Ground Elevation Research Articles

High-Resolution Spaceborne SAR Geolocation Accuracy Analysis and Error Correction

High-accuracy geolocation is crucial for high-resolution spaceborne SAR images. Most advanced SAR satellites have a theoretical geolocation accuracy better than 1 m, but this may be unrealizable with less accurate external data, such as atmospheric parameters and ground elevations. To investigate the actual SAR geolocation accuracy in common applications, we analyze the properties of different geolocation errors, propose a geolocation procedure, and conduct experiments on TerraSAR-X images and a pair of Tianhui-2 images. The results show that based on GNSS elevations, the geolocation accuracy is better than 1 m for TerraSAR-X and 2 m/4 m for the Tianhui-2 reference/secondary satellites. Based on the WorldDEM and the SRTM, additional geolocation errors of 2 m and 4 m are introduced, respectively. By comparing the effectiveness of different tropospheric correction methods, we find that the GACOS mapping method has advantages in terms of resolution and computational efficiency. We conclude that tropospheric errors and ground elevation errors are the primary factors influencing geolocation accuracy, and the key to improving accuracy is to use higher-accuracy DEMs. Additionally, we propose and validate a geolocation model for the Tianhui-2 secondary satellite.

Application of a new multi-elevation method for determining the elemental composition of atmospheric precipitation in coastal marine zones.

Assessing local air quality using traditional methods, such as analyzing precipitation composition, is often difficult due to the complex data, which is influenced by a variety of chemical elements from distant atmospheric sources and cyclone formation areas. This study presents a new approach to overcome these challenges: a multi-elevation sampling method that improves the accuracy of local air quality measurements. By collecting precipitation samples at different ground elevations, the technique takes advantage of the natural process where raindrops and snowflakes collect more elements as they fall through the air. This method helps to distinguish local air quality from background levels found at higher, non-industrial elevations. The primary goal was to isolate and identify the elemental fingerprints of marine influences, while excluding contributions from cyclones. In February 2023, 51 meltwater samples were collected from 17 observation points in the city of Sochi under southeast wind conditions. These samples revealed a spectrum of chemical elements, predominantly of marine origin (Mg > Na > Sr > Ca > K > Ce > Mn). The results showed significant differences in elemental concentrations between upland and coastal areas. The Geochemical Indicator of Marine Origin (GIM) ranged from 22 to 3235, confirming the strong influence of marine aerosols in the area. These findings demonstrate the effectiveness of the multi-elevation sampling method in providing robust environmental assessments. This approach, combined with the GIM index, offers valuable insights for improving environmental policies and public health, particularly in coastal regions affected by marine aerosols.

Geological and hydrological controls on the pressure regime of coalbed methane reservoir in the Yanchuannan field: Implications for deep coalbed methane exploitation in the eastern Ordos Basin, China

The pressure regimes of the No. 2 coalbed methane (CBM) reservoir in the Yanchuannan field located in the southeastern Ordos Basin are highly variable and divided into overpressured (pressure gradient >9.80 kPa/m), slightly underpressured (pressure gradient of 8–9.80 kPa/m), and moderately underpressured (pressure gradient of 5–8 kPa/m). The controlling factors for the variable pressure regimes were investigated through the analysis of geological and hydrological characteristics. The pressure regimes are controlled by different mechanisms in different hydrodynamic environments. In the closed hydrodynamic environment characterized by TDS > 10,000 mg/L and NaCl type of groundwater, the pressure regime is dominated by overpressured to slightly underpressured and is controlled by CBM migration. Overpressure was developed by thermogenic CBM generation during the coalification process and is maintained by thermogenic CBM migration from the extended northwestward and deeply buried CBM reservoir during tectonic uplift. The transition from overpressure to slight underpressure and then to moderate underpressure towards the southeast is the result of the progressively weakened migrated thermogenic CBM with increasing migration distance. In the open hydrodynamic environment characterized by TDS < 10,000 mg/L and NaHCO3 type of groundwater, the pressure regime is dominated by slightly to moderately underpressured and is governed by hydrodynamics. Groundwater is fed by meteoric recharge along the structurally upturned basin margin and creates the hydrodynamic framework during tectonic uplift. The transition from moderate to slight underpressure towards the southwest is associated with the minor decrease range in ground elevation from basin margin to basin interior and the gradually weakened runoff intensity of groundwater with increasing distance to meteoric recharge. The idealized models for the pressure regimes are established, which can provide guidance to deep CBM sweet spot identification in CBM fields in the eastern Ordos Basin and elsewhere.

