Dr. Hasan TONBUL
Harita Mühendisliği

Hasan TONBUL
Telefon
(262) 605 20 49
E-Posta
htonbul@gtu.edu.tr
Ofis
F Blok, 208
Çalışma alanları
Uzaktan Algılama ve Uygulamaları, Dijital Görüntü İşleme, Orman Yangını İzlenmesi ve Analizi, Obje Tabanlı Sınıflandırma, Görüntü Segmentasyonu, Parametre Optimizasyonu

ORCID

Google Scholar

Researcgate

Papers in International Journals

1. Yilmaz, EO., Tonbul, H., Kavzoglu, T. (2023). Marine mucilage mapping with explained deep learning model using water-related spectral indices: A case study of Dardanelles Strait, Turkey. Stochastic Environmental Research and Risk Assessment (Accepted).

2. Colkesen, I., Kavzoglu, T., Atesoglu, A., Tonbul, H., Ozturk, M. Y. (2023). Multi-seasonal evaluation of hybrid poplar (P. Deltoides) plantations using Worldview-3 imagery and State-Of-The-Art ensemble learning algorithms. Advances in Space Research, 71(7), 3022–3044. https://doi.org/10.1016/j.asr.2022.10.044

3. Tonbul, H., Colkesen, I.,Kavzoglu, T. (2022). Pixel- and Object-Based ensemble learning for forest burn severity using USGS FIREMON and Mediterranean condition dNBRs in Aegean ecosystem (Turkey). Advances in Space Research, 69(10), 3609–3632. https://doi.org/10.1016/j.asr.2022.02.051

4. Tonbul, H., Kavzoglu, T. (2020). Semi-Automatic Building Extraction from WorldView-2 Imagery Using Taguchi Optimization. Photogrammetric Engineering; Remote Sensing, 86(9), 547–555. https://doi.org/10.14358/PERS.86.9.547;

5.Tonbul, H., Colkesen, I., Kavzoglu, T. (2020). Classification of poplar trees with object-based ensemble learning algorithms using Sentinel-2A imagery. Journal of Geodetic Science, 10(1), 14–22.https://doi.org/10.1515/jogs-2020-0003

6.Kavzoglu, T.,Tonbul, H. (2018). An experimental comparison of multi-resolution segmentation, SLIC and K-means clustering for object-based classification of VHR imagery. International Journal of Remote Sensing, 39(18), 1–17.;https://doi.org/10.1080/01431161.2018.1506592

7.Kavzoglu, T., Tonbul, H., Yildiz Erdemir, M., Colkesen, I. (2018). Dimensionality Reduction and Classification of Hyperspectral Images Using Object-Based Image Analysis. Journal of the Indian Society of Remote Sensing, 46(8), 1297–1306.https://doi.org/10.1007/s12524-018-0803-1

8.Kavzoglu, T., Erdemir, M. Y.,Tonbul, H. (2017). Classification of semi urban landscapes from very high-resolution satellite images using a regionalized multiscale segmentation approach. Journal of Applied Remote Sensing, 11(03), https://doi.org/10.1117/1.JRS.11.035016

Book/Book Chapters

1. Kavzoglu, T., Colkesen, İ., Tonbul, H., Ozturk, M. Y. (2021). Temporal analysis of forest fires with remote sensing technologies: Mediterranean and Aegean Fires in 2021. In T. Kavzoglu (Ed.), Forest Fires Causes, Effects, Monitoring, Precautions and Rehabilitation Activities (pp. 219–251). Turkish Academy of Science;https://doi.org/10.53478/TUBA.2021.048

Papers in National Journals

1. Atesoglu, A., Kavzoglu, T., Colkesen, İ., Ozlusoylu, S., Tonbul, H., Yılmaz, E. O., Öztürk, Yusuf, M. (2022). Türkiye’de hızlı büyüyen türlere ait spektral kütüphane kurulması: kavak türleri çalışması. Bartın Orman Fakültesi Dergisi. https://doi.org/10.24011/barofd.1099984

2. Kavzoglu, T., Tonbul, H., Colkesen, İ., Sefercik, U. G. (2021). The Use of Object-Based Image Analysis for Monitoring 2021 Marine Mucilage Bloom in the Sea of Marmara. International Journal of Environment and Geoinformatics, 8(4), 529–536. https://doi.org/10.30897/ijegeo.99087

3. Tonbul, H., Kavzoglu, T. (2020). A Spectral Band Based Comparison of Unsupervised Segmentation Evaluation Methods for Image Segmentation Parameter Optimization. International Journal of Environment and Geoinformatics, 7(2), 132–139. https://doi.org/10.30897/ijegeo.641216

