Fernando Sedano

Comprehensive Monitoring of Wildfires in Europe: The European Forest Fire Information System (EFFIS)

Fires are an integral component of ecosystem dynamics in European landscapes. However, uncontrolled fires cause large environmental and economic damages, especially in the Mediterranean region. On average, about 65000 fires occur in Europe every year, burning approximately half a million ha of wildland and forest areas; most of the burnt area, over 85%, is in the European Mediterranean region. Trends in number of fires and burnt areas in the Mediterranean region are presented in Fig. 1.

Mapping the Daily Progression of Large Wildland Fires Using MODIS Active Fire Data

High temporal resolution information on burnt area is needed to improve fire behaviour and emissions models. We used the Moderate Resolution Imaging Spectroradiometer (MODIS) thermal anomaly and active fire product (MO(Y)D14)asinputtoakriginginterpolationtoderivecontinuousmapsofthetimingofburntareafor16largewildland fires. For each fire, parameters for the kriging model were defined using variogram analysis. The optimal number of observations used to estimate a pixels time of burning varied between four and six among the fires studied. The median standarderrorfromkrigingrangedbetween0.80and3.56daysandthemedianstandarderrorfromgeolocationuncertainty was between 0.34 and 2.72 days. For nine fires in the south-western US, the accuracy of the kriging model was assessed using high spatial resolution daily fire perimeter data available from the US Forest Service. For these nine fires, we also assessed the temporal reporting accuracy of the MODIS burnt area products (MCD45A1 and MCD64A1). Averaged over the nine fires, the kriging method correctly mapped 73% of the pixels within the accuracy of a single day, compared with 33% for MCD45A1 and 53% for MCD64A1. Systematic application of this algorithm to wildland fires in the future may lead to new information about vegetation, climate and topographic controls on fire behaviour. Additional keywords: carbon emissions, fire growth, fire propagation, fire spread.

Quantifying fire-wide carbon emissions in interior Alaska using field measurements and Landsat imagery

Carbon emissions from boreal forest fires are projected to increase with continued warming and constitute a potentially significant positive feedback to climate change. The highest consistent combustion levels are reported in interior Alaska and can be highly variable depending on the consumption of soil organic matter. Here we present an approach for quantifying emissions within a fire perimeter using remote sensing of fire severity. Combustion from belowground and aboveground pools was quantified at 22 sites (17 black spruce and five white spruce-aspen) within the 2010 Gilles Creek burn in interior Alaska, constrained by data from eight unburned sites. We applied allometric equations and estimates of consumption to calculate carbon losses from aboveground vegetation. The position of adventitious spruce roots within the soil column, together with estimated prefire bulk density and carbon concentrations, was used to quantify belowground combustion. The differenced Normalized Burn Ratio (dNBR) exhibited a clear but nonlinear relationship with combustion that differed by forest type. We used a multiple regression model based on transformed dNBR and deciduous fraction to scale carbon emissions to the fire perimeter, and a Monte Carlo framework to assess uncertainty. Because of low-severity and unburned patches, mean combustion across the fire perimeter (1.98 ± 0.34 kg C m−2) was considerably less than within a defined core burn area (2.67 ± 0.40 kg C m−2) and the mean at field sites (2.88 ± 0.23 kg C m−2). These areas constitute a significant fraction of burn perimeters in Alaska but are generally not accounted for in regional-scale estimates. Although total combustion in black spruce was slightly lower than in white spruce-aspen forests, black spruce covered most of the fire perimeter (62%) and contributed the majority (67 ± 16%) of total emissions. Increases in spring albedo were found to be a viable alternative to dNBR for modeling emissions.

Increasing Spatial Detail of Burned Scar Maps Using IRS‑AWiFS Data for Mediterranean Europe

Abstract: A two stage burned scar detection approach is applied to produce a burned scar map for Mediterranean Europe using IRS-AWiFS imagery acquired at the end of the 2009 fire season. The first stage identified burned scar seeds based on a learning algorithm (Artificial Neural Network) coupled with a bootstrap aggregation process. The second stage implemented a region growing process to extend the area of the burned scars. Several ancillary datasets were used for the accuracy assessment and a final visual check was performed to refine the burned scar product. Training data for the learning algorithm were obtained from MODIS-based polygons, which were generated by the Rapid Damage Assessment module of the European Forest Fire Information System. The map produced from this research is the first attempt to increase the spatial detail of current burned scar maps for the Mediterranean region. The map has been analyzed and compared to existing burned area polygons from the European Forest Fire Information System. The comparison showed that the IRS-AWiFS-based burned scar map improved the delineation of burn scars; in addition the process identified a number of small burned scars that were not detected on lower resolution sensor data. Nonetheless, the results do not clearly support the improved capability for the detection of smaller burned scars. A number of reasons can be provided for the under-detection of burned scars, these include: the lack of a full coverage and cloud free imagery, the time lag between forest fires and image acquisition date and the occurrence of fires after the image acquisition dates. On the other hand, the limited

