Hsing‐Chung Chang

1.4k total citations
69 papers, 1.0k citations indexed

About

Hsing‐Chung Chang is a scholar working on Aerospace Engineering, Ecology and Environmental Engineering. According to data from OpenAlex, Hsing‐Chung Chang has authored 69 papers receiving a total of 1.0k indexed citations (citations by other indexed papers that have themselves been cited), including 28 papers in Aerospace Engineering, 21 papers in Ecology and 18 papers in Environmental Engineering. Recurrent topics in Hsing‐Chung Chang's work include Synthetic Aperture Radar (SAR) Applications and Techniques (28 papers), Remote Sensing in Agriculture (14 papers) and Geophysical Methods and Applications (14 papers). Hsing‐Chung Chang is often cited by papers focused on Synthetic Aperture Radar (SAR) Applications and Techniques (28 papers), Remote Sensing in Agriculture (14 papers) and Geophysical Methods and Applications (14 papers). Hsing‐Chung Chang collaborates with scholars based in Australia, Japan and China. Hsing‐Chung Chang's co-authors include Linlin Ge, Chris Rizos, Alex Hay‐Man Ng, Kui Zhang, Xiaojing Li, Makoto Omura, Yusen Dong, Yueguan Yan, Jonas Geldmann and Vanessa M. Adams and has published in prestigious journals such as SHILAP Revista de lepidopterología, Scientific Reports and Journal of Environmental Management.

In The Last Decade

Hsing‐Chung Chang

62 papers receiving 989 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Hsing‐Chung Chang Australia 18 490 266 201 199 178 69 1.0k
R. S. Chatterjee India 14 306 0.6× 237 0.9× 101 0.5× 331 1.7× 207 1.2× 64 850
Waldir Renato Paradellá Brazil 19 391 0.8× 216 0.8× 130 0.6× 255 1.3× 169 0.9× 80 897
Constantinos Loupasakis Greece 18 419 0.9× 145 0.5× 159 0.8× 205 1.0× 599 3.4× 67 1.1k
Fabiana Calò Italy 19 837 1.7× 183 0.7× 99 0.5× 409 2.1× 570 3.2× 44 1.5k
Carolina Guardiola‐Albert Spain 16 258 0.5× 114 0.4× 35 0.2× 274 1.4× 164 0.9× 49 745
Hahn Chul Jung United States 24 370 0.8× 160 0.6× 63 0.3× 333 1.7× 109 0.6× 52 1.4k
Prinya Nutalaya Thailand 12 187 0.4× 116 0.4× 50 0.2× 168 0.8× 184 1.0× 18 891
Francesco Stecchi Italy 11 201 0.4× 77 0.3× 53 0.3× 601 3.0× 168 0.9× 20 1.1k
Chao Jia China 17 62 0.1× 71 0.3× 112 0.6× 219 1.1× 100 0.6× 95 937
Yi He China 23 179 0.4× 49 0.2× 61 0.3× 114 0.6× 528 3.0× 70 1.3k

Countries citing papers authored by Hsing‐Chung Chang

Since Specialization
Citations

This map shows the geographic impact of Hsing‐Chung 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 Hsing‐Chung Chang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Hsing‐Chung Chang more than expected).

Fields of papers citing papers by Hsing‐Chung Chang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Hsing‐Chung 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 Hsing‐Chung Chang. The network helps show where Hsing‐Chung Chang may publish in the future.

