A5070369693- Remote-Sensing Image Classification
- Remote Sensing and Land Use
- Advanced Computational Techniques and Applications
- Satellite Image Processing and Photogrammetry
- Synthetic Aperture Radar (SAR) Applications and Techniques
- Advanced Image and Video Retrieval Techniques
- Remote Sensing in Agriculture
- Metallic Glasses and Amorphous Alloys
- Geographic Information Systems Studies
- 3D Surveying and Cultural Heritage
- Impact of Light on Environment and Health
- Advanced Image Fusion Techniques
- Robotics and Sensor-Based Localization
- Advanced SAR Imaging Techniques
- Remote Sensing and LiDAR Applications
- Data Management and Algorithms
- Infrared Target Detection Methodologies
- Land Use and Ecosystem Services
- Video Surveillance and Tracking Methods
- Image Retrieval and Classification Techniques
- Magnetic Properties and Applications
- Advanced Vision and Imaging
- Automated Road and Building Extraction
- Urban Heat Island Mitigation
- Radar Systems and Signal Processing
State Key Laboratory of Information Engineering in Surveying Mapping and Remote Sensing
2016-2025
Wuhan University
2016-2025
Sichuan University
2022-2025
Weifang Chinese Medicine Hospital
2024
Beijing Jiaotong University
2012-2023
Lanzhou University
2018-2021
Indiana University School of Medicine
2021
Indiana University – Purdue University Indianapolis
2017-2021
Wuhan University of Science and Technology
2019
National University of Defense Technology
2012-2018
Monthly composites of night-time light acquired from the Meteorological Satellite Program's Operational Linescan System (DMSP/OLS) had been used to evaluate socio-economic dynamics and human rights during Syrian Civil War, which started in March 2011. However, DMSP/OLS monthly are not available subsequent February 2014, only for that period were Suomi National Polar-orbiting Partnership satellite's Visible Infrared Imaging Radiometer Suite (Suomi NPP/VIIRS). This article proposes an...
The past years have witnessed great progress on remote sensing (RS) image interpretation and its wide applications. With RS images becoming more accessible than ever before, there is an increasing demand for the automatic of these images. In this context, benchmark datasets serve as essential prerequisites developing testing intelligent algorithms. After reviewing existing in research community interpretation, article discusses problem how to efficiently prepare a suitable dataset...
Early warning systems (EWSs) to detect and monitor landslides are a great challenge. They important due the high cost of catastrophic challenging because difficulty in identifying diverse range landslide-triggering factors. While there has been very limited number successes, recent advances Earth observation (EO) from ground, aircraft, space have dramatically improved our ability active landslides. A growing body geotechnical theory suggests that prefailure behavior can offer clues location...
Deep learning techniques have been widely applied to hyperspectral image (HSI) classification and achieved great success. However, the deep neural network model has a large parameter space requires number of labeled data. methods for HSI usually follow patchwise framework. Recently, fast patch-free global (FPGA) architecture was proposed according spatial context information. FPGA difficulty in extracting most discriminative features when sample data are imbalanced. In this article,...
Coronavirus Disease 2019 (COVID-19) is a highly infectious virus that has created health crisis for people all over the world. Social distancing proved to be an effective non-pharmaceutical measure slow down spread of COVID-19. As unmanned aerial vehicle (UAV) flexible mobile platform, it promising option use UAV social distance monitoring. Therefore, we propose lightweight pedestrian detection network accurately detect pedestrians by human head in real-time and then calculate between on...
Automated extraction of roads from remotely sensed data come forth various usages ranging digital twins for smart cities, intelligent transportation, urban planning, autonomous driving, to emergency management. Many studies have focused on promoting the progress methods automated road aerial and satellite optical images, synthetic aperture radar (SAR) LiDAR point clouds. In past 10 years, no a more comprehensive survey this topic could be found in literature. This paper attempts provide that...
This study investigates whether night-time light images acquired from the Defense Meteorological Satellite Program's Operational Linescan System provide spatial and temporal insight with regard to humanitarian aspects of Syrian crisis. Evaluating ongoing crisis in Syria is challenging since reliable witness reports are hard gather a war zone. Therefore satellite images, as one few sources objective information, potentially great importance. We used 38 monthly composites covering period...
This letter presents a Bag-of-Visual Words (BOV) representation for object-based classification in land-use/cover mapping of high spatial resolution aerial photograph. The method is introduced to handle the special characteristics images, i.e., variability spectral and content. Specifically, patch detection description are used divide represent various subregions objects comprising multiple homogeneous components. Moreover, BOV constructed with statistics occurrence visual words, which...
The released VIIRS DNB nightly images, also known as daily nighttime provide rich information for time series analysis of global socioeconomic dynamics. Anisotropic characteristic is a possible factor that influences the radiance at night and its analysis. This study aims to investigate relationship between viewing angles Suomi NPP satellite in urban areas. First, twenty-nine points were selected globally explore angle variation views night. We found zenith (VZA) consistent (e.g. 0° 70°)...
Luojia 1-01 satellite, launched on 2 June 2018, provides a new data source of nighttime light at 130 m resolution and shows potential for mapping urban extent. In this paper, using VIIRS imagery, we compared several methods extracting areas, including Human Settlement Index (HSI), Simple Thresholding Segmentation (STS) SVM supervised classification. According to the accuracy assessment, HSI method LJ1-01 had best performance in extent extraction, which presented largest Kappa Coefficient...
The accurate location of clouds in images is prerequisite for many high-resolution satellite imagery applications such as atmospheric correction, land cover classifications, and target recognition. Thus, we propose a novel approach cloud detection using machine learning multi-feature fusion based on comparative analysis typical spectral, textural, other feature differences between backgrounds. To validate this method, tested it 102 Gao Fen-1(GF-1) Fen-2(GF-2) images. overall accuracy our...