Search Results (27)

Segmenting agricultural fields into management zones (MZ) is a core principle of precision agriculture (PA). However, the widespread adoption of PA remains limited, partly due to operational barriers in MZ segmentation. These barriers often involve the necessity for advanced programming skills and a strong statistical background, in addition to the lack of a free, integrated and straightforward tool that executes the entire workflow. Addressing this gap required the development of the open-source QGIS plugin Precision Zones. The plugin reproducibly implements the entire MZ segmentation pipeline: (i) raster layers preprocessing; (ii) dimensionality reduction via Principal Component Analysis (PCA); (iii) multivariate clustering using K-Means ++, with integrated support for determining the optimal number of zones through the Elbow and Silhouette methods; (iv) spatial filtering of MZ to mitigate noise; and (v) assessment of MZ agronomic effectiveness using statistical metrics (i.e., within-zone variance reduction). This tool enables practical MZ segmentation for a wide range of agricultural applications, eliminating the need for programming knowledge. Despite its robust architecture, as a novel tool, it has not yet been formally characterized and presented to the scientific community. Therefore, this study describes the Precision Zones plugin, address the step-by-step user decisions and presents its validation. In a reproducible case study, the plugin produced agronomically coherent MZ and reduced within-zone variability (VR%) for most soil attributes analyzed. The study concludes that Precision Zones provides a reproducible, user-friendly workflow that bridges the gap between advanced spatial analysis and practical precision agriculture applications for growers, consultants and researchers. Full article

Metropolitan areas have become the primary spatial form for China’s new-era urbanization. However, these boundaries have traditionally been delineated based on administrative factors, resulting in a notable discrepancy with the actual functional connections. To tackle this challenge, this study aims to devise and implement an innovative ‘PET’ tri-dimensional coupling model, leveraging the principles of integrated urban subsystems to scientifically delineate functional metropolitan boundaries. The proposed method integrates Population flow (P), Economic density (E), and Transportation accessibility (T) on a fine-grained 1 km raster grid. To enhance accuracy, the crucial population flow component is simulated using a gravity model calibrated with real-world Baidu Migration data. Applying this model to 35 potential metropolitan areas, our findings reveal two key points. First, a comparative analysis with five officially approved plans reveals a significant spatial alignment in core functional zones, which corroborates the model’s accuracy. effectiveness. Secondly, these delineations clearly quantify the notable difference between the ‘functional space’ influenced by socioeconomic factors and the ‘administrative space’ delineated by jurisdictional boundaries. In summary, this research presents a replicable methodology for delineating functional metropolitan areas. It offers vital technical support and policy guidance for optimizing regional planning, enhancing inter-city coordination, and promoting China’s national strategy for regional development. Full article

This paper introduces a single-shot ultrafast imaging technique termed wavelength and polarization time-encoded ultrafast raster imaging (WP-URI). By integrating raster imaging principles with wavelength- and polarization-based temporal encoding, the system uses a spatial raster mask and time–space mapping to aggregate multiple two-dimensional temporal raster images onto a single detector plane, thereby enabling the effective spatial separation and extraction of target information. Finally, the target dynamics are recovered using a reconstruction algorithm based on the Nyquist–Shannon sampling theorem. Numerical simulations demonstrate the single-shot acquisition of four dynamic frames at 25 trillion frames per second (Tfps) with an intrinsic spatial resolution of 50 line pairs per millimeter (lp/mm) and a wide field of view. The WP-URI technique achieves unparalleled spatio-temporal resolution and frame rates, offering significant potential for investigating ultrafast phenomena such as matter interactions, carrier dynamics in semiconductor devices, and femtosecond laser–matter processes. Full article

