Contents lists available at ScienceDirect Remote Sensing of Environment journal homepage: www.elsevier.com/locate/rse A patch-based algorithm for global and daily burned area mapping M.L. Campagnolo a, ⁎ , D. Oom a , M. Padilla b , J.M.C. Pereira a a Forest Research Centre, School of Agriculture, University of Lisbon, Portugal b Department of Geography, University of Leicester, United Kingdom of Great Britain and Northern Ireland ARTICLE INFO Keywords: Burned area Spatiotemporal patches Graphs Active fires MODIS Hybrid algorithm ABSTRACT Increasing availability of dense time series of moderate spatial resolution satellite data for mapping global burned areas calls for mapping algorithms designed to easily integrate data at different spatial and temporal resolutions, irrespective of particular grid constraints. In this paper, we describe a novel hybrid approach for global burned area mapping that combines active fire data and time series of surface reflectance using graphs, which provide a flexible and efficient way of extracting spatiotemporal consistent patches. Our approach has three main steps. Firstly, we analyze burn-sensitive vegetation index time series to de- termine for each location a set of events, which are the dates for which the spectral-temporal signal indicates the possibility of a burn. Secondly, we explore the spatiotemporal distribution of all events and active fires to determine a subset of events with strong evidence of corresponding to burned areas. Those events are used as positive occurrences for training a one-class maximum entropy classifier and obtain, for each candidate event, a likelihood of it actually corresponding to a burn. Finally, we build a graph that combines all previous in- formation, from which we extract spatiotemporal patches of densely connected events. Patches with strong evidence of burning determine the burned area map at any given time period. This research is part of the European Space Agency's Climate Change Initiative (ESA-CCI) and aims ultimately at generating Sentinel-3 daily global burned area products at 500 m spatial resolution. Towards that end, we test our approach with spatially and spectrally similar MODIS gridded surface reflectance (MOD/MYD09GA), as well as non-gridded active fire (MCD14ML) 2008 data and CCI global land cover maps. Using 105 independent Landsat fire reference perimeters to validate global results, we show that our algorithm applied to MOD/ MYD09GA data (PT-M09) has very similar accuracy (44%) measured by the Dice coefficient compared with MCD64A1 v006 (45%). Moreover, PT-M09 exhibits a higher commission error but a lower omission error than MCD64A1. Due to their coarse resolution, this kind of product cannot capture very small burn areas. The bias relative to the reference burned area indicates that the algorithm presented in the current study underestimates burned area by 14% of the area actually burned according to reference data, which is lower than the under- estimation in MCD64A1 (28%). We also analyzed the temporal accuracy of the patch based algorithm and concluded that the average time difference to active fires detection is 3.43 days, which is similar to MCD64A1 (3.75 days). Finally, we performed a sensitivity analysis which shows that total mapped burned areas varies only 3% when the main algorithm threshold that separates “burned” and “unburned” patches varies from quantile 45% to 55%. 1. Introduction As a global ecological factor affecting atmospheric and terrestrial systems over multiple temporal and spatial scales (Bowman et al., 2009), fire disturbance has been recognized as one of the Essential Climate Variables (ECV) defined by the Global Climate Observing System (GCOS). Accordingly, the European Space Agency, under the framework of the Climate Change Initiative (ESA-CCI), has made concerted efforts to create new tools to explore Sentinel-3 imagery for the development of global burned area products. The algorithm de- scribed in this paper is part of that effort and is in particular designed to efficiently handle large volumes of daily global data, and to provide the necessary flexibility to combine high temporal resolution surface re- flectance imagery with other sources of burned area evidence, such as active fires from multiple sensors. Since at the time of writing major reprocessing of ESA/Sentinel-3 https://doi.org/10.1016/j.rse.2019.111288 Received 8 January 2019; Received in revised form 19 June 2019; Accepted 27 June 2019 ⁎ Corresponding author. E-mail addresses: mlc@isa.ulisboa.pt (M.L. Campagnolo), duarteoom@isa.ulisboa.pt (D. Oom), mp489@leicester.ac.uk (M. Padilla), jmcpereira@isa.ulisboa.pt (J.M.C. Pereira). Remote Sensing of Environment 232 (2019) 111288 0034-4257/ © 2019 Elsevier Inc. All rights reserved. T