El Instituto Geográfico Agustín Codazzi (IGAC) de Colombia y UNOOSA firmaron en el año 2011 un acuerdo de cooperación para establecer la Oficina Regional de Apoyo en Colombia. IGAC promueve en Colombia el uso de información obtenida desde el espacio para distintos propósitos y ha apoyado a ONU-SPIDER en sus actividades conducidas en América Latina y el Caribe. Como Oficina Regional de Apoyo, IGAC continúa ofreciendo expertos a ONU-SPIDER para su Asesoría Técnica a países de la región con el objetivo de contribuir en los esfuerzos de fortalecimiento de capacidades en la región.
The objective is to monitor vegetation recovery after the large fires of 2003 in Portugal using a time-series of MODIS Terra Enhanced Vegetation Index (EVI) data. Post-fire vegetation regeneration rate was estimated using Olson’s model. We attempted to model it as a function of fire history, including number of times burned prior to 2003. This study shows that satellite imagery can be very valuable for studying post-fire vegetation response, and this can contribute to a better understanding of wildfires, lead to improved management strategies for prevention, or even improve allocation of firefighting resources.
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The Twentieth century saw fundamental shifts in northern Eurasian political and land-management paradigms, in Russiaculminating in the political transition of 1991. We used the1972 to 2001 Landsat archive bracketing this transition toobserve change trends in southern central Siberian Russia inprimarily forested study sites. Landsat resolved conifer, mixed,deciduous and young forest; cuts, burns, and insect disturbance;and wetland, agriculture, bare, urban, and water landcovers. Over 70 percent of forest area in the three study siteswas likely disturbed prior to 1974. Conifer forest decreasedover the 1974 to 2001 study period, with the greatest decrease1974 to 1990. Logging activity (primarily in conifers) declinedmore during the 1991 to 2001 post-Soviet period. The area ofYoung forest increased more during the 1974 to 1990 timeperiod. Deciduous forest increased over both time periods.Agriculture declined over both time periods contributing toforest regrowth in this...
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Disturbance of the vegetated land surface, due to factors such as fire, insect infestation, windthrow andharvesting, is a fundamental driver of the composition forested landscapes with information on disturbanceproviding critical insights into species composition, vegetation condition and structure. Long-term climatevariability is expected to lead to increases in both the magnitude and distribution of disturbances. As aconsequence it is important to develop monitoring systems to better understand these changes in theterrestrial biosphere as well to inform managers about disturbance agents more typically captured throughspecific monitoring programs (such as focused on insect, fire, or agricultural conditions). Changes in thecondition, composition and distribution pattern of vegetation can lead to changes in the spectral and thermalsignature of the land surface. Using a 6-year time series of MODerate-resolution Imaging Spectroradiometer(MODIS) Land Surface Temperature (...
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Wildfires significantly affect the boreal ecosystem of Siberia. However, records on burnt areas and fire impact are still not satisfactory in Russia. The dense smoke from active burning and the persistent cloud covers impeded the application of optical sensors to the detection of burnt area in Siberia forest during the summer fire season. The high resolution SAR data are of limited use for burnt area identification because of the enormous size of boreal Russia. In this paper, the medium resolution (150 meters) ENVISAT wide swath SAR data (ASAR_WSM) were investigated through analyzing the backscatter dynamics of fire scars in Siberia boreal forest. We firstly compared seven time series backscatter of ASAR data in burnt forest and adjacent unburnt forest, then applied Principle Component Analysis to pre and post fire images for detecting the burnt area change and finally we compared the visibility on ASAR images among fire scars formed in different years. Results...
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Space and airborne sensors have been used to map area burned, assess characteristics of active fires, and characterize post-fire ecological effects. Confusion about fire intensity, fire severity, burn severity, and related terms can result in the potential misuse of the inferred information by land managers and remote sensing practitioners who require unambiguous remote sensing products for fire management. The objective of the present paper is to provide a comprehensive review of current and potential remote sensing methods used to assess fire behavior and effects and ecological responses to fire. We clarify the terminology to facilitate development and interpretation of comprehensible and defensible remote sensing products, present the potential and limitations of a variety of approaches for remotely measuring active fires and their post-fire ecological effects, and discuss challenges and future directions of fire-related remote sensing research.
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During the great wildfire event in South East Europe in the summer of 2007, a fire occurred in the montane forest belt of the Majella National Park, Italy. The fire was the largest recorded in history and the only one recorded in a beech forest in the park and Europe. The management of the park expressed its interest to use satellite remote sensing data and techniques as an alternative method to map fire scars and to assess the effect of the fire on plant biodiversity and regeneration. The study asked the following questions: (1) What are the location, time, severity and distribution of these fires? (2) Can fire scars in the montane forest belt be mapped accurately using medium resolution satellite imagery? (3) What is the species composition and diversity of tree seedlings and herbaceous plants in post-fire and in unburned beech forest and black pine plantation? (4) Does beech and black pine regenerate after forest fire?
The MODIS Terra and Aqua active fire...
An automatic burned area mapping system with Landsat TM has been developed. Given only the boundary of the burned area, the system can determine the severity of burns. Burn severity map shows the texture of burned area, which reflect the affect of topography and biomass status. The SupervisedART-II neural network has been employed. Bands 3,4 and 5 have been used. Post-fire, as well as multi-temporal images have been incorporated in to the network. Using different-sized trainings sets and different dynamic parameters have tested system performance.
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In the last decade, forest fire in South East Asia has drawn attention from international level. Particularly in Indonesia during 1997-1998, it has been reported that 500.000 ha of tropical forests were destroyed in 1998. Loss of forests and effects from greenhouse gases influence the regional and global climatic systems. In Thailand, forest fire annually occur in dry season February till May. In Thailand, half of total forest area is occupied by mixed deciduous and dry dipterocarp forests, which are affected by forest fire almost every year. Up-to-date information in term of post-fire recovery is scarce. Remote sensing, which can provide accurate information and facilitate routine observation in inaccessible areas, has not been considered to assess post-fire recovery. GIS techniques have not been applied to integrate spatio-temporal data. This study attempts to use remote sensing, GIS and field data to assess forest recovery after fire and investigate the relationship...
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Forest fire is a kind of worldwide natural calamity. It is extensively distributed with high occurrence frequency and destroys forest resources thus disturbing normal living order of people and leading to environmental deterioration. The appearance and development of modernistic new high technologies, such as Remote Sensing (RS), Geographic Information System (GIS) and Internet, have given more convenience for preventing and decreasing disaster than before. In this study, basing on analyzing the information of related bands of Advanced Along Track Scanning Radiometer (AATSR) and integration of background GIS data, a forest fire identification methodology has been developed. At the same times, the accuracy of the results by using AATSR and Moderate Resolution Image Spectroradiometer (MODIS) data has been tested in northeast of China.
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