To promote the sustainable use of land resources and improve air pollution control, this study investigates the spatiotemporal dynamics of industrial land development and the heterogeneity of PM_2.5 concentrations across regions. Based on national land transaction data and PM_2.5 raster datasets, the analysis employs Moran’s I, a hot and cold spot analysis, and multivariate linear regression to examine how the transaction frequency, transaction area, and total transaction price of industrial land influence PM_2.5 concentrations in 286 cities from 2010 to 2021. The study focuses on quantifying the impact of industrial land development on PM_2.5 concentrations. The main findings are as follows: (1) the frequency of industrial land transactions varies significantly across regions, with clear intra-regional differences. The transaction area and total transaction price decrease in the following order: “East-West-Central-North-East” and “East-Central-West-North-East”, respectively. (2) The spatial clustering of PM_2.5 concentrations has intensified, with hot spots concentrated in Eastern and Central cities. Cold spots are distributed in bands along the Southern coast and scattered patterns in Heilongjiang Province. (3) The influence of industrial land development on PM_2.5 concentrations has generally weakened nationwide, with the strongest effects observed in the Eastern region. Among the development indicators, the impact of the transaction area is increasing, while those of the transaction frequency and total price are declining, showing clear regional disparities. Therefore, integrating sustainable development principles into the adjustment of the industrial land market is essential for effective air pollution prevention. Full article

The Topographic Chart of the Kingdom of Poland (pol. Topograficzna Karta Królestwa Polskiego, commonly referred to as ‘the Quartermaster’s Map’, hereinafter: TKKP) is the first Polish modern topographic map of Poland (1:126,000, 1843). Cartographic historians acclaim its conception by the General Quartermaster of the Polish Army, noting its editorial principles and technical execution as exemplars of the early 19th-century cartographic standards. Today, it stands as a national heritage relic, furnishing invaluable insights into the former Polish Kingdom’s topography. Although extensively utilised in geographical and historical inquiries, the TKKP has yet to undergo a comprehensive geomatic investigation and publication as spatial data services. Primarily, this delay stems from the challenges of mosaicking and georeferencing its 60 constituent sheets, owing to the uncertain mathematical framework and irregular sheet cuts. In 2023, the authors embarked on rectifying this by creating a unified TKKP mosaic and georeferencing the map to contemporary reference data benchmarks. This endeavour involved scrutinising the map’s mathematical accuracy and verifying prior findings. The resultant product is accessible via the ‘Maps with the Past’ platform, developed by the Institute of History of the Polish Academy of Sciences The dissemination of raster data services adhering to OGC standards such as WMTS (Web Map Tile Service), ECW (Enhanced Compression Wavelet), and COG (Cloud Optimized GeoTIFF) facilitates the swift and seamless integration of the generated data into web and GIS tools. The digital edition of the TKKP emerges as a pivotal resource for investigations spanning natural and anthropogenic environmental transformations, sustainable development, and cultural heritage studies. Full article

For the building emergency evacuation path planning problem, existing algorithms suffer from low convergence efficiency and the problem of getting trapped in local optima. The Bloch Spherical Quantum Genetic Algorithm (BQGA) based on the least-squares principle for single-robot path planning and Bloch Spherical Quantum Bee Colony Algorithm (QABC) for multi-robots path planning are studied. Firstly, the characteristics of three-dimensional path planning are analyzed, and a linear decreasing inertia weighting approach is used to balance the global search ability of chromosomes and accelerate the search performance of the algorithm. Then, the application algorithm can generate a clear motion trajectory in the raster map. Thirdly, the least squares approach is used to fit the results, thus obtaining a progressive path. Finally, multi-robots path planning approaches based on QABC are discussed, respectively. The experimental results show that BQGA and QABC do not need to have a priori knowledge of the map, and they have strong reliability and practicality and can effectively avoid local optimum. In terms of convergence speed, BQGA improved by 3.39% and 2.41%, respectively, while QABC improved by 13.31% and 17.87%, respectively. They are more effective in sparse paths. Full article

