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Assessing variability and long-term trends in burned area by merging multiple satellite fire products
L. Giglio, J. T. Randerson, G. R. van der Werf, P. S. Kasibhatla, G. J. Collatz, D. C. Morton,R. S. DeFries
Biogeosciences (BG) & Discussions (BGD) , 2010,
Abstract: Long term, high quality estimates of burned area are needed for improving both prognostic and diagnostic fire emissions models and for assessing feedbacks between fire and the climate system. We developed global, monthly burned area estimates aggregated to 0.5° spatial resolution for the time period July 1996 through mid-2009 using four satellite data sets. From 2001–2009, our primary data source was 500-m burned area maps produced using Moderate Resolution Imaging Spectroradiometer (MODIS) surface reflectance imagery; more than 90% of the global area burned during this time period was mapped in this fashion. During times when the 500-m MODIS data were not available, we used a combination of local regression and regional regression trees developed over periods when burned area and Terra MODIS active fire data were available to indirectly estimate burned area. Cross-calibration with fire observations from the Tropical Rainfall Measuring Mission (TRMM) Visible and Infrared Scanner (VIRS) and the Along-Track Scanning Radiometer (ATSR) allowed the data set to be extended prior to the MODIS era. With our data set we estimated that the global annual area burned for the years 1997–2008 varied between 330 and 431 Mha, with the maximum occurring in 1998. We compared our data set to the recent GFED2, L3JRC, GLOBCARBON, and MODIS MCD45A1 global burned area products and found substantial differences in many regions. Lastly, we assessed the interannual variability and long-term trends in global burned area over the past 13 years. This burned area time series serves as the basis for the third version of the Global Fire Emissions Database (GFED3) estimates of trace gas and aerosol emissions.
Assessing variability and long-term trends in burned area by merging multiple satellite fire products
L. Giglio,J. T. Randerson,G. R. van der Werf,P. S. Kasibhatla
Biogeosciences Discussions , 2009,
Abstract: Long term, high quality estimates of burned area are needed for improving both prognostic and diagnostic fire emissions models and for assessing feedbacks between fire and the climate system. We developed global, monthly burned area estimates aggregated to 0.5° spatial resolution for the time period July 1996 through mid-2009 using four satellite data sets. From 2001–2009, our primary data source was 500-m burned area maps produced using Moderate Resolution Imaging Spectroradiometer (MODIS) surface reflectance imagery; more than 90% of the global area burned during this time period was mapped in this fashion. During times when the 500-m MODIS data were not available, we used a combination of local regression and regional regression trees to develop relationships between burned area and Terra MODIS active fire data. Cross-calibration with fire observations from the Tropical Rainfall Measuring Mission (TRMM) Visible and Infrared Scanner (VIRS) and the Along-Track Scanning Radiometer (ATSR) allowed the data set to be extended prior to the MODIS era. With our data set we estimated the global annual area burned for the years 1997–2008 varied between 330 and 431 Mha, with the maximum occurring in 1998. We compared our data set to the recent GFED2, L3JRC, GLOBCARBON, and MODIS MCD45A1 global burned area products and found substantial differences in many regions. Lastly, we assessed the interannual variability and long-term trends in global burned area over the past 12 years. This burned area time series serves as the basis for the third version of the Global Fire Emissions Database (GFED3) estimates of trace gas and aerosol emissions.
