Application of multispectral UAV to estimate mangrove biomass in Vietnam: A case study in Dong Rui commune, Quang Ninh Province

IF 1.8 Q3 ECOLOGY
D. Ngo, H. Nguyen, Khanh Nguyen, Cuong Dang, Hieu Nguyen, N. Dang, T. Pham
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引用次数: 0

Abstract

Mangroves play an important role in coastal estuarine areas with different ecological functions, such as reducing the impact of waves and currents, accumulating biomass and sequestering carbon. However, estimation of terrestrial biomass in mangrove areas, especially in Vietnam, has not been fully studied. The application of unmanned aerial vehicles (UAV), mounted with multispectral cameras combined with field verification is an effective method for estimating terrestrial biomass for mangroves, as it reduces field survey time and allows for greater spatial range research. In this study, ground biomass was estimated for the mangrove area in the Dong Rui commune, based on multispectral image data obtained from UAV and survey results in 16 standard cells measuring actual biomass according to four regression models: Log-Log, Log-Lin, Lin-Log and Lin-Lin. The results of comparing the data from these four models show that the log-log model has the highest accuracy with a high correlation coefficient (R2 = 0.831). Based on the results of the analysis and selection of ground-based biomass estimation models, a biomass map was established for the UAV flying area in the Dong Rui mangrove forest with biomass values ranging from 20 Mg/ha to 150 Mg/ha. In summary, we present a biomass estimation method through four basic linear regression models for mangrove areas, based on multispectral image data obtained from ultrahigh-resolution UAV. The resulting research results can serve as a basis for managers to calculate and synchronise the payment of carbon services, thus contributing to effectively promoting the livelihoods of local people.
多光谱无人机在越南红树林生物量估算中的应用——以广宁省东瑞公社为例
红树林在具有不同生态功能的沿海河口地区发挥着重要作用,如减少海浪和洋流的影响、积累生物量和固碳。然而,对红树林地区,特别是越南红树林地区陆地生物量的估计尚未得到充分研究。安装有多光谱相机并结合实地核查的无人机的应用是估计红树林陆地生物量的有效方法,因为它减少了实地调查时间,并允许进行更大的空间范围研究。在本研究中,根据无人机获得的多光谱图像数据和16个标准细胞的调查结果,根据Log-Log、Log-Lin、Lin-Log和Lin-Lin四个回归模型测量实际生物量,估算了东瑞公社红树林区域的地面生物量。对这四个模型的数据进行比较结果表明,log-log模型具有最高的精度,相关系数较高(R2=0.831)。基于对陆基生物量估算模型的分析和选择结果,建立了东瑞红树林无人机飞行区的生物量图,生物量值在20 Mg/ha至150 Mg/ha之间。总之,我们基于超高分辨率无人机获得的多光谱图像数据,通过四个基本的线性回归模型,提出了一种红树林区域生物量估计方法。由此产生的研究结果可以作为管理者计算和同步碳服务支付的基础,从而有助于有效促进当地人民的生计。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
One Ecosystem
One Ecosystem Environmental Science-Nature and Landscape Conservation
CiteScore
4.60
自引率
0.00%
发文量
26
审稿时长
12 weeks
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