In this paper, we report our use of a hardware encoder-based synchronization method for a fast terahertz time-domain spectroscopy raster scanner built with the commercially available TeraFlash Smart platform. We describe the principles of our method, including our incorporation of synchronization signals from various devices included in the scanner. We also describe its implementation in a microcontroller with a dedicated counter. By such means, a fast scanning mode was obtained, which was 35 times faster than a traditional step-by-step approach. To validate the proposed synchronization method, we carried out measurements using the USAF 1951 resolution test and a fiberglass plate with a set of intentionally introduced defects. Our results confirmed that the TDS scanner with the developed synchronization method was able to capture high-quality images with resolutions as high as those obtained using traditional step-by-step scanning, but with significantly reduced scanning times. Full article

Due to the lack of theoretical research on the amount of spatio-temporal information in high-speed photography technologies, obtaining an optimized system with the best amount of spatio-temporal information remains a challenge, resulting in insufficient effective information and observation accuracy for ultrafast events. This paper presents an ultrafast raster imaging (URI) system with a large amount of spatio-temporal information based on the all-optical raster principle in single-shot. Specifically, we derive the optimal equation of spatial resolution and the expression for the maximum amount of spatio-temporal information that can achieve excellent performance for a URI system. It serves as a general guideline for obtaining a large amount of information design in the URI system. Compared with the existing URI systems, the advanced URI system exhibits an improvement of nearly one order of magnitude in the amount of spatio-temporal information and more than twofold in spatial resolution. It shows great potential for capturing intricate and non-repetitive ultrafast events on the femtosecond time scale. Full article

Building outlines are important for emergency response, urban planning, and change analysis and can be quickly extracted from remote sensing images and raster maps using deep learning technology. However, such building outlines often have irregular boundaries, redundant points, inaccurate positions, and unclear turns arising from variations in the image quality, the complexity of the surrounding environment, and the extraction methods used, impeding their direct utility. Therefore, this study proposes a simplification and regularization algorithm for right-angled polygon building outlines with jagged edges. First, the minimum bounding rectangle of the building outlines is established and populated with a square grid based on the smallest visible length principle. Overlay analysis is then applied to the grid and original buildings to extract the turning points of the outlines. Finally, the building orientation is used as a reference axis to sort the turning points and reconstruct the simplified building outlines. Experimentally, the proposed simplification method enhances the morphological characteristics of building outlines, such as parallelism and orthogonality, while considering simplification principles, such as the preservation of the direction, position, area, and shape of the building. The proposed algorithm provides a new simplification and regularization method for right-angled polygon building outlines with jagged edges. Full article

Libraries with pre-written codes optimize the workflow in cartography and reduce labour intensive data processing by iteratively applying scripts to implementing mapping tasks. Most existing Geographic Information System (GIS) approaches are based on traditional software with a graphical user’s interface which significantly limits their performance. Although plugins are proposed to improve the functionality of many GIS programs, they are usually ad hoc in finding specific mapping solutions, e.g., cartographic projections and data conversion. We address this limitation by applying the principled approach of Geospatial Data Abstraction Library (GDAL), library for conversions between cartographic projections (PROJ) and Geographic Resources Analysis Support System (GRASS) GIS for geospatial data processing and morphometric analysis. This research presents topographic analysis of the dataset using scripting methods which include several tools: (1) GDAL, a translator library for raster and vector geospatial data formats used for converting Earth Global Relief Model (ETOPO1) GeoTIFF in XY Cartesian coordinates into World Geodetic System 1984 (WGS84) by the ‘gdalwarp’ utility; (2) PROJ projection transformation library used for converting ETOPO1 WGS84 grid to cartographic projections (Cassini–Soldner equirectangular, Equal Area Cylindrical, Two-Point Equidistant Azimuthal, and Oblique Mercator); and (3) GRASS GIS by sequential use of the following modules: r.info, d.mon, d.rast, r.colors, d.rast.leg, d.legend, d.northarrow, d.grid, d.text, g.region, and r.contour. The depth frequency was analysed by the module ‘d.histogram’. The proposed approach provided a systematic way for morphometric measuring of topographic data and combine the advantages of the GDAL, PROJ, and GRASS GIS tools that include the informativeness, effectiveness, and representativeness in spatial data processing. The morphometric analysis included the computed slope, aspect, profile, and tangential curvature of the study area. The data analysis revealed the distribution pattern in topographic data: 24% of data with elevations below 400 m, 13% of data with depths −5000 to −6000 m, 4% of depths have values −3000 to −4000 m, the least frequent data (−6000 to 7000 m) <1%, 2% of depths have values −2000 to 3000 m in the basin, while other values are distributed proportionally. Further, by incorporating the generic coordinate transformation software library PROJ, the raster grid was transformed into various cartographic projections to demonstrate distortions in shape and area. Scripting techniques of GRASS GIS are demonstrated for applications in topographic modelling and raster data processing. The GRASS GIS shows the effectiveness for mapping and visualization, compatibility with libraries (GDAL, PROJ), technical flexibility in combining Graphical User Interface (GUI), and command-line data processing. The research contributes to the technical cartographic development. Full article