A global view of shifting cultivation: Recent, current, and future extent

Mosaic landscapes under shifting cultivation, with their dynamic mix of managed and natural land covers, often fall through the cracks in remote sensing–based land cover and land use classifications, as these are unable to adequately capture such landscapes’ dynamic nature and complex spectral and spatial signatures. But information about such landscapes is urgently needed to improve the outcomes of global earth system modelling and large-scale carbon and greenhouse gas accounting. This study combines existing global Landsat-based deforestation data covering the years 2000 to 2014 with very high-resolution satellite imagery to visually detect the specific spatio-temporal pattern of shifting cultivation at a one-degree cell resolution worldwide. The accuracy levels of our classification were high with an overall accuracy above 87%. We estimate the current global extent of shifting cultivation and compare it to other current global mapping endeavors as well as results of literature searches. Based on an expert survey, we make a first attempt at estimating past trends as well as possible future trends in the global distribution of shifting cultivation until the end of the 21st century. With 62% of the investigated one-degree cells in the humid and sub-humid tropics currently showing signs of shifting cultivation—the majority in the Americas (41%) and Africa (37%)—this form of cultivation remains widespread, and it would be wrong to speak of its general global demise in the last decades. We estimate that shifting cultivation landscapes currently cover roughly 280 million hectares worldwide, including both cultivated fields and fallows. While only an approximation, this estimate is clearly smaller than the areas mentioned in the literature which range up to 1,000 million hectares. Based on our expert survey and historical trends we estimate a possible strong decrease in shifting cultivation over the next decades, raising issues of livelihood security and resilience among people currently depending on shifting cultivation.

A Kalman Filter-Based Method to Generate Continuous Time Series of Medium-Resolution NDVI Images

A data assimilation method to produce complete temporal sequences of synthetic medium-resolution images is presented. The method implements a Kalman filter recursive algorithm that integrates medium and moderate resolution imagery. To demonstrate the approach, time series of 30-m spatial resolution NDVI images at 16-day time steps were generated using Landsat NDVI images and MODIS NDVI products at four sites with different ecosystems and land cover-land use dynamics. The results show that the time series of synthetic NDVI images captured seasonal land surface dynamics and maintained the spatial structure of the landscape at higher spatial resolution. The time series of synthetic medium-resolution NDVI images were validated within a Monte Carlo simulation framework. Normalized residuals decreased as the number of available observations increased, ranging from 0.2 to below 0.1. Residuals were also significantly lower for time series of synthetic NDVI images generated at combined recursion (smoothing) than individually at forward and backward recursions (filtering). Conversely, the uncertainties of the synthetic images also decreased when the number of available observations increased and combined recursions were implemented.

Accuracy Assessment of a Remote Sensing-Based, Pan-European Forest Cover Map Using Multi-Country National Forest Inventory Data

A pan-European forest cover map (FMAP2006) was produced using a novel automated classification approach using remotely sensed data from fine resolution satellite instruments. In contrast to previous classification accuracy assessments of such continental scale land cover products, the current study aimed for a reliable assessment at different geographical levels: pan-European, regional and local level. A unique data set consisting of detailed field inventory plots was provided via a collaboration with the national forest inventories (NFIs) in Europe. Close to 900,000 field plots were available for the assessment. The fine spatial resolution of the FMAP2006 facilitated the label assignment of the field plots to subsets of mapped pixels for the accuracy assessment process, thereby overcoming scale and definition difficulties encountered in previous studies with coarser resolution products. An overall accuracy of 88% was achieved at pan-European level based on the field plots of the NFIs. It is demonstrated that important differences exist for the class accuracies in different geographical regions, particularly at the regional and local level.

Data Assimilation of PROBA-V 100 and 300 m

The project for on-board autonomy-vegetation (PROBA-V) satellite can produce global daily images at 300-m spatial resolution. Three sensors are mounted on the same platform. Two off-nadir-viewing sensors acquire imagery at 300-m spatial resolution, whereas a nadir-viewing sensor acquires imagery at 100-m spatial resolution. The swath of the nadir-viewing sensor is only half of the swath of a single off-nadir-viewing sensor. Using this sensor only, the revisit time is five days. Here, we present a data assimilation method to increase the temporal resolution of the 100-m product. The method implements a Kalman filter recursive algorithm that integrates the images at 100 and 300-m resolution to generate the assimilated imagery at the fine spatial detail (100 m). The proposed method can be applied for global products. In this study, it has been applied to a region in western Europe (Flanders) during the growing season. This region is particularly challenging due to frequent cloud cover (45% cloud cover on average). The assimilated product is a cloud-free time series at the temporal resolution of the 300-m data, while preserving the spatial detail of the 100-m data. Quantitative results show the potential of the method compared to a simple data assimilation and the Savitzky-Golay (SG) filter. The added value of the improved spatial resolution from 300 to 100 m has also been illustrated for monitoring agriculture via remote sensing in this area.

Investing in the Fight: Assessing the Use of the Commander's Emergency Response Program in Afghanistan

This report examines the use of the Commanders Emergency Response Program (CERP) in Afghanistan. It explores the effectiveness of CERP in supporting tactical operations in Afghanistan during the counterinsurgency-focused 2010–2013 time frame using both qualitative and quantitative methods and describes CERPs origins, history, and existing research on the effectiveness of CERP in Iraq and Afghanistan.