Ling Chang

58 papers receiving 1.2k citations

Ling Chang's Hit Papers

Fast Statistically Homogeneous Pixel Selection for Covariance Matrix Estimation for Multitemporal InSAR 2014 · 211 citations
2110+4+8Years since publication50100150200

Peers

Ling Chang
Comparison fields: 5 of 52
  • Aerospace Engineering 874
  • Management, Monitoring, Policy and Law 84
  • Civil and Structural Engineering 101
  • Earth-Surface Processes 29
  • Media Technology 32
Replace Paolo Dabove with:
Paolo Dabove Italy
Alessio Rucci Italy
Yixian Tang China
D. Leva Italy
Stella I. Pytharouli United Kingdom
Hongdong Fan China
Donatella Dominici Italy
Yongsheng Li China
Maria Alicandro Italy
Giorgia Giardina United Kingdom
Ling Chang relative to Paolo Dabove Italy Paolo Dabove's profile →
Citations per field
00.5×2×2.7×
Paolo Dabove · 1×
Citations per year

Countries citing papers authored by Ling Chang

Since Specialization
Citations

This map shows the geographic impact of Ling Chang's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Ling Chang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ling Chang more than expected).

Fields of papers citing papers by Ling Chang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ling Chang. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Ling Chang. The network helps show where Ling Chang may publish in the future.

Co-authors

The 25 scholars most cited alongside Ling Chang, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Ling Chang Line = papers co-authored together Ling Chang links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 64 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Fast Statistically Homogeneous Pixel Selection for Covariance Matrix Estimation for Multitemporal InSAR
Hit paper breakdown →
2014211
2 2016112
3 201478
4 201578
5 202455
6 201852
7 201851
8 201949
9 201946
10 201541
11 202241
12 201432
13 201930
14 202429
15 201326
16 202026
17 202321
18 202119
19 200717
20 202117

About Ling Chang

Ling Chang is a scholar working on Aerospace Engineering, Management, Monitoring, Policy and Law, Media Technology, Atmospheric Science and Ocean Engineering, having authored 64 papers that have together received 1.2k indexed citations. Recurring topics across this work include Synthetic Aperture Radar (SAR) Applications and Techniques (54 papers), Landslides and related hazards (6 papers), Remote-Sensing Image Classification (4 papers), Advanced SAR Imaging Techniques (3 papers), Cryospheric studies and observations (2 papers), Image and Signal Denoising Methods (2 papers), Railway Engineering and Dynamics (2 papers) and Microbial bioremediation and biosurfactants (1 paper). The work is most often cited by research in Aerospace Engineering (874 citations), Management, Monitoring, Policy and Law (84 citations), Civil and Structural Engineering (101 citations), Earth-Surface Processes (29 citations) and Media Technology (32 citations). Ling Chang has collaborated with scholars based in Netherlands, China and United States. Frequent co-authors include Ramon F. Hanssen, Rolf P. B. J. Dollevoet, Mi Jiang, Xiaoli Ding, Rakesh Malhotra, Alfred Stein, Haoyu Wang, Freek J. Van Leijen, Jicang Wu and Valeri L. Markine. Their work appears in journals such as International Journal of Applied Earth Observation and Geoinformation, IEEE Transactions on Geoscience and Remote Sensing, Remote Sensing, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing and International Journal of Remote Sensing.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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