Estimating Aboveground Biomass in Dense Hyrcanian Forests by the Use of Sentinel-2 Data
Due to the challenges brought by field measurements to estimate the aboveground biomass (AGB), such as the remote locations and difficulties in walking in these areas, more accurate and cost-effective methods are required, by the use of remote sensing. In this study, Sentinel-2 data were used for es...
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MDPI AG
2022-01-01
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| Series: | Forests |
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| Online Access: | https://www.mdpi.com/1999-4907/13/1/104 |
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| author | Fardin Moradi Ali Asghar Darvishsefat Manizheh Rajab Pourrahmati Azade Deljouei Stelian Alexandru Borz |
| author_facet | Fardin Moradi Ali Asghar Darvishsefat Manizheh Rajab Pourrahmati Azade Deljouei Stelian Alexandru Borz |
| author_sort | Fardin Moradi |
| collection | DOAJ |
| description | Due to the challenges brought by field measurements to estimate the aboveground biomass (AGB), such as the remote locations and difficulties in walking in these areas, more accurate and cost-effective methods are required, by the use of remote sensing. In this study, Sentinel-2 data were used for estimating the AGB in pure stands of <i>Carpinus betulus</i> (L., common hornbeam) located in the Hyrcanian forests, northern Iran. For this purpose, the diameter at breast height (DBH) of all trees thicker than 7.5 cm was measured in 55 square plots (45 × 45 m). In situ AGB was estimated using a local volume table and the specific density of wood. To estimate the AGB from remotely sensed data, parametric and nonparametric methods, including Multiple Regression (MR), Artificial Neural Network (ANN), k-Nearest Neighbor (kNN), and Random Forest (RF), were applied to a single image of the Sentinel-2, having as a reference the estimations produced by in situ measurements and their corresponding spectral values of the original spectral (B2, B3, B4, B5, B6, B7, B8, B8a, B11, and B12) and derived synthetic (IPVI, IRECI, GEMI, GNDVI, NDVI, DVI, PSSRA, and RVI) bands. Band 6 located in the red-edge region (0.740 nm) showed the highest correlation with AGB (<i>r</i> = −0.723). A comparison of the machine learning methods indicated that the ANN algorithm returned the best ABG-estimating performance (<i>%RMSE</i> = 19.9). This study demonstrates that simple vegetation indices extracted from Sentinel-2 multispectral imagery can provide good results in the AGB estimation of <i>C. betulus</i> trees of the Hyrcanian forests. The approach used in this study may be extended to similar areas located in temperate forests. |
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| institution | Directory Open Access Journal |
| issn | 1999-4907 |
| language | English |
| last_indexed | 2024-03-10T01:28:16Z |
| publishDate | 2022-01-01 |
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| spelling | doaj.art-ee45c41f1a4c475bb8f6d429ca188d7d2023-11-23T13:47:54ZengMDPI AGForests1999-49072022-01-0113110410.3390/f13010104Estimating Aboveground Biomass in Dense Hyrcanian Forests by the Use of Sentinel-2 DataFardin Moradi0Ali Asghar Darvishsefat1Manizheh Rajab Pourrahmati2Azade Deljouei3Stelian Alexandru Borz4Department of Forestry and Forest Economics, Faculty of Natural Resources, University of Tehran, Karaj P.O. Box 1417643184, IranDepartment of Forestry and Forest Economics, Faculty of Natural Resources, University of Tehran, Karaj P.O. Box 1417643184, IranDepartment of Forestry and Forest Economics, Faculty of Natural Resources, University of Tehran, Karaj P.O. Box 1417643184, IranDepartment of Forest Engineering, Forest Management Planning and Terrestrial Measurements, Faculty of Silviculture and Forest Engineering, Transilvania University of Brasov, Şirul Beethoven 1, 500123 Brasov, RomaniaDepartment of Forest Engineering, Forest Management Planning and Terrestrial Measurements, Faculty of Silviculture and Forest Engineering, Transilvania University of Brasov, Şirul Beethoven 1, 500123 Brasov, RomaniaDue to the challenges brought by field measurements to estimate the aboveground biomass (AGB), such as the remote locations and difficulties in walking in these areas, more accurate and cost-effective methods are required, by the use of remote sensing. In this study, Sentinel-2 data were used for estimating the AGB in pure stands of <i>Carpinus betulus</i> (L., common hornbeam) located in the Hyrcanian forests, northern Iran. For this purpose, the diameter at breast height (DBH) of all trees thicker than 7.5 cm was measured in 55 square plots (45 × 45 m). In situ AGB was estimated using a local volume table and the specific density of wood. To estimate the AGB from remotely sensed data, parametric and nonparametric methods, including Multiple Regression (MR), Artificial Neural Network (ANN), k-Nearest Neighbor (kNN), and Random Forest (RF), were applied to a single image of the Sentinel-2, having as a reference the estimations produced by in situ measurements and their corresponding spectral values of the original spectral (B2, B3, B4, B5, B6, B7, B8, B8a, B11, and B12) and derived synthetic (IPVI, IRECI, GEMI, GNDVI, NDVI, DVI, PSSRA, and RVI) bands. Band 6 located in the red-edge region (0.740 nm) showed the highest correlation with AGB (<i>r</i> = −0.723). A comparison of the machine learning methods indicated that the ANN algorithm returned the best ABG-estimating performance (<i>%RMSE</i> = 19.9). This study demonstrates that simple vegetation indices extracted from Sentinel-2 multispectral imagery can provide good results in the AGB estimation of <i>C. betulus</i> trees of the Hyrcanian forests. The approach used in this study may be extended to similar areas located in temperate forests.https://www.mdpi.com/1999-4907/13/1/104aboveground biomassestimationremote sensingSentinel-2Iranmultiple regression |
| spellingShingle | Fardin Moradi Ali Asghar Darvishsefat Manizheh Rajab Pourrahmati Azade Deljouei Stelian Alexandru Borz Estimating Aboveground Biomass in Dense Hyrcanian Forests by the Use of Sentinel-2 Data Forests aboveground biomass estimation remote sensing Sentinel-2 Iran multiple regression |
| title | Estimating Aboveground Biomass in Dense Hyrcanian Forests by the Use of Sentinel-2 Data |
| title_full | Estimating Aboveground Biomass in Dense Hyrcanian Forests by the Use of Sentinel-2 Data |
| title_fullStr | Estimating Aboveground Biomass in Dense Hyrcanian Forests by the Use of Sentinel-2 Data |
| title_full_unstemmed | Estimating Aboveground Biomass in Dense Hyrcanian Forests by the Use of Sentinel-2 Data |
| title_short | Estimating Aboveground Biomass in Dense Hyrcanian Forests by the Use of Sentinel-2 Data |
| title_sort | estimating aboveground biomass in dense hyrcanian forests by the use of sentinel 2 data |
| topic | aboveground biomass estimation remote sensing Sentinel-2 Iran multiple regression |
| url | https://www.mdpi.com/1999-4907/13/1/104 |
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