Linshan Yang

2.9k citations

72 papers · 2.3k · 1 hit paper · h-index 26

Impact in

Environmental Engineering top 1%
- Hydrological Forecasting Using AI
Global and Planetary Change top 2%
- Land Use and Ecosystem Services
- Hydrology and Drought Analysis
- Plant Water Relations and Carbon Dynamics
- Environmental Changes in China

Papers in

Environmental Engineering 19
- Hydrological Forecasting Using AI 16
Global and Planetary Change 24
- Hydrology and Drought Analysis 9
- Land Use and Ecosystem Services 7
- Plant Water Relations and Carbon Dynamics 5

Co-authors: Qi Feng (44 shared papers)Zhenliang Yin (33 shared papers)Xiaohu Wen (25 shared papers)Ravinesh Chand Deo (17 shared papers)Meng Zhu (25 shared papers)Jutao Zhang (17 shared papers)Yongge Li (8 shared papers)Jan Adamowski (13 shared papers)
Journals: Journal of Hydrology (7 papers)The Science of The Total Environment (6 papers)Water (6 papers)Remote Sensing (6 papers)Hydrology research (4 papers)
Partner nations: China Australia Canada

In The Last Decade

Linshan Yang

71 papers receiving 2.3k citations

Linshan Yang's Hit Papers

align trajectories log scale

The role of land use change in affecting ecosystem services and the ecological security pattern of the Hexi Regions, Northwest China 2022 · 251 citations

What are hit papers?

Paper score: A paper's citations measured against the top-1% bar of its own field and year: the square root of citations ÷ bar, so 1 means right at the bar and 2 means four times its citations. The bar blends the citation counts that enter the top 1% of the paper's subfields in its year (weighted 89.5%), of those subfields over all years (0.5%) and of its year across all fields (10%); a subfield and year with fewer than 400 papers takes its year's bar. Papers from 2026 are not scored yet: in an unfinished year, when a paper appeared matters more than how it is cited.

Hit paper: A paper cited at least 1.5× the top-1% bar of its field and year: a paper score of at least √1.5.

2022 The Science of The Total Environment

Peers

Countries citing papers authored by Linshan Yang

Since Specialization

Citations

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

Fields of papers citing papers by Linshan Yang

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Linshan Yang, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Linshan Yang Line = papers co-authored together Linshan Yang links everyone, so they are left out of the graph.

All Works

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20 of 20 papers shown

Showing the 20 most-cited of 72 papers — load more, or switch the sort, to bring in the rest.

