Intelligence in Ecology: How Internet of Things Expands Insights into the Missing CO2 Sink
文献类型：期刊论文
| 作者 | Wang, Wenfeng1; Chen, Xi1; Zheng, Hongwei1; Lv, Zhihan1; Liu, Zhengjia1; Qian, Jing1; Hu, Ping1 |
| 刊名 | SCIENTIFIC PROGRAMMING
 |
| 出版日期 | 2016 |
| 关键词 | CONTINUOUS WAVELET TRANSFORMS UNCERTAINTY PRINCIPLE MATRIX DILATIONS FRAMES |
| 通讯作者 | Chen, X (reprint author), Chinese Acad Sci, Xinjiang Inst Ecol & Geog, State Key Lab Desert & Oasis Ecol, Urumqi 830011, Peoples R China. |
| 英文摘要 | Arid region characterizes more than 30% of the Earth's total land surface area and the area is still increasing due to the trends of desertification, yet the extent to which it modulates the global C balance has been inadequately studied. As an emerging technology, IoT monitoring can combine researchers, instruments, and field sites and generate archival data for a better understanding of soil abiotic CO2 uptake in arid region. Images' similarity analyses based on IoT monitoring can help ecologists to find sites where the abiotic uptake can temporally dominate and how the negative soil respiration fluxes were produced, while IoT monitoring with a set of intelligent video recognition algorithms enables ecologists to revisit these sites and the experiments details through the videos. Therefore, IoT monitoring of geospatial images, videos, and associated optimization and control algorithms should be a research priority towards expanding insights for soil abiotic CO2 uptake and a better understanding of how the uptake happens in arid region. Nevertheless, there are still considerable uncertainties and difficulties in determining the overall perspective of IoT monitoring for insights into the missing CO2 sink. |
| 学科主题 | Computer Science |
| 类目[WOS] | Computer Science, Software Engineering |
| 收录类别 | SCI |
| 语种 | 英语 |
| WOS记录号 | WOS:000383530600001 |
| 源URL | [http://ir.radi.ac.cn/handle/183411/39515]  |
| 专题 | 遥感与数字地球研究所_SCI/EI期刊论文_期刊论文 |
| 作者单位 | 1.Chinese Acad Sci, Xinjiang Inst Ecol & Geog, State Key Lab Desert & Oasis Ecol, Urumqi 830011, Peoples R China 2.Chinese Acad Sci, Shenzhen Inst Adv Technol, High Performance Comp Ctr, Shenzhen 518055, Peoples R China 3.Chinese Acad Sci, Inst Remote Sensing & Digital Earth, State Key Lab Remote Sensing Sci, Beijing 100101, Peoples R China 4.Chinese Acad Sci, Shenzhen Inst Adv Technol, Ctr Geospatial Informat, Shenzhen 518055, Peoples R China |
| 推荐引用方式 GB/T 7714 | Wang, Wenfeng,Chen, Xi,Zheng, Hongwei,et al. Intelligence in Ecology: How Internet of Things Expands Insights into the Missing CO2 Sink[J]. SCIENTIFIC PROGRAMMING,2016. |
| APA | Wang, Wenfeng.,Chen, Xi.,Zheng, Hongwei.,Lv, Zhihan.,Liu, Zhengjia.,...&Hu, Ping.(2016).Intelligence in Ecology: How Internet of Things Expands Insights into the Missing CO2 Sink.SCIENTIFIC PROGRAMMING. |
| MLA | Wang, Wenfeng,et al."Intelligence in Ecology: How Internet of Things Expands Insights into the Missing CO2 Sink".SCIENTIFIC PROGRAMMING (2016). |
入库方式： OAI收割
来源：遥感与数字地球研究所
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