Ali Shamsoddini

406 total citations
28 papers, 324 citations indexed

About

Ali Shamsoddini is a scholar working on Environmental Engineering, Ecology and Nature and Landscape Conservation. According to data from OpenAlex, Ali Shamsoddini has authored 28 papers receiving a total of 324 indexed citations (citations by other indexed papers that have themselves been cited), including 15 papers in Environmental Engineering, 11 papers in Ecology and 5 papers in Nature and Landscape Conservation. Recurrent topics in Ali Shamsoddini's work include Remote Sensing in Agriculture (11 papers), Remote Sensing and LiDAR Applications (10 papers) and Forest ecology and management (5 papers). Ali Shamsoddini is often cited by papers focused on Remote Sensing in Agriculture (11 papers), Remote Sensing and LiDAR Applications (10 papers) and Forest ecology and management (5 papers). Ali Shamsoddini collaborates with scholars based in Iran, Australia and United Kingdom. Ali Shamsoddini's co-authors include John Trinder, Simit Raval, Russell Turner, P.N. Denbigh, Xiaofeng Li, Mojtaba Maghrebi, S. Travis Waller, Meisam Nazari, Emily Sarver and Alijafar Mousivand and has published in prestigious journals such as SHILAP Revista de lepidopterología, International Journal of Remote Sensing and ISPRS Journal of Photogrammetry and Remote Sensing.

In The Last Decade

Ali Shamsoddini

26 papers receiving 316 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 Shamsoddini Iran 11 157 116 57 56 47 28 324
Guoyuan Li China 12 214 1.4× 101 0.9× 21 0.4× 70 1.3× 73 1.6× 36 476
Christine E. Blinn United States 12 168 1.1× 225 1.9× 74 1.3× 180 3.2× 53 1.1× 19 465
Yang Dam Eo South Korea 11 184 1.2× 165 1.4× 26 0.5× 63 1.1× 100 2.1× 60 519
Yu-Hsuan Tu Saudi Arabia 12 245 1.6× 261 2.3× 23 0.4× 87 1.6× 23 0.5× 18 550
Gabriela Takahashi Miyoshi Brazil 10 322 2.1× 341 2.9× 36 0.6× 85 1.5× 30 0.6× 20 550
Hengqian Zhao China 9 103 0.7× 120 1.0× 28 0.5× 96 1.7× 36 0.8× 37 321
Won-Kyung Baek South Korea 11 113 0.7× 67 0.6× 17 0.3× 81 1.4× 72 1.5× 34 322
Nusret Demir Türkiye 13 188 1.2× 107 0.9× 11 0.2× 69 1.2× 17 0.4× 38 343
Salman Ashraf New Zealand 11 65 0.4× 97 0.8× 12 0.2× 62 1.1× 52 1.1× 21 340
Dajun Li China 11 128 0.8× 78 0.7× 23 0.4× 43 0.8× 28 0.6× 25 308