#	Work
1	The role of land use change in affecting ecosystem services and the ecological security pattern of the Hexi Regions, Northwest China The Science of The Total Environment ·Yongge Li, Wei Liu, Qi Feng, Meng Zhu, Linshan Yang, Jutao Zhang, Xinwei Yin Hit paper breakdown →	2022	251
2	Identifying separate impacts of climate and land use/cover change on hydrological processes in upper stream of Heihe River, Northwest China Hydrological Processes ·Linshan Yang, Qi Feng, Zhenliang Yin, Xiaohu Wen, Jianhua Si, Changbin Li, Ravinesh Chand Deo	2016	149
3	Two-phase extreme learning machines integrated with the complete ensemble empirical mode decomposition with adaptive noise algorithm for multi-scale runoff prediction problems Journal of Hydrology ·Xiaohu Wen, Qi Feng, Ravinesh Chand Deo, Min Wu, Zhenliang Yin, Linshan Yang, Vijay P. Singh	2019	122
4	Deep learning hybrid model with Boruta-Random forest optimiser algorithm for streamflow forecasting with climate mode indices, rainfall, and periodicity Journal of Hydrology ·A. A. Masrur Ahmed, Ravinesh Chand Deo, Qi Feng, Afshin Ghahramani, Nawin Raj, Zhenliang Yin, Linshan Yang	2021	120
5	The role of climate change and vegetation greening on the variation of terrestrial evapotranspiration in northwest China's Qilian Mountains The Science of The Total Environment ·Linshan Yang, Qi Feng, Jan Adamowski, Zhenliang Yin, Xiaohu Wen, Meng Zhu +1 other	2020	96
6	Effects of land use and land cover change on soil organic carbon storage in the Hexi regions, Northwest China Journal of Environmental Management ·Yongge Li, Wei Liu, Feng Qi, Meng Zhu, Linshan Yang, Jutao Zhang	2022	94
7	Domino effect of climate change over two millennia in ancient China’s Hexi Corridor Nature Sustainability ·Qi Feng, Linshan Yang, Ravinesh Chand Deo, Amir AghaKouchak, Jan Adamowski, Roger C. Stone, Zhenliang Yin, Wei Liu	2019	77
8	Deep Learning Forecasts of Soil Moisture: Convolutional Neural Network and Gated Recurrent Unit Models Coupled with Satellite-Derived MODIS, Observations and Synoptic-Scale Climate Index Data Remote Sensing ·A. A. Masrur Ahmed, Ravinesh Chand Deo, Nawin Raj, Afshin Ghahramani, Qi Feng, Zhenliang Yin, Linshan Yang	2021	71
9	Variation in actual evapotranspiration and its ties to climate change and vegetation dynamics in northwest China Journal of Hydrology ·Linshan Yang, Qi Feng, Meng Zhu, Liuming Wang, Jan Adamowski, Xiaohu Wen, Zhenliang Yin +1 other	2022	71
10	LSTM integrated with Boruta-random forest optimiser for soil moisture estimation under RCP4.5 and RCP8.5 global warming scenarios Stochastic Environmental Research and Risk Assessment ·A. A. Masrur Ahmed, Ravinesh Chand Deo, Afshin Ghahramani, Nawin Raj, Qi Feng, Zhenliang Yin, Linshan Yang	2021	64
11	Integrating genetic algorithm and support vector machine for modeling daily reference evapotranspiration in a semi-arid mountain area Hydrology research ·Zhenliang Yin, Xiaohu Wen, Qi Feng, Zhibin He, Songbing Zou, Linshan Yang	2016	63
12	Contributions of climate, elevated atmospheric CO2 concentration and land surface changes to variation in water use efficiency in Northwest China CATENA ·Linshan Yang, Qi Feng, Xiaohu Wen, Rahim Barzegar, Jan Adamowski, Meng Zhu, Zhenliang Yin	2022	62
13	New double decomposition deep learning methods for river water level forecasting The Science of The Total Environment ·A. A. Masrur Ahmed, Ravinesh Chand Deo, Afshin Ghahramani, Qi Feng, Nawin Raj, Zhenliang Yin, Linshan Yang	2022	61
14	Regional vegetation dynamics and its response to climate change—a case study in the Tao River Basin in Northwestern China Environmental Research Letters ·Changbin Li, Jiaguo Qi, Linshan Yang, Shuaibing Wang, Wenjin Yang, Gaofeng Zhu, Songbing Zou, Feng Zhang	2014	54
15	Design and evaluation of SVR, MARS and M5Tree models for 1, 2 and 3-day lead time forecasting of river flow data in a semiarid mountainous catchment Stochastic Environmental Research and Risk Assessment ·Zhenliang Yin, Qi Feng, Xiaohu Wen, Ravinesh Chand Deo, Linshan Yang, Jianhua Si, Zhibin He	2018	53
16	Quantitative Assessment for the Spatiotemporal Changes of Ecosystem Services, Tradeoff–Synergy Relationships and Drivers in the Semi-Arid Regions of China Remote Sensing ·Yongge Li, Wei Liu, Qi Feng, Meng Zhu, Linshan Yang, Jutao Zhang	2022	48
17	Hybrid deep learning method for a week-ahead evapotranspiration forecasting Stochastic Environmental Research and Risk Assessment ·A. A. Masrur Ahmed, Ravinesh Chand Deo, Qi Feng, Afshin Ghahramani, Nawin Raj, Zhenliang Yin, Linshan Yang	2021	47
18	Random forest predictive model development with uncertainty analysis capability for the estimation of evapotranspiration in an arid oasis region Hydrology research ·Min Wu, Qi Feng, Xiaohu Wen, Ravinesh Chand Deo, Zhenliang Yin, Linshan Yang, Danrui Sheng	2020	43
19	Assessing Variation in Water Balance Components in Mountainous Inland River Basin Experiencing Climate Change Water ·Zhenliang Yin, Qi Feng, Songbing Zou, Linshan Yang	2016	40
20	Future Projection with an Extreme-Learning Machine and Support Vector Regression of Reference Evapotranspiration in a Mountainous Inland Watershed in North-West China Water ·Zhenliang Yin, Qi Feng, Linshan Yang, Ravinesh Chand Deo, Xiaohu Wen, Jianhua Si, Shengchun Xiao	2017	38

About Linshan Yang

Linshan Yang is a scholar working on Environmental Engineering, Global and Planetary Change, Water Science and Technology, Soil Science and Atmospheric Science, having authored 72 papers that have together received 2.3k indexed citations. Recurring topics across this work include Hydrological Forecasting Using AI (16 papers), Hydrology and Watershed Management Studies (14 papers), Hydrology and Drought Analysis (9 papers), Land Use and Ecosystem Services (7 papers), Soil Carbon and Nitrogen Dynamics (6 papers), Environmental and Agricultural Sciences (5 papers), Plant Water Relations and Carbon Dynamics (5 papers) and Cryospheric studies and observations (4 papers). The work is most often cited by research in Environmental Engineering (717 citations), Global and Planetary Change (868 citations), Water Science and Technology (446 citations), Soil Science (168 citations) and Ecology (196 citations). Linshan Yang has collaborated with scholars based in China, Australia and Canada. Frequent co-authors include Qi Feng, Zhenliang Yin, Xiaohu Wen, Ravinesh Chand Deo, Meng Zhu, Jutao Zhang, Yongge Li, Jan Adamowski, Jianhua Si and A. A. Masrur Ahmed. Their work appears in journals such as Journal of Hydrology, The Science of The Total Environment, Water, Remote Sensing and Hydrology research.

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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Linshan Yang's Hit Papers

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