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Estimation of Aboveground Biomass of Maritime Pine (Pinus pinaster Ait.) Plantations Using Sentinel-1 and Sentinel-2 Satellite Images in Bartın

Year 2024, Volume: 5 Issue: 1, 15 - 27, 28.03.2024

Eren Gürsoy Özdemir Aziz Demiralay Batuhan Şahin

https://doi.org/10.48123/rsgis.1327406

Abstract

Forests are a crucial component in the world ecosystem, covering approximately one-third of the earth's surface, hosting more than half of the biodiversity on the planet, holding a significant amount of carbon released into the atmosphere, and strongly impacting climate change. Accurate forest biomass estimation is essential in reducing carbon emissions and increasing carbon sink areas. With the development of satellite technologies and remote sensing systems, estimating the Above Ground Biomass (AGB) with active and passive systems has become possible. In this study, the effects of band and vegetation index values on Above Ground Biomass (AGB) estimation were investigated in Maritime pine (Pinus pinaster Ait.) reforestation areas in Bartın using data from the Sentinel-1 radar and Sentinel-2 optical satellite provided free of charge to researchers by the European Space Agency (ESA), along with the Multiple Linear Regression (MLR) and Random Forest (RF) methods. The relationships between AGB values obtained from ground sample plot data and the satellite data were examined, and 16 models were developed. The best results for AGB estimation were achieved using the model that incorporated the Sentinel-1 VH backscatter value, the Normalized Difference Vegetation Index (NDVI) derived from Sentinel-2, and the RF method (R2=0.61, RMSE= 49.412 t/ha).

Keywords

Biomass Above ground biomass Sentinel-1 Sentinel-2 Maritime pine

References

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Bartın’daki Sahil Çamı (Pinus pinaster Ait.) Ağaçlandırma Alanlarında Sentinel-1 ve Sentinel-2 Uydu Görüntüleri Kullanılarak Toprak Üstü Biyokütlenin Kestirilmesi

Year 2024, Volume: 5 Issue: 1, 15 - 27, 28.03.2024

Eren Gürsoy Özdemir Aziz Demiralay Batuhan Şahin

https://doi.org/10.48123/rsgis.1327406

Abstract

Ormanlar, yaklaşık olarak yeryüzünün üçte birini kaplayan, gezegendeki biyoçeşitliliğin yarısından fazlasına ev sahipliği yapan, atmosfere salınan karbonun önemli bir miktarını tutan, iklim değişimi konusunda da güçlü bir etkiye sahip dünya ekosistemindeki çok önemli bir bileşendir. Ormanlık alanların biyokütlesinin doğru bir şekilde kestirilmesi, karbon salınımlarının azaltılması ve karbon yutak alanlarının artırılması kapsamında büyük önem taşımaktadır. Uydu teknolojilerinin ve uzaktan algılama sistemlerinin gelişmesiyle birlikte aktif ve pasif sistemler ile Toprak Üstü Biyokütlenin (TÜB) kestiriminin yapılması mümkün hale gelmiştir. Bu çalışmada, Bartın’daki sahil çamı (Pinus pinaster Ait.) ağaçlandırmalarında, Avrupa Uzay Ajansı (ESA) tarafından araştırmacılara ücretsiz sunulan Sentinel-1 radar, Sentinel-2 optik uydu verileri ile Çoklu Doğrusal Regresyon (ÇDR) ve Rastgele Orman (RO) yöntemlerinden yararlanılarak bant ve bitki örtüsü indeksi değerlerinin TÜB kestirimine etkileri ve yersel örnekleme alan verilerinden elde edilen TÜB değerleri ile ilişkileri araştırılmaktadır. 16 modelin geliştirildiği çalışmada, Sentinel-1 VH geri saçılım değeri, Sentinel-2’den türetilmiş normalize edilmiş fark bitki örtüsü indeksi değeri (NDVI) füzyonu ve RO yöntemi kullanıldığı model ile TÜB kestiriminde en iyi sonuç elde edilmiştir (R2=0.61, RMSE= 49.412 t/ha).

