Dongping Ming
YOU?
Author Swipe
View article: A Multi-Level Segmentation Method for Mountainous Camellia oleifera Plantation with High Canopy Closure Using UAV Imagery
A Multi-Level Segmentation Method for Mountainous Camellia oleifera Plantation with High Canopy Closure Using UAV Imagery Open
Camellia oleifera is an important economic tree species in China. Accurate estimation of canopy structural parameters of C. oleifera is essential for yield prediction and plantation management. However, this remains challenging in mountain…
View article: Hybrid-SegUFormer: A Hybrid Multi-Scale Network with Self-Distillation for Robust Landslide InSAR Deformation Detection
Hybrid-SegUFormer: A Hybrid Multi-Scale Network with Self-Distillation for Robust Landslide InSAR Deformation Detection Open
Landslide deformation monitoring via InSAR is crucial for assessing the risk of hazards. Quick and accurate detection of active deformation zones is crucial for early warning and mitigation planning. While the application of deep learning …
View article: Apple Orchard Mapping in China Based on an Automatic Sample Generation Algorithm and Random Forest
Apple Orchard Mapping in China Based on an Automatic Sample Generation Algorithm and Random Forest Open
Accurate apple orchard mapping plays a vital role in managing agricultural resources. However, national-scale apple orchard mapping faces challenges such as the “same spectrum with different objects” phenomenon between apple trees and othe…
View article: A Fast and Efficient Denoising and Surface Reflectance Retrieval Method for ZY1-02D Hyperspectral Data
A Fast and Efficient Denoising and Surface Reflectance Retrieval Method for ZY1-02D Hyperspectral Data Open
Hyperspectral remote sensing is crucial due to its continuous spectral information, especially in the quantitative remote sensing (QRS) field. Surface reflectance (SR), a fundamental product in QRS, can play a pivotal role in application a…
View article: Change detection of slow-moving landslide with multi-source SBAS-InSAR and Light-U2Net
Change detection of slow-moving landslide with multi-source SBAS-InSAR and Light-U2Net Open
Interferometric Synthetic Aperture Radar (InSAR) techniques are commonly used approach for identifying Slow-moving Landslide (SML). However, most SML boundary identification with deep learning are based on single-source InSAR data, which c…
View article: A DeBERTa-Based Semantic Conversion Model for Spatiotemporal Questions in Natural Language
A DeBERTa-Based Semantic Conversion Model for Spatiotemporal Questions in Natural Language Open
To address current issues in natural language spatiotemporal queries, including insufficient question semantic understanding, incomplete semantic information extraction, and inaccurate intent recognition, this paper proposes NL2Cypher, a D…
View article: Deep Merge: Deep-Learning-Based Region Merging for Remote Sensing Image Segmentation
Deep Merge: Deep-Learning-Based Region Merging for Remote Sensing Image Segmentation Open
Image segmentation represents a fundamental step in analyzing very high-spatial-resolution (VHR) remote sensing imagery. Its objective is to partition an image into segments that best match with geo-objects. However, the diverse appearance…
View article: SDG 11.3 Assessment of African Industrial Cities by Integrating Remote Sensing and Spatial Cooperative Simulation: With MFEZ in Zambia as a Case Study
SDG 11.3 Assessment of African Industrial Cities by Integrating Remote Sensing and Spatial Cooperative Simulation: With MFEZ in Zambia as a Case Study Open
Urban areas in sub-Saharan Africa are facing significant developmental challenges due to rapid population growth and urban expansion, this study aims to predict urban growth and assess the SDG 11.3.1 indicator in the Chambishi multi-facili…
View article: Landslide Hazard Analysis Combining BGA-Net-Based Landslide Susceptibility Perception and Small Baseline Subset Interferometric Synthetic Aperture Radar in the Baige Section in the Upper Reaches of Jinsha River
Landslide Hazard Analysis Combining BGA-Net-Based Landslide Susceptibility Perception and Small Baseline Subset Interferometric Synthetic Aperture Radar in the Baige Section in the Upper Reaches of Jinsha River Open
The geological and topographic conditions in the upper reaches of the Jinsha River are intricate, with frequent occurrences of landslides. Landslide Susceptibility Prediction (LSP) in this area is a crucial aspect of geological disaster ri…
View article: Cascaded framework for earthquake building damage detection combining spatial and frequency domain feature integration
Cascaded framework for earthquake building damage detection combining spatial and frequency domain feature integration Open
Building collapse is a major cause of casualties after an earthquake, so accurately extracting building damage information is critical for post-earthquake assessment and rescue. Currently, most deep learning methods focus on the end-to-end…
View article: Data-Driven Deformation Prediction of Accumulation Landslides in the Middle Qinling-Bashan Mountains Area
Data-Driven Deformation Prediction of Accumulation Landslides in the Middle Qinling-Bashan Mountains Area Open
Accurately predicting landslide deformation based on monitoring data is key to successful early warning of landslide disasters. Landslide displacement–time curves offer an intuitive reflection of the landslide motion process and deformatio…
View article: HODet: A New Detector for Arbitrary-Oriented Rectangular Object in Optical Remote Sensing Imagery
HODet: A New Detector for Arbitrary-Oriented Rectangular Object in Optical Remote Sensing Imagery Open
Object detection from remote sensing images is a key technology for Earth observation applications, which has important scientific research value. Ground objects in remote sensing images appear at arbitrary angles. However, object detectio…
View article: DeepMerge: Deep-Learning-Based Region-Merging for Image Segmentation
DeepMerge: Deep-Learning-Based Region-Merging for Image Segmentation Open
Image segmentation aims to partition an image according to the objects in the scene and is a fundamental step in analysing very high spatial-resolution (VHR) remote sensing imagery. Current methods struggle to effectively consider land obj…
