Raster Size Research Articles

GEOGRAPHIC INFORMATION MODEL OF PRECIPITATION INTENSITY

The paper analyses the technological features of building a geoinformation model to study the precipitation intensity in Ukraine. Analysis of natural phenomena requires promptness in obtaining and updating initial data. For this reason, today, geoinformation technologies most often use remote sensing data, mainly in raster format. We collected the raw data on precipitation intensity from the Global Precipitation Climatology Centre website of the German Meteorological Service (DWD). It is monthly data for 2022 in raster format with a raster size of 1 degree. For the organisation and analysis of geographical information, we chose the most suitable new software product, SAGA GIS, designed for geoscientific analysis automation. The advantages of this system are the availability of a complete set of geophysical analysis methods, the spatial algorithms implementation, and open-source code. After data loading, we geoprocessed the data, in particular, using the SAGA software module ‘Set Coordinate Reference System’ and selected the WGS84 coordinate system for the required layers. To prepare the data for analytical studies, we limited them to the administrative boundaries of Ukraine and transformed the WGS84 coordinate system into a UTM 36N projection. Using SAGA analytical tools, we grouped the data by season. Then, we determined the distribution of precipitation intensity over the territory for each season, identifying areas with the highest and lowest precipitation intensity and a part of the territory with the highest annual precipitation. The results of this work may have practical significance for various sectors of the economy and decision-making on adaptation to climate change. They can be relevant both for scientific research and practical application in fields related to environmental assessment. By supplementing the model with data for other subsequent or previous periods, it will be possible to determine trends in precipitation intensity by regions of Ukraine or physiographic zones of its territory. Keywords: modelling, precipitation intensity, geodatabase, geoprocessing, seasonality, software modules, SAGA GIS.

Tensile and Compression Strength Prediction and Validation in 3D-Printed Short-Fiber-Reinforced Polymers.

In the current study, a methodology is validated for predicting the internal spatially varying strength properties in a single 3D-printed bead composed of 13%, by weight, carbon-fiber-filled acrylonitrile butadiene styrene. The presented method allows for the characterization of the spatially varying microstructural behavior yielding a local anisotropic stiffness and strength that can be integrated in a finite element framework for a bulk estimate of the effective stiffness and strength. The modeling framework is presented with a focus on composite structures made from large area additive manufacturing (LAAM). LAAM is an extrusion-based process yielding components on the order of meters, with a typical raster size of 10 mm. The presented modeling methods are applicable to other short-fiber-reinforced polymer processing methods as well. The results provided indicate the modeling framework yields results for the effective strength and stiffness that align with experimental characterization to within ∼1% and ∼10% for the longitudinal compressive and tensile strength, respectively, and to within ∼3% and ∼50% for the longitudinal compressive and tensile stiffness, respectively.

Two-Dimensional-Simultaneous Localisation and Mapping Study Based on Factor Graph Elimination Optimisation

A robust multi-sensor fusion simultaneous localization and mapping (SLAM) algorithm for complex road surfaces is proposed to improve recognition accuracy and reduce system memory occupation, aiming to enhance the computational efficiency of light detection and ranging in complex environments. First, a weighted signed distance function (W-SDF) map-based SLAM method is proposed. It uses a W-SDF map to capture the environment with less accuracy than the raster size but with high localization accuracy. The Levenberg–Marquardt method is used to solve the scan-matching problem in laser SLAM; it effectively alleviates the limitations of the Gaussian–Newton method that may lead to insufficient local accuracy, and reduces localisation errors. Second, ground constraint factors are added to the factor graph, and a multi-sensor fusion localisation algorithm is proposed based on factor graph elimination optimisation. A sliding window is added to the chain factor graph model to retain the historical state information within the window and avoid high-dimensional matrix operations. An elimination algorithm is introduced to transform the factor graph into a Bayesian network to marginalize the historical states and reduce the matrix dimensionality, thereby improving the algorithm localisation accuracy and reducing the memory occupation. Finally, the proposed algorithm is compared and validated with two traditional algorithms based on an unmanned cart. Experiments show that the proposed algorithm reduces memory consumption and improves localisation accuracy compared to the Hector algorithm and Cartographer algorithm, has good performance in terms of accuracy, reliability and computational efficiency in complex pavement environments, and is better utilised in practical environments.

