Cartografía de combustible y potenciales de incendio en el continente africano utilizando FCCS

Revista oficial de la Asociación Española de Teledetección[EN] This paper presents the methodology used for the development of a fuel map for the African Continent, using FCCS (Fuel Characteristic Classification System). The cartography of the fuelbeds was based on global cartographic information obtained from remote sensing imaging, and the variables associated to each fuelbed were extracted from existing vegetation databases. A total of 75 fuelbeds were developed, and from the variables assigned to each of them, different Fire Potentials were calculated using default environmental variables. These potentials allow the estimation of surface fire behavior, crown fire and available fuel, depending on the characteristics of the existing vegetation.[ES] Este trabajo presenta la metodología utilizada para el desarrollo de un mapa de combustibles para el con-tinente africano, utilizando el Sistema FCCS (Fuel Characteristic Classification System). La cartografía de los perfiles de combustible se basó en el uso de información cartográfica global obtenida mediante teledetección, y las variables asociadas se extrajeron de bases de datos de vegetación existentes. Se generaron un total de 75 perfiles de combusti-ble, y a partir de las variables asignadas a cada uno se calcularon distintos Potenciales de Incendio utilizando valores de variables ambientales estándar. Estos potenciales permiten estimar el comportamiento del fuego de superficies, el fuego de copas, y la cantidad de combustible disponible, en función de las características de la vegetación existente.Al proyecto CERESS (Coupling land surface Energy and water balance from Remote sensing for mapping Evapotranspiration, water Stress and Soil moisture, ref: AGL2011-30498-C02-01) financiado por el Ministerio de Ciencia e Innovación español. El co-autor C. Balbontín N. agradece el financiamiento del Ministerio de Educación de Chile a través de su proyecto FONDECYT Iniciación Cod. 11140843.Pettinari, M.; Chuvieco, E. (2015). Mapping of fuels and fire potentials in the African Continent using FCCS. Revista de Teledetección. (43):1-10. https://doi.org/10.4995/raet.2015.2302SWORD1104

Development of a Sentinel-2 burned area algorithm: Generation of a small fire database for sub-Saharan Africa

A locally-adapted multitemporal two-phase burned area (BA) algorithm has been developed using as inputs Sentinel-2 MSI reflectance measurements in the short and near infrared wavebands plus the active fires detected by Terra and Aqua MODIS sensors. An initial burned area map is created in the first step, from which tile dependent statistics are extracted for the second step. The whole Sub-Saharan Africa (around 25 M km(2)) was processed with this algorithm at a spatial resolution of 20 m, from January to December 2016. This period covers two half fire seasons on the Northern Hemisphere and an entire fire season in the South. The area was selected as existing BA products account it to include around 70% of global BA. Validation of this product was based on a two-stage stratified random sampling of Landsat multitemporal images. Higher accuracy values than existing global BA products were observed, with Dice coefficient of 77% and omission and commission errors of 26.5% and 19.3% respectively. The standard NASA BA product (MCD64A1 c6) showed a similar commission error (20.4%), but much higher omission errors (59.6%), with a lower Dice coefficient (53.6%). The BA algorithm was processed over > 11,000 Sentinel-2 images to create a database that would also include small fires (< 100 ha). This is the first time a continental BA product is generated from medium resolution sensors (spatial resolution = 20 m), showing their operational potential for improving our current understanding of global fire impacts. Total BA estimated from our product was 4.9 M km(2), around 80% larger area than what the NASA BA product (MCD64A1 c6) detected in the same period (2.7 M km(2)). The main differences between the two products were found in regions where small fires (< 100 ha) account for a significant proportion of total BA, as global products based on coarse pixel sizes (500 m for MCD64A1) unlikely detect them. On the negative side, Sentinel-2 based products have lower temporal resolution and consequently are more affected by cloud/cloud shadows and have less temporal reporting accuracy than global BA products. The product derived from S2 imagery would greatly contribute to better understanding the impacts of small fires in global fire regimes, particularly in tropical regions, where such fires are frequent. This product is named FireCCISFD11 and it is publicly available at: https://www.esa-fire-cci.org/node/262, last accessed on November 2018.This research was carried out within the Fire_cci project (https://www.esa-fire-cci.org/, last accessed on November 2018), contract no. 4000115006/15/I-NB, which has been funded by the European Space Agency (ESA) under the Climate Change Initiative Programme. The FireCCISFD11 product can be downloaded at https://www.esa-fire-cci.org/node/262 (last accessed on November 2018)

Burn severity and regeneration in large forest fires: an analysis from Landsat time series

