Keiko Ioki

447 total citations
22 papers, 349 citations indexed

About

Keiko Ioki is a scholar working on Environmental Engineering, Nature and Landscape Conservation and Ecology. According to data from OpenAlex, Keiko Ioki has authored 22 papers receiving a total of 349 indexed citations (citations by other indexed papers that have themselves been cited), including 18 papers in Environmental Engineering, 14 papers in Nature and Landscape Conservation and 14 papers in Ecology. Recurrent topics in Keiko Ioki's work include Remote Sensing and LiDAR Applications (18 papers), Remote Sensing in Agriculture (13 papers) and Forest ecology and management (13 papers). Keiko Ioki is often cited by papers focused on Remote Sensing and LiDAR Applications (18 papers), Remote Sensing in Agriculture (13 papers) and Forest ecology and management (13 papers). Keiko Ioki collaborates with scholars based in Japan, Malaysia and United Kingdom. Keiko Ioki's co-authors include Yukihiro MORIMOTO, Junichi Imanishi, Takeshi Sasaki, Mui‐How Phua, Satoshi Tsuyuki, Gen Takao, Yasumasa Hirata, Hideki Saito, Youngkeun Song and Mazlan Hashim and has published in prestigious journals such as Remote Sensing of Environment, Biological Conservation and Forest Ecology and Management.

In The Last Decade

Keiko Ioki

21 papers receiving 339 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Keiko Ioki Japan 11 289 203 167 89 75 22 349
Songqiu Deng Japan 11 243 0.8× 150 0.7× 124 0.7× 117 1.3× 80 1.1× 18 368
Olivier R. van Lier Canada 10 377 1.3× 254 1.3× 239 1.4× 142 1.6× 104 1.4× 14 487
Olga Brovkina Czechia 10 208 0.7× 180 0.9× 84 0.5× 100 1.1× 53 0.7× 29 301
Chad Babcock United States 12 225 0.8× 199 1.0× 140 0.8× 131 1.5× 43 0.6× 25 363
Fugen Jiang China 11 306 1.1× 281 1.4× 163 1.0× 138 1.6× 44 0.6× 20 419
Radomir Bałazy Poland 10 155 0.5× 116 0.6× 123 0.7× 87 1.0× 57 0.8× 20 286
Reik Leiterer Switzerland 9 320 1.1× 260 1.3× 182 1.1× 118 1.3× 72 1.0× 25 428
Nataliia Rehush Switzerland 9 204 0.7× 127 0.6× 96 0.6× 71 0.8× 67 0.9× 14 282
Sebastian Schnell Sweden 10 363 1.3× 231 1.1× 292 1.7× 195 2.2× 88 1.2× 17 486
Jee-Cheng Wu Taiwan 3 375 1.3× 154 0.8× 254 1.5× 59 0.7× 175 2.3× 6 411