High Precision And Resolution Chlorine Isotopic Analysis Of Apatite Using NanoSIMS

This paper reports a high analytical precision method for measuring the Cl isotopic composition of apatite using a CAMECA NanoSIMS 50L with Faraday Cup detectors (FC). Six apatite standard samples were used for calibration. Three sets of focused Cs+ beams with currents of ~400 pA (~Φ 700 nm), 1 nA (~Φ 1μm), and 2 nA (~Φ 1.5 μm) were used with different raster sizes (4 × 4 μm2, 8 × 8 μm2, and 10 × 10 μm2, respectively). We performed depth effect experiments with three primary beam settings to optimize the instrument configuration. While using a primary beam of 2 nA with a raster size of ~10 μm, the external precision of each session varied from 0.06 to 0.48 ‰ (1SD) depending on the Cl concentration of the measured apatite. For standards with a Cl content higher than 0.5 %, the external precision was mostly higher than 0.2 ‰. Using 1 nA and 0.4 nA with spatial resolutions of ~8 μm and 5 μm, the external precision for standards with Cl contents >1 % ranged from 0.12 to 0.2 ‰ and 0.10 to 0.33 ‰, respectively. This technique enables high-precision measurements of chlorine isotopes with high spatial resolutions and can be applied to small apatite minerals in extraterrestrial samples.

Optimal resolution of soil properties maps varies according to their geographical extent and location

The important development of digital soil mapping (DSM) these last decades has led to a large number of maps of soil properties with increasingly finer raster size. Map resolution is mostly determined by expert knowledge or by matching with the resolution of existing data, while scale is recognized as a major issue. Using the pH and the C/N ratio describing the surface horizon of forest soils and estimated by bioindication, we evaluated the effect of resolution changes on model and map performance for different geographical extents. Using 40,663 plots from the national forest inventory and 25 environmental variables calculated at eight different spatial resolution levels (50, 100, 250, 500, 1000, 8000, 16,000, and 50,000 m), we modeled and mapped pH and C/N over a vast and diversified area of 91,000 km2 in the north-east of France. The models highlighted the importance of geology in pH and C/N spatial variations, and to a lesser extent the importance of stand type, climate and topography, with a slight influence of data resolution on predictor selection. On the contrary, the accuracy of model or map performance decreased significantly above 1000 m resolution. Significant performance differences were observed according to the location and the size of the geographical extent. Globally, the more heterogeneous environmental characteristics and the smaller the geographical extent, the better fine spatial resolution performed. In addition, the aggregation of fine-resolution pH or C/N maps at a coarser cell size improved map performance as compared to the direct use of the coarse-resolution predictors. The impact of resolution changes on map accuracy varies according to the mapping procedure, the local environment, and the geographical extent, and should be evaluated in DSM studies to optimize map accuracy.

DEM-cGAN Framework Constrained by Feature Lines and Elevation Range

<p indent=0mm>Currently, large-scale terrain generation methods still rely on traditional mathematical algorithms, which lack user’s control and are difficult to be realized. Although deep learning techniques have been used in terrain generation, the related training datasets are not publicly available and the inherent defects of classical generative networks have not been improved. To obtain more realistic terrain data, a terrain dataset consisting of feature sketches, grayscale images, elevation segmentation images, and elevation models is created. Also, DEM-cGAN framework constrained by feature lines and elevation range is proposed, and a dual-scale parallel network ParallelGen is designed. Users can obtain elevation data with DEM-cGAN by sketching the terrain feature lines and giving the elevation range. Multiple experiments are conducted on the generated results at the visual, numerical, and geographic levels. The results show that, DEM-cGAN framework can correctly generate elevation data with a maximum raster size of 512×512. And the results reproduce the undulation trend in the feature sketch and conform to the realistic geographic laws.

Geonomics: Forward-Time, Spatially Explicit, and Arbitrarily Complex Landscape Genomic Simulations.

