Nana Yan

2.9k total citations
80 papers, 2.0k citations indexed

About

Nana Yan is a scholar working on Global and Planetary Change, Water Science and Technology and Environmental Engineering. According to data from OpenAlex, Nana Yan has authored 80 papers receiving a total of 2.0k indexed citations (citations by other indexed papers that have themselves been cited), including 63 papers in Global and Planetary Change, 30 papers in Water Science and Technology and 26 papers in Environmental Engineering. Recurrent topics in Nana Yan's work include Plant Water Relations and Carbon Dynamics (37 papers), Hydrology and Watershed Management Studies (24 papers) and Climate variability and models (18 papers). Nana Yan is often cited by papers focused on Plant Water Relations and Carbon Dynamics (37 papers), Hydrology and Watershed Management Studies (24 papers) and Climate variability and models (18 papers). Nana Yan collaborates with scholars based in China, Egypt and United States. Nana Yan's co-authors include Bingfang Wu, Weiwei Zhu, Zonghan Ma, Shanlong Lu, Hao Wang, Hongwei Zeng, Miao Zhang, Alfred Stein, Qiang Xing and Xin Du and has published in prestigious journals such as The Science of The Total Environment, Remote Sensing of Environment and Scientific Reports.

In The Last Decade

Nana Yan

79 papers receiving 1.9k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Nana Yan China 26 1.3k 672 537 472 407 80 2.0k
Songhao Shang China 26 1.1k 0.8× 699 1.0× 331 0.6× 474 1.0× 345 0.8× 96 1.9k
Xianhong Xie China 25 1.5k 1.1× 966 1.4× 773 1.4× 725 1.5× 603 1.5× 80 2.5k
Balaji Narasimhan India 20 1.4k 1.0× 908 1.4× 316 0.6× 624 1.3× 407 1.0× 71 2.2k
Muhammad Jehanzeb Masud Cheema Pakistan 27 928 0.7× 699 1.0× 349 0.6× 490 1.0× 437 1.1× 85 2.2k
G. P. Obi Reddy India 19 957 0.7× 534 0.8× 611 1.1× 772 1.6× 225 0.6× 70 1.9k
Carmelo Cammalleri Italy 28 2.1k 1.6× 669 1.0× 567 1.1× 908 1.9× 541 1.3× 80 2.8k
Milan Gocić Serbia 24 2.1k 1.6× 858 1.3× 329 0.6× 742 1.6× 631 1.6× 57 3.0k
Yun Yang United States 25 1.2k 0.9× 394 0.6× 745 1.4× 679 1.4× 368 0.9× 52 1.9k
Wei Fang China 29 2.0k 1.5× 1.2k 1.8× 293 0.5× 505 1.1× 331 0.8× 65 3.1k

Countries citing papers authored by Nana Yan

Since Specialization
Citations

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

Fields of papers citing papers by Nana Yan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Nana Yan