A Global Evaluation of Radar‐Derived Digital Elevation Models: SRTM, NASADEM, and GLO‐30

AbstractThis study evaluates global radar‐derived digital elevation models (DEMs), namely the Shuttle Radar Topography Mission (SRTM), NASADEM and GLO‐30 DEMs. We evaluate their accuracy over bare‐earth terrain and characterize elevation biases induced by forests using global Lidar measurements from the Ice, Cloud, and Land Elevation Satellite (ICESat)'s Geoscience Laser Altimeter System (GLAS), the Global Ecosystem Dynamics Investigation (GEDI) and the ICESat‐2 Advanced Topographic Laser Altimeter System (ATLAS) instruments collected on locally flat terrain. Our analysis is based on error statistics calculated for each DEM tile, which are then summarized as global error percentiles, providing a regional characterization of DEM quality. We find NASADEM to be a significant improvement upon the SRTM V3. Over bare ground areas, the mean elevation bias and root mean square error (RMSE) improved from 0.68 to 2.50 m respectively to 0.00 and 1.5 m as compared to ICESat/GLAS. GLO‐30 is more accurate with bare ground elevation bias and RMSE were below 0.05 and 0.55 m. Similar improvements were observed when compared to GEDI and ICESat‐2 measurements. The DEM biases associated with the presence of vegetation vary linearly with canopy height, and more closely follow the percentile of Lidar Relative Height (RH50). Other factors such as canopy density, radar frequency and Lidar technology also contribute to observed elevation biases. This global analysis highlights the potential of various technologies for mapping of Earth's topography, and the need for more advanced remote sensing observations that can resolve vegetation structure and sub‐canopy ground elevation.

Flood Vulnerability Assessment in Paradip Coastal Area Using Weighted Overlay Index

Paradip, a prominent coastal city on India's eastern seaboard, presents a unique combination of environmental challenges and urban pressures. It has the largest tidal range among major regional tidal gauge stations, including Vishakhapatnam and Chennai. The city experiences an annual sea level rise of 2.33 mm, with projections indicating an increase of 0.183 feet by 2047 and 0.76 feet over the next century. The city's unique environmental and urban issues are exacerbated by its placement within the Mahanadi River's deltaic deposits, floodplains, and coastal marine deposits along the Bay of Bengal. The shoreline of Paradip is topographically uniform, with ground elevations ranging from 3.6 to 5.7 meters. According to India's Wind and Cyclone Hazard Map, Paradip is in the "Very High Damage Risk Zone," indicating the presence of significant wind speeds along the coast. The paper digs into these vulnerabilities and their possible influence on the coastal community, emphasizing the city's need to strike a balance between urban growth and ecological preservation. One of the main problems is flooding. Rainwater enters government buildings and impoverished areas because of encroachments on natural drainage systems. Dryland capable of residential, agricultural, and other economic activities is submerged by overflowing water which causes loss of life, property, and infrastructure. This study evaluates flood vulnerabilities in Paradip, a coastal city, using GIS and a weighted overlay index. By integrating satellite imagery, digital elevation models (DEM), and historical data on rainfall and soil types, we developed a detailed flood vulnerability map that categorises areas into high, moderate, and low risk. ArcGIS Pro 2.7.3 software and a weighted overlay index were utilized for the collection, processing, and display of spatial and attribute data. spatial analysis was the process used to produce the flood vulnerability map. The results provide essential insights for urban planning and flood mitigation strategies, with direct implications for improving disaster preparedness and climate resilience. The flood vulnerability map was then compared to the masterplan of Paradip which was proposed for 2030, to know the actual vulnerable area and to defy some major which were proposed by Paradip development authority. The study illustrates how remote sensing and GIS techniques can be effectively utilized to generate flood vulnerability data essential for informed decision-making.

