Nanjing Surveying and Mapping Research Institute (China)

Multi-CD mini: a dataset for 3D urban semantic change detection with high spatial resolution imagery and nDSM

Urban semantic change detection (SCD) using remote sensing imagery is critical for monitoring urban dynamics, yet traditional two-dimensional (2D) methods suffer from occlusion, shadow interference, geometric distortion and an inability to quantify vertical variations. Integratin...

High-resolution land cover mapping from coarse labels via a noisy label learning-guided cross-scale framework

High-resolution remote sensing images (HRSIs) provide essential data support for land cover mapping, where deep learning has shown great promise. However, deep learning-based methods rely on abundant high-quality annotations, while low-resolution coarse labels are difficult to us...

Pathfinder-Based Analysis of Capacity Matching and Bottleneck Migration Along Evacuation Chains in Underground Commercial Complexes

Underground commercial complexes form a multi-stage evacuation chain linking horizontal transfer, vertical discharge, and exit allocation. Pathfinder simulations examined occupant-profile composition, stair width, corridor configuration, and pedestrian diversion through single-fa...

Modeling the carbon landscape of Northwest China: from climatic controls to vegetation-driven hotspots

Abstract Background As a sensitive response area to global climate change, the terrestrial ecosystem carbon sink function of the Northwest Arid Region of China is not only a core element in constructing the regional ecological security barrier but also a crucial strategic fulcrum...

Prediction of ground vibration induced by high-speed trains over elevated tracks based on machine learning

To address the issue of the complexity and high computational cost of ground vibration prediction models induced by high-speed trains crossing bridges, this study proposes a prediction method based on machine learning. Initially, this research derives a dataset of ground vibratio...

FeaturePointNet: A Semi-Supervised Geometric-Aware Graph Transformer for Dominant Point Extraction from Building Outlines

Extracting dominant points from complex building outlines is an important task in cartography and building footprint simplification. This study proposes a semi-supervised, geometric-aware graph-Transformer framework for automatic dominant point selection from vector point sequenc...

Spatiotemporal Prediction of Urban Land Subsidence Using ConvLSTM Enhanced with Spatial Attention Mechanism

Rapid urbanization has increasingly posed risks of inducing land subsidence in newly developed urban districts, posing growing threats to infrastructure safety. This study focuses on a selected rectangular area within the Shannan New District of Huainan City. Based on 94 Sentinel...

A method for intelligent recognition and multi-parameter inversion of photovoltaic panels based on UAV-LiDAR point clouds and DGRNet

Addressing the shortcomings of existing monitoring methods for mountainous photovoltaic power plants—including insufficient 3D data acquisition, low levels of automation, and point cloud recognition methods that are poorly adapted to mountainous scenarios, lack systematic compari...

A robust adaptive InSAR-GNSS fusion approach for three-dimensional surface deformation monitoring

Urban land subsidence threatens coastal infrastructure, especially in reclaimed and densely developed areas. Single-geometry InSAR (Interferometric Synthetic Aperture Radar) provides wide-area LOS (line-of-sight) deformation but is limited in resolving 3D (three-dimensional) grou...