View article: Research on Fine Estimation of People Trapped after Earthquake on Single Building Level Based on Multi-Source Data
Research on Fine Estimation of People Trapped after Earthquake on Single Building Level Based on Multi-Source Data Open
Risk assessments of people who are trapped are an important basis for scientific and effective emergency rescue after an earthquake. Currently, most models are based on the kilometer grid scale or community scale that gauge the population …
View article: Tree Species Classification Based on ASDER and MALSTM-FCN
Tree Species Classification Based on ASDER and MALSTM-FCN Open
Tree species classification based on multi-source remote sensing data is essential for ecological evaluation, environmental monitoring, and forest management. The optimization of classification features and the performance of classificatio…
View article: A Stepwise Framework for Fine-Scale Mining Area Types Recognition in Large-Scale Scenes by GF-5 and GF-2 Images
A Stepwise Framework for Fine-Scale Mining Area Types Recognition in Large-Scale Scenes by GF-5 and GF-2 Images Open
Quickly obtaining fine-scale mining area types information in large-scale scenes is significant for dynamically detecting mineral resources. Currently, mining area types recognition methods encounter challenges such as low recognition accu…
View article: Building Extraction From High Spatial Resolution Remote Sensing Images of Complex Scenes by Combining Region-Line Feature Fusion and OCNN
Building Extraction From High Spatial Resolution Remote Sensing Images of Complex Scenes by Combining Region-Line Feature Fusion and OCNN Open
Building extraction from remote sensing imagery has been a research hotspot for some time with the advancement of AI in remote sensing. However, the edges of buildings extracted using existing techniques are commonly broken and inaccurate …
View article: Susceptibility-Guided Landslide Detection Using Fully Convolutional Neural Network
Susceptibility-Guided Landslide Detection Using Fully Convolutional Neural Network Open
Automatic landslide detection based on very high spatial resolution remote sensing images is crucial for disaster prevention and mitigation applications. With the rapid development of deep-learning techniques, state-of-the-art semantic seg…
View article: Feature Engineering of Geohazard Susceptibility Analysis Based on the Random Forest Algorithm: Taking Tianshui City, Gansu Province, as an Example
Feature Engineering of Geohazard Susceptibility Analysis Based on the Random Forest Algorithm: Taking Tianshui City, Gansu Province, as an Example Open
In this paper, Feature Engineering (FE) was applied to Landslide Susceptibility Mapping (LSM), while the most suitable conditioning feature dataset and analysis method were tested and analyzed. Tianshui city was taken as the study area, th…
View article: Landslide hazard analysis based on SBAS-InSAR and MCE-CNN model: a case study of Kongtong, Pingliang
Landslide hazard analysis based on SBAS-InSAR and MCE-CNN model: a case study of Kongtong, Pingliang Open
A new multi-channel expanded convolutional neural network (MCE-CNN) model was proposed for landslide hazard analysis based on 'dynamic and static' + 'internal and external' factors. Firstly, 102 landslide samples were collected in Kongtong…
View article: Operational earthquake-induced building damage assessment using CNN-based direct remote sensing change detection on superpixel level
Operational earthquake-induced building damage assessment using CNN-based direct remote sensing change detection on superpixel level Open
Accurate and quick building damage assessment is an indispensable step after a destructive earthquake. Acquiring building damage information of the seismic area in a remotely sensed way enables a timely emergency response. Existing remote …
View article: BTS: a binary tree sampling strategy for object identification based on deep learning
BTS: a binary tree sampling strategy for object identification based on deep learning Open
Object-based convolutional neural networks (OCNNs) have achieved great performance in the field of land-cover and land-use classification. Studies have suggested that the generation of object convolutional positions (OCPs) largely determin…
View article: Aircraft Detection in High Spatial Resolution Remote Sensing Images Combining Multi-Angle Features Driven and Majority Voting CNN
Aircraft Detection in High Spatial Resolution Remote Sensing Images Combining Multi-Angle Features Driven and Majority Voting CNN Open
Aircraft is a means of transportation and weaponry, which is crucial for civil and military fields to detect from remote sensing images. However, detecting aircraft effectively is still a problem due to the diversity of the pose, size, and…
View article: Identification of Multiscale Spatial Structure of Lunar Impact Crater: A Semivariogram Approach
Identification of Multiscale Spatial Structure of Lunar Impact Crater: A Semivariogram Approach Open
Identifying the spatial structure of lunar impact craters is necessary to increase our understanding of past geologic processes on the Moon. However, detecting multiscale spatial structures of craters in images in appropriate resolutions u…
View article: Landslide Susceptibility Mapping Using Feature Fusion-Based CPCNN-ML in Lantau Island, Hong Kong
Landslide Susceptibility Mapping Using Feature Fusion-Based CPCNN-ML in Lantau Island, Hong Kong Open
Landslide susceptibility mapping (LSM) is an effective way to predict spatial probability of landslide occurrence. Existing convolutional neural network (CNN)-based methods apply self-built CNN with simple structure, which failed to reach …
View article: GaoFen-1 Remote Sensing Image Forest Extraction Using Object-based CNN
GaoFen-1 Remote Sensing Image Forest Extraction Using Object-based CNN Open
As an important natural resource, forest plays a vital role in regulating regional climatic conditions and maintaining the balance of the Earth's ecosystem. At the same time, the major changes in China's natural resource management system …