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Evaluating the potential of GF-1 pan-multispectral camera imagery for identifying the quasi-circular vegetation patches in the Yellow River Delta, China

机译:评估GF-1 PAN-MULTISP光谱相机图像的潜力,用于识别黄河三角洲的准圆形植被斑块

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Gaofen-1 (GF-1) is the first high resolution optical imaging satellite of China primary civilian Earth observation project under the China High-resolution Earth Observation System. With the GF-1 trio launched on March 31, 2018, the combined 3+1 GF-1 constellation will offer one-day revisit coverage, which provides more available high resolution remote sensing images for monitoring decametric-scale vegetation patches and long-term pattern dynamics. In this study, a panchromatic image, the original multispectral image, and the pan-sharpened multispectral image from GF-1 Panmultispectral Camera was compared to evaluate their potential for identifying the quasi-circular vegetation patches (QVPs) in the Yellow River Delta, China. The results showed that high spatial resolution was more important for identifying the QVPs than more additional spectral bands of GF-1, and the pan-sharpened multispectral image had the highest identification accuracy of the QVPs (F-measure is 64.6%). In the future, multi-temporal pan-sharpened GF-1 images should be used to obtain higher accuracy, which is basis for studying vegetation patch pattern dynamics.
机译:高芬-1(GF-1)是中国高分辨率地球观测系统下中国小平民地球观测项目的第一个高分辨率光学影像卫星。在2018年3月31日推出的GF-1 TRIO时,合并的3 + 1 GF-1星座将提供一天的Revisit覆盖范围,为监测欺诈型植被斑块和长期提供更多可用的高分辨率遥感图像模式动态。在该研究中,比较了来自GF-1 Panmultispectral相机的全色图像,原始多光谱图像和PAN尖锐的多光谱图像,以评估它们在中国黄河三角洲识别准圆形植被斑块(QVPS)的可能性。结果表明,对于鉴定QVP而言,高空间分辨率比GF-1的更多额外光谱带更重要,并且PAN锐化的多光谱图像具有QVPS的最高识别精度(F测量值为64.6%)。将来,应使用多时间泛尖锐的GF-1图像来获得更高的准确性,即研究植被补丁模式动态的基础。

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