Research on linear and nonlinear spectral mixture models for estimating vegetation fractional cover of Nitraria bushes
文献类型：期刊论文
| 作者 | Ji, Cuicui1; Jia, Yonghong1; Li, Xiaosong1; Wang, Jinying1 |
| 刊名 | Yaogan Xuebao/Journal of Remote Sensing
 |
| 出版日期 | 2016 |
| 卷号 | 20期号:6页码:1402-1412 |
| 通讯作者 | Li, Xiaosong (lixs@radi.ac.cn) |
| 英文摘要 | Sand invasion is intensified by the serious degradation and disappearance of Nitraria bushes, which has a serious effect on the oasis ecological security of deserts. Quantitative analysis of different multiple scattering factors in mixed spectral contribution for the ecological environment on deserts is particularly important. Timely monitoring of spatial and temporal variations in photosynthetic/non-photosynthetic vegetation(PV/NPV) fraction cover provides essential information for guiding management practices on land desertification and research on vegetation recession mechanism. In this paper, taking the typical vegetation of Nitraria bushes in Minqin County of Gansu Province as an example, mixed and endmember spectra, and fraction information were acquired by ground-controlling spectroscopy experiment. Then, the fractional cover of PV(fpv) and that of NPV (fnpv) were estimated by linear and nonlinear spectral mixture models (NSMM) (including Kernel NSMM (KNSMM) and bilinear spectral mixture model (BSMM)), respectively. Fully constrained least square method was adopted to mix the models, and the fraction of every endmember and the accuracy information of all the samples were calculated. The performances of the models were compared based on root mean square error (RMSE) of the unmixing model and accuracy of field validation, and the endmember fraction of field validation is based on the abundance of digital image classification by the neural network classification algorithm. Results show that (1) compared with the traditional three-endmember model (PV, NPV, and bare soil (BS)), the four-endmember model, which incorporates an additional shadow endmember, can effectively improve both the accuracy of spectral mixture model(RMSE decreased from 0.0429 to 0.0052 and improved 16% in accuracy) and the estimation precision of fpvand fnpv(increased by 44% and 83%, respectively). (2)Moreover, the precision of the unmixing of model could be improved by BSMM considering the multiple scattering between NPV and BS endmembers. However, the improved precision was insignificant. Also, considering the nonlinear parameters, the performance of KNSMM was slightly lower than that of the LSMM model. (3) The validation RMSE of fpvwas 0.1177(R2=0.7049), and that of fnpvwas 0.0835 (R2=0.4896) with LSMM based on PV/NPV, BS, and shadow endmembers. Process monitoring describes the multiple photon-scattering effect among PV/NPV, BS, and shadows in Nitrariabushes. The selection and application of the types of NSMMs should be confirmed according to specific research object and the required precision. Shadows cannot be ignored in estimating vegetation fractional cover, especially in improving fnpvaccuracy. This finding illustrates that the types and number of endmembers chosen are significant in improving the accuracy of fraction estimation. The conclusion also shows that LSMM is suitable to estimate fpvand fnpvof Nitraria bushes accurately based on PV/NPV, BS, and shadow endmembers. © 2016, Science Press. All right reserved. |
| 收录类别 | EI |
| 语种 | 中文 |
| WOS记录号 | WOS:20165003125374 |
| 源URL | [http://ir.radi.ac.cn/handle/183411/39648]  |
| 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. School of Remote Sensing and Information Engineering, Wuhan University, Wuhan 2.430079, China 3. Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 4.100101, China |
| 推荐引用方式 GB/T 7714 | Ji, Cuicui,Jia, Yonghong,Li, Xiaosong,et al. Research on linear and nonlinear spectral mixture models for estimating vegetation fractional cover of Nitraria bushes[J]. Yaogan Xuebao/Journal of Remote Sensing,2016,20(6):1402-1412. |
| APA | Ji, Cuicui,Jia, Yonghong,Li, Xiaosong,&Wang, Jinying.(2016).Research on linear and nonlinear spectral mixture models for estimating vegetation fractional cover of Nitraria bushes.Yaogan Xuebao/Journal of Remote Sensing,20(6),1402-1412. |
| MLA | Ji, Cuicui,et al."Research on linear and nonlinear spectral mixture models for estimating vegetation fractional cover of Nitraria bushes".Yaogan Xuebao/Journal of Remote Sensing 20.6(2016):1402-1412. |
入库方式： OAI收割
来源：遥感与数字地球研究所
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