利用哨点图像估算河内市quoc oai地区水稻生物量

Khac Dang Vu, Trang Doan Hoai
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引用次数: 0

摘要

在水稻生产过程中,秸秆剩余物之一由于露天焚烧产生温室气体排放,成为环境污染物。这就是为什么气体排放的识别需要估计水稻生物量的数量。利用遥感数据确定河内市国海区水稻种植面积并估算干稻生物量。一方面,利用Sentinel-2遥感影像对土地覆盖类型进行分类,识别水稻的空间分布,并通过回归分析得到水稻生物量的范围;另一方面,利用Sentinel-1雷达图像计算夏季的水稻生物量,而Sentinel-2图像受到云雾和薄雾的限制。验证后的图像分类总体准确率为86.31%,Kappa指数为0.81。同时,回归分析表明,雷达图像中VV和VH的后向散射值与地面实测干稻生物量具有较高的相关性(R = 0.923, R2 = 0.852),平均误差较低(RMSE = 6.58 kg\100 m2)。通过线性回归方法,研究发现,整个青海地区的干稻米总生物量为28728.5吨,这是在2021年夏秋稻种植后揭示的。这项研究的结果证明了该方法的有效性,并有助于支持管理人员在未来提出适当的政策来监测和保护环境。
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USING SENTINEL IMAGES FOR THE ESTIMATION OF RICE BIOMASS IN QUOC OAI DISTRICT (HANOI)
During the rice production process, the rice straw - one of the residual products becomes an environmental pollutant due to the open burning giving rise to greenhouse gases emission. That’s why the identification of gas emissions needs to estimate the amount of rice biomass. Remote sensing data has been exploited to determine the area of rice cultivation and to estimate the dry rice biomass in Quoc Oai district, Hanoi city. On the one hand, the Sentinel-2 image was used to classify the land cover categories, thereby identifying the spatial distribution of the rice to delimit the extent of rice biomass, which was obtained from regression analysis. On the other hand, the Sentinel-1 radar image was used to calculate the rice biomass during the summer season when Sentinel-2 images have constraints due to clouds, fog, and mist. The validation of image classification has provided an overall accuracy of 86.31% with a Kappa index of 0.81. Meanwhile, the regression analysis shows a high correlation between the backscattering values of VV and VH in the radar image and the dry rice biomass measured on the ground (R = 0.923 and R2 = 0.852), with a relatively low average error (RMSE = 6.58 kg\100 m2). By linear regression method, the study has found the total dry rice biomass of 28728.5 tons, which was revealed after the Summer-Autumn rice crop 2021 for the whole Quoc Oai district. The results from this study have proved the effectiveness of the method and they have contributed to supporting managers in proposing the appropriate policies to monitor and protect the environment in the future.
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