Dr. Linhui Wang | Remote Sensing | Research Excellence Award

Dr. Linhui Wang | Remote Sensing | Research Excellence Award

University of Chinese Academy of Sciences | China

Dr. Linhui Wang is a doctoral researcher specializing in satellite image registration, on-board processing, and remote sensing algorithms, with strong expertise in lightweight feature databases, precise geometric rectification, and near real-time registration for spaceborne systems. His research integrates digital image processing, SAR imaging, machine learning, and GPU-accelerated computing, including CUDA-based implementations, to improve accuracy and efficiency under strict storage and computational constraints. He has published in leading journals and conferences in geoscience and remote sensing. According to Scopus and Google Scholar records, his work has received 16 citations across 15 documents, with an h-index of 3, reflecting growing academic impact in satellite imaging and signal processing research.

Citation Metrics (Scopus)

20

16

12

8

4

0

Citations
16

Documents
4

h-index
3

          🟦 Citations   🟥 Documents   🟩 h-index

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Mr. Thyago Lima | Remote Sensing | Research Excellence Award

Mr. Thyago Lima | Remote Sensing | Research Excellence Award

São Paulo State University | Brazil

Mr. Thyago Anthony Soares Lima is a geographer and disaster-risk analyst specializing in remote sensing, InSAR, and multi-hazard urban risk assessment. His research focuses on characterizing ground deformation, identifying subsidence typologies, and integrating geological, geomorphological, and geospatial data to strengthen urban resilience. He develops workflows that link land subsidence with flooding, erosion, and slope-instability risks, enabling evidence-based planning for hazard-prone regions. His work bridges geoscience and public decision-making by producing operational subsidence and hazard maps used by civil-defense agencies, planners, and environmental managers. His contributions advance sustainable territorial management and innovative methodologies in geoinformatics and environmental hazard analysis.

Citation Metrics (Google Scholar)

100

75

50

25

10

0

 

Citations
8

Documents
20

h-index
2

Citations
Documents
h-index


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