The assessment of rock outcrops’ predisposition to the main possible kinematisms represents the preliminary step of stability analysis: Markland’s tests for sliding and toppling constitute a milestone due to the ease of use and interpretation of results. Orientation and friction angles of the main discontinuity sets and orientation of rock faces are required as input to perform the test on a stereonet graphically. However, for natural outcrops, the orientation of rock faces could vary significantly, and the test should be performed assuming all the representative ones. To speed up this process, the authors set up an automatic procedure based on the GIS environment working principles and developed it in Matlab language. Main discontinuity sets orientation and relative friction angles, along with slope and aspect data representing the rockface orientation of the considered outcrop, are the input data. The slope and aspect data are in GeoTIFF format, the most common format for georeferenced raster files employed in a GIS environment. The Matlab code performs Markland’s tests for planar and wedge sliding and flexural toppling, considering all the possible sets or intersections of sets, and provides the output with the same extent and georeferencing of the input data. The outputs are a series of GeoTIFF raster files describing the result for each kinematism separately and globally, which can be imported directly into GIS. The global results can also be used to map source areas for 3D rockfall numerical simulations. The code was validated through a case study by comparing its results with those obtained by performing the conventional tests singularly on a number of significant rock faces. The results obtained in the case study show that the algorithm produces reliable results consistent with those provided by traditional methods. Full article

With the ever-increasing popularity of unmanned aerial vehicles and other platforms providing dense point clouds, filters for the identification of ground points in such dense clouds are needed. Many filters have been proposed and are widely used, usually based on the determination of an original surface approximation and subsequent identification of points within a predefined distance from such surface. We presented a new filter, the multidirectional shift rasterization (MDSR) algorithm, which is based on a different principle, i.e., on the identification of just the lowest points in individual grid cells, shifting the grid along both the planar axis and subsequent tilting of the entire grid. The principle was presented in detail and both visually and numerically compared with other commonly used ground filters (PMF, SMRF, CSF, and ATIN) on three sites with different ruggedness and vegetation density. Visually, the MDSR filter showed the smoothest and thinnest ground profiles, with the ATIN the only filter comparably performing. The same was confirmed when comparing the ground filtered by other filters with the MDSR-based surface. The goodness of fit with the original cloud is demonstrated by the root mean square deviations (RMSDs) of the points from the original cloud found below the MDSR-generated surface (ranging, depending on the site, between 0.6 and 2.5 cm). In conclusion, this paper introduced a newly developed MDSR filter that outstandingly performed at all sites, identifying the ground points with great accuracy while filtering out the maximum of vegetation and above-ground points and outperforming the aforementioned widely used filters. The filter dilutes the cloud somewhat; in such dense point clouds, however, this can be perceived as a benefit rather than as a disadvantage. Full article

