Chihiro Haga

516 total citations
27 papers, 338 citations indexed

About

Chihiro Haga is a scholar working on Global and Planetary Change, Environmental Engineering and Ecology. According to data from OpenAlex, Chihiro Haga has authored 27 papers receiving a total of 338 indexed citations (citations by other indexed papers that have themselves been cited), including 20 papers in Global and Planetary Change, 6 papers in Environmental Engineering and 4 papers in Ecology. Recurrent topics in Chihiro Haga's work include Land Use and Ecosystem Services (10 papers), Forest Management and Policy (6 papers) and Forest Ecology and Biodiversity Studies (4 papers). Chihiro Haga is often cited by papers focused on Land Use and Ecosystem Services (10 papers), Forest Management and Policy (6 papers) and Forest Ecology and Biodiversity Studies (4 papers). Chihiro Haga collaborates with scholars based in Japan, China and United States. Chihiro Haga's co-authors include Takanori Matsui, Takashi Machimura, Shizuka Hashimoto, Osamu Saitô, Kiichiro Hayashi, Junko Morimoto, Hiroaki Takagi, Kazuhiko Takeuchi, Rajarshi Dasgupta and Xiaoyu Gan and has published in prestigious journals such as SHILAP Revista de lepidopterología, Environmental Science & Technology and The Science of The Total Environment.

In The Last Decade

Chihiro Haga

25 papers receiving 332 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Chihiro Haga Japan 12 152 86 72 32 31 27 338
Ying-Chen Lin Taiwan 15 94 0.6× 107 1.2× 193 2.7× 21 0.7× 61 2.0× 23 574
Joe Kiesecker United States 5 206 1.4× 97 1.1× 197 2.7× 57 1.8× 72 2.3× 6 506
Gabriel Gaona Ecuador 6 65 0.4× 54 0.6× 91 1.3× 50 1.6× 78 2.5× 14 484
Krishna Raj India 9 326 2.1× 46 0.5× 146 2.0× 68 2.1× 57 1.8× 18 441
Diogo Corrêa Santos Brazil 9 182 1.2× 60 0.7× 135 1.9× 28 0.9× 37 1.2× 16 391
James L. Fridley United States 6 89 0.6× 28 0.3× 107 1.5× 47 1.5× 37 1.2× 19 297
Kathleen M. Trauth United States 7 175 1.2× 20 0.2× 156 2.2× 13 0.4× 83 2.7× 30 341

Countries citing papers authored by Chihiro Haga

Since Specialization
Citations

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

Fields of papers citing papers by Chihiro Haga

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Chihiro Haga

This figure shows the co-authorship network connecting the top 25 collaborators of Chihiro Haga. A scholar is included among the top collaborators of Chihiro Haga 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 Chihiro Haga. Chihiro Haga 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.
Machimura, Takashi, et al.. (2024). Scenario-based land use simulation and integrated analysis of karst ecosystem service bundles. Global Ecology and Conservation. 54. e03096–e03096. 1 indexed citations
3.
Haga, Chihiro, Takanori Matsui, Masahiro Nakaoka, et al.. (2023). Modeling desirable futures at local scale by combining the nature futures framework and multi-objective optimization. Sustainability Science. 6 indexed citations
4.
Ishida, Shu, et al.. (2023). Twitter Mining for Detecting Interest Trends on Biodiversity: Messages from Seven Language Communities. Sustainability. 15(17). 12893–12893. 1 indexed citations
5.
Haga, Chihiro, Junko Morimoto, Satoshi Suzuki, et al.. (2023). Leaving disturbance legacies conserves boreal conifers and maximizes net CO2 absorption under climate change and more frequent and larger windthrow regimes. Landscape Ecology. 38(7). 1785–1805. 2 indexed citations
6.
Machimura, Takashi, et al.. (2023). Land Change Modeler For Evaluating Urbanization Driven By Universities In The Periurban Area Of Yogyakarta City, Indonesia. Journal of Catholic Education. 16(2). 2 indexed citations
7.
Hashimoto, Shizuka, et al.. (2023). Development of a method for downscaling ecological footprint and biocapacity to a 1-km square resolution. Sustainability Science. 18(3). 1549–1568. 5 indexed citations
8.
Saito, Ryusei, Jing Guo, Chihiro Haga, et al.. (2023). Does Deep Learning Enhance the Estimation for Spatially Explicit Built Environment Stocks through Nighttime Light Data Set? Evidence from Japanese Metropolitans. Environmental Science & Technology. 57(9). 3971–3979. 13 indexed citations
9.
10.
Guigue, Julien, Chihiro Haga, Samuel Munyaka Kimani, et al.. (2022). Carbon and nitrogen dynamics as affected by land-use and management change from original rice paddies to orchard, wetland, parking area and uplands in a mountain village located in Shonai region, Northeast Japan. Soil Science & Plant Nutrition. 68(1). 114–123. 6 indexed citations
11.
Tanaka, Kentaro, et al.. (2022). Renewable energy Nexus: Interlinkages with biodiversity and social issues in Japan. SHILAP Revista de lepidopterología. 6. 100069–100069. 9 indexed citations
12.
Matsui, Takanori, et al.. (2021). Impact of urbanization on the food–water–land–ecosystem nexus: A study of Shenzhen, China. The Science of The Total Environment. 808. 152138–152138. 32 indexed citations
13.
Morimoto, Junko, Chihiro Haga, Satoshi Suzuki, et al.. (2021). Long-term cumulative impacts of windthrow and subsequent management on tree species composition and aboveground biomass: A simulation study considering regeneration on downed logs. Forest Ecology and Management. 502. 119728–119728. 9 indexed citations
15.
Oda, Tomohiro, et al.. (2021). Errors and uncertainties associated with the use of unconventional activity data for estimating CO2 emissions: the case for traffic emissions in Japan. Environmental Research Letters. 16(8). 84058–84058. 11 indexed citations
16.
Saito, Ryusei, et al.. (2020). DEVELOPMENT OF A METHOD OF ESTIMATION OF TOTAL FLOOR AREA USING DEEP LEARNING BASED ON NIGHTTIME-LIGHT DATA. Journal of Japan Society of Civil Engineers Ser G (Environmental Research). 76(6). II_1–II_7.
17.
Suzuki, Masato, et al.. (2020). A new survey method using convolutional neural networks for automatic classification of bird calls. Ecological Informatics. 61. 101164–101164. 21 indexed citations
19.
Haga, Chihiro, Shizuka Hashimoto, Hiroko Kurokawa, et al.. (2018). Simulation of natural capital and ecosystem services in a watershed in Northern Japan focusing on the future underuse of nature: by linking forest landscape model and social scenarios. Sustainability Science. 14(1). 89–106. 14 indexed citations
20.
Hashimoto, Shizuka, Rajarshi Dasgupta, Takanori Matsui, et al.. (2018). Scenario analysis of land-use and ecosystem services of social-ecological landscapes: implications of alternative development pathways under declining population in the Noto Peninsula, Japan. Sustainability Science. 14(1). 53–75. 39 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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