Co-authorship network of co-authors of Hsing‐Chung Chang

This figure shows the co-authorship network connecting the top 25 collaborators of Hsing‐Chung Chang. A scholar is included among the top collaborators of Hsing‐Chung Chang based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Hsing‐Chung Chang. Hsing‐Chung Chang is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Chang, Hsing‐Chung, et al.. (2025). Estimating Urban Linear Heat (UHIULI) Effect Along Road Typologies Using Spatial Analysis and GAM Approach. Atmosphere. 16(7). 864–864. 1 indexed citations
2.
Wang, Qiong, et al.. (2025). Optimizing UAV-SfM photogrammetry for efficient monitoring of gully erosion in high-relief terrains. Measurement. 256. 118154–118154.
3.
Ens, Emilie, Philip A. Clarke, Hsing‐Chung Chang, et al.. (2024). Not All Edible Nuts Are Eaten: Evidence for Continued Aboriginal Cultural Use and Dispersal of Bunya Pine (Araucaria bidwillii) in Southern But Not in Northern Queensland. Journal of Ethnobiology. 44(2). 129–140. 2 indexed citations
4.
Chang, Hsing‐Chung, et al.. (2024). UAV and panoramic photography: innovating soil and water conservation infrastructure monitoring and management. Canadian Journal of Civil Engineering. 52(4). 446–459.
5.
Ng, Alex Hay‐Man, Linlin Ge, Hsing‐Chung Chang, & Zheyuan Du. (2023). Geodetic Monitoring for Land Deformation. Remote Sensing. 15(1). 283–283. 1 indexed citations
6.
Gibson, Rebecca K., Anthea L. Mitchell, & Hsing‐Chung Chang. (2023). Image Texture Analysis Enhances Classification of Fire Extent and Severity Using Sentinel 1 and 2 Satellite Imagery. Remote Sensing. 15(14). 3512–3512. 9 indexed citations
7.
Chang, Hsing‐Chung, et al.. (2021). Identifying Invasive Weed Species in Alpine Vegetation Communities Based on Spectral Profiles. SHILAP Revista de lepidopterología. 1(2). 177–191. 2 indexed citations
8.
Maina, Joseph, et al.. (2021). Land use planning to support climate change adaptation in threatened plant communities. Journal of Environmental Management. 298. 113533–113533.
9.
Davies, Peter J., et al.. (2020). Planning for cooler cities: a plan quality evaluation for Urban Heat Island consideration. Journal of Environmental Policy & Planning. 22(4). 531–553. 16 indexed citations
10.
Geldmann, Jonas, et al.. (2020). Management resourcing and government transparency are key drivers of biodiversity outcomes in Southeast Asian protected areas. Biological Conservation. 253. 108875–108875. 35 indexed citations
11.
12.
Beggs, Paul J., et al.. (2019). Hot and bothered? Associations between temperature and crime in Australia. International Journal of Biometeorology. 63(6). 747–762. 45 indexed citations
13.
Chang, Hsing‐Chung, et al.. (2015). Remote Sensing Analysis Techniques and Sensor Requirements to Support the Mapping of Illegal Domestic Waste Disposal Sites in Queensland, Australia. Remote Sensing. 7(10). 13053–13069. 42 indexed citations
14.
Ng, Alex Hay‐Man, Linlin Ge, Kui Zhang, et al.. (2011). Deformation mapping in three dimensions for underground mining using InSAR – Southern highland coalfield in New South Wales, Australia. International Journal of Remote Sensing. 32(22). 7227–7256. 76 indexed citations
15.
Chang, Hsing‐Chung, Alex Hay‐Man Ng, Kui Zhang, et al.. (2009). Monitoring longwall mine subsidence and far-field displacements using multi-wavelength radar interferometry. UNSWorks (University of New South Wales, Sydney, Australia).
16.
Dong, Yusen, et al.. (2009). SAR Interferometry for Monitoring the Ground Displacement of the Wenchuan M_S 8.0 Earthquake. 28(6). 119–124. 1 indexed citations
17.
Ge, Linlin, Kui Zhang, Alex Hay‐Man Ng, et al.. (2008). Preliminary Results of Satellite Radar Differential Interferometry for the Co-seismic Deformation of the 12 May 2008 Ms8.0 Wenchuan Earthquake. Annals of GIS. 14(1). 12–19. 31 indexed citations
18.
Ge, Linlin, Hsing‐Chung Chang, Alex Hay‐Man Ng, & Chris Rizos. (2008). Radar interferometry for safe coal mining in China. 179–183. 1 indexed citations
19.
Dong, Yusen, Linlin Ge, Hsing‐Chung Chang, & Zhi Zhang. (2007). Mine Subsidence Monitoring by Differential InSAR. Wuhan Daxue xuebao. Xinxi kexue ban. 32(10). 888–891. 5 indexed citations
20.
Chang, Hsing‐Chung, et al.. (2005). Mine Subsidence Monitoring: A Comparison Among Envisat, ERS and JERS-1. 572(572). 953–958. 13 indexed citations

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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