Improvement of spatial estimation for soil organic carbon stocks in Yuksekova plain using Sentinel 2 imagery and gradient descent–boosted regression tree
Yazarlar (6)
Prof. Dr. Mesut Budak Siirt Üniversitesi, Türkiye
Elif Günal
Dr. Öğr. Üyesi Miraç Kılıç Adiyaman University, Türkiye
Prof. Dr. İsmail Çelik Çukurova Üniversitesi, Türkiye
Dr. Öğr. Üyesi Mesut Sırrı Siirt University, Türkiye
Doç. Dr. Nurullah ACİR Kırşehir Ahi Evran Üniversitesi, Türkiye
| Makale Türü |
Özgün Makale
(SSCI, AHCI, SCI, SCI-Exp dergilerinde yayınlanan tam makale)
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| Dergi Adı | ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH (Q1) | ||
| Dergi ISSN | 0944-1344 Dergi Bilgileri (2023) | ||
| Dergi Tarandığı Indeksler | SCI-Expanded | ||
| Makale Dili | Türkçe | Basım Tarihi | 04-2023 |
| Cilt / Sayı / Sayfa | 30 / 18 / 53253–53274 | DOI | 10.1007/s11356-023-26064-8 |
| Makale Linki | http://dx.doi.org/10.1007/s11356-023-26064-8 | ||
| UAK Araştırma Alanları |
Toprak Bilimi
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| Özet |
| Carbon sequestration in earth surface is higher than the atmosphere, and the amount of carbon stored in wetlands is much greater than all other land surfaces. The purpose of this study was to estimate soil organic carbon stocks (SOCS) and investigate spatial distribution pattern of Yuksekova wetlands and surrounding lands in Hakkari province of Turkey using machine learning and remote sensing data. Disturbed and undisturbed soil samples were collected from 10-cm depth in 50 locations differed with land use and land cover. Vegetation, soil, and moisture indices were calculated using Sentinel 2 Multispectral Sensor Instrument (MSI) data. Significant correlations (p≤0.01) were obtained between the indices and SOCS; thus, the remote sensing indices (ARVI 0.43, BI −0.43, GSI −0.39, GNDI 0.44, NDVI 0.44, NDWI 0.38, and SRCI 0.51) were used as covariates in multi-layer perceptron neural network (MLP) and … |
| Anahtar Kelimeler |
| Vegetation radiometric index, Soil radiometric index, Multi-layer perceptron neural network, CORINE land cover, Wetland |
BM Sürdürülebilir Kalkınma Amaçları
| Atıf Sayıları | |
| Web of Science | 22 |
| Google Scholar | 35 |