scholarly journals Contrasting Post-Fire Dynamics between Africa and South America based on MODIS Observations

2019 ◽  
Vol 11 (9) ◽  
pp. 1074 ◽  
Author(s):  
Lei Zhou ◽  
Yuhang Wang ◽  
Yonggang Chi ◽  
Shaoqiang Wang ◽  
Quan Wang
Keyword(s):  
South America ◽  
Land Cover ◽  
Northern Hemisphere ◽  
Vegetation Dynamics ◽  
Fire Regime ◽  
High Density ◽  
Forest Recovery ◽  
Burned Area ◽  
Fire Dynamics ◽  
The Impact

Fire is an important driver of land cover change throughout the world, affecting processes such as deforestation, forest recovery and vegetation transition. Little attention has been given to the role of fire in shaping the temporal and spatial land cover changes among continents. This study has integrated two MODIS products (MCD64A1: Burned area and MCD12Q1: Land cover) over Africa and South America from 2001–2013 to explore the vegetation dynamics after fires. The results indicated that while Africa suffered from repeated fires, more than 50% of the total burned area in South America experienced only one fire. The vegetation dynamics of the high-density vegetated regions in the 10 years after a fire showed that the forest losses in the first year after a fire in Africa were slightly larger than that in South America (Africa: 17.2% vs. South America: 14.5% in the Northern Hemisphere). The continental comparison suggested that early successional forests in Africa recovered relatively fast (northern part: 10.2 years; southern part: 12.8 years) than in South America, which recovered (18.4 years) slowly in Northern Hemisphere or ever with no recovery in the Southern Hemisphere. No clear information of the recoveries of other vegetation types (i.e., shrub, grass and crop) in Africa or South America could be identified from the satellite data. In addition, we also analyzed the changes of high-density vegetation in non-burned regions in both continents. These findings highlighted the impact of the fire regime on the vegetation changes in Africa, which appear resilient to fire, but there were complex systems in South America related to fires.

scholarly journals About Validation-Comparison of Burned Area Products

2020 ◽  
Vol 12 (23) ◽  
pp. 3972
Author(s):  
Germán M. Valencia ◽  
Jesús A. Anaya ◽  
Éver A. Velásquez ◽  
Rubén Ramo ◽  
Francisco J. Caro-Lopera
Keyword(s):  
South America ◽  
Land Cover ◽  
Northern Hemisphere ◽  
Random Matrix Theory ◽  
Random Matrix ◽  
Matrix Theory ◽  
Permutation Tests ◽  
Comparison Method ◽  
Burned Area ◽  
Tropical Regions

This paper proposes a validation-comparison method for burned area (BA) products. The technique considers: (1) bootstrapping of scenes for validation-comparison and (2) permutation tests for validation. The research focuses on the tropical regions of Northern Hemisphere South America and Northern Hemisphere Africa and studies the accuracy of the BA products: MCD45, MCD64C5.1, MCD64C6, Fire CCI C4.1, and Fire CCI C5.0. The first and second parts consider methods based on random matrix theory for zone differentiation and multiple ancillary variables such as BA, the number of burned fragments, ecosystem type, land cover, and burned biomass. The first method studies the zone effect using bootstrapping of Riemannian, full Procrustes, and partial Procrustes distances. The second method explores the validation by using distance permutation tests under uncertainty. The results refer to Fire CCI 5.0 with the best BA description, followed by MCD64C6, MCD64C5.1, MCD45, and Fire CCI 4.1. It was also found that biomass, total BA, and the number of fragments affect the BA product accuracy.

scholarly journals Representation of fire, land-use change and vegetation dynamics in the Joint UK Land Environment Simulator vn4.9 (JULES)

2019 ◽  
Vol 12 (1) ◽  
pp. 179-193 ◽  
Author(s):  
Chantelle Burton ◽  
Richard Betts ◽  
Manoel Cardoso ◽  
Ted R. Feldpausch ◽  
Anna Harper ◽  
...  
Keyword(s):  
Land Use ◽  
Land Use Change ◽  
Land Cover ◽  
Vegetation Cover ◽  
Land Surface ◽  
Vegetation Dynamics ◽  
Fire Disturbance ◽  
Substantial Contribution ◽  
Surface Model ◽  
The Impact

Abstract. Disturbance of vegetation is a critical component of land cover, but is generally poorly constrained in land surface and carbon cycle models. In particular, land-use change and fire can be treated as large-scale disturbances without full representation of their underlying complexities and interactions. Here we describe developments to the land surface model JULES (Joint UK Land Environment Simulator) to represent land-use change and fire as distinct processes which interact with simulated vegetation dynamics. We couple the fire model INFERNO (INteractive Fire and Emission algoRithm for Natural envirOnments) to dynamic vegetation within JULES and use the HYDE (History Database of the Global Environment) land cover dataset to analyse the impact of land-use change on the simulation of present day vegetation. We evaluate the inclusion of land use and fire disturbance against standard benchmarks. Using the Manhattan metric, results show improved simulation of vegetation cover across all observed datasets. Overall, disturbance improves the simulation of vegetation cover by 35 % compared to vegetation continuous field (VCF) observations from MODIS and 13 % compared to the Climate Change Initiative (CCI) from the ESA. Biases in grass extent are reduced from −66 % to 13 %. Total woody cover improves by 55 % compared to VCF and 20 % compared to CCI from a reduction in forest extent in the tropics, although simulated tree cover is now too sparse in some areas. Explicitly modelling fire and land use generally decreases tree and shrub cover and increases grasses. The results show that the disturbances provide important contributions to the realistic modelling of vegetation on a global scale, although in some areas fire and land use together result in too much disturbance. This work provides a substantial contribution towards representing the full complexity and interactions between land-use change and fire that could be used in Earth system models.

