Ali Raza

1.0k total citations
37 papers, 627 citations indexed

About

Ali Raza is a scholar working on Global and Planetary Change, Environmental Engineering and Water Science and Technology. According to data from OpenAlex, Ali Raza has authored 37 papers receiving a total of 627 indexed citations (citations by other indexed papers that have themselves been cited), including 26 papers in Global and Planetary Change, 13 papers in Environmental Engineering and 12 papers in Water Science and Technology. Recurrent topics in Ali Raza's work include Plant Water Relations and Carbon Dynamics (17 papers), Hydrology and Watershed Management Studies (11 papers) and Remote Sensing in Agriculture (8 papers). Ali Raza is often cited by papers focused on Plant Water Relations and Carbon Dynamics (17 papers), Hydrology and Watershed Management Studies (11 papers) and Remote Sensing in Agriculture (8 papers). Ali Raza collaborates with scholars based in China, Pakistan and Egypt. Ali Raza's co-authors include Ahmed Elbeltagi, Yongguang Hu, Sajjad Hussain, Aman Srivastava, Siham Acharki, Ram L. Ray, Muhammad Mubeen, Wajid Nasim, Muhammad Shoaib and Dinesh Kumar Vishwakarma and has published in prestigious journals such as SHILAP Revista de lepidopterología, Scientific Reports and International Journal of Hydrogen Energy.

In The Last Decade

Ali Raza

33 papers receiving 608 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Ali Raza China 15 374 221 148 120 89 37 627
David Santillán Spain 20 209 0.6× 131 0.6× 165 1.1× 83 0.7× 33 0.4× 54 1.2k
Duc-Anh An-Vo Australia 16 185 0.5× 91 0.4× 203 1.4× 60 0.5× 43 0.5× 35 669
M. Mancini Italy 12 336 0.9× 142 0.6× 205 1.4× 40 0.3× 167 1.9× 29 626
Mustafa Tombul Türkiye 13 329 0.9× 434 2.0× 325 2.2× 41 0.3× 123 1.4× 29 790
Roberta Padulano Italy 16 268 0.7× 122 0.6× 225 1.5× 116 1.0× 101 1.1× 36 568
Shaoxiu Ma China 15 238 0.6× 147 0.7× 38 0.3× 129 1.1× 132 1.5× 49 684
Ali Naghi Ziaei Iran 13 185 0.5× 240 1.1× 264 1.8× 62 0.5× 29 0.3× 57 609
Jiren Li China 17 340 0.9× 318 1.4× 361 2.4× 69 0.6× 143 1.6× 51 673
Rozi Abdullah Malaysia 12 227 0.6× 147 0.7× 199 1.3× 72 0.6× 30 0.3× 30 450
Daniele Masseroni Italy 18 406 1.1× 281 1.3× 269 1.8× 88 0.7× 63 0.7× 49 800

