Nga Nhu Le

809 total citations
10 papers, 612 citations indexed

About

Nga Nhu Le is a scholar working on Ecology, Environmental Engineering and Molecular Biology. According to data from OpenAlex, Nga Nhu Le has authored 10 papers receiving a total of 612 indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Ecology, 4 papers in Environmental Engineering and 3 papers in Molecular Biology. Recurrent topics in Nga Nhu Le's work include Coastal wetland ecosystem dynamics (9 papers), Remote Sensing and LiDAR Applications (4 papers) and Remote Sensing in Agriculture (3 papers). Nga Nhu Le is often cited by papers focused on Coastal wetland ecosystem dynamics (9 papers), Remote Sensing and LiDAR Applications (4 papers) and Remote Sensing in Agriculture (3 papers). Nga Nhu Le collaborates with scholars based in Japan, Vietnam and New Zealand. Nga Nhu Le's co-authors include Tien Dat Pham, Nam Thang Ha, Junshi Xia, Dieu Tien Bui, Naoto Yokoya, Wataru Takeuchi, Kunihiko Yoshino, Luong Viet Nguyen, Tien Duc Pham and Thị Hương Đào and has published in prestigious journals such as Earth-Science Reviews, Sensors and International Journal of Remote Sensing.

In The Last Decade

Nga Nhu Le

10 papers receiving 602 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Nga Nhu Le Japan 10 451 226 212 92 71 10 612
Yuanhui Zhu China 10 603 1.3× 285 1.3× 213 1.0× 34 0.4× 80 1.1× 32 786
Agung Budi Harto Indonesia 11 155 0.3× 89 0.4× 149 0.7× 56 0.6× 23 0.3× 62 440
Enrico C. Paringit Philippines 11 291 0.6× 171 0.8× 184 0.9× 46 0.5× 13 0.2× 44 492
Polyanna da Conceição Bispo Brazil 13 198 0.4× 190 0.8× 153 0.7× 21 0.2× 13 0.2× 54 493
Min Yan China 12 217 0.5× 102 0.5× 154 0.7× 19 0.2× 22 0.3× 38 457
Hannah M. Cooper United States 9 204 0.5× 127 0.6× 174 0.8× 61 0.7× 12 0.2× 12 406
Jianing Zhen China 13 323 0.7× 146 0.6× 147 0.7× 15 0.2× 34 0.5× 24 560
Hamdan Omar Malaysia 11 303 0.7× 287 1.3× 142 0.7× 15 0.2× 48 0.7× 51 495
Anthea L. Mitchell Australia 11 585 1.3× 428 1.9× 336 1.6× 11 0.1× 35 0.5× 27 830

Countries citing papers authored by Nga Nhu Le

Since Specialization
Citations

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

Fields of papers citing papers by Nga Nhu Le

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Nga Nhu Le. 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 Nga Nhu Le. The network helps show where Nga Nhu Le may publish in the future.

Co-authorship network of co-authors of Nga Nhu Le

This figure shows the co-authorship network connecting the top 25 collaborators of Nga Nhu Le. A scholar is included among the top collaborators of Nga Nhu Le 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 Nga Nhu Le. Nga Nhu Le is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

10 of 10 papers shown
1.
Pham, Tien Dat, Nam Thang Ha, Neil Saintilan, et al.. (2023). Advances in Earth observation and machine learning for quantifying blue carbon. Earth-Science Reviews. 243. 104501–104501. 34 indexed citations
2.
Pham, Tien Dat, et al.. (2022). Mapping Multi-Decadal Mangrove Extent in the Northern Coast of Vietnam Using Landsat Time-Series Data on Google Earth Engine Platform. Remote Sensing. 14(18). 4664–4664. 12 indexed citations
3.
Le, Nga Nhu, et al.. (2021). Learning from multimodal and multisensor earth observation dataset for improving estimates of mangrove soil organic carbon in Vietnam. International Journal of Remote Sensing. 42(18). 6866–6890. 18 indexed citations
4.
Pham, Tien Dat, Naoto Yokoya, Junshi Xia, et al.. (2020). Comparison of Machine Learning Methods for Estimating Mangrove Above-Ground Biomass Using Multiple Source Remote Sensing Data in the Red River Delta Biosphere Reserve, Vietnam. Remote Sensing. 12(8). 1334–1334. 114 indexed citations
6.
Pham, Tien Dat, Naoto Yokoya, Nga Nhu Le, et al.. (2020). Improvement of Mangrove Soil Carbon Stocks Estimation in North Vietnam Using Sentinel-2 Data and Machine Learning Approach. GIScience & Remote Sensing. 58(1). 68–87. 70 indexed citations
8.
Pham, Tien Dat, Junshi Xia, Gerald Baier, Nga Nhu Le, & Naoto Yokoya. (2019). Mangrove Species Mapping Using Sentinel-1 and Sentinel-2 Data in North Vietnam. 6102–6105. 13 indexed citations
9.
Pham, Tien Dat, Dieu Tien Bui, Kunihiko Yoshino, & Nga Nhu Le. (2018). Optimized rule-based logistic model tree algorithm for mapping mangrove species using ALOS PALSAR imagery and GIS in the tropical region. Environmental Earth Sciences. 77(5). 36 indexed citations
10.
Pham, Tien Dat, Kunihiko Yoshino, Nga Nhu Le, & Dieu Tien Bui. (2018). Estimating aboveground biomass of a mangrove plantation on the Northern coast of Vietnam using machine learning techniques with an integration of ALOS-2 PALSAR-2 and Sentinel-2A data. International Journal of Remote Sensing. 39(22). 7761–7788. 78 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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