT) can be used to monitor soil temperature and pH in real time, so hope for the long term it can increase crop production. The purpose of this research is to make a prototype design system with Internet of Things (IoT) technology to obtain temperature and pH data. This tool will test the functional accuracy. This research for measuring the characteristics of land based on IOT uses a prototype method consisting of Communication, Quick Plan, Modelling Quick Design, Construction of prototype, and Development Delivery & Feedback. Assembling the Wemos microcontroller, D1 R1, Breadboard, DS18B20 temperature sensor, 4700 Ohm Resistor, soil pH sensor, and 16x2 I2C LCD and connected using jumper cables with application control will be implemented into Wemos D1 R1 using the C++ programming language using Arduino IDE. Testing of the tool is carried out to ensure that the sensor is functionally able to read the temperature and pH of the soil correctly. Testing used black box method and was implemented in 5 land axis points at Politeknik Negeri Jember. The results used tools and litmus paper showed the same value. The conclusion and benefit of detecting land characteristics using the Wemos microcontroller showed more detailed measurement results with numbers behind the comma and a tool accuration rate of 100%.

CT Scans of Asbestos Cement Pipes as a Reference for Condition Assessment of Water Mains

The water distribution network of The Netherlands contains around 30,000 km of asbestos cement (AC) pipes, which constitutes around 25% of the total network. As a pipe material, AC has a relatively poor performance, and therefore is a high priority for renewal. To help decide an effective order of replacement, the water utilities need condition assessment techniques that help them determine which pipes have the highest risk of failure. In the presented work, X-ray computed tomography (CT) was used to measure the degradation of AC pipes taken out of the field. These scans provide a description of the pipe degradation with unmatched detail. The results are compared with strength tests performed on the same pipes, revealing that detailed knowledge of the complete pipe degradation is more important than previously assumed. Moreover, comparison of the CT results to those of a commercial, non-destructive inspection technique was used as a new avenue for validation of this technique, demonstrating its future usefulness for attaining the detailed measurement of pipe degradation required by water utilities.

High frequency observation during the sand and dust storms in the Qingtu Lake Observatory

Partially due to the global climate change, the sand and dust storms (SDS) occurred more and more frequently, yet a detailed measurement of the SDS event at different heights is still lacking. Here we provide a high frequency observation in the Qingtu Lake Observation Array (QLOA), China. The wind and dust information were measured simultaneously at different wall-normal heights during the SDS process. The datasets span the period from 17 March to 9 June 2016. The wind speed and direction are recorded by a sonic anemometer with a sampling frequency 50 Hz, while the particulate matter 10 (PM10) is sampled simultaneously by a dust monitor with a sampling frequency 1 Hz. The wall-normal array had 11 sonics and monitors spaced logarithmically from z = 0.9 to 30 m, where the spacing is about 2-meter between the sonic anemometer and dust monitor at the same height. Based on its non-stationary feature, the SDS event can be divided into three stages, i.e., ascending, stabilizing and descending stages, in which the dynamic mechanism of the wind and dust fields might be different. This is preliminarily characterized via the classical Fourier power analysis. Temporal evolution of the scaling exponent from Fourier power analysis suggests slightly below the classical Kolmogorov value of −5/3 for the three-dimensional homogeneous and isotropic turbulence. During the stabilizing stage, the collected PM10 shows a very intermittent pattern, which can be further linked with the burst events in the turbulent atmospheric boundary layer. This dataset is valuable for a better understanding the SDS dynamics, which has being publicly available at Zenodo through the DOI 10.5281/zenodo.5034196 (Li et al., 2021a).

Core-CT: A MATLAB application for the quantitative analysis of sediment and coral cores from X-ray computed tomography (CT)

<div> <p>X-ray computed tomography (CT) is a non-destructive imaging technique that provides three-dimensional (3D) visualisation and high-resolution quantitative data in the form of CT numbers. CT numbers are derived as a function of the X-ray energy, effective atomic number and density of the sample. The sensitivity of the CT number to changes in material density allows it to successfully identify facies changes within sediment cores by detecting downcore shifts in sediment properties, and quantify skeletal linear extension rates and the volume of internal voids from biological erosion of coral cores. Here we present two algorithms to analyse CT scan images specific to geoscience research packaged within an open source MATLAB application (Core-CT). The first algorithm facilitates the computation of representative CT numbers from a user-defined region of interest to identify boundaries of density change (e.g. sedimentary facies, laminations, coral growth bands). The second algorithm enables the segmentation of regions with major density contrast (e.g. internal void space or biogenic material) and the geometric measurements of these irregularities. The versatility of Core-CT for geoscience applications is then demonstrated by utilising CT scans from a range of environmental settings comprising both sediment (Lake Huelde, Chile and Kallang River Basin, Singapore) and coral cores (Thuwal region of Red Sea, Saudi Arabia). Analysis of sediment cores show the capabilities of Core-CT to: 1) locate tsunami deposits from lacustrine sediments, 2) provide rapid and detailed measurement of varved sediments, and 3) identify sedimentary facies from an unsplit shallow marine sediment core. Analysis of coral cores allow us to successfully measure skeletal linear extension from annual growth bands, and provide volumetric quantification and 3D visualisation of internal bioerosion. Core-CT is an accessible, multi-use MATLAB based program that is freely available at GitHub  (https://github.com/yuting-yan/Core-CT).</p> </div><p> </p>

Stabilization System for UAV Landing on Rough Ground by Adaptive 3D Sensing and High-Speed Landing Gear Adjustment

This paper proposes a real-time landing gear control system based on adaptive and high-speed 3D sensing to enable the safe landing of unmanned aerial vehicles (UAVs) on rough ground. The proposed system controls the measurement area on the ground according to the position and attitude of the UAV and enables high-speed 3D sensing of the focused areas in which the landing gears are expected to contact the ground. Furthermore, the spatio-temporal resolution of the measurement can be improved by focusing a measurement area and the proposed system can recognize the detailed shape of the ground and the dynamics. These detailed measurement results are used to control the lengths of the landing gears at high speed, and it is ensured that all the landing gears contact the ground simultaneously to reduce the instability at touchdown. In the experiment setup, the proposed system realized high-speed sensing for heights of contact points of two landing gears at a rate of 100 Hz and almost simultaneous contact on ground within 36 ms.