Countries citing papers authored by Ali Raza

Since Specialization
Citations

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

Fields of papers citing papers by Ali Raza

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ali Raza

This figure shows the co-authorship network connecting the top 25 collaborators of Ali Raza. A scholar is included among the top collaborators of Ali Raza 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 Ali Raza. Ali Raza 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.
Hussain, Sajjad, Saeed Ahmad Qaisrani, Zafar Iqbal, et al.. (2025). Using google earth engine to detect the land use changes, climate change and vegetation dynamics. Geoscience Letters. 12(1).
2.
Elbeltagi, Ahmed, Aman Srivastava, Xinchun Cao, et al.. (2025). An interpretable machine learning approach based on SHAP, Sobol and LIME values for precise estimation of daily soybean crop coefficients. Scientific Reports. 15(1). 36594–36594. 1 indexed citations
3.
Almazah, Mohammed M. A., et al.. (2025). Improving Reference Evapotranspiration Predictions with Hybrid Modeling Approach. Earth Systems and Environment. 10(1). 139–156. 2 indexed citations
4.
Acharki, Siham, Ali Raza, Dinesh Kumar Vishwakarma, et al.. (2025). Comparative assessment of empirical and hybrid machine learning models for estimating daily reference evapotranspiration in sub-humid and semi-arid climates. Scientific Reports. 15(1). 2542–2542. 17 indexed citations
5.
Elbeltagi, Ahmed, et al.. (2025). Integration of MRMR algorithm with advanced neural networks for modeling long-term crop water demand in agricultural basins. Applied Water Science. 15(8). 1 indexed citations
6.
Raza, Ali, et al.. (2024). Improving carbon flux estimation in tea plantation ecosystems: A machine learning ensemble approach. European Journal of Agronomy. 160. 127297–127297. 17 indexed citations
7.
Raza, Ali, Dinesh Kumar Vishwakarma, Siham Acharki, et al.. (2024). Use of gene expression programming to predict reference evapotranspiration in different climatic conditions. Applied Water Science. 14(7). 11 indexed citations
8.
9.
Zhu, Hongjian, et al.. (2024). Nanoscale mineralogy and organic structure characterization of shales: Insights via AFM-IR spectroscopy. ADVANCES IN GEO-ENERGY RESEARCH. 13(3). 231–236. 13 indexed citations
10.
Raza, Ali, Siham Acharki, Sajjad Hussain, et al.. (2023). Land use/land change detection and determination of land surface temperature variation in green belt (Nasirabad) district of Balochistan, Pakistan. SN Applied Sciences. 5(11). 6 indexed citations
11.
Nauman, Muhammad, et al.. (2023). A review of recent advancements in micro combustion techniques to enhance flame stability and fuel residence time. International Journal of Hydrogen Energy. 49. 1165–1193. 39 indexed citations
12.
Shoaib, Muhammad, et al.. (2023). Using Ensembles of Machine Learning Techniques to Predict Reference Evapotranspiration (ET0) Using Limited Meteorological Data. Hydrology. 10(8). 169–169. 10 indexed citations
13.
Hussain, Sajjad, Ali Raza, Hazem Ghassan Abdo, et al.. (2023). Relation of land surface temperature with different vegetation indices using multi-temporal remote sensing data in Sahiwal region, Pakistan. Geoscience Letters. 10(1). 55 indexed citations
14.
Elbeltagi, Ahmed, Aman Srivastava, Abdullah Hassan Al-Saeedi, et al.. (2023). Forecasting Long-Series Daily Reference Evapotranspiration Based on Best Subset Regression and Machine Learning in Egypt. Water. 15(6). 1149–1149. 14 indexed citations
15.
Hussain, Sajjad, Muhammad Mubeen, Wajid Nasim, et al.. (2023). Investigation of Irrigation Water Requirement and Evapotranspiration for Water Resource Management in Southern Punjab, Pakistan. Sustainability. 15(3). 1768–1768. 29 indexed citations
16.
Hu, Yongguang, Ali Raza, Siham Acharki, et al.. (2023). Land Use/Land Cover Change Detection and NDVI Estimation in Pakistan’s Southern Punjab Province. Sustainability. 15(4). 3572–3572. 62 indexed citations
17.
Raza, Ali, Saber Kouadri, Ram L. Ray, et al.. (2023). Modelling reference evapotranspiration using principal component analysis and machine learning methods under different climatic environments. Irrigation and Drainage. 72(4). 945–970. 23 indexed citations
18.
Raza, Ali, Nadhir Al‐Ansari, Yongguang Hu, et al.. (2022). Misconceptions of Reference and Potential Evapotranspiration: A PRISMA-Guided Comprehensive Review. Hydrology. 9(9). 153–153. 15 indexed citations
19.
Hussain, Sajjad, Shujing Qin, Wajid Nasim, et al.. (2022). Monitoring the Dynamic Changes in Vegetation Cover Using Spatio-Temporal Remote Sensing Data from 1984 to 2020. Atmosphere. 13(10). 1609–1609. 49 indexed citations
20.
Basheer, Muhammad Farhan, et al.. (2019). The Paradox of Managerial Dividend Policy in Corporate Malaysia. Review of Economics and Development Studies. 5(1). 197–204. 1 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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