Unmanned aerial vehicle-based aerial survey of mines in Shanxi Province based on image data

Abstract Accurately monitoring the change of mine area in the mining process is beneficial to mine safety management. This paper briefly introduces the collection of remote sensing images by unmanned aerial vehicles (UAVs) and its application in measuring surface mining subsidence and surrounding vegetation in the mining area. A case study was carried out in some mining areas of Nanshan Mountain, Yuncheng City, Shanxi Province. The surface mining subsidence value and vegetation-related parameters were measured by comparing the digital elevation model and multi-spectral images collected on May 12 and June 12, 2023. The validity experiment verified that the UAV image data could be used to measure the mining subsidence and vegetation parameters. Moreover, it was found that mining underground coal could lead to significant ground subsidence and pollute the surrounding environment, reducing vegetation. The innovation of this article lies in using UAV-collected remote sensing images instead of manually collecting ground elevation data and vegetation distribution data, providing effective references for safe mining in mining areas.

Efficiency Analysis of Open Polygon Method in Land Mapping in Mojoroto Kediri

In the building establishment process, the geotechnical characteristics of soil have a significant impact on the structural performance of buildings. Therefore, soil mapping becomes a critical step in understanding the properties of soil that can affect foundation and structural stability. The mapping method used is open polygon mapping, which allows flexibility in determining land boundaries. Measurements were taken at three survey points: roadside, middle of the field, and edge of the field. The mapping results reveal variations in soil characteristics that need to be considered in development planning to ensure solid and stable building foundations. The implementation of Geographic Information Systems (GIS) in this process facilitates deeper data analysis and better visualization of field conditions. The mapping results show significant variations in ground elevation at each survey point, emphasizing the importance of understanding the area's topography. Additionally, area measurements were conducted using open polygon data, providing fundamental information for area development planning. Contour maps generated through Surfer software provide clear visualization of ground elevations at each survey point, enhancing understanding of the area's topography. This research contributes significantly to understanding soil characteristics and topography in the rear area of Mojoroto. It is expected to serve as a guide for area development planning, ensuring the stability and safety of future building structures. Thus, soil mapping is a critical step in ensuring the safety and sustainability of future buildings and contributes to sustainable area development planning.

UAV Modelling of Proglacial Landscapes, Axel Heiberg Island Nunavut

This project involved using a UAV to create digital models and products that enhance visualization and understanding of the moraines of White and Thompson Glaciers, Axel Heiberg Island, Nunavut. UAV surveying offers an effective alternative to high-resolution satellite imagery for documenting highly dynamic proglacial landscapes. Proglacial landforms and sediments provide insights into glacier characteristics and the behavior of glacier termini. UAV surveying allows for high-resolution examination of moraine features and the creation of digital elevation models (DEMs) that facilitate topographic modeling and the detection of changes. A Mavic 3M Drone was employed with UGCS flight planning software. UGCS flight planning software was selected for its ability to create orthomosaic flight plans that consider ground elevation, ensuring accurate Ground Sampling Distance (GSD). A 2m Arctic DEM was uploaded to UGCS prior to planning flight routes, allowing for more precise measurements. Post processing was done in Drone2Map and Agisoft Metashape to create both 2D orthomosaics and 3D models respectively. The results of this work will be used as a visual tool to study current aspects of the moraines, including extent, depositional processes, and present hydrodynamic energy environments. This information will be compared to historical air photos and previous studies to examine changes the moraines over a sixty-year period.

Analysis of stress field in the head area of the Three Gorges Reservoir based on coupled fluid-solid theory

