A5010850496- Synthetic Aperture Radar (SAR) Applications and Techniques
- Advanced SAR Imaging Techniques
- Soil Moisture and Remote Sensing
- Remote-Sensing Image Classification
- Geophysical Methods and Applications
- Satellite Image Processing and Photogrammetry
- Remote Sensing and Land Use
- Remote Sensing in Agriculture
- Cryospheric studies and observations
- Plant Water Relations and Carbon Dynamics
- Remote Sensing and LiDAR Applications
- Underwater Acoustics Research
- Landslides and related hazards
- Oil Spill Detection and Mitigation
- Geophysics and Gravity Measurements
- Smart Agriculture and AI
- Traffic Prediction and Management Techniques
- Arctic and Antarctic ice dynamics
- Climate variability and models
- Advanced Sensor and Control Systems
- Acoustic Wave Phenomena Research
- Machine Fault Diagnosis Techniques
- Ocean Waves and Remote Sensing
- Climate change and permafrost
- Vehicle emissions and performance
State Key Laboratory of Information Engineering in Surveying Mapping and Remote Sensing
2014-2025
Wuhan University
2015-2025
Nanjing University of Science and Technology
2002-2024
North China University of Science and Technology
2024
Hubei University of Technology
2024
Fudan University Shanghai Cancer Center
2024
Institute of Crop Sciences
2007-2023
Chinese Academy of Agricultural Sciences
2007-2023
Sanya University
2022-2023
Shanghai Maritime University
2018-2022
Abstract Accurate and high-resolution crop yield water productivity (CWP) datasets are required to understand predict spatiotemporal variation in agricultural production capacity; however, for maize wheat, two key staple dryland crops China, currently lacking. In this study, we generated evaluated a long-term data series, at 1-km resolution of CWP wheat across based on the multiple remotely sensed indicators random forest algorithm. Results showed that MOD16 products an accurate alternative...
This letter introduces an efficiency-manifold-learning-based supervised graph embedding (SGE) algorithm for polarimetric synthetic aperture radar (POLSAR) image classification. We use a linear dimensionality reduction technology named SGE to obtain low-dimensional subspace which can preserve the discriminative information from training samples. Various POLSAR decomposition features are stacked into input feature cube in original high-dimensional space. The is then implemented project learned...
The statistical region merging (SRM) algorithm exhibits efficient performance in solving significant noise corruption and does not depend on the data distribution. These advantages make SRM suitable for segmentation of synthetic aperture radar (SAR) images, which are characterized by speckle different distributions various types spatial resolutions. However, original is designed RGB gray images additive having a range [0, 255]. In this letter, generalized so that it can be applied to with...
Crops are vulnerable to strong winds, and the resulting lodging damage can have a great effect on yield. We characterize lodged wheat canola using polarimetric features derived from series of synthetic aperture radar data. Reflection asymmetry reduced differential extinction observed for wheat, but not canola, whose canopy structure has high degree randomness. The circular-pol correlation coefficient is explored as an indicator wheat. results demonstrate that capability PolSAR in monitoring...
Mapping soil organic carbon (SOC) plays a crucial role in agricultural productivity and water management. This study discusses the potential of active passive remote sensing for SOC estimation modeling areas, incorporating synthetic aperture radar (SAR) data (L-band quad-polarization C-band dual-polarization), multi-spectrum (MS) data, brightness temperature (TB) data. The performance five advanced machine learning regression (MLR) models was assessed, focusing on spatial interpolation...
Synthetic aperture radar (SAR) has often been used in earthquake damage assessment due to its extreme versatility and almost all-weather, day-and-night capability. In this article, we demonstrate the potential use only post-event, high-resolution airborne polarimetric SAR (PolSAR) imagery estimate level at block scale. Intact buildings with large orientation angles have a similar scattering mechanism collapsed buildings; they are all volume-scattering dominant reflection asymmetric, which...
A number of earthquakes have occurred in recent years, posing a challenge to Earth observation techniques. Owing the all-weather response capability, synthetic aperture radar (SAR) has become key tool for collapse interpretation. As requirement multitemporal data is usually not satisfied practice, interpretation using only postevent SAR imagery indispensable emergency rescue. Despite being found that texture relationship with building damage, few measures been adopted simple threshold...
In this letter, a comprehensive study of the mapping building collapse levels by use postearthquake synthetic aperture radar (SAR) images is addressed. Although previous studies have successfully quantified level postevent SAR, types features that are benefit to final accuracy still remain unknown. This letter takes Yushu earthquake as case contribute in two key areas. First, Chinese dual-band airborne SAR system (CASMSAR), which collected very-high-resolution X-band and P-band (0.50 1.1 m,...
The GaoFen-3 (GF-3) satellite is the first fully polarimetric synthetic aperture radar (SAR) designed for civil use in China. operates C-band and has 12 imaging modes various applications. Three SAR (PolSAR) are provided with a resolution of up to 8 m. Although calibration (PolCAL) system periodically undertaken, there still some residual distortion images. In order assess accuracy this improve image quality, we analyzed errors performed PolCAL experiment based on scattering properties...
The mean shift algorithm, which uses a moving window and utilizes both spatial range information contained in an image, is widely employed digital image filtering segmentation. However, because of the large dynamic synthetic aperture radar (SAR) images, applying conventional algorithm directly to SAR will not produce meaningful results. This paper proposes adaptive variable asymmetric bandwidth selection approach be used newly derived generalized algorithm. proposed very versatile can for...
Synthetic aperture radar (SAR) is a significant application in maritime monitoring, which can provide SAR data throughout the day and all weather conditions. With development of artificial intelligence big technologies, data-driven convolutional neural network (CNN) has become widely used ship detection. However, accuracy, feature visualization, analysis detection need to be improved further, when CNN method used. In this letter, we propose two-stage for land-contained sea area without...
In object-based image analysis of high-resolution images, the number features can reach hundreds, so it is necessary to perform feature reduction prior classification. this paper, a selection method based on combination genetic algorithm (GA) and tabu search (TS) presented. The proposed GATS aims reduce premature convergence GA by use TS. A prematurity index first defined judge situation during search. When does take place, an improved mutation operator executed, in which TS performed...
The vibration signals collected by acceleration sensors are interspersed with noise interference, which increases the difficulty of fault diagnosis for rolling bearings. For this reason, a bearing method based on complete ensemble empirical model decomposition adaptive (CEEMDAN) and improved convolutional neural network (CNN) is proposed. Firstly, original signal decomposed into series intrinsic modal function (IMF) components using CEEMDAN algorithm, filtered according to correlation...