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Remote sensing of fractional cover of vegetation and exposed bedrock for karst rocky desertification assessment

机译:岩溶岩石荒漠化评估植被植被分数覆盖的遥感

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The fractional cover of vegetation (PV) and exposed bedrock are key ecological indicators of the extent and degree of land degradation in karst regions. In this study, we suggested and compared new methodology for direct and objective estimation of key indicators of karst rocky desertification with hyperspectral and multispectral imagery. The results showed that the Hyperion estimated fractional covers of PV had good correlation with the field surveyed fractional covers and the R2 (coefficient of determination) and RMSE (root mean square error) for PV was 0.91 and 0.05, respectively; while for exposed bedrock was not so good, 0.53 and 0.11, respectively. It demonstrated that hyperspectral imagery was able to directly estimate the key ecological indicators of karst rocky desertification, which was in a heterogeneous landscape. As for the ASTER imagery, the results were not so accurate. It showed that multispectral imagery could not be used to effectively estimate the fractional cover of PV and exposed bedrock. Our study indicates that it could use hyperspectral imagery to directly and effectively estimate the fractional cover of PV and exposed bedrock for karst rocky desertification assessment in a heterogeneous landscape of karst ecosystem.
机译:植被(PV)和暴露的基岩的分数覆盖是喀斯特地区土地降解程度和程度的关键生态指标。在这项研究中,我们建议并比较了具有高光谱和多光谱图像的喀斯特岩石荒漠化关键指标的直接和客观估算新方法。结果表明,PV的Hyperion估计的分数盖与PV的场测量的分数盖和R2(判定系数)和R2(均方根误差)分别为0.91和0.05,分别与0.91和0.05的R2(均方根均误差)良好;虽然对于暴露的基岩,但不太好,0.53和0.11。它表明,高光谱图像能够直接估计喀斯特岩石荒漠化的关键生态指标,这是一种异质景观。至于Aster Imagery,结果并不是如此准确。它表明,多光谱图像不能用于有效地估计光伏和暴露基岩的分数盖。我们的研究表明,它可以使用高光谱图像直接和有效地估计在喀斯特生态系统的异构景观中喀斯特岩石荒漠化评估的PV和暴露基岩的分数覆盖。

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