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A preliminary version of a global automatic burned-area (BA) algorithm at medium spatial resolution was developed in Google Earth Engine (GEE), based on Landsat or Sentinel-2 reflectance images. The algorithm involves two main steps: initial burned candidates are identified by analyzing spectral changes around MODIS hotspots, and those candidates are then used to estimate the burn probability for each scene. The burning dates are identified by analyzing the temporal evolution of burn probabilities. The algorithm was processed, and its quality assessed globally using reference data from 2019 derived from Sentinel-2 data at 10 m, which involved 369 pairs of consecutive images in total located in 50 20 × 20 km2 areas selected by stratified random sampling. Commissions were around 10% with both satellites, although omissions ranged between 27 (Sentinel-2) and 35% (Landsat), depending on the selected resolution and dataset, with highest omissions being in croplands and forests; for their part, BA from Sentinel-2 data at 20 m were the most accurate and fastest to process. In addition, three 5 × 5 degree regions were randomly selected from the biomes where most fires occur, and BA were detected from Sentinel-2 images at 20 m. Comparison with global products at coarse resolution FireCCI51 and MCD64A1 would seem to show to a reliable extent that the algorithm is procuring spatially and temporally coherent results, improving detection of smaller fires as a consequence of higher-spatial-resolution data. The proposed automatic algorithm has shown the potential to map BA globally using medium-spatial-resolution data (Sentinel-2 and Landsat) from 2000 onwards, when MODIS satellites were launched.

Dam removal has been demonstrated to be one of the most frequent and effective fluvial restoration actions but at most dam removals, especially of small dams, there has been little geomorphological monitoring. The results of the geomorphological monitoring implemented in two dams in the rivers Urumea and Leitzaran (northern Spain) are presented. The one from the River Urumea, originally 3.5 m high and impounding 500 m of river course, was removed instantaneously whereas that in the River Leitzaran, 12.5 m high, and impounding 1500 m of river course, is in its second phase of a four‐stage removal process. Changes in channel morphology, sediment size and mobility and river bed morphologies were assessed. The monitoring included several different techniques: topographical measurements of the channel, terrestrial laser scanner measurements of river bed and bars, sediment grain size and transport; all of them repeated in four (May, August, November 2011 and May 2012) and five (July and September 2013, April and August 2014 and June 2015) fieldwork campaigns in the River Urumea and River Leitzaran, respectively. Geomorphic responses of both dam removals are presented, and compared. Morphological channel adjustments occurred mainly shortly after dam removals, but with differences among the one removed instantaneously, that was immediate, whereas that conducted by stages took longer. Degradational processes were observed upstream of both dams (up to 1.2 m and 4 m in the River Urumea and River Leitzaran, respectively), but also aggradational processes (pool filling), upstream of Inturia Dam (2.85 m at least). Less evident aggradational processes were observed downstream of the dams (up to 0.37 m and 0.50 m in the River Urumea and River Leitzaran, respectively). Flood events, especially a 100 year flood registered during the monitoring period of Mendaraz Dam removal, reactivated geomorphological processes as incision and bank erosion, whereas longitudinal profile recovery, grain‐size sorting and upstream erosion took longer. Copyright © 2016 John Wiley & Sons, Ltd.

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