Understanding the drivers of spatial patterns of genomic diversity has emerged as a major goal of evolutionary genetics. The flexibility of forward-time simulation makes it especially valuable for these efforts, allowing for the simulation of arbitrarily complex scenarios in a way that mimics how real populations evolve. Here, we present Geonomics, a Python package for performing complex, spatially explicit, landscape genomic simulations with full spatial pedigrees that dramatically reduces user workload yet remains customizable and extensible because it is embedded within a popular, general-purpose language. We show that Geonomics results are consistent with expectations for a variety of validation tests based on classic models in population genetics and then demonstrate its utility and flexibility with a trio of more complex simulation scenarios that feature polygenic selection, selection on multiple traits, simulation on complex landscapes, and nonstationary environmental change. We then discuss runtime, which is primarily sensitive to landscape raster size, memory usage, which is primarily sensitive to maximum population size and recombination rate, and other caveats related to the model’s methods for approximating recombination and movement. Taken together, our tests and demonstrations show that Geonomics provides an efficient and robust platform for population genomic simulations that capture complex spatial and evolutionary dynamics.

Research on Estimation Method of Geometric Features of Structured Negative Obstacle Based on Single-Frame 3D Laser Point Cloud

A single VLP-16 LiDAR estimation method based on a single-frame 3D laser point cloud is proposed to address the problem of estimating negative obstacles’ geometrical features in structured environments. Firstly, a distance measurement method is developed to determine the estimation range of the negative obstacle, which can be used to verify the accuracy of distance estimation. Secondly, the 3D point cloud of a negative obstacle is transformed into a 2D elevation raster image, making the detection and estimation of negative obstacles more intuitive and accurate. Thirdly, we compare the effects of a StatisticalOutlierRemoval filter, RadiusOutlier removal, and Conditional removal on 3D point clouds, and the effects of a Gauss filter, Median filter, and Aver filter on 2D image denoising, and design a flowchart for point cloud and image noise reduction and denoising. Finally, a geometrical feature estimation method is proposed based on the elevation raster image. The negative obstacle image in the raster is used as an auxiliary line, and the number of pixels is derived from the OpenCV-based Progressive Probabilistic Hough Transform to estimate the geometrical features of the negative obstacle based on the raster size. The experimental results show that the algorithm has high accuracy in estimating the geometric characteristics of negative obstacles on structured roads and has a practical application value for LiDAR environment perception research.

Spherowell, a novel system inducing autonomous spheroid formation of cell monolayers

Purpose: Cell spheroids are the most frequently used system for in vitro chondrogenic differentiation and are gaining increasingly importance in clinical applications. However, drawbacks of currently used systems are the lack of early-readout parameters and time as well as reagent intensive procedures. While this can be partially alleviated by process automation, it is often not feasible due to high cost of necessary equipment. Herein we present a completely new concept of spheroid formation (SpheroWell) allowing for mass-production of chondrogenic spheroids from monolayer via growth surface compartmentation with promising applications in cartilage regeneration and in vitro screening applications. Methods: Standard 60 mm cell culture dishes were compartmentalized with a 1 mm or 3 mm raster by laser engraving. Telomerase immortalized adipose derived stromal/stem cells (ASC/TERT1) were seeded in mono-culture and in co-culture with primary human articular chondrocytes (hAC) at a total cell number of 1 x 106 cells/dish on compartmentalized dishes. Co-cultures were conducted at 1:4, 1:1 and 4:1 hAC:ASC ratios. Cells were cultured in differentiation media containing low concentrations of TGFβ-3 and BMP-6 (1 ng/ml). The spheroid formation process was analysed using time-laps imaging and bright field-/confocal microscopy and the resulting spheroid sizes were measured. Chondrogenic differentiation and internal structure were compared to standard pellet culture using qRT-PCR (collagen type 1/2 (Col1/2) and aggrecan (Agg)) and (immuno-) histochemistry (Alcian blue and collagen type II). As a model for tissue regeneration spheroids were embedded into fibrin hydrogel and the cellular outgrowth and matrix deposition were analysed. Finally the system was assessed for its usability as an in vitro testing system using the spheroid formation process as an early readout parameter by assessing the effect of interleukin-1β (IL-1β) on the formation kinetics. Results: After initial seeding, spheroids self-assembled in a multi-phase process. After a short proliferation phase, edge regions (especially in compartment corners) began to retract, followed by roll-up of the monolayer and final condensation into a spheroid (Figure 1). For ASC/TERT1 mono-cultures this process took about 3 weeks, while addition of hAC accelerated the formation time to 1-2 weeks in a cell-ratio dependent manner. However, while ASC and co-cultures up to 1:1 ratio formed pellets of constant size, hAC ratios over 50% lead to variable and smaller spheroids due to faster and incomplete monolayer formation. Apart from cell ratios, spheroid sizes could be controlled by varying the raster size, yielding highly reproducible mean diameters of 340.9 and 134.4 (SD < 10%) for 3 mm and 1 mm raster respectively (with ASC mono-cultures). When comparing spheroids from raster plates with standard pellet culture comparable differentiation capacity was visible despite the 2D-phase of the initial monolayer in SpheroWells. Internal structures revealed differences with spheroids showing strands of matrix homogenously distributed over the cross-section, while pellets generally showed a pronounced aligned cortex region. When embedding spheroids from raster plates into fibrin hydrogels cellular outgrowth into the hydrogel could be observed, with outgrowth speed being controllable via hydrogel density. Matrix deposition could be observed around the outgrowing cells, which was especially pronounced in co-cultures. Finally, first results using the system as an in vitro testing system were obtained. Treatment of raster plate cultures with IL-1β showed a strong reduction in spheroid formation time serving as early readout parameters, while as expected showing abolishment of Col2 expression in endpoint analysis. Conclusions: The new culture system, SpheroWell, is highly efficient in spheroid generation, saving time and culture medium and allowing for additional early read outs via tracking the spheroid formation process. The ability to produce and maintain hundreds of spheroids within one dish, which can be easily integrated into pre-existing production and research workflows makes it attractive for high throughput testing and clinical spheroid application.

