Knowledge Resource Center for Ecological Environment in Arid Area
| DOI | 10.3390/rs13020233 |
| Assessing Leaf Biomass of Agave sisalana Using Sentinel-2 Vegetation Indices | |
| Vuorinne, Ilja; Heiskanen, Janne; Pellikka, Petri K. E. | |
| 通讯作者 | Heiskanen, J (corresponding author), Univ Helsinki, Dept Geosci & Geog, Helsinki 00014, Finland. ; Heiskanen, J (corresponding author), Univ Helsinki, Inst Atmospher & Earth Syst Res, Fac Sci, Helsinki 00014, Finland. |
| 来源期刊 | REMOTE SENSING
 |
| EISSN | 2072-4292 |
| 出版年 | 2021 |
| 卷号 | 13期号:2 |
| 英文摘要 | Biomass is a principal variable in crop monitoring and management and in assessing carbon cycling. Remote sensing combined with field measurements can be used to estimate biomass over large areas. This study assessed leaf biomass of Agave sisalana (sisal), a perennial crop whose leaves are grown for fibre production in tropical and subtropical regions. Furthermore, the residue from fibre production can be used to produce bioenergy through anaerobic digestion. First, biomass was estimated for 58 field plots using an allometric approach. Then, Sentinel-2 multispectral satellite imagery was used to model biomass in an 8851-ha plantation in semi-arid south-eastern Kenya. Generalised Additive Models were employed to explore how well biomass was explained by various spectral vegetation indices (VIs). The highest performance (explained deviance = 76%, RMSE = 5.15 Mg ha(-1)) was achieved with ratio and normalised difference VIs based on the green (R560), red-edge (R740 and R783), and near-infrared (R865) spectral bands. Heterogeneity of ground vegetation and resulting background effects seemed to limit model performance. The best performing VI (R740/R783) was used to predict plantation biomass that ranged from 0 to 46.7 Mg ha(-1) (mean biomass 10.6 Mg ha(-1)). The modelling showed that multispectral data are suitable for assessing sisal leaf biomass at the plantation level and in individual blocks. Although these results demonstrate the value of Sentinel-2 red-edge bands at 20-m resolution, the difference from the best model based on green and near-infrared bands at 10-m resolution was rather small. |
| 英文关键词 | generalized additive models remote sensing sisal crassuleacean acid metabolism multispectral precision agriculture bioenergy carbon |
| 类型 | Article |
| 语种 | 英语 |
| 开放获取类型 | Green Published, gold |
| 收录类别 | SCI-E |
| WOS记录号 | WOS:000611954100001 |
| WOS关键词 | RED-EDGE ; LANDSAT ; COVER ; PERFORMANCE ; YIELD ; RESOLUTION ; SCALES |
| WOS类目 | Environmental Sciences ; Geosciences, Multidisciplinary ; Remote Sensing ; Imaging Science & Photographic Technology |
| WOS研究方向 | Environmental Sciences & Ecology ; Geology ; Remote Sensing ; Imaging Science & Photographic Technology |
| 资源类型 | 期刊论文 |
| 条目标识符 | http://119.78.100.177/qdio/handle/2XILL650/348130 |
| 作者单位 | [Vuorinne, Ilja; Heiskanen, Janne; Pellikka, Petri K. E.] Univ Helsinki, Dept Geosci & Geog, Helsinki 00014, Finland; [Heiskanen, Janne] Univ Helsinki, Inst Atmospher & Earth Syst Res, Fac Sci, Helsinki 00014, Finland; [Pellikka, Petri K. E.] Wuhan Univ, State Key Lab Informat Engn Surveying Mapping & R, Wuhan 430000, Peoples R China |
| 推荐引用方式 GB/T 7714 | Vuorinne, Ilja,Heiskanen, Janne,Pellikka, Petri K. E.. Assessing Leaf Biomass of Agave sisalana Using Sentinel-2 Vegetation Indices[J],2021,13(2). |
| APA | Vuorinne, Ilja,Heiskanen, Janne,&Pellikka, Petri K. E..(2021).Assessing Leaf Biomass of Agave sisalana Using Sentinel-2 Vegetation Indices.REMOTE SENSING,13(2). |
| MLA | Vuorinne, Ilja,et al."Assessing Leaf Biomass of Agave sisalana Using Sentinel-2 Vegetation Indices".REMOTE SENSING 13.2(2021). |
| 条目包含的文件 | 条目无相关文件。 | |||||
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