Timing Constraints on Remote Sensing of Wildland Fire Burned Area in the Southeastern US  [PDF]
Joshua J. Picotte,Kevin Robertson
Remote Sensing , 2011, DOI: 10.3390/rs3081680
Abstract: Remote sensing using Landsat Thematic Mapper (TM) satellite imagery is increasingly used for mapping wildland fire burned area and burn severity, owing to its frequency of collection, relatively high resolution, and availability free of charge. However, rapid response of vegetation following fire and frequent cloud cover pose challenges to this approach in the southeastern US. We assessed these timing constraints by using a series of Landsat TM images to determine how rapidly the remotely sensed burn scar signature fades following prescribed burns in wet flatwoods and depression swamp community types in the Apalachicola National Forest, Florida, USA during 2006. We used both the Normalized Burn Ratio (NBR) of reflectance bands sensitive to vegetation and exposed soil cover, as well as the change in NBR from before to after fire (dNBR), to estimate burned area. We also determined the average and maximum amount of time following fire required to obtain a cloud-free image for burns in each month of the year, as well as the predicted effect of this time lag on percent accuracy of burn scar estimates. Using both NBR and dNBR, the detectable area decreased linearly 9% per month on average over the first four months following fire. Our findings suggest that the NBR and dNBR methods for monitoring burned area in common southeastern US vegetation community types are limited to an average of 78–90% accuracy among months of the year, with individual burns having values as low as 38%, if restricted to use of Landsat 5 TM imagery. However, the majority of burns can still be mapped at accuracies similar to those in other regions of the US, and access to additional sources of satellite imagery would improve overall accuracy.
SATELLITE OBSERVATIONS FOR EDUCATION OF CLIMATE CHANGE
ILONA PAJTóK-TARI,JáNOS MIKA,ZOLTáN UTASI
Aerul ?i Apa : Componente ale Mediului , 2011,
Abstract: This paper surveys the key statements of the IPCC (2007) Reportbased mainly on the satellite-borne observations to support teaching climatechange and geography by using the potential of this technology. In theIntroduction we briefly specify the potential and the constraints of remote sensing.Next the key climate variables for indicating the changes are surveyed. Snow andsea-ice changes are displayed as examples for these applications. Testing theclimate models is a two-sided task involving satellites, as well. Validation of theability of reconstructing the present climate is the one side of the coin, whereassensitivity of the climate system is another key task, leading to consequences onthe reality of the projected changes. Finally some concluding remarks arecompiled, including a few ideas on the ways how these approaches can be appliedfor education of climate change.
Distribution Patterns of Burned Areas in the Brazilian Biomes: An Analysis Based on Satellite Data for the 2002–2010 Period  [PDF]
Fernando Moreira de Araújo,Laerte Guimar?es Ferreira,Arielle Elias Arantes
Remote Sensing , 2012, DOI: 10.3390/rs4071929
Abstract: Fires modify the structure of vegetation communities, the carbon and water cycles, the soil’s chemistry, and affect the climate system. Within this context, this work aimed to understand the distribution patterns of burned areas in Brazil, during the period of 2002 to 2010, taking into consideration each one of the six Brazilian biomes (Amazon, Caatinga, Cerrado, Atlantic Forest, Pampa and Pantanal) and the respective major land cover classes. Data from the MODIS MCD45A1 product (burned area), as well as thermal anomalies (MOD14 and MYD14) and precipitation (TRMM), were analyzed according to the 2002 Brazilian official land cover and land use map (PROBIO). The Brazilian savanna biome, known as Cerrado, presented the largest concentration of burned areas detected by MODIS (73%), followed by the Amazon (14%), Pantanal (6%), Atlantic Forest (4%), Caatinga (3%), and Pampa (0,06%) biomes. Indeed, in the years of 2007 and 2010, 90% and 92% of Brazil’s burned areas were concentrated in the Cerrado and Amazon biomes, respectively. TRMM data indicated that during these two years there was a significant influence of La Ni?a, causing low rainfall in the Amazon, Cerrado, Caatinga, and Atlantic Forest biomes. Regarding the land cover classes, approximately 81% of the burned areas occurred over remnant vegetation areas. Although no unequivocal correlation can be established between burned areas and new land conversions, the conspicuous concentration of fire scars, particularly in Amazon–Cerrado transition (i.e., the Arc of Deforestation) is certainly not a simple coincidence. Such patterns and trends corroborate the need of improved territorial governance, in addition to the implementation of systematic fire warning and preventive systems.