The Three Gorges Reservoir, one of the largest water conservation system in the world, has been of keen interest to scientists globally since its impoundment. After construction of the dam, there has been a significant increase in seismic activity in the head area of the reservoir. It is generally accepted that earthquakes in this region are predominantly caused by the Jiuwanxi and Xiannvshan faults. This study focused on the stress changes occurring in the research area. A three-dimensional finite element model of the reservoir area was constructed using the geological structure and digital ground elevation data of the reservoir area. The fluid-solid coupling theory was applied to calculate the dynamic spatial changes in pore pressure and Coulomb stress in the faults and surrounding rocks during reservoir impoundment. The findings indicated that the added head pore water pressure at the bottom of the reservoir had a maximum impact range of approximately −2800 m on the surrounding rock, whereas the Xiannvshan and Jiuwanxi faults had a maximum diffusion range of approximately −4300 m. Rock permeability also played a significant role in the water storage process. During the 1 56 m water impoundment stage, owing to rapid water storage activity, stress could not be transmitted to both sides in a timely manner, resulting in the formation of an extreme stress change zone at −4000 m inside the fault. This may have been the reason for the frequent earthquakes during this stage. The 17 5 m cycle water storage stage also exhibited a significant degree of seismicity, potentially attributable to the long-term infiltration of reservoir water and accumulation of stress in the previous stage. The stress in the study area at the four stages are in a process of accumulation-release-accumulation-release.

Camera-based mapping in search-and-rescue via flying and ground robot teams

Search and rescue (SaR) is challenging, due to the unknown environmental situation after disasters occur. Robotics has become indispensable for precise mapping of the environment and for locating the victims. Combining flying and ground robots more effectively serves this purpose, due to their complementary features in terms of viewpoint and maneuvering. To this end, a novel, cost-effective framework for mapping unknown environments is introduced that leverages You Only Look Once and video streams transmitted by a ground and a flying robot. The integrated mapping approach is for performing three crucial SaR tasks: localizing the victims, i.e., determining their position in the environment and their body pose, tracking the moving victims, and providing a map of the ground elevation that assists both the ground robot and the SaR crew in navigating the SaR environment. In real-life experiments at the CyberZoo of the Delft University of Technology, the framework proved very effective and precise for all these tasks, particularly in occluded and complex environments.

Investigating the drivers of urban cover-collapse sinkholes in shanghai: analyzing dominant factors and proposing mitigation strategies

Urban cover-collapse sinkholes pose a significant global challenge due to their destructive impacts. Previous studies have identified groundwater fluctuations, subsurface soil conditions, pipeline leakage, precipitation, and subterranean construction activities as key contributors to these phenomena. However, unique geological settings across different urban environments lead to variations in the primary factors influencing sinkhole formation. This study focuses on Shanghai, a city notable for its extensive urbanization and rich historical context, to explore the dynamics of sinkholes within urbanized areas worldwide. We employ spatial analysis and statistical methods to examine data on sinkholes recorded in the past two decades in Shanghai, correlating these events with the city’s shallow sand layer, ground elevation, and proximity to surface water. Our goal is to identify the dominant factors governing sinkhole occurrence in Shanghai and to lay the groundwork for their effective scientific management and prevention. Key findings indicate that most sinkholes in the area are associated with a thin shallow sand layer, low to moderate ground elevations, and the absence of nearby rivers. Additionally, many sinkholes correlate with subterranean voids within the confined aquifer beneath the cohesive soil layer. The lack of historical river channels, obscured by urban development, also indirectly contributes to sinkhole formation. We recommend enhancing urban river management and drainage systems to mitigate potential damage from water accumulation.

Header Height Detection and Terrain-Adaptive Control Strategy Using Area Array LiDAR

During the operation of combine harvesters, the cutting platform height is typically controlled using manual valve hydraulic systems, which can result in issues such as delays in adjustment and high labor intensity, affecting both the quality and efficiency of the operation. There is an urgent need to enhance the automation level. Conventional methods frequently employ single-point measurements and lack extensive area coverage, which means their results do not fully represent the terrain’s variations in the area and are prone to local anomalies. Given the inherently undulating terrain of farmland during harvesting, a control strategy that does not adjust for minor undulations but only for significant ones proves to be more rational. To this end, a sine wave superposition model was established to simulate three-dimensional ground elevation changes, and an area array LiDAR was used to collect 8 × 8 data for the header height. The effects of mounds and stubble on the measurement results were analyzed, and a dynamic process simulation model for the solenoid valve core was developed to analyze the on/off delay characteristics of a three-position four-way electromagnetic directional valve. Moreover, a physical model of the hydraulic system was constructed based on the Simscape module in Simulink, and the Bang Bang switch predictive control system based on position threshold was introduced to achieve early switching of the electromagnetic directional valve circuit. In addition, an automatic control system for cutting platform height was designed based on an STM32 microcontroller. The control system was tested on the hydraulic automatic control test rig developed by Shanxi Agricultural University. The simulation and experimental results demonstrated that the control system and strategy were robust to output disturbances, effectively enhancing the intelligence and environmental adaptability of agricultural machinery operations.