Countries citing papers authored by Ali Shamsoddini

Since Specialization
Citations

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

Fields of papers citing papers by Ali Shamsoddini

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ali Shamsoddini

This figure shows the co-authorship network connecting the top 25 collaborators of Ali Shamsoddini. A scholar is included among the top collaborators of Ali Shamsoddini 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 Shamsoddini. Ali Shamsoddini 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.
Shamsoddini, Ali, et al.. (2023). Crop mapping through a hybrid machine learning and deep learning method. Remote Sensing Applications Society and Environment. 33. 101090–101090. 18 indexed citations
2.
Shamsoddini, Ali, et al.. (2022). Global-scale biomass estimation based on machine learning and deep learning methods. Remote Sensing Applications Society and Environment. 28. 100868–100868. 11 indexed citations
3.
Shamsoddini, Ali, et al.. (2021). Urban Tree Canopy Mapping Using Object Oriented Classification and Machine Learning Algorithms. 13(1). 17–32. 1 indexed citations
4.
Salehi, Hamid, et al.. (2021). Spatial and Temporal Resolution Improvement of Actual Evapotranspiration Maps Using Landsat and MODIS Data Fusion. Frontiers in Environmental Science. 9. 6 indexed citations
5.
Morid, Saeed, et al.. (2021). Validation of the CHIRPS and CPC-Unified products for estimating extreme daily precipitation over southwestern Iran. Theoretical and Applied Climatology. 146(3-4). 1207–1225. 3 indexed citations
6.
Mousivand, Alijafar, et al.. (2020). Comparative analysis of LAI retrieval from hyperspectral imagery using machine learning approaches. 12(3). 47–64. 1 indexed citations
7.
Shamsoddini, Ali, et al.. (2019). SPOT-5 Spectral and Textural Data Fusion for Forest Mean Age and Height Estimation. 9(1). 119–130.
8.
Shamsoddini, Ali & Simit Raval. (2018). Mapping red edge-based vegetation health indicators using Landsat TM data for Australian native vegetation cover. Earth Science Informatics. 11(4). 545–552. 15 indexed citations
9.
Mousivand, Alijafar, et al.. (2017). Air pollution estimation using traffic volume data and primary weather data: case study Mashhad. 21(2). 197–218. 1 indexed citations
10.
Shamsoddini, Ali, et al.. (2017). TEHRAN AIR POLLUTANTS PREDICTION BASED ON RANDOM FOREST FEATURE SELECTION METHOD. SHILAP Revista de lepidopterología. XLII-4/W4. 483–488. 22 indexed citations
11.
Maghrebi, Mojtaba, Ali Shamsoddini, & S. Travis Waller. (2016). Fusion based learning approach for predicting concrete pouring productivity based on construction and supply parameters. Construction Innovation. 16(2). 185–202. 9 indexed citations
12.
Shamsoddini, Ali, et al.. (2016). Extracting hurricane eye morphology from spaceborne SAR images using morphological analysis. ISPRS Journal of Photogrammetry and Remote Sensing. 117. 115–125. 39 indexed citations
13.
Maghrebi, Mojtaba, Ali Shamsoddini, & S. Travis Waller. (2015). Machine Learning Fusion Based Technique for Predicting the Concrete Pouring Production Rate Based on Traffic and Supply Chain Parameters. Transportation Research Board 94th Annual MeetingTransportation Research Board. 1 indexed citations
14.
Shamsoddini, Ali, John Trinder, & Russell Turner. (2015). Paired-data fusion for improved estimation of pine plantation structure. International Journal of Remote Sensing. 36(8). 1995–2009. 2 indexed citations
15.
Raval, Simit, Emily Sarver, Ali Shamsoddini, et al.. (2014). Satellite remote sensing-based estimates of biomass production on reclaimed coal mines. Mining Engineering. 66(4). 76–82. 9 indexed citations
16.
Shamsoddini, Ali, et al.. (2013). Non-linear methods for inferring lidar metrics using SPOT-5 textural data. SHILAP Revista de lepidopterología. II-5/W2. 259–264. 4 indexed citations
17.
Shamsoddini, Ali, John Trinder, & Russell Turner. (2013). Pine plantation structure mapping using WorldView-2 multispectral image. International Journal of Remote Sensing. 34(11). 3986–4007. 44 indexed citations
18.
Trinder, John, et al.. (2013). Relating WorldView-2 data to pine plantation lidar metrics. SHILAP Revista de lepidopterología. II-5/W2. 301–306. 2 indexed citations
19.
Shamsoddini, Ali. (2012). RADAR BACKSCATTER AND OPTICAL TEXTURAL INDICES FUSION FOR PINE PLANTATION STRUCTURE MAPPING. SHILAP Revista de lepidopterología. I-7. 309–314. 7 indexed citations
20.
Shamsoddini, Ali & P.N. Denbigh. (2001). A sound segregation algorithm for reverberant conditions. Speech Communication. 33(3). 179–196. 19 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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