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The Application of High Spatial Resolution Remote Sensing Image for Vegetation Type Recognition in Dagou Valley

机译:高分辨率遥感影像在大沟河谷植被类型识别中的应用

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This paper present a detail processing procedure about SPOT5 image applied for vegetation type recognition, and determines the capacity of high spatial resolution satellite image data to discriminate vegetation type in a complex ecosystem. A high spatial resolution SPOT5 image, captured in April 2005, and coincident field data covering the Dagou valley, was used in this analysis. Image geometric rectification and image fusion are then introduced to take prepare for classification. Subsequently, a maximum likelihood classification algorithm was applied to the SPOT5 image data to map the vegetation classes. Field validation and accuracy assessment are crucial to ensure the reliability of classification results. The strategy of field work and the resulting accuracy evaluations were presented, and yielded the high classification accuracy (overall accuracy=83.86%, Kappa=80.23%). The result showed that the information on vegetation types can be mapped effectively from high spatial resolution satellite image data.
机译:本文提出了一种用于植被类型识别的SPOT5图像的详细处理程序,并确定了高分辨率空间卫星图像数据在复杂生态系统中区分植被类型的能力。在此分析中,使用了高空间分辨率的SPOT5图像(于2005年4月捕获)以及覆盖大沟河谷的重合现场数据。然后引入图像几何校正和图像融合,为分类做准备。随后,将最大似然分类算法应用于SPOT5图像数据以映射植被类别。现场验证和准确性评估对于确保分类结果的可靠性至关重要。提出了野外工作策略和由此产生的准确性评估,并获得了很高的分类准确性(总体准确性= 83.86%,Kappa = 80.23%)。结果表明,可以从高分辨率的卫星图像数据中有效地映射有关植被类型的信息。

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