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首页> 外文会议>International Geoscience and Remote Sensing Symposium >Testing and Comparing the Applicability of Sentinel-2 and Landsat 8 Reflectance Data in Estimating Mountainous Herbaceous Biomass Before and After Fire Using Random Forest Modelling
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Testing and Comparing the Applicability of Sentinel-2 and Landsat 8 Reflectance Data in Estimating Mountainous Herbaceous Biomass Before and After Fire Using Random Forest Modelling

机译：使用随机森林建模之前和火灾估算山地草本生物量估算山地草本生物量的测试和比较

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摘要

Herbaceous biomass is an important indicator of rangeland quantity. Grasslands cover vast areas in South Africa. It supports livestock production which is crucial for livelihoods and biodiversity conservation including ecotourism and conservation purposes. Grasslands, especially the mountainous ones, are threatened by the number of factors including global environmental changes. Latter changes include climate change, overgrazing, a proliferation of invasive species, unmanaged fires, and other land-use changes. There is a need to continuously monitor grasslands and remote sensing is an ideal, particularly in mountainous areas. The objective of the study was to test and compare the applicability of Sentinel-2 and Landsat 8 data acquired before and after fire occurrence in estimating biomass in the Golden Gate Highland National Park (GGHNP). Random forest model was used to predict biomass using Sentinel-2 and Landsat 8 reflectance data. Sentinel-2 and Landsat 8 reflectance data explained over 80% of biomass variation in the mountainous areas. The results indicate that both Sentinel 2 and Landsat 8 provide useful information for grass biomass estimation in mountainous environments.
机译：草本生物量是牧场数量的重要指标。草原在南非覆盖了广阔的地区。它支持畜牧业生产，这对生计和生物多样性保护至关重要，包括生态旅游和保护目的。草原，尤其是山地，受到全球环境变化的因素的数量受到威胁。后一种变化包括气候变化，过度吸血，侵入性物种的扩散，无托管的火灾和其他土地使用变化。需要连续监控草原，遥感是一个理想的，特别是在山区。该研究的目的是测试并比较在估算金门高地国家公园（GGHNP）的生物量之前和之后获得的Sentinel-2和Landsat 8数据的适用性。随机森林模型用于使用Sentinel-2和Landsat 8反射数据来预测生物量。 Sentinel-2和Landsat 8反射数据在山区的80％以上解释了80％的生物量变化。结果表明，Sentinel 2和Landsat 8都为山区环境中的草生物量估计提供了有用的信息。

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