4. Tonbul, H.,Kavzoglu, T. (2018). Nesne tabanlı görüntü analizinde görüntü bölütleme yaklaşımları ve bölütleme kalitesinin analizi. Harita Dergisi, 84(160), 12–23

5. Tonbul, H.,Kavzoglu, T. (2017). Nesne-Tabanlı Sınıflandırmada Segmentasyon (Bölütleme) Kalitesinin Sınıflandırma Doğruluğu Üzerine Etkisinin İncelenmesi. Afyon Kocatepe Üniversitesi Fen ve Mühendislik Bilimleri Dergisi, 17(Özel Sayı).118-125.

Published International Conference Papers

1. Tonbul, H., Yilmaz, E. O., Kavzoglu, T. (2023). Comparative Analysis of Deep Learning and Machine Learning Models for Burned Area Estimation Using Sentinel-2 Image: A case study in Mugla-Bodrum, Turkey. 10th International Conference on Recent Advances in Space Technologies (RAST2023), 1-5. https://doi.org/10.1109/RAST57548.2023.10197926

2. Colkesen, I., Sefercik U.G., Kavzoglu, T., Tonbul, H., Ozturk, M. Y., Altuntas, O. Y., Nazar ,Aydin I., (2023). Classification of hybrid maize seeds (Zea mays) with object-based machine learning algorithms using multispectral UAV imagery. 6th Intercontinental Geoinformation Days (IGD), 1-5.

3. Colkesen, I., Kavzoglu, T., Tonbul, H., Ozturk, M. Y.,Yilmaz, E. O. (2022). Poplar Tree Index (PTI): A new vegetation ındex for monitoring poplar cultivated areas. IEEE International Geoscience and Remote Sensing Symposium (IGARSS 2022), 5567–5570. https://doi.org/10.1109/IGARSS46834.2022.9883085

4. Kavzoglu, T., Colkesen, I., Tonbul, H., Ozturk, M. Y. (2022). Evaluation of potential use of Worldview-3 ımagery in object-based classification of hybrid poplar (P. Deltoides) Cultivated Fields. International Symposium on Applied Geoinformatics (ISAG2021). https://doi.org/10.15659/isag2021.12536

5. Kavzoglu, T., Tonbul, H., Colkesen, İ. (2021). Evaluation of atmospheric correction methods for Sentinel-2 ımagery in the spectral ıdentification of poplar (Populus Deltoides Bartr.) Species. 42nd Asian Conference on Remote Sensing (ACRS 2021), 1–7.

6.Tonbul, H.,Kavzoglu, T. (2019). Application of Taguchi optimization and ANOVA statistics in optimal parameter setting of multi-resolution segmentation. 9th International Conference on Recent Advances in Space Technologies (RAST2019), 387–391. https://doi.org/10.1109/RAST.2019.8767784

7. Kavzoglu, T., Tonbul, H., Colkesen, I. (2019). Agricultural crop type mapping using object-based ımage analysis with advanced ensemble learning algorithms. 40th Asian Conference on Remote Sensing (ACRS2019), 1–7.

8. Kavzoglu, T., Yilmaz, E. O., Tonbul, H. (2019). Object-based land use/cover change detection using spatio-temporal images; a case study in metropolitan city of Istanbul, Turkey. 40th Asian Conference on Remote Sensing (ACRS2019), 1–7.

9. Colkesen, I., Tonbul, H., Kavzoglu, T. (2019). Object-based image classification of poplar tree with ensemble learning methods using Sentinel-2 imagery. International Symposium on Applied Geoinformatics (ISAG2019), 203–207.

10. Tonbul, H., Colkesen, İ., Kavzoglu, T. (2019). Forest fire and burn severity analysis in Cefalu region of Italy using Sentinel-2 imagery. International Symposium on Applied Geoinformatics (ISAG2019), 208–211.

11. Kavzoglu, T., Tonbul, H. (2018). Segmentation quality assessment for varying spatial resolutions of very high-resolution satellite ımagery. Eurasian GIS Congress, 1–6.

12. Kavzoglu, T., Tonbul, H., Colkesen, I. (2018). Dimensionality reduction for hyperspectral ımages to ımprove object-based ımage classification using feature selection and principal components analysis. 39th Asian Conference on Remote Sensing (ACRS2018), 1–5.