Calibration of CCD sensors mounted on geodetic measuring systems

If the eyepiece of a total station is replaced with a CCD sensor, the most important task is to calibrate the instrument. Calibration establishes a connection between the readings on the horizontal and vertical circles of the total station and the readings in the coordinate system of the CCD sensor. Our calibration method uses a collimator in a few meters distance, which serves as a target at infinity during the calibration. We tested the calibration using a QDaedalus astrogeodetic measuring system. The optimal number of calibration measurements, the optimal raster size, and the temperature dependence of the measurements were investigated.

Optimization of SIMS analytical parameters for water content measurement of olivine

Secondary ion mass spectrometry (SIMS) has a wide range of applications in Earth Science research, thanks to its high precision and sensitivity, and its capacity in direct insitu micromeasurement. The technique is operated in ultra‐high vacuum (UHV) conditions, especially for the measurement of volatiles such as hydrogen, or the water content in nominally anhydrous minerals (NAMs). To minimize the water background and obtain accurate and precise water contents in NAMs (eg, olivine) critical parameters such as presputtering time, field aperture (FA), dynamic transfer on/off, and primary beam current intensity were investigated for a CAMECA IMS 1280‐HR system. When the chamber vacuum reaches approximately 2 × 10−9 mbar, we set the DTOS OFF, raster size to 50 μm and primary beam current to 5 nA, and used 2000 μm FA and 170‐second presputtering time. Consequently, an approximately 1.2 ppmw water background and 3.6 ppmw limit of detection (LOD) were yielded, from analyzing the San Carlos olivine. Meanwhile, the water content and homogeneity of a range of olivine minerals were characterized for potential use as reference materials for SIMS water content measurement. Olivine water content calibration curve was also established by comparing the Fourier transform infrared (FTIR) results with the SIMS‐measured 16O1H−/16O− ratios. Accuracy and precision of water content measurement were estimated to be better than approximately 10% in this study.

NanoSIMS Imaging of D/H Ratios on FIB Sections.

