地球信息科学学报 ›› 2018, Vol. 20 ›› Issue (11): 1667-1678.doi: 10.12082/dqxxkx.2018.180196
收稿日期:
2018-04-19
修回日期:
2018-08-25
出版日期:
2018-11-20
发布日期:
2018-11-28
通讯作者:
王静璞
E-mail:wang1636@sina.cn;wangjp@ldu.edu.cn
作者简介:
作者简介:王光镇(1991-),男,硕士生,主要从事草原植被遥感监测研究。E-mail:
基金资助:
WANG Guangzhen(), WANG Jingpu*(
), HAN Liu, CHAI Guoqi, WANG Zhoulong
Received:
2018-04-19
Revised:
2018-08-25
Online:
2018-11-20
Published:
2018-11-28
Contact:
WANG Jingpu
E-mail:wang1636@sina.cn;wangjp@ldu.edu.cn
Supported by:
摘要:
定量的估算非光合植被覆盖度(Fractional Cover of Non-photosynthetic Vegetation, fNPV)对草原生态系统碳储存、植被生产力、土壤侵蚀和火灾监测均具有重要的意义。本文以锡林郭勒草原实测高光谱和样方盖度为数据源,利用NPV(Non-Photosynthetic Vegetation)、PV(Photosynthetic Vegetation)、BS(Bare Soil)的平均光谱通过线性光谱混合模型模拟得到混合场景光谱,寻找区分NPV/PV/BS的敏感性波段,然后分别评价不同多光谱指数与fNPV的相关性。最后利用野外混合场景实验验证光谱指数估算fNPV的有效性。在此基础上,探讨基于OLI数据的NDVI(Normalized Difference Vegetation Index)-DFI(Dead Fuel Index)特征空间是否满足三元线性混合模型的基本假设。结果表明:短波红外(SWIR)波段是区分NPV/PV/BS的敏感性波段,以此为基础构建的OLI-DFI指数具备有效区分NPV/PV/BS的潜力。在模拟混合场景条件下,OLI-DFI和MODIS-DFI指数均与fNPV呈显著相关,决定性系数R2分别为0.84和0.94,均方根误差RMSE分别为0.09和0.05,而NDI和NDSVI指数与fNPV相关性很低。与模拟混合场景相比,在野外混合场景下OLI-DFI和MODIS-DFI指数估算fNPV的有效性均有一定程度的降低,R2分别为0.65和0.75,RMSE分别为0.14和0.12。基于OLI数据构建的NDVI-DFI特征空间满足三元线性混合模型的基本假设,可有效的估算fNPV。
王光镇, 王静璞, 韩柳, 柴国奇, 王周龙. 基于实测光谱模拟Landsat-8 OLI数据估算非光合 植被覆盖度[J]. 地球信息科学学报, 2018, 20(11): 1667-1678.
WANG Guangzhen,WANG Jingpu,HAN Liu,CHAI Guoqi,WANG Zhoulong. Estimating Fractional Cover of Non-photosynthetic Vegetation Using Field Spectral to Simulate Landsat-8 OLI[J]. Journal of Geo-information Science, 2018, 20(11): 1667-1678.
表2
3种混合场景下不同光谱指数与fNPV的R2"
组分状况 | 光谱指数 | 决定系数R2 | RMSE |
---|---|---|---|
NPV-PV-BS | OLI-DFI | 0.84*** | 0.09 |
MODIS-DFI | 0.94*** | 0.05 | |
NDI | 0.25** | 0.19 | |
NDSVI | 0.09* | 0.21 | |
NPV-PV | OLI-DFI | 0.98*** | 0.03 |
MODIS-DFI | 0.99*** | 0.03 | |
NDI | 0.99*** | 0.02 | |
NDSVI | 0.97*** | 0.02 | |
NPV-BS | OLI-DFI | 0.98*** | 0.04 |
MODIS-DFI | 0.99*** | 0.03 | |
NDI | 0.99*** | 0.01 | |
NDSVI | 0.99*** | 0.05 |
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