scholarly journals Global assessment of land cover changes and rural-urban interface in Portugal

2017 ◽  
Author(s):  
Marj Tonini ◽  
Joana Parente ◽  
Mario Pereira
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Urban Areas ◽  
Global Assessment ◽  
Fire Regime ◽  
Land Use Changes ◽  
Population Increase ◽  
Burnt Area ◽  
Agricultural Areas ◽  
The Impact

Abstract. The wildland-/rural-urban interface (WUI/RUI) is a particularly important aspect of the fire regime. In Mediterranean basin most of the fires in this pyro region are caused by humans and the risk and consequences are particularly high due to the close proximity to population, human infrastructures and urban areas. Population increase, urban growth and the rapid changes in land use incurred in Europe over the last 30 years has been unprecedented, especially nearby the metropolitan areas, and some of these trends are expected to continue. Associated to high socioeconomic development, Portugal experienced in the last decades significant land cover/land use changes (LCLUC), population dynamics and demographic trends in response to migration, rural abandonment, and ageing of rural population. This study aims to assess the evolution of RUI in Portugal, from 1990 to 2012, based on LCLUC providing also a quantitative characterization of forest fires dynamics in relation to the burnt area. Obtained results disclose important LCLUC which spatial distribution is far from uniform within the territory. A significant increase in artificial surfaces is registered nearby the main metropolitan communities of the northwest and littoral-central and southern regions, whilst the abandonment of agricultural land nearby the inland urban areas leads to an increase of uncultivated semi-natural and forest areas. Within agricultural areas, heterogeneous patches suffered the greatest changes and are the main contributors to the increase of urban areas. Moreover these are among the LCLU classes with higher burnt area, reasons why heterogeneous agricultural areas have been included in the definition of RUI. Finally, the mapped RUI’s area, burnt area and burnt area within RUI allow to conclude that, form 1990 to 2012 in Portugal, RUI increased more than two thirds and total burnt area decreased one third. Nevertheless, burnt area within RUI doubled, which emphasize the significance of RUI for land and fire managers. This research provides a first quantitative global assessment of RUI in Portugal and presents an innovative analysis on the impact of land use changes on burnt areas.

scholarly journals Sensitivity of simulated historical burned area to environmental andanthropogenic controls: A comparison of seven fire models

2019 ◽  
Author(s):  
Lina Teckentrup ◽  
Sandy P. Harrison ◽  
Stijn Hantson ◽  
Angelika Heil ◽  
Joe R. Melton ◽  
...  
Keyword(s):  
Land Use ◽  
Global Change ◽  
Fire Regime ◽  
Fire Behavior ◽  
Fire Regimes ◽  
Burned Area ◽  
Strong Response ◽  
Fire Models ◽  
In Fire ◽  
The Impact

Abstract. Understanding how fire regimes change over time is of major importance for understanding their future impact on the Earth system, including society. Large differences in simulated burned area between fire models show that there is substantial uncertainty associated with modelling global change impacts on fire regimes. We draw here on sensitivity simulations made by seven global dynamic vegetation models participating in the Fire Model Intercomparison Project (FireMIP) to understand how differences in models translate into differences in fire regime projections. The sensitivity experiments isolate the impact of the individual drivers of fire, which are prescribed in the simulations. Specifically these drivers are atmospheric CO2, population density, land-use change, lightning and climate. The seven models capture spatial patterns in burned area. However, they show considerable differences in the burned area trends since 1900. We analyse the trajectories of differences between the sensitivity and reference simulation to improve our understanding of what drives the global trend in burned area. Where it is possible, we link the inter-model differences to model assumptions. Overall, these analyses reveal that the strongest differences leading to diverging trajectories are related to the way anthropogenic ignitions and suppression, as well as the effects of land-use on vegetation and fire, are incorporated in individual models. This points to a need to improve our understanding and model representation of the relationship between human activities and fire to improve our abilities to model fire for global change applications. Only two models show a strong response to CO2 and the response to lightning on global scale is low for all models. The sensitivity to climate shows a spatially heterogeneous response and globally only two models show a significant trend. It was not possible to attribute the climate-induced changes in burned area to model assumptions or specific climatic parameters. However, the strong influence of climate on the inter-annual variability in burned area, shown by all the models, shows that we need to pay attention to the simulation of fire weather but also meteorological influences on biomass accumulation and fuel properties in order to better capture extremes in fire behavior.

scholarly journals Modeling the Impact of Urbanization on Local Meteorological Conditions in Sofia

