FIRED Angola Nov 2000 - July 2024
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This is event-level polygons for the fire event delineation (FIRED) product for ANGOLA from November 2000 to July 2024. It is derived from the MODIS MCD64A1 burned area product (see https://lpdaac.usgs.gov/products/mcd64a1v061/ for more details). The MCD64A1 is a monthly raster grid of estimated burned dates. Firedpy (https://github.com/earthlab/firedpy) is an algorithm that converts these rasters into events by stacking the entire time series into a spatial-temporal data cube, then uses an algorithm to assign event identification numbers to pixels that fit into the same 3-dimensional spatial temporal window. This particular dataset was created using a spatial parameter of 1 pixels and 5 days. Daily polygons are included and the event identification numbers are the same for both files, but the event-level product has only single polygons for each entire event, while the daily product has separate polygons for each date per event. See the associated paper for more details on the methods and more: Balch, J.K.; St. Denis, L.A.; Mahood, A.L.; Mietkiewicz, N.P.; Williams, T.M.; McGlinchy, J.; Cook, M.C. FIRED (Fire Events Delineation): An Open, Flexible Algorithm and Database of US Fire Events Derived from the MODIS Burned Area Product (2001–2019). Remote Sens. 2020, 12, 3498. https://doi.org/10.3390/rs12213498
本数据集为2000年11月至2024年7月安哥拉(ANGOLA)的火灾事件勾画(Fire Event Delineation, FIRED)产品的事件级多边形数据。其源自中分辨率成像光谱仪(MODIS)MCD64A1火烧面积产品(详细信息参见https://lpdaac.usgs.gov/products/mcd64a1v061/)。MCD64A1是包含估算过火日期的逐月栅格数据集。Firedpy算法(https://github.com/earthlab/firedpy)可将此类栅格转化为火灾事件:首先将完整时间序列堆叠为时空数据立方体(spatial-temporal data cube),随后通过算法为落入同一三维时空窗口的像元分配事件识别编号。本次发布的该数据集采用的空间参数为1个像元,时间参数为5天。数据集包含逐日多边形数据,两类文件的事件识别编号保持一致,但事件级产品仅为每个完整事件提供单个多边形,而逐日产品则为事件的每个日期生成独立多边形。有关方法及更多细节请参阅相关论文: Balch, J.K.; St. Denis, L.A.; Mahood, A.L.; Mietkiewicz, N.P.; Williams, T.M.; McGlinchy, J.; Cook, M.C. FIRED (Fire Events Delineation): An Open, Flexible Algorithm and Database of US Fire Events Derived from the MODIS Burned Area Product (2001–2019). Remote Sens. 2020, 12, 3498. https://doi.org/10.3390/rs12213498