Revista oficial de la Asociación Española de Teledetección[EN] The main objective of this study is to take a close look at post-fire recovery patterns in forestry areas under different burn severity conditions. We also investigate the time that forestry ecosystems take to recover their pre-fire condition. In this context, this study analyses both the level of severity in Uncastillo forest wildfire (7.664ha), one of the greatest occurred in Spain in 1994, and the pattern of natural recovery in the following decades (until 2014) using annual Landsat time series (sensors TM&ETM+). Burn severity has been estimated by means of PROSPECT and GeoSAIL radiative transfer models following methodologies described in De Santis and Chuvieco (2009). On the other hand, recovery processes have been assessed from spectral profiles using the LandTrendr model (Landsat-based Detection of Trends in Disturbance and Recovery) (Kennedy et al., 2010). Results contribute to a further understanding of the post-fire evolution in forestry areas and to develop effective strategies for sustainable forest management.[ES] El objetivo de este estudio es contribuir a una mejor comprensión de los patrones de regeneración postincendio a partir de la severidad del fuego, así como estudiar el tiempo previsible que determinados ecosistemas forestales emplearán en recuperar su estado inicial. El estudio analiza el grado de severidad del incendio de Uncastillo de 1994 (7664 ha), uno de los mayores ocurridos en España en ese año, así como su dinámica de regeneración natural en las dos décadas siguientes (hasta 2014) mediante el empleo de series temporales de imágenes Landsat (sensores TM y ETM+). La estimación de la severidad post-incendio se ha basado en el uso de los modelos de transferencia radiativa PROSPECT y GeoSAIL, siguiendo la metodología propuesta por De Santis y Chuvieco (2009). Por su parte, los procesos de regeneración se han caracterizado mediante el empleo de trayectorias espectrales mediante el uso del modelo LandTrendr (Landsat-based Detection of Trends in Disturbance and Recovery) (Kennedy et al., 2010). Los resultados de este estudio contribuyen a una mayor comprensión de la dinámica general post-incendio de las áreas forestales y en último término permiten desarrollar estrategias efectivas para una gestión forestal sostenible.Ministerio de Economía y Competitividad. Proyecto Severidad y regeneración en grandes incendios forestales mediante teledetección y S.I.G (SERGISAT)(Ref. CGL2014-57013-C2-1-R–SERGISAT; CGL2014-57013-C2-2-R–SERGISATEste trabajo se ha desarrollado con la finan-ciación procedente del proyecto Severidad y regeneración en grandes incendios forestales mediante teledetección y S.I.G (SERGISAT)(Ref. CGL2014-57013-C2-1-R–SERGISAT; CGL2014-57013-C2-2-R–SERGISAT, Ministerio de Economía y Competitividad). Nuestro agra-decimiento también al Dr. Justin Braaten del Laboratory for Applications of Remote Sensing in Ecology de la Oregon State University, por su apoyo en el uso de LandTrendr.Martínez, S.; Chuvieco, E.; Aguado, I.; Salas, J. (2017). Severidad y regeneración en grandes incendios forestales: análisis a partir de series temporales de imágenes Landsat. Revista de Teledetección. (49):17-32. https://doi.org/10.4995/raet.2017.7182SWORD17324

Recent global and regional trends in burned area and their compensating environmental controls

The apparent decline in the global incidence of fire between 1996 and 2015, as measured by satellite- observations of burned area, has been related to socioeconomic and land use changes. However, recent decades have also seen changes in climate and vegetation that influence fire and fire-enabled vegetation models do not reproduce the apparent decline. Given that the satellite-derived burned area datasets are still relatively short (<20 years), this raises questions both about the robustness of the apparent decline and what causes it. We use two global satellite-derived burned area datasets and a data-driven fire model to (1) assess the spatio-temporal robustness of the burned area trends and (2) to relate the trends to underlying changes in temperature, precipitation, human population density and vegetation conditions. Although the satellite datasets and simulation all show a decline in global burned area over ~20 years, the trend is not significant and is strongly affected by the start and end year chosen for trend analysis and the year-to-year variability in burned area. The global and regional trends shown by the two satellite datasets are poorly correlated for the common overlapping period (2001–2015) and the fire model simulates changes in global and regional burned area that lie within the uncertainties of the satellite datasets. The model simulations show that recent increases in temperature would lead to increased burned area but this effect is compensated by increasing wetness or increases in population, both of which lead to declining burned area. Increases in vegetation cover and density associated with recent greening trends lead to increased burned area in fuel-limited regions. Our analyses show that global and regional burned area trends result from the interaction of compensating trends in controls of wildfire at regional scales