Keywords

Biyokütle Toprak üstü biyokütle Sentinel-1 Sentinel-2 Sahil çamı

Supporting Institution

TÜBİTAK BİDEB

Thanks

Çalışma, TÜBİTAK BİDEB 2209-A Üniversite Öğrencileri Araştırma Projeleri Destekleme Programı kapsamında 2021/2 dönemi 1919B012106792 başvuru nolu proje olarak desteklenmiştir. Desteklerinden dolayı TÜBİTAK BİDEB ‘e ve uydu görüntülerinin ücretsiz olarak temin edilmesinde sağladığı imkanlardan dolayı Avrupa Uzay Ajansına (ESA) teşekkür ederiz.

References

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  • Breiman, L. (2001). Random Forests. Machine Learning, 45, 5–32. https://doi.org/10.1023/A:1010933404324
  • Çepel, N., Dündar, M., & Günel, A. (1977). Türkiye’nin önemli yetişme bölgelerinde saf sarıçam ormanlarının gelişimi ile bazı edafik ve fizyografik etmenler arasındaki ilişkiler (Proje No: TOAG 154). TÜBİTAK, Tarım ve Ormancılık Araştırma Grubu, TÜBİTAK Yayınları No:354, TOAG Seri No: 65, Ankara.
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  • Flores-Anderson, A. I., Herndon, K. E., Thapa, R. B., & Cherrington, E. (2019). The SAR handbook: Comprehensive methodologies for forest monitoring and biomass estimation (No. MSFC-E-DAA-TN67454). https://gis1.servirglobal.net/TrainingMaterials/SAR/SARHB_FullRes.pdf
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  • Georgopoulos, N., Sotiropoulos, C., Stefanidou, A., & Gitas, I. Z. (2022). Total Stem Biomass Estimation Using Sentinel-1 and -2 Data in a Dense Coniferous Forest of Complex Structure and Terrain. Forests, 13, 2157. https://doi.org/10.3390/f13122157
  • Ghasemi, N., Sahebi, M. R., & Mohammadzadeh, A. (2013). Biomass Estimation of a Temperate Deciduous Forest Using Wavelet Analysis. IEEE Transactions on Geoscience and Remote Sensing, 51(2), 765–776. https://doi.org/10.1109/TGRS.2012.2205260
  • Ghosh, P., Mandal, D., Bhattacharya, A., Nanda, M. K., & Bera, S. (2018). Assessing Crop Monitoring Potential of Sentinel-2 in A Spatio-Temporal Scale. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, XLII-5, 227–231. https://doi.org/10.5194/isprs-archives-XLII-5-227-2018
  • Guerra-Hernández, J., Narine, L. L., Pascual, A., Gonzalez-Ferreiro, E., Botequim, B., Malambo, L., Neuenschwander, A., Popescu, S. C., & Godinho, S. (2022). Aboveground biomass mapping by integrating ICESat-2, SENTINEL-1, SENTINEL-2, ALOS2/PALSAR2, and topographic information in Mediterranean forests. GIScience & Remote Sensing, 59(1), 1509–1533. https://doi.org/10.1080/15481603.2022.2115599
  • Günel, A. (1981). Orman Hasılat Bilgisi. İstanbul Üniversitesi Yayınları.
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There are 51 citations in total.

Details

Primary Language Turkish
Subjects Photogrammetry and Remote Sensing
Journal Section Research Articles
Authors

Eren Gürsoy Özdemir 0000-0002-1829-9624

Aziz Demiralay This is me 0009-0003-5814-1607

Batuhan Şahin This is me 0009-0003-8646-4980

Early Pub Date March 24, 2024
Publication Date March 28, 2024
Submission Date July 14, 2023
Acceptance Date November 1, 2023
Published in Issue Year 2024 Volume: 5 Issue: 1

Cite

APA Özdemir, E. G., Demiralay, A., & Şahin, B. (2024). Bartın’daki Sahil Çamı (Pinus pinaster Ait.) Ağaçlandırma Alanlarında Sentinel-1 ve Sentinel-2 Uydu Görüntüleri Kullanılarak Toprak Üstü Biyokütlenin Kestirilmesi. Türk Uzaktan Algılama Ve CBS Dergisi, 5(1), 15-27. https://doi.org/10.48123/rsgis.1327406
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