Nian-Wei Ku

463 total citations
9 papers, 393 citations indexed

About

Nian-Wei Ku is a scholar working on Environmental Engineering, Nature and Landscape Conservation and Insect Science. According to data from OpenAlex, Nian-Wei Ku has authored 9 papers receiving a total of 393 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Environmental Engineering, 8 papers in Nature and Landscape Conservation and 5 papers in Insect Science. Recurrent topics in Nian-Wei Ku's work include Remote Sensing and LiDAR Applications (9 papers), Forest ecology and management (8 papers) and Forest Ecology and Biodiversity Studies (5 papers). Nian-Wei Ku is often cited by papers focused on Remote Sensing and LiDAR Applications (9 papers), Forest ecology and management (8 papers) and Forest Ecology and Biodiversity Studies (5 papers). Nian-Wei Ku collaborates with scholars based in United States. Nian-Wei Ku's co-authors include Sorin Popescu, R. Sheridan, Marian Eriksson, Shruthi Srinivasan, Demetrios Gatziolis, Cristine L.S. Morgan, Tan Zhou, Samuel K. Moore, Lonesome Malambo and William L. Rooney and has published in prestigious journals such as Forest Ecology and Management, Remote Sensing and Biomass and Bioenergy.

In The Last Decade

Nian-Wei Ku

8 papers receiving 382 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Nian-Wei Ku United States	6	332	220	181	108	88	9	393
Daniel de Almeida Papa Brazil	7	323 1.0×	178 0.8×	207 1.1×	81 0.8×	122 1.4×	14	441
Hudson Franklin Pessoa Veras Brazil	6	324 1.0×	118 0.5×	198 1.1×	91 0.8×	60 0.7×	13	391
Russell Turner Australia	12	240 0.7×	155 0.7×	174 1.0×	85 0.8×	85 1.0×	17	352
Samuli Junttila Finland	16	303 0.9×	177 0.8×	263 1.5×	98 0.9×	175 2.0×	40	532
Lixia Ma China	10	338 1.0×	171 0.8×	262 1.4×	47 0.4×	105 1.2×	22	482
Reik Leiterer Switzerland	9	320 1.0×	182 0.8×	260 1.4×	72 0.7×	118 1.3×	25	428
Olga Brovkina Czechia	10	208 0.6×	84 0.4×	180 1.0×	53 0.5×	100 1.1×	29	301
Jonas Bohlin Sweden	10	327 1.0×	195 0.9×	207 1.1×	126 1.2×	67 0.8×	21	397
John A. Scrivani United States	9	280 0.8×	241 1.1×	189 1.0×	96 0.9×	125 1.4×	10	431
Fugen Jiang China	11	306 0.9×	163 0.7×	281 1.6×	44 0.4×	138 1.6×	20	419

Countries citing papers authored by Nian-Wei Ku

Since Specialization

Citations

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

Fields of papers citing papers by Nian-Wei Ku

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Nian-Wei Ku. 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 Nian-Wei Ku. The network helps show where Nian-Wei Ku may publish in the future.

Co-authorship network of co-authors of Nian-Wei Ku

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

All Works

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9 of 9 papers shown

1.

Malambo, Lonesome, et al.. (2023). Regional Stem Volume Mapping: A Feasibility Assessment of Scaling Tree-Level Estimates. Forests. 14(3). 506–506. 1 indexed citations

2.

Ku, Nian-Wei, Sorin Popescu, & Marian Eriksson. (2021). Regionalization of an Existing Global Forest Canopy Height Model for Forests of the Southern United States. Remote Sensing. 13(9). 1722–1722. 3 indexed citations

3.

Malambo, Lonesome, Sorin Popescu, Nian-Wei Ku, et al.. (2019). A Deep Learning Semantic Segmentation-Based Approach for Field-Level Sorghum Panicle Counting. Remote Sensing. 11(24). 2939–2939. 47 indexed citations

4.

Ku, Nian-Wei & Sorin Popescu. (2019). A comparison of multiple methods for mapping local-scale mesquite tree aboveground biomass with remotely sensed data. Biomass and Bioenergy. 122. 270–279. 30 indexed citations

5.

Srinivasan, Shruthi, Sorin Popescu, Marian Eriksson, R. Sheridan, & Nian-Wei Ku. (2015). Terrestrial Laser Scanning as an Effective Tool to Retrieve Tree Level Height, Crown Width, and Stem Diameter. Remote Sensing. 7(2). 1877–1896. 124 indexed citations

6.

Sheridan, R., Sorin Popescu, Demetrios Gatziolis, Cristine L.S. Morgan, & Nian-Wei Ku. (2014). Modeling Forest Aboveground Biomass and Volume Using Airborne LiDAR Metrics and Forest Inventory and Analysis Data in the Pacific Northwest. Remote Sensing. 7(1). 229–255.

7.

Sheridan, R., Sorin Popescu, Demetrios Gatziolis, Cristine L.S. Morgan, & Nian-Wei Ku. (2014). Modeling Forest Aboveground Biomass and Volume Using Airborne LiDAR Metrics and Forest Inventory and Analysis Data in the Pacific Northwest. Remote Sensing. 7(1). 229–255. 77 indexed citations

8.

Srinivasan, Shruthi, Sorin Popescu, Marian Eriksson, R. Sheridan, & Nian-Wei Ku. (2014). Multi-temporal terrestrial laser scanning for modeling tree biomass change. Forest Ecology and Management. 318. 304–317. 87 indexed citations

9.

Ku, Nian-Wei, Sorin Popescu, R. James Ansley, Humberto L. Perotto‐Baldivieso, & Anthony M. Filippi. (2012). Assessment of Available Rangeland Woody Plant Biomass with a Terrestrial Lidar System. Photogrammetric Engineering & Remote Sensing. 78(4). 349–361. 24 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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