The D/H ratio imaging of weakly hydrated minerals prepared as focused ion beam (FIB) sections is developed in order to combine isotopic imaging by nanoscale secondary ion mass spectrometry (NanoSIMS) of micrometer-sized grains with other nanoscale imaging techniques, such as transmission electron microscopy. In order to maximize the accuracy, sensitivity, precision, and reproducibility of D/H ratios at the micrometer size, while minimizing the surface contamination at the same time, we explored all instrumental parameters known to influence the measurement of D/H ratios in situ. Optimal conditions were found to be obtained with the use of (i) a Cs+ ion source and detection of H- and D- at low mass resolving power, (ii) a primary beam intensity of 100 pA, and (iii) raster sizes in the range of 8-15 μm. Nominally anhydrous minerals were used to evaluate the detection limits and indicate a surface contamination level of ∼200 ppm equivalent H2O under these conditions. With the high primary intensity used here, the dwell time is not a parameter as critical as found in previous studies and a dwell time of 1 ms/px is used to minimize dynamic contamination during analysis. Analysis of FIB sections was found to reduce significantly static contamination due to sample preparation and improved accuracy compared to using polished sections embedded not only in epoxy but in indium as well. On amphiboles, the typical overall uncertainty including reproducibility is ∼20 ‰ on bulk FIB sections and ∼50 ‰ at the 1.5 μm scale using image processing (1σ).

Raptor

With the increase in amount of remote sensing data, there have been efforts to efficiently process it to help ecologists and geographers answer queries. However, they often need to process this data in combination with vector data, for example, city boundaries. Existing efforts require one dataset to be converted to the other representation, which is extremely inefficient for large datasets. In this demonstration, we focus on the zonal statistics problem, which computes the statistics over a raster layer for each polygon in a vector layer. We demonstrate three approaches, vector-based, raster-based, and raptor-based approaches. The latter is a recent effort of combining raster and vector data without a need of any conversion. This demo will allow users to run their own queries in any of the three methods and observe the differences in their performance depending on different raster and vector dataset sizes.

REGISTRATION OF UAV DATA AND ALS DATA USING POINT TO DEM DISTANCES FOR BATHYMETRIC CHANGE DETECTION

Abstract. This paper shows a method to register point clouds from images of UAV-mounted airborne cameras as well as airborne laser scanner data. The focus is a general technique which does rely neither on linear or planar structures nor on the point cloud density. Therefore, the proposed approach is also suitable for rural areas and water bodies captured via different sensor configurations. This approach is based on a regular 2.5D grid generated from the segmented ground points of the 3D point cloud. It is assumed that initial values for the registration are already estimated, e.g. by measured exterior orientation parameters with the UAV mounted GNSS and IMU. These initial parameters are finely tuned by minimizing the distances between the 3D points of a target point cloud to the generated grid of the source point cloud in an iteration process. To eliminate outliers (e.g., vegetation points) a threshold for the distances is defined dynamically at each iteration step, which filters ground points during the registration. The achieved accuracy of the registration is up to 0.4 m in translation and up to 0.3 degrees in rotation, by using a raster size of the DEM of 2 m. Considering the ground sampling distance of the airborne data which is up to 0.4 m between the scan lines, this result is comparable to the result achieved by an ICP algorithm, but the proposed approach does not rely on point densities and is therefore able to solve registrations where the ICP have difficulties.

The choice of an area zonation method based on the territorial share of industrial society heritage: The post-industrial cultural landscape Kamenicko as a case study

The data from a field survey on the areas and sites of the industrial period heritage was put through GIS processing to identify the areas (zones) with a predefined share of heritage as special types of the present landscape. Experiments with available interpolation methods (binary with focal statistics, IDW, kernel regression and combinations of these) were applied to varying quadrate raster sizes and point clouds led to valuable results. A statistical comparison was used for the best output selection represented by the focal statistics of a 15×15 pixel moving window on binary map data with the 30 m ground pixel size. The identified cores of the post-industrial landscape were given with appropriate development proposals.

High-mass-resolution MALDI mass spectrometry imaging of metabolites from formalin-fixed paraffin-embedded tissue.

