Muzaffer Can İban

732 total citations · 1 hit paper
26 papers, 500 citations indexed

About

Muzaffer Can İban is a scholar working on Global and Planetary Change, Management, Monitoring, Policy and Law and Environmental Engineering. According to data from OpenAlex, Muzaffer Can İban has authored 26 papers receiving a total of 500 indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Global and Planetary Change, 9 papers in Management, Monitoring, Policy and Law and 7 papers in Environmental Engineering. Recurrent topics in Muzaffer Can İban's work include Landslides and related hazards (5 papers), Earthquake Detection and Analysis (4 papers) and Flood Risk Assessment and Management (4 papers). Muzaffer Can İban is often cited by papers focused on Landslides and related hazards (5 papers), Earthquake Detection and Analysis (4 papers) and Flood Risk Assessment and Management (4 papers). Muzaffer Can İban collaborates with scholars based in Türkiye, Norway and Azerbaijan. Muzaffer Can İban's co-authors include Aliihsan Şekertekin, Süleyman Sefa Bilgilioğlu, Erman Şentürk, Cemali Altuntaş, İrem Daloğlu Çetinkaya, Mustafa Toker, A. Monaco, Mahir Yazar, Davide Oscar Nitti and Raffaele Nutricato and has published in prestigious journals such as SHILAP Revista de lepidopterología, Remote Sensing and Environmental Science and Pollution Research.

In The Last Decade

Muzaffer Can İban

22 papers receiving 480 citations

Hit Papers

Machine learning based wildfire susceptibility mapping us... 2022 2026 2023 2024 2022 25 50 75 100
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. Machine learning based wildfire susceptibility mapping using remotely sensed fire data and GIS: A case study of Adana and Mersin provinces, Turkey
    2022 116 citations Muzaffer Can İban, Aliihsan Şekertekin profile →

Peers

Muzaffer Can İban
Firoozeh Karimi United States
Umer Khalil Pakistan
Conrad Zorn New Zealand
Farhad Hosseinali Iran
Hossein Nazmfar Iran
Davoud Omarzadeh Iran
Elżbieta Bielecka Poland
H A Faraji Sabokbar Iran
K. F. Turkman Portugal
Qiuwen Zhang China
Firoozeh Karimi United States
Muzaffer Can İban
Citations per year, relative to Muzaffer Can İban Muzaffer Can İban (= 1×) peers Firoozeh Karimi

Countries citing papers authored by Muzaffer Can İban

Since Specialization
Citations

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

Fields of papers citing papers by Muzaffer Can İban

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Muzaffer Can İban. 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 Muzaffer Can İban. The network helps show where Muzaffer Can İban may publish in the future.

Co-authorship network of co-authors of Muzaffer Can İban

This figure shows the co-authorship network connecting the top 25 collaborators of Muzaffer Can İban. A scholar is included among the top collaborators of Muzaffer Can İban 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 Muzaffer Can İban. Muzaffer Can İban 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.
2.
Bilgilioğlu, Süleyman Sefa, et al.. (2025). Explainable Sinkhole Susceptibility Mapping Using Machine-Learning-Based SHAP: Quantifying and Comparing the Effects of Contributing Factors in Konya, Türkiye. Applied Sciences. 15(6). 3139–3139. 2 indexed citations
3.
İban, Muzaffer Can, et al.. (2024). A Geospatial Dataframe of Collapsed Buildings in Antakya City after the 2023 Kahramanmaraş Earthquakes Using Object Detection Based on YOLO and VHR Satellite Images. Istanbul Technical University Academic Open Archive (Istanbul Technical University). 3915–3919.
4.
İban, Muzaffer Can, et al.. (2024). Next-level vegetation health index forecasting: A ConvLSTM study using MODIS Time Series. Environmental Science and Pollution Research. 31(12). 18932–18948. 8 indexed citations
5.
6.
İban, Muzaffer Can, et al.. (2024). DEEP LEARNING-BASED SCENE CLASSIFICATION OF VERY HIGH-RESOLUTION SATELLITE IMAGERY FOR POST-EARTHQUAKE DAMAGE ASSESSMENT: A CASE STUDY OF THE 2023 KAHRAMANMARAŞ EARTHQUAKES. SHILAP Revista de lepidopterología. XLVIII-4/W9-2024. 249–256. 3 indexed citations
7.
İban, Muzaffer Can, et al.. (2023). Identifying the source types of the seismic events using discriminant functions and tree-based machine learning algorithms at Soma Region, Turkey. Environmental Earth Sciences. 82(11). 1 indexed citations
8.
Yazar, Mahir, İrem Daloğlu Çetinkaya, Muzaffer Can İban, & Süleyman Sefa Bilgilioğlu. (2023). The green divide and heat exposure: urban transformation projects in istanbul. Frontiers in Environmental Science. 11. 5 indexed citations
9.
İban, Muzaffer Can & Süleyman Sefa Bilgilioğlu. (2023). Snow avalanche susceptibility mapping using novel tree-based machine learning algorithms (XGBoost, NGBoost, and LightGBM) with eXplainable Artificial Intelligence (XAI) approach. Stochastic Environmental Research and Risk Assessment. 37(6). 2243–2270. 42 indexed citations
10.
Amoroso, Nicola, Davide Oscar Nitti, Raffaele Nutricato, et al.. (2023). PSI Spatially Constrained Clustering: The Sibari and Metaponto Coastal Plains. Remote Sensing. 15(10). 2560–2560. 5 indexed citations
11.
İban, Muzaffer Can, et al.. (2022). Monitoring land use and land cover change near a nuclear power plant construction site: Akkuyu case, Turkey. Environmental Monitoring and Assessment. 194(10). 724–724. 15 indexed citations
12.
Altuntaş, Cemali, et al.. (2022). Machine learning-based snow depth retrieval using GNSS signal-to-noise ratio data. GPS Solutions. 26(4). 15 indexed citations
13.
İban, Muzaffer Can, et al.. (2022). Monitoring burn severity and air pollutants in wildfire events using remote sensing data: the case of Mersin wildfires in summer 2021. Gümüşhane Üniversitesi Fen Bilimleri Enstitüsü Dergisi. 9 indexed citations
14.
İban, Muzaffer Can & Erman Şentürk. (2021). Machine learning regression models for prediction of multiple ionospheric parameters. Advances in Space Research. 69(3). 1319–1334. 26 indexed citations
15.
İban, Muzaffer Can & Erman Şentürk. (2021). İyonosfer Parametrelerinin Çok Katmanlı Algılayıcılar ile Kestirimi. El-Cezeri Fen ve Mühendislik Dergisi.
16.
İban, Muzaffer Can. (2020). Geospatial Data Science Response to COVID-19 Crisis and Pandemic Isolation Tracking. DergiPark (Istanbul University). 1(1). 1–7. 4 indexed citations
17.
18.
İban, Muzaffer Can. (2020). Türkiye Kırsal Arazi Kullanımına Yönelik Bir Konumsal Veri Altyapısının Modellenmesi. SHILAP Revista de lepidopterología. 5(3). 209–227. 3 indexed citations
19.
İban, Muzaffer Can. (2019). Türkiye’de Arazi Kullanımı ve Ekonomik Kalkınma. DergiPark (Istanbul University). 1(1). 24–32. 1 indexed citations
20.
İban, Muzaffer Can, et al.. (2019). A model for big spatial rural data infrastructure in Turkey: Sensor-driven and integrative approach. Land Use Policy. 91. 104376–104376. 16 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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