哥白尼气候变化服务烧伤面积组件的业务实施:从MODIS 250 m到OLCI300 m数据

Joshua Lizundia-Loiola, M. Franquesa, M. Boettcher, G. Kirches, M. L. Pettinari, E. Chuvieco
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引用次数: 1

摘要

摘要基于Sentinel-3海洋和陆地颜色仪(OLCI)近红外(NIR)反射和中分辨率成像光谱仪(MODIS)热异常数据,提出了一种新的全球300米可操作燃烧面积(BA)产品C3SBA10。该产品是在哥白尼气候变化服务(C3S)中生成的。由于C3S是一项欧洲服务,它的目标是广泛使用欧洲哥白尼卫星任务,称为哨兵。因此,该服务的一个组成部分是将以前开发的算法应用于Sentinel传感器。在BA数据集的情况下,由欧洲航天局(ESA)气候变化计划(CCI)开发的前体BA数据集(FireCCI51)基于MODIS传感器的250 m分辨率近红外波段,其工作重点是使该BA算法适应Sentinel-3 OLCI传感器的特征,后者提供与MODIS相似的空间和时间分辨率。作为BA算法的先驱,OLCI的算法以两阶段的方式将热异常和光谱信息结合起来,首先选择高概率被烧毁的热异常,减少调试错误,然后应用上下文增长来完全检测BA补丁,减少遗漏错误。新的BA产品包括S3 OLCI数据的完整时间序列(2017年至今)。按照FireCCI项目的规范,最终数据集以两种不同的格式提供:每月全分辨率大陆图和每月包含0.25度分辨率聚合数据的全局文件。为了便于全球植被动态和大气排放模式的使用,还包括了几个辅助层,如土地覆盖和无云观测。C3SBA10产品2017 - 2019年的年BA检测值分别为3.77 Mkm2、3.59 Mkm2和3.63 Mkm2。对C3SBA10和前体FireCCI51的质量和一致性进行了共同期(2017-2019)评估。采用分层随机抽样设计,使用来自Landsat-8图像的参考数据进行全球空间验证。C3SBA10显示的佣金错误在14 - 22%之间,遗漏错误在50 - 53%之间,与fireci51产品相似。使用470万起活火也验证了时间报告的准确性。88%的检测是在火灾后10天内完成的。C3SBA10和FireCCI51使用4种不同网格大小(0.050、0.10、0.25和0.50)进行的时空一致性评估显示,C3SBA10和FireCCI51的全球年相关性为0.93 ~ 0.99。这两个产品之间的高度一致性确保了从2001年到现在的全球BA数据提供。这些数据集可通过哥白尼气候数据存储库(DOI: https://doi.org/10.24381/cds.f333cf85, Lizundia-Loiola et al. (2020a))免费获得。
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Operational implementation of the burned area component of the Copernicus Climate Change Service: from MODIS 250 m to OLCI 300 m data
Abstract. This paper presents a new global, operational burned area (BA) product at 300 m, called C3SBA10, generated from Sentinel-3 Ocean and Land Colour Instrument (OLCI) near-infrared (NIR) reflectance and Moderate Resolution Imaging Spectroradiometer (MODIS) thermal anomaly data. This product was generated within the Copernicus Climate Change Service (C3S). Since C3S is a European service, it aims to use extensively the European Copernicus satellite missions, named Sentinels. Therefore, one of the components of the service is adapting previous developed algorithms to the Sentinel sensors. In the case of BA datasets, the precursor BA dataset (FireCCI51), which was developed within the European Space Agency's (ESA) Climate Change Initiative (CCI), was based on the 250 m-resolution NIR band of the MODIS sensor, and the effort has been focused on adapting this BA algorithm to the characteristics of the Sentinel-3 OLCI sensor, which provides similar spatial and temporal resolution to MODIS. As the precursor BA algorithm, the OLCI's one combines thermal anomalies and spectral information in a two-phase approach, where first thermal anomalies with a high probability of being burned are selected, reducing commission errors, and then a contextual growing is applied to fully detect the BA patch, reducing omission errors. The new BA product includes the full time-series of S3 OLCI data (2017–present). Following the specifications of the FireCCI project, the final datasets are provided in two different formats: monthly full-resolution continental tiles, and monthly global files with aggregated data at 0.25-degree resolution. To facilitate the use by global vegetation dynamics and atmospheric emission models several auxiliary layers were included, such as land cover and cloud-free observations. The C3SBA10 product detected 3.77 Mkm2, 3.59 Mkm2, and 3.63 Mkm2 of annual BA from 2017 to 2019, respectively. The quality and consistency assessment of C3SBA10 and the precursor FireCCI51 was done for the common period (2017–2019). The global spatial validation was performed using reference data derived from Landsat-8 images, following a stratified random sampling design. The C3SBA10 showed commission errors between 14–22 % and omission errors from 50 to 53 %, similar to those presented by the FireCCI51 product. The temporal reporting accuracy was also validated using 4.7 million active fires. 88 % of the detections were made within 10 days after the fire by both products. The spatial and temporal consistency assessment performed between C3SBA10 and FireCCI51 using four different grid sizes (0.05o, 0.10o, 0.25o, and 0.50o) showed global, annual correlations between 0.93 and 0.99. This high consistency between both products ensures a global BA data provision from 2001 to present. The datasets are freely available through the Copernicus Climate Data Store (CDS) repository (DOI: https://doi.org/10.24381/cds.f333cf85 , Lizundia-Loiola et al. (2020a)).
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