Enhancing phenology modeling through the integration of artificial light at night effects
文献类型：期刊论文
| 作者 | Xia, Haoming1,2,3; Qiao, Longxin; Guo, Yan; Ru, Xutong4,5; Qin, Yaochen; Zhou, Yuyu4,5; Wu, Chaoyang6 |
| 刊名 | REMOTE SENSING OF ENVIRONMENT
 |
| 出版日期 | 2024-03-15 |
| 卷号 | 303页码:113997 |
| 关键词 | Artificial light at night Climate change Day length Phenology Urbanization |
| DOI | 10.1016/j.rse.2024.113997 |
| 产权排序 | 7 |
| 文献子类 | Article ; Early Access |
| 英文摘要 | Spring vegetation phenology is closely influenced by photoperiod, and the presence of artificial light at Night (ALAN) therefore substantially impacts the phenological response of plants to climate change. How ALAN impacts spring phenology in relative to warming and what are the drivers regulate these impacts are not well understood. Here we focused on the extra-tropical terrestrial ecosystem (>30 degrees N) of China where the highest urbanization has experienced using satellite images to extract the start of the growing season (SOS) from three independent datasets, as well as ALAN data from harmonized global nighttime light (NTL over 2001-2018. We found that ALAN caused earlier SOS both at the ecosystem level and for the major climate zones, and this advanced effect weakened at lower latitude regions and for the high-altitude ecosystems. Further, we discovered that the advanced effect of ALAN on SOS was strengthened in areas with lower chilling days and with the increased distance from the city center. We therefore derived a new model for the estimation of SOS including the effects of ALAN and the new model provided improved representation of SOS in terms of higher proportions of significant pixels between model estimates and observations, higher correlation coefficients, lower root mean square error, Akaike information criterion and higher Kling-Gupta efficiency. Our results highlight that the effects of ALAN on SOS were influenced by latitude, elevation, and winter chilling. Overall, our study sheds light on the impact of human activities on plant spring phenology and provides insights for predicting plant growth patterns under future urbanization and global climate change. |
| WOS关键词 | DORMANCY RELEASE ; BUD BURST ; TREE ; AMPLIFICATION ; PHOTOPERIOD ; RESPONSES ; BUDBURST ; PREDICT ; AUTUMN ; GROWTH |
| WOS研究方向 | Environmental Sciences & Ecology ; Remote Sensing ; Imaging Science & Photographic Technology |
| 语种 | 英语 |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/202752]  |
| 专题 | 陆地表层格局与模拟院重点实验室_外文论文 |
| 作者单位 | 1.Henan Univ, Coll Geog & Environm Sci, Kaifeng 475004, Peoples R China 2.Xinyang Acad Ecol Res, Henan Dabieshan Natl Field Observat & Res Stn Fore, Kaifeng 475004, Peoples R China 3.Henan Univ, Henan Key Lab Integrated Air Pollut Control & Ecol, Kaifeng 475004, Peoples R China 4.Henan Univ, Key Lab Geospatial Technol Middle & Lower Yellow R, Minist Educ, Kaifeng 475004, Peoples R China 5.Univ Hong Kong, Dept Geog, Hong Kong 999077, Peoples R China 6.Univ Hong Kong, Urban Syst Inst, Hong Kong 999077, Peoples R China 7.Chinese Acad Sci, Key Lab Land Surface Pattern & Simulat, Inst Geog Sci & Nat Resources Res, Beijing 100101, Peoples R China |
| 推荐引用方式 GB/T 7714 | Xia, Haoming,Qiao, Longxin,Guo, Yan,et al. Enhancing phenology modeling through the integration of artificial light at night effects[J]. REMOTE SENSING OF ENVIRONMENT,2024,303:113997. |
| APA | Xia, Haoming.,Qiao, Longxin.,Guo, Yan.,Ru, Xutong.,Qin, Yaochen.,...&Wu, Chaoyang.(2024).Enhancing phenology modeling through the integration of artificial light at night effects.REMOTE SENSING OF ENVIRONMENT,303,113997. |
| MLA | Xia, Haoming,et al."Enhancing phenology modeling through the integration of artificial light at night effects".REMOTE SENSING OF ENVIRONMENT 303(2024):113997. |
入库方式： OAI收割
来源：地理科学与资源研究所
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