Evaluation of ALOS PALSAR Imagery for Burned Area Mapping in Greece Using Object-Based Classification  [PDF]
Anastasia Polychronaki,Ioannis Z. Gitas,Sander Veraverbeke,Annekatrien Debien
Remote Sensing , 2013, DOI: 10.3390/rs5115680
Abstract: In this work, the potential of Advanced Land Observing Satellite (ALOS) Phased Array type L-band Synthetic Aperture Radar (PALSAR) imagery to map burned areas was evaluated in two study areas in Greece. For this purpose, we developed an object-based classification scheme to map the fire-disturbed areas using the PALSAR imagery acquired before and shortly after fire events. The advantage of employing an object-based approach was not only the use of the temporal variation of the backscatter coefficient, but also the incorporation in the classification of topological features, such as neighbor objects, and class related features, such as objects classified as burned. The classification scheme resulted in mapping the burned areas with satisfactory results: 0.71 and 0.82 probabilities of detection for the two study areas. Our investigation revealed that the pre-fire vegetation conditions and fire severity should be taken in consideration when mapping burned areas using PALSAR in Mediterranean regions. Overall, findings suggest that the developed scheme could be applied for rapid burned area assessment, especially to areas where cloud cover and fire smoke inhibit accurate mapping of burned areas when optical data are used.
Arctic Climate Variability and Trends from Satellite Observations  [PDF]
Xuanji Wang,Jeffrey Key,Yinghui Liu,Charles Fowler,James Maslanik,Mark Tschudi
Advances in Meteorology , 2012, DOI: 10.1155/2012/505613
Abstract: Arctic climate has been changing rapidly since the 1980s. This work shows distinctly different patterns of change in winter, spring, and summer for cloud fraction and surface temperature. Satellite observations over 1982–2004 have shown that the Arctic has warmed up and become cloudier in spring and summer, but cooled down and become less cloudy in winter. The annual mean surface temperature has increased at a rate of 0.34°C per decade. The decadal rates of cloud fraction trends are ?3.4%, 2.3%, and 0.5% in winter, spring, and summer, respectively. Correspondingly, annually averaged surface albedo has decreased at a decadal rate of ?3.2%. On the annual average, the trend of cloud forcing at the surface is ?2.11 W/m2 per decade, indicating a damping effect on the surface warming by clouds. The decreasing sea ice albedo and surface warming tend to modulate cloud radiative cooling effect in spring and summer. Arctic sea ice has also declined substantially with decadal rates of ?8%, ?5%, and ?15% in sea ice extent, thickness, and volume, respectively. Significant correlations between surface temperature anomalies and climate indices, especially the Arctic Oscillation (AO) index, exist over some areas, implying linkages between global climate change and Arctic climate change. 1. Introduction Recent observations have shown dramatic decreases in Northern Hemisphere sea ice extent and thickness [1–9]. Over the last two decades, the changes in many aspects of the Arctic climate system have been observed, including surface temperature and albedo, atmospheric circulation, precipitation, snowfall, biogeochemical cycle, and vegetation [10–16]. Arctic climate change is also reflected in the changes in climate indices such as the Arctic Oscillation (AO), which indicates that a significant change in the climate system occurred in the late 1970s and early 1980s [17–21]. How the interactions and feedbacks of all climate components play a role in Arctic climate change is a challenging issue. A recent study, for example, shows how clouds respond to changes in sea ice cover, such that a cloudier Arctic is expected with less sea ice cover in the future [22]. Numerous climate modeling studies have shown that the Arctic is one of the most sensitive regions to global climate change as a result of the positive feedback between surface temperature, surface albedo, and ice extent, known as the ice-albedo feedback [23–27]. This fundamental theory has been confirmed by a variety of observational evidence, though records of Arctic climate change are relatively brief and, for surface
Total solar irradiance satellite composites and their phenomenological effect on climate  [PDF]
Nicola Scafetta
Physics , 2009,
Abstract: Herein I discuss and propose updated satellite composites of the total solar irradiance covering the period 1978-2008. The composites are compiled from measurements made with the three ACRIM experiments. Measurements from the NIMBUS7/ERB and the ERBS/ERBE satellite experiments are used to fill the gap from June 1989 to October 1991 between ACRIM1 and ACRIM2 experiments. The climate implications of the alternative satellite composites are discussed by using a phenomenological climate model for reconstructing the total solar irradiance signature on climate during the last four centuries.
