A Large-Scale Building Unsupervised Extraction Method Leveraging Airborne LiDAR Point Clouds and Remote Sensing Images Based on a Dual P-Snake Model.

Automatic large-scale building extraction from the LiDAR point clouds and remote sensing images is a growing focus in the fields of the sensor applications and remote sensing. However, this building extraction task remains highly challenging due to the complexity of building sizes, shapes, and surrounding environments. In addition, the discreteness, sparsity, and irregular distribution of point clouds, lighting, and shadows, as well as occlusions of the images, also seriously affect the accuracy of building extraction.

Data Quality Assessment of Gravity Recovery and Climate Experiment Follow-On Accelerometer.

Accelerometers are mainly used to measure the non-conservative forces at the center of mass of gravity satellites and are the core payloads of gravity satellites. All kinds of disturbances in the satellite platform and the environment will affect the quality of the accelerometer data. This paper focuses on the quality assessment of accelerometer data from the GRACE-FO satellites.

A new representation method of the relative position between objects in the image based on the histogram of position sensing forces.

Let the computer apprehend and describe the representation of the relative position between objects of the image by the way of the common intuition of the human is an important task of the computer vision and pattern recognition. To complete this task, the position sensing parameter and histogram of position sensing forces are proposed in this paper. The position sensing parameter can represent the spatial relative position of the point with regard to the reference object, and the point is from the argument object.

The GWR model-based regional downscaling of GRACE/GRACE-FO derived groundwater storage to investigate local-scale variations in the North China Plain.

Groundwater storage and depletion fluctuations in response to groundwater availability for irrigation require understanding on a local scale to ensure a reliable groundwater supply. However, the coarser spatial resolution and intermittent data gaps to estimate the regional groundwater storage anomalies (GWSA) prevent the Gravity Recovery and Climate Experiment (GRACE) and GRACE Follow-On (GARCE-FO) mission from being applied at the local scale. To enhance the resolution of GWSA measurements using machine learning approaches, numerous recent efforts have been made.

Enhancing Mechanical Properties of 3D Printing Metallic Lattice Structure Inspired by Bambusa Emeiensis.

Metallic additive manufacturing process parameters, such as inclination angle and minimum radius, impose constraints on the printable lattice cell configurations in complex components. As a result, their mechanical properties are usually lower than their design values. Meanwhile, due to unavoidable process constraints (e.

Security risk assessment and visualization study of key nodes of sea lanes: case studies on the Tsugaru Strait and the Makassar Strait.

Key nodes of sea lanes are important hubs for global trade and cargo transportation and play important roles in ensuring the safety of maritime transportation and maintaining the stability of the global supply chain. The safety guarantee of key nodes of sea lanes is facing more risks and higher requirements currently because the global shipping industry is gradually recovering. This paper focuses on key nodes of sea lanes, conducting regional security risk assessment and risk spatial scale visualization.

Impact of the COVID-19 pandemic on urban human mobility - A multiscale geospatial network analysis using New York bike-sharing data.

The COVID-19 pandemic breaking out at the end of 2019 has seriously impacted urban human mobility and poses great challenges for traffic management and urban planning. An understanding of this influence from multiple perspectives is urgently needed. In this study, we propose a multiscale geospatial network framework for the analysis of bike-sharing data, aiming to provide a new perspective for the exploration of the pandemic impact on urban human mobility.

Featured services and performance of BDS-3.

BeiDou Global Navigation Satellite System (BDS-3) not only performs the normal positioning, navigation and timing (PNT) functions, but also provides featured services, which are divided into geostationary orbit (GEO) and medium earth orbit (MEO) satellite-based featured services in this paper. The former refers to regional services consisting of the regional short message communication service (RSMCS), the radio determination satellite service (RDSS), the BDS satellite-based augmented service (BDSBAS) and the satellite-based precise point positioning service via B2b signal (B2b-PPP). The latter refers to global services consisting of the global short message communication service (GSMCS) and the MEO satellite-based search and rescue (MEOSAR) service.

Helmert Variance Component Estimation for Multi-GNSS Relative Positioning.

The Multi-constellation Global Navigation Satellite System (Multi-GNSS) has become the standard implementation of high accuracy positioning and navigation applications. It is well known that the noise of code and phase measurements depend on GNSS constellation. Then, Helmert variance component estimation (HVCE) is usually used to adjust the contributions of different GNSS constellations by determining their individual variances of unit weight.

Performance Analysis of Positioning Solution Using Low-Cost Single-Frequency U-Blox Receiver Based on Baseline Length Constraint.

With the rapid development of the satellite navigation industry, low-cost and high-precision Global Navigation Satellite System (GNSS) positioning has recently become a research hotspot. The traditional application of GNSS may be further extended thanks to the low cost of measuring instruments, but effective methods are also desperately needed due to the low quality of the data obtained using these instruments. Thus, in this paper, we propose the analysis and evaluation of the ambiguity fixed-rate and positioning accuracy of single-frequency Global Positioning System (GPS) and BeiDou Navigation Satellite System (BDS) data, collected from a low-cost u-blox receiver, based on the Constrained LAMBDA (CLAMBDA) method with a baseline length constraint, instead of the classical LAMBDA method.

GNSS Precise Kinematic Positioning for Multiple Kinematic Stations Based on A Priori Distance Constraints.

When applying the Global Navigation Satellite System (GNSS) for precise kinematic positioning in airborne and shipborne gravimetry, multiple GNSS receiving equipment is often fixed mounted on the kinematic platform carrying the gravimetry instrumentation. Thus, the distances among these GNSS antennas are known and invariant. This information can be used to improve the accuracy and reliability of the state estimates.

An Imaging Sensor-Aided Vision Navigation Approach that Uses a Geo-Referenced Image Database.

In determining position and attitude, vision navigation via real-time image processing of data collected from imaging sensors is advanced without a high-performance global positioning system (GPS) and an inertial measurement unit (IMU). Vision navigation is widely used in indoor navigation, far space navigation, and multiple sensor-integrated mobile mapping. This paper proposes a novel vision navigation approach aided by imaging sensors and that uses a high-accuracy geo-referenced image database (GRID) for high-precision navigation of multiple sensor platforms in environments with poor GPS.