Guiying Li

3.3k total citations · 1 hit paper
57 papers, 2.6k citations indexed

About

Guiying Li is a scholar working on Ecology, Environmental Engineering and Global and Planetary Change. According to data from OpenAlex, Guiying Li has authored 57 papers receiving a total of 2.6k indexed citations (citations by other indexed papers that have themselves been cited), including 38 papers in Ecology, 34 papers in Environmental Engineering and 29 papers in Global and Planetary Change. Recurrent topics in Guiying Li's work include Remote Sensing in Agriculture (38 papers), Remote Sensing and LiDAR Applications (24 papers) and Land Use and Ecosystem Services (23 papers). Guiying Li is often cited by papers focused on Remote Sensing in Agriculture (38 papers), Remote Sensing and LiDAR Applications (24 papers) and Land Use and Ecosystem Services (23 papers). Guiying Li collaborates with scholars based in China, United States and Brazil. Guiying Li's co-authors include Dengsheng Lu, Emilio F. Morán, Guangxing Wang, Lijuan Liu, Qi Chen, Qihao Weng, Mateus Batistella, Luciano Vieira Dutra, Scott Hetrick and Wenhui Kuang and has published in prestigious journals such as Frontiers in Plant Science, International Journal of Remote Sensing and Remote Sensing.

In The Last Decade

Guiying Li

53 papers receiving 2.5k citations

Hit Papers

A survey of remote sensing-based aboveground biomass esti... 2014 2026 2018 2022 2014 200 400 600

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Guiying Li China 26 1.5k 1.5k 1.2k 598 407 57 2.6k
Aniruddha Ghosh United States 20 1.2k 0.8× 1.5k 1.0× 800 0.7× 288 0.5× 334 0.8× 39 2.6k
Giorgos Mallinis Greece 29 972 0.7× 1.3k 0.9× 1.6k 1.3× 351 0.6× 323 0.8× 85 2.7k
Saurabh Channan United States 17 996 0.7× 1.3k 0.9× 1.7k 1.4× 224 0.4× 257 0.6× 29 2.5k
Markus Immitzer Austria 24 1.6k 1.1× 2.6k 1.8× 1.1k 0.9× 344 0.6× 531 1.3× 62 3.3k
Bangqian Chen China 28 1.0k 0.7× 1.9k 1.3× 1.6k 1.3× 322 0.5× 159 0.4× 76 3.1k
L. Monika Moskal United States 29 2.4k 1.6× 2.0k 1.4× 1.2k 1.0× 1.1k 1.9× 190 0.5× 75 3.4k
Inge Jonckheere Belgium 19 1.3k 0.9× 2.5k 1.7× 1.9k 1.5× 950 1.6× 728 1.8× 31 4.0k
Mark Chopping United States 21 940 0.6× 1.3k 0.9× 1.1k 0.9× 279 0.5× 147 0.4× 51 2.0k
Steven A. Sader United States 27 1.1k 0.8× 2.1k 1.4× 1.8k 1.5× 496 0.8× 395 1.0× 56 3.3k
Xihan Mu China 28 1.6k 1.1× 2.0k 1.4× 1.3k 1.1× 267 0.4× 155 0.4× 111 3.0k

Countries citing papers authored by Guiying Li

Since Specialization
Citations

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

Fields of papers citing papers by Guiying Li

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Guiying Li. 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 Guiying Li. The network helps show where Guiying Li may publish in the future.