Arctic Climate Variability and Trends from Satellite Observations  [PDF]
Xuanji Wang,Jeffrey Key,Yinghui Liu,Charles Fowler,James Maslanik,Mark Tschudi
Advances in Meteorology , 2012, DOI: 10.1155/2012/505613
Abstract: Arctic climate has been changing rapidly since the 1980s. This work shows distinctly different patterns of change in winter, spring, and summer for cloud fraction and surface temperature. Satellite observations over 1982–2004 have shown that the Arctic has warmed up and become cloudier in spring and summer, but cooled down and become less cloudy in winter. The annual mean surface temperature has increased at a rate of 0.34°C per decade. The decadal rates of cloud fraction trends are −3.4%, 2.3%, and 0.5% in winter, spring, and summer, respectively. Correspondingly, annually averaged surface albedo has decreased at a decadal rate of −3.2%. On the annual average, the trend of cloud forcing at the surface is −2.11 W/m2 per decade, indicating a damping effect on the surface warming by clouds. The decreasing sea ice albedo and surface warming tend to modulate cloud radiative cooling effect in spring and summer. Arctic sea ice has also declined substantially with decadal rates of −8%, −5%, and −15% in sea ice extent, thickness, and volume, respectively. Significant correlations between surface temperature anomalies and climate indices, especially the Arctic Oscillation (AO) index, exist over some areas, implying linkages between global climate change and Arctic climate change.
Assessing Resilience to Climate Change in US Cities  [PDF]
Casilda Saavedra,William W. Budd,Nicholas P. Lovrich
Urban Studies Research , 2012, DOI: 10.1155/2012/458172
Abstract: In the face of uncertainties associated with climate change, building adaptive capacity and resilience at the community level emerges as an essential and timely element of local planning. However, key social factors that facilitate the effective building and maintenance of urban resilience are poorly understood. Two groups of US cities differing markedly in their commitment to climate change are contrasted with respect to their planning approaches and actions related to mitigation and adaptation strategies, and also in relation to social features that are believed to enhance adaptive capacity and resilience to climate change. The first group manifests a strong commitment to climate change mitigation and adaptation, and the second group has demonstrated little or no such commitment. These cities are compared with respect to several noteworthy social features, including level of social capital, degree of unconventional thought, and level of cultural diversity. These characteristics are postulated to contribute to the adaptive capacity of communities for dealing with the impacts of climate change. The aim is to determine to what extent there is a relationship between social/cultural structures and urban commitment and planning for climate change that could discriminate between climate change resilient and nonresilient urban areas. 1. Introduction In their efforts to promote sustainability local governments around the world are confronting the challenge of mitigation and adaptation to climate change because climate change-related disturbances can transform the face of communities in profound ways. It is clear that no thorough plan promoting sustainability should ignore the potential impacts of climate change. Sustainability is closely related to the capacity of systems to persist and transform themselves in the presence of significant perturbations and still provide the ecosystem services that sustain life. Holling [1] has defined sustainability as “the capacity to create, test, and maintain adaptive capacity” while Lebel et al. [2] argue that in order to attain sustainable development, societies need to enhance their capacity to manage resilience. To deal successfully with climate change, decision makers in urban areas have to apply adaptive management, develop the ability to live with uncertainty, and foster transformations without losing opportunities for achieving a sustainable future. Climate change is one of the main sources of uncertainty facing all levels of government today. According to Wilson [3], “building climate change considerations into
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