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首页> 外文期刊>Remote Sensing >Subpixel Inundation Mapping Using Landsat-8 OLI and UAV Data for a Wetland Region on the Zoige Plateau, China
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Subpixel Inundation Mapping Using Landsat-8 OLI and UAV Data for a Wetland Region on the Zoige Plateau, China

机译:使用Zosage高原湿地地区Landsat-8 OLI和UAV数据进行亚像素淹没制图

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摘要

Wetland inundation is crucial to the survival and prosperity of fauna and flora communities in wetland ecosystems. Even small changes in surface inundation may result in a substantial impact on the wetland ecosystem characteristics and function. This study presented a novel method for wetland inundation mapping at a subpixel scale in a typical wetland region on the Zoige Plateau, northeast Tibetan Plateau, China, by combining use of an unmanned aerial vehicle (UAV) and Landsat-8 Operational Land Imager (OLI) data. A reference subpixel inundation percentage (SIP) map at a Landsat-8 OLI 30 m pixel scale was first generated using high resolution UAV data (0.16 m). The reference SIP map and Landsat-8 OLI imagery were then used to develop SIP estimation models using three different retrieval methods (Linear spectral unmixing (LSU), Artificial neural networks (ANN), and Regression tree (RT)). Based on observations from 2014, the estimation results indicated that the estimation model developed with RT method could provide the best fitting results for the mapping wetland SIP (R2 = 0.933, RMSE = 8.73%) compared to the other two methods. The proposed model with RT method was validated with observations from 2013, and the estimated SIP was highly correlated with the reference SIP, with an R2 of 0.986 and an RMSE of 9.84%. This study highlighted the value of high resolution UAV data and globally and freely available Landsat data in combination with the developed approach for monitoring finely gradual inundation change patterns in wetland ecosystems.
机译:湿地淹没对于湿地生态系统中动植物群落的生存和繁荣至关重要。即使表面淹没的微小变化也可能对湿地生态系统的特征和功能产生重大影响。这项研究结合了无人机和Landsat-8作战陆地成像仪(OLI),提出了一种新的方法,用于在中国东北藏高原高原的Zoige高原典型湿地区域中的亚像素尺度上进行湿地淹没制图。 )数据。首先使用高分辨率UAV数据(0.16 m)生成Landsat-8 OLI 30 m像素比例下的参考子像素浸没百分比(SIP)图。然后,使用三种不同的检索方法(线性光谱分解(LSU),人工神经网络(ANN)和回归树(RT)),将参考SIP地图和Landsat-8 OLI图像用于开发SIP估计模型。根据2014年的观察结果,估计结果表明,与其他两种方法相比,使用RT方法开发的估计模型可以为测绘湿地SIP提供最佳拟合结果(R2 = 0.933,RMSE = 8.73%)。 RT方法提出的模型已通过2013年的观察得到验证,估计的SIP与参考SIP高度相关,R2为0.986,RMSE为9.84%。这项研究强调了高分辨率无人机数据和全球免费提供的Landsat数据的价值,并结合了用于监测湿地生态系统中精细渐进淹没变化模式的已开发方法。

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