Land surface response to groundwater drawdown and recovery in Taiyuan city, Northern China, analyzed with a long-term elevation change measurements from leveling and multi-sensor InSAR

In recent years, a comprehensive program of groundwater management was adopted in Taiyuan city, Northern China, with the aim to prevent the lowering of groundwater level and manage land subsidence due to excessive groundwater pumping in the past decades. Groundwater recovery has been observed in this city following the termination of groundwater pumping. While the link between land subsidence and groundwater pumping is well documented, how the land surface responds to the recovery of groundwater has not been studied in detail. In this study, we analyzed the leveling data from 1956 to 2000 to investigate changes in ground elevation in response to groundwater drawdown prior to the termination of groundwater pumping and combined them with InSAR (Interferometric Synthetic Aperture Radar) displacement data during 2003–2020 to evaluate the effect of groundwater recharge after the termination of groundwater pumping. A method was proposed to merge InSAR time series of displacement derived from multiple satellites (ENVISAT, COSMO-SkyMed, TerraSAR-X, and Sentinel-1) to achieve a consistent, long-term continuous deformation. We found that previous groundwater depression cones in Taiyuan (Xizhang, Wanbailin, Wujiabao, and Xiayuan) have turned into groundwater recovery and the corresponding subsidence centers have switched to land uplift. The subsidence center of Xizhang, north of Taiyuan city, experienced a total subsidence of 749 mm by Aug 2003; it then turned into uplift with an amount of rebound of 9.2 % of previous subsidence by the end of 2020. In central area of Taiyuan, the cumulated subsidence is 1127 mm in Wanbailin, 1817 mm in Xiayuan, and 3343 mm in Wujiabao. Beginning in Aug 2010, they all turned into land uplift, with a rebound of 7.9 %, 4.8 % and 3.6 % of the previous subsidence in each center, respectively. An analysis of the correlation between groundwater level and ground displacement suggests that the ground uplift is related to the poro-elastic rebound mechanism in the porous aquifer system, which is caused by the rise in pore pressure with groundwater recovery, and the amount of subsidence/uplift is controlled by the stratigraphic properties. The adverse impacts on the built environment due to the rising groundwater level were discussed. The findings improve our understanding of anthropogenic ground deformation in complex urban aquifers influenced by groundwater pumping and recharge and provides essential information that can contribute to future groundwater management and groundwater-related hazard mitigation over the Taiyuan city.

Seasonal migration patterns of Siberian Rubythroat (Calliope calliope) facing the Qinghai–Tibet Plateau

BackgroundSmall songbirds respond and adapt to various geographical barriers during their annual migration. Global flyways reveal the diverse migration strategies in response to different geographical barriers, among which are high-elevation plateaus. However, few studies have been focused on the largest and highest plateau in the world, the Qinghai–Tibet Plateau (QTP) which poses a significant barrier to migratory passerines. The present study explored the annual migration routes and strategies of a population of Siberian Rubythroats (Calliope calliope) that breed on the north-eastern edge of the QTP.MethodsOver the period from 2021 to 2023, we applied light-level geolocators (13 deployed, seven recollected), archival GPS tags (45 deployed, 17 recollected), and CAnMove multi-sensor loggers (with barometer, accelerometer, thermometer, and light sensor, 20 deployed, six recollected) to adult males from the breeding population of Siberian Rubythroat on the QTP. Here we describe the migratory routes and phenology extracted or inferred from the GPS and multi-sensor logger data, and used a combination of accelerometric and barometric data to describe the elevational migration pattern, flight altitude, and flight duration. All light-level geolocators failed to collect suitable data.ResultsBoth GPS locations and positions derived from pressure-based inference revealed that during autumn, the migration route detoured from the bee-line between breeding and wintering grounds, leading to a gradual elevational decrease. The spring route was more direct, with more flights over mountainous areas in western China. This different migration route during spring probably reflects a strategy for faster migration, which corresponds with more frequent long nocturnal migration flights and shorter stopovers during spring migration than in autumn. The average flight altitude (1856 ± 781 m above sea level) was correlated with ground elevation but did not differ between the seasons.ConclusionsOur finding indicates strong, season-dependent impact of the Qinghai–Tibet Plateau on shaping passerine migration strategies. We hereby call for more attention to the unexplored central-China flyway to extend our knowledge on the environment-migration interaction among small passerines.