The application of intelligent equipment and technologies such as robots and unmanned vehicles is an important part of the construction of intelligent mines, and has become China’s national coal energy development strategy and the consensus of the coal industry. Environment perception and instant positioning is one of the key technologies destined to realize unmanned and autonomous navigation in underground coal mines, and simultaneous location and mapping (SLAM) is an effective method of deploying this key technology. The underground space of a coal mine is long and narrow, the environment is complex and changeable, the structure is complex and irregular, and the lighting is poor. This is a typical unstructured environment, which poses a great challenge to SLAM. This paper summarizes the current research status of underground coal mine map construction based on visual SLAM and Lidar SLAM, and analyzes the defects of the LeGO-LOAM algorithm, such as loopback detection errors or omissions. We use SegMatch to improve the loopback detection module of LeGO-LOAM, use the iterative closest point (ICP) algorithm to optimize the global map, then propose an improved SLAM algorithm, namely LeGO-LOAM-SM, and describe its principle and implementation. The performance of the LeGO-LOAM-SM was also tested using the KITTI dataset 00 sequence and SLAM experimental data collected in two coal mine underground simulation scenarios, and the performance indexes such as the map construction effect, trajectory overlap and length deviation, absolute trajectory error (ATE), and relative pose error (RPE) were analyzed. The results show that the map constructed by LeGO-LOAM-SM is clearer, has a better loopback effect, the estimated trajectory is smoother and more accurate, and the translation and rotation accuracy is improved by approximately 5%. This can construct more accurate point cloud map and low drift position estimation, which verifies the effectiveness and accuracy of the improved algorithm. Finally, to satisfy the navigation requirements, the construction method of a two-dimensional occupancy grid map was studied, and the underground coal mine simulation environment test was carried out. The results show that the constructed raster map can effectively filter out outlier noise such as dynamic obstacles, has a mapping accuracy of 0.01 m, and the required storage space compared with the point cloud map is reduced by three orders of magnitude. The research results enrich the SLAM algorithm and implementation in unstructured environments such as underground coal mines, and help to solve the problems of environment perception, real-time positioning, and the navigation of coal mine robots and unmanned vehicles. Full article

Trace elements, functionalized nanoparticles and labeled entities can be localized with sub-mm spatial resolution by X-ray fluorescence imaging (XFI). Here, small animals are raster scanned with a pencil-like synchrotron beam of high energy and low divergence and the X-ray fluorescence is recorded with an energy-dispersive detector. The ability to first perform coarse scans to identify regions of interest, followed by a close-up with a sub-mm X-ray beam is desirable, because overall measurement time and X-ray dose absorbed by the (biological) specimen can thus be minimized. However, the size of X-ray beams at synchrotron beamlines is usually strongly dependent on the actual beamline setup and can only be adapted within specific pre-defined limits. Especially, large synchrotron beams are non-trivial to generate. Here, we present the concept of graphite-based, convex reflection optics for the one-dimensional enlargement of a 1 mm wide synchrotron beam by a factor of 5 to 10 within a 1 m distance. Four different optics are tested and characterized and their reflection properties compared to ray tracing simulations. The general shape and size of the measured reflection profiles agree with expectations. Enhancements with respect to homogeneity and efficiency can be expected with improved optics manufacturing. A mouse phantom is used for a proof-of-principle XFI experiment demonstrating the applicability of coarse and fine scans with the suggested optics design. Full article

This study focuses on the determination and examination of both the Land Surface Temperature (LST) and the atmospheric temperature in the city of Catania Sicily (Italy), through freely available satellite remote sensing images from the Sentinel-2 and MODIS missions. Satellite images were processed as raster data in free and open-source GIS environments. The GIS software allows the retrieval, processing of the satellite images for the estimation of the LST and the atmospheric temperature with a very coarse spatial resolution. In particular, the proposed procedure allows increasing the spatial resolution of satellite images, from 250 m (LRES) to 10 m (HRES) through the principle of “Disaggregation of thermal images”. The analysis provided georeferenced maps which show the LST, as well as the atmospheric temperature within the investigated area with a very fine resolution, 10 m. Such spatial resolution reveals evident correlations between areas with different urban densities and their microclimate. An important result of this study is that significant LST differences can be observed during both day (15–17 °C) and night (2–3 °C) between green and built-up areas. The outcomes of this study highlight the effectiveness of the combined use of satellite remote sensing and GIS for analyzing the thermal response of urbanized areas with different built density. Full article