Countries citing papers authored by Keiko Ioki

Since Specialization
Citations

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

Fields of papers citing papers by Keiko Ioki

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Keiko Ioki

This figure shows the co-authorship network connecting the top 25 collaborators of Keiko Ioki. A scholar is included among the top collaborators of Keiko Ioki 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 Keiko Ioki. Keiko Ioki 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.
2.
Grady, Kevin C., et al.. (2024). Lessons learned from 25 years of operational large-scale restoration: The Sow-A-Seed project, Sabah, Borneo. Ecological Engineering. 206. 107282–107282. 2 indexed citations
3.
Ioki, Keiko, et al.. (2022). Estimating aboveground biomass changes in a human-modified tropical montane forest of Borneo using multi-temporal airborne LiDAR data. Remote Sensing Applications Society and Environment. 28. 100821–100821. 6 indexed citations
4.
5.
Ioki, Keiko, et al.. (2020). Evaluation of allometries for estimating above-ground biomass using airborne LiDAR data in tropical montane forest of Northern Borneo. IOP Conference Series Earth and Environmental Science. 540(1). 12039–12039. 1 indexed citations
6.
Ioki, Keiko, et al.. (2019). Supporting forest conservation through community-based land use planning and participatory GIS – lessons from Crocker Range Park, Malaysian Borneo. Journal for Nature Conservation. 52. 125740–125740. 21 indexed citations
7.
Phua, Mui‐How, Keiko Ioki, Reuben Nilus, et al.. (2017). Synergistic use of Landsat 8 OLI image and airborne LiDAR data for above-ground biomass estimation in tropical lowland rainforests. Forest Ecology and Management. 406. 163–171. 28 indexed citations
8.
Phua, Mui‐How, David A. Coomes, Satoshi Tsuyuki, et al.. (2017). Seeing trees from space: above-ground biomass estimates of intact and degraded montane rainforests from high-resolution optical imagery. iForest - Biogeosciences and Forestry. 10(3). 625–634. 6 indexed citations
9.
Phua, Mui‐How, Keiko Ioki, Mazlan Hashim, et al.. (2016). Estimating Logged-Over Lowland Rainforest Aboveground Biomass in Sabah, Malaysia Using Airborne LiDAR Data. Terrestrial Atmospheric and Oceanic Sciences. 27(4). 481–481. 12 indexed citations
10.
Tsuyuki, Satoshi, et al.. (2016). Performance of a photogrammetric digital elevation model in a tropical montane forest environment. Journal of Forest Planning. 21(2). 39–52. 2 indexed citations
11.
Song, Youngkeun, Junichi Imanishi, Takeshi Sasaki, Keiko Ioki, & Yukihiro MORIMOTO. (2016). Estimation of broad-leaved canopy growth in the urban forested area using multi-temporal airborne LiDAR datasets. Urban forestry & urban greening. 16. 142–149. 25 indexed citations
12.
Ioki, Keiko, Satoshi Tsuyuki, Yasumasa Hirata, et al.. (2015). Evaluation of the similarity in tree community composition in a tropical rainforest using airborne LiDAR data. Remote Sensing of Environment. 173. 304–313. 11 indexed citations
13.
Ioki, Keiko, Satoshi Tsuyuki, Yasumasa Hirata, et al.. (2014). Estimating above-ground biomass of tropical rainforest of different degradation levels in Northern Borneo using airborne LiDAR. Forest Ecology and Management. 328. 335–341. 60 indexed citations
14.
Phua, Mui‐How, Satoshi Tsuyuki, Keiko Ioki, et al.. (2014). Estimation of Above-Ground Biomass of a Tropical Forest in Northern Borneo Using High-resolution Satellite Image. Journal of Forest and Environmental Science. 30(2). 233–242. 12 indexed citations
15.
Sasaki, Takeshi, Junichi Imanishi, Keiko Ioki, Youngkeun Song, & Yukihiro MORIMOTO. (2013). Estimation of forest foliage distribution using airborne LiDAR. 18(1). 23–28. 1 indexed citations
16.
Sasaki, Takeshi, Junichi Imanishi, Keiko Ioki, Youngkeun Song, & Yukihiro MORIMOTO. (2013). Estimation of leaf area index and gap fraction in two broad-leaved forests by using small-footprint airborne LiDAR. Landscape and Ecological Engineering. 12(1). 117–127. 17 indexed citations
17.
Ioki, Keiko, Junichi Imanishi, Takeshi Sasaki, Youngkeun Song, & Yukihiro MORIMOTO. (2012). Vegetation Mapping of Urban Forest Using Airborne Laser Scanning in Kyoto City, Japan: Towards Woody Biomass Utilization. Waste and Biomass Valorization. 4(2). 213–220. 1 indexed citations
18.
Sasaki, Takeshi, et al.. (2011). Object-based classification of land cover and tree species by integrating airborne LiDAR and high spatial resolution imagery data. Landscape and Ecological Engineering. 8(2). 157–171. 61 indexed citations
19.
Ioki, Keiko, et al.. (2009). Estimating stand volume in broad-leaved forest using discrete-return LiDAR: plot-based approach. Landscape and Ecological Engineering. 6(1). 29–36. 46 indexed citations
20.

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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