Spectroscopic Phenological Characterization of Mangrove Communities

Spaceborne spectroscopic imaging offers the potential to improve our understanding of biodiversity and ecosystem services, particularly for challenging and rich environments like mangroves. Understanding the signals present in large volumes of high-dimensional spectroscopic observations of vegetation communities requires the characterization of seasonal phenology and response to environmental conditions. This analysis leverages both spectroscopic and phenological information to characterize vegetation communities in the Sundarban riverine mangrove forest of the Ganges–Brahmaputra delta. Parallel analyses of surface reflectance spectra from NASA’s EMIT imaging spectrometer and MODIS vegetation abundance time series (2000–2022) reveal the spectroscopic and phenological diversity of the Sundarban mangrove communities. A comparison of spectral and temporal feature spaces rendered with low-order principal components and 3D embeddings from Uniform Manifold Approximation and Projection (UMAP) reveals similar structures with multiple spectral and temporal endmembers and multiple internal amplitude continua for both EMIT reflectance and MODIS Enhanced Vegetation Index (EVI) phenology. The spectral and temporal feature spaces of the Sundarban represent independent observations sharing a common structure that is driven by the physical processes controlling tree canopy spectral properties and their temporal evolution. Spectral and phenological endmembers reside at the peripheries of the mangrove forest with multiple outward gradients in amplitude of reflectance and phenology within the forest. Longitudinal gradients of both phenology and reflectance amplitude coincide with LiDAR-derived gradients in tree canopy height and sub-canopy ground elevation, suggesting the influence of surface hydrology and sediment deposition. RGB composite maps of both linear (PC) and nonlinear (UMAP) 3D feature spaces reveal a strong contrast between the phenological and spectroscopic diversity of the eastern Sundarban and the less diverse western Sundarban.

Precise Motion Compensation of Multi-Rotor UAV-Borne SAR Based on Improved PTA

In recent years, with the miniaturization of high-precision position and orientation systems (POS), precise motion errors during SAR data collection can be calculated based on high-precision POS. However, compensating for these errors remains a significant challenge for multi-rotor UAV-borne SAR systems. Compared with large aircrafts, multi-rotor UAVs are lighter, slower, have more complex flight trajectories, and have larger squint angles, which result in significant differences in motion errors between building targets and ground targets. If the motion compensation is based on ground elevation, the motion error of the ground target will be fully compensated, but the building target will still have a large residual error; as a result, although the ground targets can be well-focused, the building targets may be severely defocused. Therefore, it is necessary to further compensate for the residual motion error of building targets based on the actual elevation on the SAR image. However, uncompensated errors will affect the time–frequency relationship; furthermore, the ω-k algorithm will further change these errors, resulting in errors in SAR images becoming even more complex and difficult to compensate for. To solve this problem, this paper proposes a novel improved precise topography and aperture-dependent (PTA) method that can precisely compensate for motion errors in the UAV-borne SAR system. After motion compensation and imaging processing based on ground elevation, a secondary focus is applied to defocused buildings. The improved PTA fully considers the coupling of the residual error with the time–frequency relationship and ω-k algorithm, and the precise errors in the two-dimensional frequency domain are determined through numerical calculations without any approximations. Simulation and actual data processing verify the effectiveness of the method, and the experimental results show that the proposed method in this paper is better than the traditional method.

