Modeling Soil CO2 Efflux in a Subtropical Forest by Combining Fused Remote Sensing Images with Linear Mixed Effect Models
文献类型：期刊论文
| 作者 | Ablat, Xarapat2; Huang, Chong2; Tang, Guoping; Erkin, Nurmemet1; Sawut, Rukeya4 |
| 刊名 | REMOTE SENSING
 |
| 出版日期 | 2023-03-01 |
| 卷号 | 15期号:5页码:1415 |
| 关键词 | forest soil carbon emission multisource remote sensing fusion land-atmosphere interactions regional earth system simulation tropical and subtropical forests |
| DOI | 10.3390/rs15051415 |
| 文献子类 | Article |
| 英文摘要 | Monitoring tropical and subtropical forest soil CO2 emission efflux (FSCO2) is crucial for understanding the global carbon cycle and terrestrial ecosystem respiration. In this study, we addressed the challenge of low spatiotemporal resolution in FSCO2 monitoring by combining data fusion and model methods to improve the accuracy of quantitative inversion. We used time series Landsat 8 LST and MODIS LST fusion images and a linear mixed effect model to estimate FSCO2 at watershed scale. Our results show that modeling without random factors, and the use of Fusion LST as the fixed predictor, resulted in 47% (marginal R-2 = 0.47) of FSCO2 variability in the Monthly random effect model, while it only accounted for 19% of FSCO2 variability in the Daily random effect model and 7% in the Seasonally random effect model. However, the inclusion of random effects in the model's parameterization improved the performance of both models. The Monthly random effect model that performed optimally had an explanation rate of 55.3% (conditional R-2 = 0.55 and t value > 1.9) for FSCO2 variability and yielded the smallest deviation from observed FSCO2. Our study highlights the importance of incorporating random effects and using Fusion LST as a fixed predictor to improve the accuracy of FSCO2 monitoring in tropical and subtropical forests. |
| WOS关键词 | LAND-SURFACE TEMPERATURE ; SPLIT-WINDOW ALGORITHM ; ATMOSPHERE CO2 ; MODIS DATA ; RESPIRATION ; LANDSAT-8 ; EXCHANGE ; RETRIEVAL |
| WOS研究方向 | Environmental Sciences & Ecology ; Geology ; Remote Sensing ; Imaging Science & Photographic Technology |
| WOS记录号 | WOS:000947891100001 |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/200726]  |
| 专题 | 资源与环境信息系统国家重点实验室_外文论文 |
| 作者单位 | 1.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, State Key Lab Resources & Environm Informat Syst, Beijing 100101, Peoples R China 2.Sun Yat Sen Univ, Sch Geog & Planning, Guangzhou 510275, Peoples R China 3.Xinjiang Normal Univ, Coll Geog Sci & Tourism, Urumqi 830054, Peoples R China 4.Xinjiang Agr Univ, Coll Resource & Environm, Urumqi 830052, Peoples R China |
| 推荐引用方式 GB/T 7714 | Ablat, Xarapat,Huang, Chong,Tang, Guoping,et al. Modeling Soil CO2 Efflux in a Subtropical Forest by Combining Fused Remote Sensing Images with Linear Mixed Effect Models[J]. REMOTE SENSING,2023,15(5):1415. |
| APA | Ablat, Xarapat,Huang, Chong,Tang, Guoping,Erkin, Nurmemet,&Sawut, Rukeya.(2023).Modeling Soil CO2 Efflux in a Subtropical Forest by Combining Fused Remote Sensing Images with Linear Mixed Effect Models.REMOTE SENSING,15(5),1415. |
| MLA | Ablat, Xarapat,et al."Modeling Soil CO2 Efflux in a Subtropical Forest by Combining Fused Remote Sensing Images with Linear Mixed Effect Models".REMOTE SENSING 15.5(2023):1415. |
入库方式： OAI收割
来源：地理科学与资源研究所
浏览0
下载0
收藏0
其他版本
除非特别说明，本系统中所有内容都受版权保护，并保留所有权利。