Formalin-fixed and paraffin-embedded (FFPE) tissue specimens are the gold standard for histological examination, and they provide valuable molecular information in tissue-based research. Metabolite assessment from archived tissue samples has not been extensively conducted because of a lack of appropriate protocols and concerns about changes in metabolite content or chemical state due to tissue processing. We present a protocol for the in situ analysis of metabolite content from FFPE samples using a high-mass-resolution matrix-assisted laser desorption/ionization fourier-transform ion cyclotron resonance mass spectrometry imaging (MALDI-FT-ICR-MSI) platform. The method involves FFPE tissue sections that undergo deparaffinization and matrix coating by 9-aminoacridine before MALDI-MSI. Using this platform, we previously detected ∼1,500 m/z species in the mass range m/z 50-1,000 in FFPE samples; the overlap compared with fresh frozen samples is 72% of m/z species, indicating that metabolites are largely conserved in FFPE tissue samples. This protocol can be reproducibly performed on FFPE tissues, including small samples such as tissue microarrays and biopsies. The procedure can be completed in a day, depending on the size of the sample measured and raster size used. Advantages of this approach include easy sample handling, reproducibility, high throughput and the ability to demonstrate molecular spatial distributions in situ. The data acquired with this protocol can be used in research and clinical practice.

Oxygen regulates lipid profiles in human primary chondrocyte cultures

Purpose: Articular cartilage is generally exposed to a finely regulated gradient of relatively low oxygen percentages (from 8% at the surface to 1% in the deepest layers). While most cartilage research is performed in supraphysiological oxygen levels (19-21%), culturing chondrocytes under hypoxic oxygen levels (≤8%) promotes the chondrogenic phenotype and cartilage-specific matrix formation. Although hypoxiainducible factor-1α is identified as a key mediator of these beneficial effects on chondrogenesis, the underlying mechanisms remain unclear. A recent study in primary chondrocytes and chondrogenically differentiating mesenchymal stem cells showed that the cholesterol metabolism is altered in hypoxic conditions. Moreover the lipid metabolism is changed in osteoarthritic cartilage and intracellular lipid accumulation is correlated with osteoarthritis (OA) severity. In this study we assessed whether healthy and OA chondrocytes have distinct responses in normoxia or hypoxia with respect to their lipid composition. Methods: Human primary chondrocytes were isolated from cartilage knee biopsies of patients (n = 5) undergoing total knee replacement. From each donor cells were isolated from macroscopically healthy and OA damaged areas. Cells were expanded in monolayer in normoxia (21% oxygen) or hypoxia (2.5% oxygen) and subsequently cultured in 3D pellets in normoxia or hypoxia for 7 days. Lipid profiles were assessed with Matrix Assisted Laser Desorption Ionization mass spectrometry imaging (MALDI MSI). Cell pellets were cryosectioned (10 μm section) and sprayed with α-Cyano-4-hydroxycinnamic acid (CHCA) matrix 5 mg/ml in methanol/water/trifluoroacetic acid (70:30:0.01) using the Suncollect (Sunchrom). A Synapt HDMS MALDI-Q-TOF (Waters) instrument was used to perform the MSI experiments with a spatial raster size of 100 μm. Principal component analysis (PCA) and discriminant analysis (DA) were used to search for spectral similarities and differences between the conditions. Biomap software was used to visualize molecular distributions. The Lipid Maps database was used for lipid assignment and tandem MS for the identification. Results: Chondrocyte cells cultured under different oxygen tensions were discriminated by MALDI MSI followed by discriminant analysis. Discriminant function 1 (DF1) described the lipid profiles specific to each oxygen tension (Figure 1). In hypoxic pellets the intensity of phosphatidylcholine (PC) 16:0/18:1 (m/z 798.5) and sphingomyelin (SM) d18:1/16:0 (m/z 741.5 and 725.5) (Figure 1A)was higher compared to normoxic pellets. Moreover, while various phosphatidylinositol (PI) were present at both oxygen tensions, the intensity of the PI's in normoxia (m/z 865.5 and 885.5) was much higher (Figure 1B). The molecular distribution of SM d18:1/16:0 at m/z 741.5 and PC 18:0/18:1 (m/z 810.6) showed a higher expression at the edges of the pellet (Figure 2). Interestingly, we found that the lipid profiles of chondrocytes harvested from either OA or healthy cartilage showed a more pronounced difference when cultured in hypoxia. In both positive and negative ion modes the second DF separated healthy from OA chondrocytes in hypoxic conditions. Conclusions: Our MALDI-MSI data show that oxygen tension modulated the lipid composition of chondrocytes. Furthermore, culturing OA or healthy chondrocytes in hypoxic conditions resulted in more pronounced differences in lipid profiles as compared to culturing in normoxia. Since glycerophospholipids, including PC, SM, PS, and PI, are key components of the lipid bilayer and involved in metabolism and cell signaling, we will next investigate how these lipids influence chondrocyte metabolism and cell signaling. (Figure presented).

