Quick Aboveground Carbon Stock Estimation of Densely Planted Shrubs by Using Point Cloud Derived from Unmanned Aerial Vehicle
文献类型：期刊论文
| 作者 | Zhang, Xueyan1,2 |
| 刊名 | REMOTE SENSING
 |
| 出版日期 | 2019-12-02 |
| 卷号 | 11期号:24页码:18 |
| 关键词 | unmanned aerial vehicle estimation model carbon sink aboveground carbon stock carbon trade densely planted shrub China |
| DOI | 10.3390/rs11242914 |
| 通讯作者 | Zhang, Xueyan(xyzhang@igsnrr.ac.cn) |
| 英文摘要 | Carbon sink trading is an important aspect of carbon trading in China, and can have important significance in offsetting carbon emissions and improving ecological compensation. The use of unmanned aerial vehicles (UAVs) offers new opportunities for shrub carbon sink and accounts as a substitute for time-consuming and expensive plot investigations to estimate the carbon sink by using the aboveground carbon stock monitored by UAV. However, the UAV-based estimation of the aboveground carbon stock of densely planted shrubs still faces certain challenges. The specific objectives of this research are as follows: (1) to test the statistical relationship between the aboveground carbon stock and volume of a densely planted shrub belt, and (2) to develop a model to estimate aboveground carbon stock by monitoring the volume of the densely planted shrub belt using a UAV. The study showed that (i) the aboveground carbon stock would increase with the increase in the volume of the shrub belt, (ii) an estimation model of the aboveground carbon stock of the densely planted shrub belt was developed (R-2=0.89, P<0.01), and (iii) the validation assessment to estimate aboveground carbon stock by using the UAV-based estimation model produced a coefficient of determination of R-2 = 0.74 and an overall root mean square error of 18.79 kg CO2e. Good prediction ability of the model was determined using leave-one-out cross-validation (LOOCV). This output information is valuable for the design of operations in the framework of precise carbon-sink accounting of shrubs. In addition, a method using an UAV was developed and validated for the quick estimation of aboveground carbon stock for densely planted shrubs, thereby providing a potential alternative to time-consuming and expensive plot investigations of aboveground carbon-stock accounting, which is necessary for shrub projects in the carbon trading market in China. |
| WOS关键词 | CROP SURFACE MODELS ; INNER-MONGOLIA ; UAV ; BIOMASS ; ALLOCATION ; IMAGERY ; HEIGHT ; CHINA ; TREES |
| 资助项目 | National Key R&D Program of China[2016YFC0500508] ; National Key R&D Program of China[2018YFC1508805] ; National Natural Science Foundation of China[31600351] ; Strategic Priority Research Program of Chinese Academy of Sciences[XDA20010302] |
| WOS研究方向 | Remote Sensing |
| 语种 | 英语 |
| WOS记录号 | WOS:000507333400030 |
| 出版者 | MDPI |
| 资助机构 | National Key R&D Program of China ; National Natural Science Foundation of China ; Strategic Priority Research Program of Chinese Academy of Sciences |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/131256]  |
| 专题 | 中国科学院地理科学与资源研究所 |
| 通讯作者 | Zhang, Xueyan |
| 作者单位 | 1.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Beijing 100101, Peoples R China 2.Chinese Acad Sci, Ctr Chinese Agr Policy, Beijing 100101, Peoples R China |
| 推荐引用方式 GB/T 7714 | Zhang, Xueyan. Quick Aboveground Carbon Stock Estimation of Densely Planted Shrubs by Using Point Cloud Derived from Unmanned Aerial Vehicle[J]. REMOTE SENSING,2019,11(24):18. |
| APA | Zhang, Xueyan.(2019).Quick Aboveground Carbon Stock Estimation of Densely Planted Shrubs by Using Point Cloud Derived from Unmanned Aerial Vehicle.REMOTE SENSING,11(24),18. |
| MLA | Zhang, Xueyan."Quick Aboveground Carbon Stock Estimation of Densely Planted Shrubs by Using Point Cloud Derived from Unmanned Aerial Vehicle".REMOTE SENSING 11.24(2019):18. |
入库方式： OAI收割
来源：地理科学与资源研究所
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