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Inter-satellite variability of grassland curing maps produced by different satellite sensors – Victoria, Australia
International Journal of Digital Earth ( IF 5.1 ) Pub Date : 2021-03-16 , DOI: 10.1080/17538947.2021.1900938
Sike Li 1
Affiliation  

ABSTRACT

Grassland fires are a serious problem in Victoria, Australia due to large quantity of dry grass. Grassland curing degree (GCD) measures the dryness of the grass and is an important factor for assessing grassland fire danger. Grassland curing maps (GCMs) display the spatial distribution of GCDs, but the quality of GCMs varies depending on the spatial resolution of the observing satellite remote sensing system. The higher the spatial resolution, the finer the GCD details and more spatial variations the GCM can reveal. In this study, GCD calculation algorithm named MapVictoria based on MODIS data is tested for Landsat 8 Sentinel 2; GCMs generated from these three satellites are contrasted by their GCD differences, defined here as inter-satellite variability (ISV). ISV is used to identify areas where higher resolution satellite GCMs should be used. Results show that spatial resolution difference (ΔSR), seasonality and geographical locations affect the magnitude of the ISV. Based on these findings, this paper provides recommendations to decision makers on where and when to use which satellite for grassland observations.



中文翻译:

不同卫星传感器产生的草原固化图的卫星间变异性——澳大利亚维多利亚

摘要

由于大量干草,草原火灾是澳大利亚维多利亚州的一个严重问题。草地固化度(GCD)衡量草地的干燥程度,是评估草地火灾危险性的重要因素。草地固化图(GCM)显示了 GCD 的空间分布,但 GCM 的质量取决于观测卫星遥感系统的空间分辨率。空间分辨率越高,GCD 细节越精细,GCM 可以揭示更多空间变化。在本研究中,基于 MODIS 数据的名为 MapVictoria 的 GCD 计算算法在 Landsat 8 Sentinel 2 上进行了测试;从这三颗卫星生成的 GCM 与其 GCD 差异形成对比,这里定义为卫星间变异性 (ISV)。ISV 用于识别应使用更高分辨率卫星 GCM 的区域。结果表明,空间分辨率差异 (ΔSR)、季节性和地理位置都会影响 ISV 的大小。基于这些发现,本文为决策者提供了关于何时何地使用哪颗卫星进行草原观测的建议。

更新日期:2021-03-16
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