GeeNet: robust and fast point cloud completion for ground elevation estimation towards autonomous vehicles

GeeNet: robust and fast point cloud completion for ground elevation estimation towards autonomous vehicles

Prediction Model of Groundwater Sulphate Based on Combined Multi-source Spatio-temporal Data

The accurate prediction of spatial variation trends in groundwater SO42- is of great significance for improving groundwater quality and regional groundwater management level. The multi-source spatio-temporal data such as land cover data, soil parameter data, digital elevation data, and groundwater pH value in the plain area of the Yarkant River Basin in 2011, 2014, 2017, and 2020 were used as characteristic variables to analyze their correlation with groundwater SO42- concentration. To enhance the prediction accuracy, the Bayesian optimization algorithm (BOA) was used to optimize the random forest regression (RFR). Based on the BOA-RFR model, the importance of the characteristic variables was analyzed, the prediction accuracy of the model was evaluated, and the groundwater SO42- prediction map was generated. The results showed that pH value, ground elevation (GE), and percentage of bare land (BAR) in the contribution area were important parameters influencing groundwater hydrochemical composition, which were significantly negatively correlated with groundwater SO42- concentration, and the importance of impact factors for predicting groundwater SO42- concentration exceeded 25 %. The geostatistical interpolation method was used as an auxiliary tool for the predictive modeling of spatial distribution. After adding auxiliary samples, the R2 of groundwater SO42- concentration prediction of the BOA-RFR model was greater than 0.96, and the maximum values of RMSE and MAE were reduced by 4.7 % and 23.8 %, respectively, compared with the minimum values of the model with fewer samples. The SO42- concentration prediction map showed that high SO42- groundwater was enriched in the northeast of the plain area of the Yarkand River Basin, an area that was expanding.

Open source robot localization for nonplanar environments

AbstractThe operational environments in which a mobile robot executes its missions often exhibit nonflat terrain characteristics, encompassing outdoor and indoor settings featuring ramps and slopes. In such scenarios, the conventional methodologies employed for localization encounter novel challenges and limitations. This study delineates a localization framework incorporating ground elevation and incline considerations, deviating from traditional two‐dimensional localization paradigms that may falter in such contexts. In our proposed approach, the map encompasses elevation and spatial occupancy information, employing Gridmaps and Octomaps. At the same time, the perception model is designed to accommodate the robot's inclined orientation and the potential presence of ground as an obstacle, besides usual structural and dynamic obstacles. We provide an implementation of our approach fully working with Nav2, ready to replace the baseline Adaptative Monte Carlo Localization (AMCL) approach when the robot is in nonplanar environments. Our methodology was rigorously tested in both simulated environments and through practical application on actual robots, including the Tiago and Summit XL models, across various settings ranging from indoor and outdoor to flat and uneven terrains. Demonstrating exceptional precision, our approach yielded error margins below 10 cm and 0.05 radians in indoor settings and less than 1.0 m in extensive outdoor routes. While our results exhibit a slight improvement over AMCL in indoor environments, the enhancement in performance is significantly more pronounced when compared to three‐dimensional simultaneous localization and mapping algorithms. This underscores the considerable robustness and efficiency of our approach, positioning it as an effective strategy for mobile robots tasked with navigating expansive and intricate indoor/outdoor environments.

Urban Building Height Extraction from Gaofen-7 Stereo Satellite Images Enhanced by Contour Matching

The traditional method for extracting the heights of urban buildings involves utilizing dense matching algorithms on stereo images to generate a digital surface model (DSM). However, for urban buildings, the disparity discontinuity issue that troubles the dense matching algorithm makes the elevations of high-rise buildings and the surrounding areas inaccurate. The occlusion caused by trees in greenbelts makes it difficult to accurately extract the ground elevation around the building. To tackle these problems, a method for building height extraction from Gaofen-7 (GF-7) stereo images enhanced by contour matching is presented. Firstly, a contour matching algorithm was proposed to extract accurate building roof elevation from GF-7 images. Secondly, a ground filtering algorithm was employed on the DSM to generate a digital elevation model (DEM), and ground elevation can be extracted from this DEM. The difference between the rooftop elevation and the ground elevation represents the building height. The presented method was verified in Yingde, Guangzhou, Guangdong Province, and Xi’an, Shaanxi Province. The experimental results demonstrate that our proposed method outperforms existing methods in building height extraction concerning accuracy.