Uncertainty characterization & validation within ESA Fire-CCI

Uncertainty characterisation and validation are critical phases to generate any Essential Climate Variable (ECV), and therefore both have been included as key deliverables of the ESA CCI programme [1]. All products generated by the CCI are required to have an associated per pixel uncertainty characterisation. This paper describes both the uncertainty characterisation framework and the related uncertainty validation exercise of the Fire-CCI projectinfo:eu-repo/semantics/publishedVersio

Soil methane sink capacity response to a long-term wildfire chronosequence in Northern Sweden

Boreal forests occupy nearly one fifth of the terrestrial land surface and are recognised as globally important regulators of carbon (C) cycling and greenhouse gas emissions. Carbon sequestration processes in these forests include assimilation of CO2 into biomass and subsequently into soil organic matter, and soil microbial oxidation of methane (CH4). In this study we explored how ecosystem retrogression, which drives vegetation change, regulates the important process of soil CH4 oxidation in boreal forests. We measured soil CH4 oxidation processes on a group of 30 forested islands in northern Sweden differing greatly in fire history, and collectively representing a retrogressive chronosequence, spanning 5000 years. Across these islands the build-up of soil organic matter was observed to increase with time since fire disturbance, with a significant correlation between greater humus depth and increased net soil CH4 oxidation rates. We suggest that this increase in net CH4 oxidation rates, in the absence of disturbance, results as deeper humus stores accumulate and provide niches for methanotrophs to thrive. By using this gradient we have discovered important regulatory controls on the stability of soil CH4 oxidation processes that could not have not been explored through shorter-term experiments. Our findings indicate that in the absence of human interventions such as fire suppression, and with increased wildfire frequency, the globally important boreal CH4 sink could be diminished

Uncertainty Characterisation & Validation within ESA Fire-CCI

Uncertainty characterisation and validation are critical phases to generate any Essential Climate Variable (ECV), and therefore both have been included as key deliverables of the ESA CCI programme [1]. All products generated by the CCI are required to have an associated per pixel uncertainty characterisation. This paper describes both the uncertainty characterisation framework and the related uncertainty validation exercise of the Fire-CCI project

Geomorphic process signatures reshaping sub‐humid Mediterranean badlands: 1. Methodological development based on high‐resolution topography

High‐resolution topography data sets have improved the spatial and temporal scales at which we are able to investigate the landscape through the analysis of landform attributes and the computation of topographic changes. Yet, to date, there have been only limited attempts to infer key geomorphic processes in terms of contributions to shaping the landscape. Highly erodible landscapes such as badlands provide an ideal demonstration of such an approach owing to the rapid changes observed over a relatively short time frame. In this technical note we present the Mapping Geomorphic Processes in the Environment (MaGPiE): a new algorithm that allows mapping of geomorphic process signatures through analysis of repeat high‐resolution topography data sets. The method is demonstrated in an experimental badland located in the southern central Pyrenees. MaGPiE is a geographic information system (GIS)‐based algorithm that uses as input: (a) terrain attributes (i.e. Slope, Roughness and Concentrated Runoff Index) extracted from digital elevation models (DEMs), and (b) a map of topographic changes (DEM of difference, DoD). Initial results demonstrate that MaGPiE allows the magnitude and the spatial distribution of the main geomorphic processes reshaping badlands to be inferred for the first time

The ESA climate change initiative: Satellite data records for essential climate variables

The ESA’s Climate Change Initiative is reprocessing and reassessing over 40 years of multi-sensor satellite records to generate consistent, traceable, long-term datasets of “essential climate variables” for the climate modeling and research communities

Integrating geospatial information into fire risk assessment

Fire risk assessment should take into account the most relevant components associated to fire occurrence. To estimate when and where the fire will produce undesired effects, we need to model both (a) fire ignition and propagation potential and (b) fire vulnerability. Following these ideas, a comprehensive fire risk assessment system is proposed in this paper, which makes extensive use of geographic information technologies to offer a spatially explicit evaluation of fire risk conditions. The paper first describes the conceptual model, then the methods to generate the different input variables, the approaches to merge those variables into synthetic risk indices and finally the validation of the outputs. The model has been applied at a national level for the whole Spanish Iberian territory at 1-km2 spatial resolution. Fire danger included human factors, lightning probability, fuel moisture content of both dead and live fuels and propagation potential. Fire vulnerability was assessed by analysing values-at-risk and landscape resilience. Each input variable included a particular accuracy assessment, whereas the synthetic indices were validated using the most recent fire statistics available. Significant relations (P < 0.001) with fire occurrence were found for the main synthetic danger indices, particularly for those associated to fuel moisture content conditions.Peer reviewe