13. Kavzoglu, T., Tonbul, H. (2017). A comparative study of segmentation quality for multi-resolution segmentation and watershed transform. 2017 8th International Conference on Recent Advances in Space Technologies (RAST2017), 113–117. https://doi.org/10.1109/RAST.2017.8002984

14. Kavzoglu, T., Tonbul, H. (2017). Selecting optimal SLIC superpixels parameters by using discrepancy measures. 38th Asian Conference on Remote Sensing (ACRS 2017), 1–7.

15. Kavzoglu, T., Yildiz Erdemir, M., Tonbul, H. (2016). Evaluating performances of spectral ındices for burned area mapping using object-based ımage analysis. Spatial Accuracy XXIII Congress, 1–7.

16. Kavzoglu, T., Yildiz Erdemir, M., Tonbul, H. (2016). A region-based multi-scale approach for object-based image analysis. International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives, 41(July), 241–247. https://doi.org/10.5194/isprsarchives-XLI-B7-241-2016

17. Tonbul, H., Kavzoglu, T.,; Kaya, S. (2016). Assessment of fire severity and post-fire regeneration based on topographical features using multitemporal Landsat imagery: A case study in Mersin, Turkey. International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives, 41(July), 763–769. https://doi.org/10.5194/isprsarchives-XLI-B8-763-2016

Published National Conference Papers

1. Tonbul, H., Kavzoglu, T., Colkesen, I., Yilmaz, E. O., Ozturk, M. Y. (2022). Populus Nigra L. Kavak Türünün Spektral Karakteristiğinin Belirlenmesinde Atmosferik Düzeltme Yaklaşımlarının Jilin-1 GP01 Görüntüsü Kullanılarak Analiz Edilmesi. XI. Türkiye Ulusal Fotogrametri ve Uzaktan Algılama Birliği (TUFUAB2022).

2. Tonbul, H., Kavzoglu, T. (2018). Worldvıew-2 görüntüsü kullanılarak nesne tabanlı görüntü analizi ve Taguchi optimizasyon tekniği ile yarı otomatik bina çıkarımı. VI I Uzaktan Algılama ve Coğrafi Bilgi Sistemleri Sempozyumu (UZALCBS2018), 1–7.

3. Tonbul, H., Kavzoglu, T. (2017). Nesne-tabanlı sınıflandırmada segmentasyon kalitesinin sınıflandırma doğruluğu üzerine etkisi. VI. Türkiye Ulusal Fotogrametri ve Uzaktan Algılama Birliği Sempozyumu (TUFUAB2017), 237–241.

4. Kavzoglu, T., Tonbul, H., Yildiz Erdemir, M., Colkesen, I. (2016). Hiperspektral görüntülerin nesne-tabanlı sınıflandırılmasında boyutsalık problemi ve parametre seçimi. VI. Uzaktan Algılama ve Coğrafi Bilgi Sistemleri Sempozyumu (UZALCBS2016), 691–698.

5. Kavzoglu, T., Kaya, S., Tonbul, H. (2014). Mekansal otokorelasyon teknikleri kullanılarak Modis uydu görüntüleri üzerinden yanmış alan ve yanma şiddetinin belirlenmesi. V. Uzaktan Algılama ve Coğrafi Bilgi Sistemleri Sempozyumu (UZALCBS2014), 1–9

Projects

1. Establishment of spectral library of Culturable populus trees and producing thematic maps using very high-resolution satellite imagery. The Scientific and Technological Research Council of Turkey (TUBITAK), Project No: 119O630, Researcher (February 2020 - August 2022).

2. Digital agriculture applications with the fusion of unmanned aerial vehicle technologies and artificial intelligence methods: monitoring the development of corn (Zea Mays), The Scientific and Technological Research Council of Turkey (TUBITAK), Project No: 112Y259, Researcher (December 2021- May 2024).

  • Doktora: Gebze Teknik Üniversitesi, Harita Mühendisliği (2021)
    Post-Doc: Vrije Üniversitesi Amsterdam, İklim Değişikliği ve Ekosistem (2024-Devam Ediyor)
  • Yüksek lisans: İstanbul Teknik Üniversitesi, Geomatik Mühendisliği (2015)
  • Lisans: İstanbul Teknik Üniversitesi, Geomatik Mühendisliği (2013)
Ödüller

1. IEEE Geoscience and Remote Sensing Society (GRSS) Türkiye Tez Yarışması - En iyi 2. Doktora Tezi Ödülü

2. American Society for Photogrammetry and Remote Sensing (ASPRS) 2021 John I. Davidson President’s Award for Practical Papers - En iyi 2.Makale Ödülü

3. Gebze Teknik Üniversitesi Akademik Ödül Değerlendirme Kurulu- 2021 Yılı Doktora Tezi Ödülü