This figure shows the co-authorship network connecting the top 25 collaborators of Nana Yan. A scholar is included among the top collaborators of Nana Yan 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 Nana Yan. Nana Yan 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.
Wang, Yixuan, et al.. (2024). A method to estimate the water storage of on-farm reservoirs by detecting slope gradients based on multi-spectral drone data. Agricultural Water Management. 307. 109241–109241.
2.
Zhou, Yanan, Nana Yan, Li Feng, et al.. (2023). Contrastive-Learning-Based Time-Series Feature Representation for Parcel-Based Crop Mapping Using Incomplete Sentinel-2 Image Sequences. Remote Sensing. 15(20). 5009–5009. 4 indexed citations
3.
Lu, Yuming, Bingfang Wu, Abdelrazek Elnashar, et al.. (2023). Downscaling wind speed based on coupled environmental factors and machine learning. International Journal of Climatology. 43(10). 4733–4755. 5 indexed citations
4.
Wu, Bingfang, Abdelrazek Elnashar, Weiwei Zhu, et al.. (2022). Incorporation of Net Radiation Model Considering Complex Terrain in Evapotranspiration Determination with Sentinel-2 Data. Remote Sensing. 14(5). 1191–1191. 8 indexed citations
5.
Lu, Yuming, et al.. (2021). Method for Environmental Flows Regulation and Early Warning with Remote Sensing and Land Cover Data. Land. 10(11). 1216–1216. 1 indexed citations
6.
Wu, Fangming, Bingfang Wu, Weiwei Zhu, et al.. (2021). ETWatch cloud: APIs for regional actual evapotranspiration data generation. Environmental Modelling & Software. 145. 105174–105174. 11 indexed citations
7.
Chang, Sheng, et al.. (2021). A Practical Satellite-Derived Vegetation Drought Index for Arid and Semi-Arid Grassland Drought Monitoring. Remote Sensing. 13(3). 414–414. 35 indexed citations
8.
Lu, Yuming, Bingfang Wu, Nana Yan, et al.. (2021). Quantifying the Contributions of Environmental Factors to Wind Characteristics over 2000–2019 in China. ISPRS International Journal of Geo-Information. 10(8). 515–515. 7 indexed citations
9.
Wu, Bingfang, et al.. (2021). Synthesizing a Regional Territorial Evapotranspiration Dataset for Northern China. Remote Sensing. 13(6). 1076–1076. 18 indexed citations
10.
Xu, Jiaming, Bingfang Wu, Dongryeol Ryu, et al.. (2020). Quantifying the contribution of biophysical and environmental factors in uncertainty of modeling canopy conductance. Journal of Hydrology. 592. 125612–125612. 8 indexed citations
11.
Yan, Nana, Bingfang Wu, & Weiwei Zhu. (2020). Assessment of Agricultural Water Productivity in Arid China. Water. 12(4). 1161–1161. 10 indexed citations
12.
Wu, Bingfang, et al.. (2019). A method for downscaling daily evapotranspiration based on 30-m surface resistance. Journal of Hydrology. 577. 123882–123882. 11 indexed citations
13.
Yan, Nana, Fuyou Tian, Bingfang Wu, Weiwei Zhu, & Mingzhao Yu. (2018). Spatiotemporal Analysis of Actual Evapotranspiration and Its Causes in the Hai Basin. Remote Sensing. 10(2). 332–332. 16 indexed citations
14.
Xu, Jiaming, et al.. (2018). Regional Daily ET Estimates Based on the Gap-Filling Method of Surface Conductance. Remote Sensing. 10(4). 554–554. 16 indexed citations
15.
Chang, Sheng, Bingfang Wu, Nana Yan, et al.. (2018). A Refined Crop Drought Monitoring Method Based on the Chinese GF-1 Wide Field View Data. Sensors. 18(4). 1297–1297. 6 indexed citations
16.
Xing, Qiang, Bingfang Wu, Nana Yan, Mingzhao Yu, & Weiwei Zhu. (2018). Sensitivity of BRDF, NDVI and Wind Speed to the Aerodynamic Roughness Length over Sparse Tamarix in the Downstream Heihe River Basin. Remote Sensing. 10(1). 56–56. 2 indexed citations
17.
Xing, Qiang, Bingfang Wu, Nana Yan, Mingzhao Yu, & Weiwei Zhu. (2017). Evaluating the Relationship between Field Aerodynamic Roughness and the MODIS BRDF, NDVI, and Wind Speed over Grassland. Atmosphere. 8(1). 16–16. 9 indexed citations
18.
Wu, Bingfang, et al.. (2017). An NDVI-Based Statistical ET Downscaling Method. Water. 9(12). 995–995. 12 indexed citations
19.
Yu, Mingzhao, Bingfang Wu, Nana Yan, Qiang Xing, & Weiwei Zhu. (2016). A Method for Estimating the Aerodynamic Roughness Length with NDVI and BRDF Signatures Using Multi-Temporal Proba-V Data. Remote Sensing. 9(1). 6–6. 18 indexed citations
20.
Wu, Bingfang, René Gommes, Miao Zhang, et al.. (2015). Global Crop Monitoring: A Satellite-Based Hierarchical Approach. Remote Sensing. 7(4). 3907–3933. 88 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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