Nitrogen isotope analysis of NaNO3 and KNO3 by nano secondary ion mass spectrometry using the 15N16O2−/14N16O2− ratio

The authors demonstrate that the Cameca NanoSIMS 50 ion probe is capable of measuring species specific stable nitrogen isotope ratios accurately on bulk sodium nitrate (NaNO3) and potassium nitrate (KNO3) standards deposited on gold substrate by using a Cs+ primary ion beam and the secondary molecular ion ratio 15N16O2−/14N16O2−. The typical precision in a given session is ±1.3‰ and the accuracy for long term measurements on the in-house NaNO3 standard is ±1.9‰ for a raster size of 5 × 5 μm2. The difference in the matrix specific instrument mass fractionation between NaNO3 and KNO3 is 7.1 ± 0.9‰. The results shown in this paper indicate that single micrometer sized nitrate particles can be measured accurately for N isotopic composition. This method can be used to conduct laboratory studies to better understand the isotope fractionation during reactions of NO on sea salt and dust surfaces.

A new approach to express ToF SIMS depth profiling

We propose a new approach to express SIMS depth profiling on a TOF.SIMS‐5 time‐of‐flight mass spectrometer. The approach is based on the instrument capability to independently perform raster scans of sputter and probe ion beams. The probed area can be much smaller than the diameter of a sputter ion beam, like in the AES depth profiling method. This circumstance alleviates limitations on the sputter beam–raster size relation, which are critical in other types of SIMS, and enables analysis on a curved‐bottomed sputter crater. By considerably reducing the raster size, it is possible to increase the depth profiling speed by an order of magnitude without radically degrading the depth resolution. A technique is proposed for successive improvement of depth resolution through profile recovery with account for the developing curvature of the sputtered crater bottom in the probed area. Experimental study of the crater bottom form resulted in implementing a method to include contribution of the instrumental artifacts in a nonstationary depth resolution function within the Hofmann's mixing–roughness–information depth model. The real‐structure experiment has shown that the analysis technique combining reduction of a raster size with a successive nonstationary recovery ensures high speed of profiling at ~100 µm/h while maintaining the depth resolution of about 30 nm at a 5 µm depth. Copyright © 2015 John Wiley &amp; Sons, Ltd.

The Impact of Multi-Sensor Data Assimilation on Plant Parameter Retrieval and Yield Estimation for Sugar Beet

Abstract. Yield Maps are a basic information source for site-specific farming. For sugar beet they are not available as in-situ measurements. This gap of information can be filled with Earth Observation (EO) data in combination with a plant growth model (PROMET) to improve farming and harvest management. The estimation of yield based on optical satellite imagery and crop growth modelling is more challenging for sugar beet than for other crop types since the plants’ roots are harvested. These are not directly visible from EO. In this study, the impact of multi-sensor data assimilation on the yield estimation for sugar beet is evaluated. Yield and plant growth are modelled with PROMET. This multi-physics, raster-based model calculates photosynthesis and crop growth based on the physiological processes in the plant, including the distribution of biomass into the different plant organs (roots, stem, leaves and fruit) at different phenological stages. The crop variable used in the assimilation is the green (photosynthetically active) leaf area, which is derived as spatially heterogeneous input from optical satellite imagery with the radiative transfer model SLC (Soil-Leaf-Canopy). Leaf area index was retrieved from RapidEye, Landsat 8 OLI and Landsat 7 ETM+ data. It could be shown that the used methods are very suitable to derive plant parameters time-series with different sensors. The LAI retrievals from different sensors are quantitatively compared to each other. Results for sugar beet yield estimation are shown for a test-site in Southern Germany. The validation of the yield estimation for the years 2012 to 2014 shows that the approach reproduced the measured yield on field level with high accuracy. Finally, it is demonstrated through comparison of different spatial resolutions that small-scale in-field variety is modelled with adequate results at 20 m raster size, but the results could be improved by recalculating the assimilation at a finer spatial resolution of 5 m.