Co-authorship network of co-authors of Guiying Li

This figure shows the co-authorship network connecting the top 25 collaborators of Guiying Li. A scholar is included among the top collaborators of Guiying Li 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 Guiying Li. Guiying Li 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
2.
Li, Guiying, et al.. (2025). Spatiotemporal patterns of annual clear-cutting distribution in tropical and subtropical regions of China with time series Landsat and CCDC. Geo-spatial Information Science. 28(6). 2763–2780. 1 indexed citations
3.
Li, Guiying, et al.. (2025). Modeling pine forest growing stock volume in subtropical regions of China using airborne Lidar data. GIScience & Remote Sensing. 62(1). 1 indexed citations
4.
Wu, Qingquan, et al.. (2025). Remote Sensing Technology for Observing Tree Mortality and Its Influences on Carbon–Water Dynamics. Forests. 16(2). 194–194. 1 indexed citations
5.
Zhang, Mingdong, Xiaolei Wu, Guiying Li, & Changwei Hu. (2025). Hierarchical manganese-containing TS-1 zeolite for the direct oxidation of cyclohexane to adipic acid with molecular oxygen: Synergy between matrix Ti and Mn species. CHINESE JOURNAL OF CATALYSIS (CHINESE VERSION). 79. 127–147.
6.
Lu, Dengsheng, et al.. (2025). 基于激光雷达数据的森林生物量估测研究. National Remote Sensing Bulletin. 29(6). 2035–2064.
7.
Li, Dengqiu, et al.. (2024). Vegetation classification in a subtropical region with Sentinel-2 time series data and deep learning. Geo-spatial Information Science. 28(1). 145–163. 6 indexed citations
8.
Li, Guiying, et al.. (2024). Developing a New Method to Rapidly Map Eucalyptus Distribution in Subtropical Regions Using Sentinel-2 Imagery. Forests. 15(10). 1799–1799. 2 indexed citations
9.
Li, Yunhe, Guiying Li, Si‐Rong Wang, & Dengsheng Lu. (2024). Retrieval of Chinese fir tree parameters under different understory conditions with the integration of handheld and airborne Lidar data. Geo-spatial Information Science. 28(5). 2183–2204. 1 indexed citations
11.
Li, Guiying, et al.. (2022). Modeling forest growing stock volume in a north subtropical region using the hierarchical Bayesian approach based on multi-source data. National Remote Sensing Bulletin. 26(3). 468–479. 3 indexed citations
12.
Li, Guiying, et al.. (2020). Modeling Forest Aboveground Carbon Density in the Brazilian Amazon with Integration of MODIS and Airborne LiDAR Data. Remote Sensing. 12(20). 3330–3330. 8 indexed citations
13.
Lu, Dengsheng, Longwei Li, Guiying Li, et al.. (2018). Examining Spatial Patterns of Urban Distribution and Impacts of Physical Conditions on Urbanization in Coastal and Inland Metropoles. Remote Sensing. 10(7). 1101–1101. 25 indexed citations
14.
Lu, Dengsheng, et al.. (2018). Examining impacts of the Belo Monte hydroelectric dam construction on land-cover changes using multitemporal Landsat imagery. Applied Geography. 97. 35–47. 49 indexed citations
15.
Li, Guiying, et al.. (2018). Examining deforestation and agropasture dynamics along the Brazilian TransAmazon Highway using multitemporal Landsat imagery. GIScience & Remote Sensing. 56(2). 161–183. 17 indexed citations
16.
Lu, Dengsheng, Guiying Li, Wenhui Kuang, & Emilio F. Morán. (2013). Methods to extract impervious surface areas from satellite images. International Journal of Digital Earth. 7(2). 93–112. 123 indexed citations
17.
Li, Guiying, et al.. (2013). Assessment and screening of non-food biodiesel plant resources in Shaanxi and Gansu provinces based on grey relation analysis.. Zhongguo Nongye Daxue xuebao. 18(6). 6–17. 1 indexed citations
18.
Lu, Dengsheng, Scott Hetrick, Emilio F. Morán, & Guiying Li. (2012). Application of Time Series Landsat Images to Examining Land-use/Land-cover Dynamic Change. Photogrammetric Engineering & Remote Sensing. 78(7). 747–755. 32 indexed citations
19.
Lu, Dengsheng, Mateus Batistella, Guiying Li, et al.. (2012). Land use/cover classification in the Brazilian Amazon using satellite images. Pesquisa Agropecuária Brasileira. 47(9). 1185–1208. 42 indexed citations
20.
Lu, Dengsheng, Qihao Weng, & Guiying Li. (2006). Residential population estimation using a remote sensing derived impervious surface approach. International Journal of Remote Sensing. 27(16). 3553–3570. 103 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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