Atmosphere ◽  
2019 ◽  
Vol 10 (7) ◽  
pp. 366 ◽  
Author(s):  
Reneta Dimitrova ◽  
Ventsislav Danchovski ◽  
Evgenia Egova ◽  
Evgeni Vladimirov ◽  
Ashish Sharma ◽  
...  
Keyword(s):  
Land Cover ◽  
Urban Areas ◽  
Meteorological Conditions ◽  
High Density ◽  
Anthropogenic Heat ◽  
Additional Stress ◽  
Residential Areas ◽  
Hypothetical Scenario ◽  
Impact Of Urbanization ◽  
The Impact

Increasing urbanization impacts the local meteorology and the quality of life for residents. Urban surface characteristics and anthropogenic heat stress lead to urban heat island effects, changes in local circulations, precipitation alteration, and amendment of the local fluxes. These modifications have a direct effect on the life and health of residents. In this study, we assessed the impact of urbanization in Sofia (Bulgaria) using the Weather Research and Forecasting (WRF) model at 500 m resolution for the summer period of 2016. We utilized the CORINE (coordination of information on the environment) 2012 land cover database to represent the urban areas in four detailed land cover types, i.e., high-intensity residential areas, low-intensity residential areas, medium/industrial areas, and developed open spaces. We performed two experiments; in the first, we substituted an urban area with the most representative rural land cover to delineate the current impact of urbanization, while in the second, we replaced the existing built-up area (all four categories) with a hypothetical scenario of high-density residential land cover showing aggressive urban development. These experiments addressed the impact of land use changes as well as the extreme effects of ongoing high-density construction on the local meteorological conditions. The results showed that urban temperatures can increase by 5 °C and that moisture can decrease by 2 g/kg in the central part of Sofia in comparison to surrounding rural areas. The results also showed that building higher and dense urban areas can significantly increase heat flux and add additional stress to the environment.

scholarly journals Global Wildfire Outlook Forecast with Neural Networks

2020 ◽  
Vol 12 (14) ◽  
pp. 2246
Author(s):  
Yongjia Song ◽  
Yuhang Wang
Keyword(s):  
Neural Network ◽  
Neural Networks ◽  
South America ◽  
Land Cover ◽  
Southern Africa ◽  
Burned Area ◽  
Good Prediction ◽  
Wildfire Occurrence ◽  
Fire Emissions ◽  
Burned Areas

Wildfire occurrence and spread are affected by atmospheric and land-cover conditions, and therefore meteorological and land-cover parameters can be used in area burned prediction. We apply three forecast methods, a generalized linear model, regression trees, and neural networks (Levenberg–Marquardt backpropagation) to produce monthly wildfire predictions 1 year in advance. The models are trained using the Global Fire Emissions Database version 4 with small fires (GFEDv4s). Continuous 1-year monthly fire predictions from 2011 to 2015 are evaluated with GFEDs data for 10 major fire regions around the globe. The predictions by the neural network method are superior. The 1-year moving predictions have good prediction skills over these regions, especially over the tropics and the southern hemisphere. The temporal refined index of agreement (IOA) between predictions and GFEDv4s regional burned areas are 0.82, 0.82, 0.8, 0.75, and 0.56 for northern and southern Africa, South America, equatorial Asia and Australia, respectively. The spatial refined IOA for 5-year averaged monthly burned area range from 0.69 in low-fire months to 0.86 in high-fire months over South America, 0.3–0.93 over northern Africa, 0.69–0.93 over southern Africa, 0.47–0.85 over equatorial Asia, and 0.53–0.8 over Australia. For fire regions in the northern temperate and boreal regions, the temporal and spatial IOA between predictions and GFEDv4s data in fire seasons are 0.7–0.79 and 0.24–0.83, respectively. The predictions in high-fire months are better than low-fire months. This study illustrates the feasibility of global fire activity outlook forecasts using a neural network model and the method can be applied to quickly assess the potential effects of climate change on wildfires.

scholarly journals Exploring the Potential of Sentinels-1 & 2 of the Copernicus Mission in Support of Rapid and Cost-effective Wildfire Assessment

2019 ◽  
Author(s):  
Alexander R. Brown ◽  
George Petropoulos ◽  
Konstantinos P. Ferentinos
Keyword(s):  
Soil Erosion ◽  
Wildland Fire ◽  
Burned Area ◽  
Mediterranean Ecosystem ◽  
Support Vector ◽  
Svm Classifier ◽  
Fire Dynamics ◽  
Burnt Area ◽  
The Impact ◽  
Sentinel 2

The present study explores the use of the recently launched Sentinel-1 and -2 data of the Copernicus mission in wildfire mapping with a particular focus on retrieving information on burnt area, burning severity as well as in quantifying changes in soil erosion. As study area, the Sierra del Gata wildfire, occurred in Spain during the summer of 2015 was selected. First, diverse image processing algorithms for burnt area extraction from Sentinel-2 data were evaluated. In the next step, burning severity maps were derived from Sentinel-2 data alone, and the synergy between Sentinel-2 & Sentinel-1 for this purpose was evaluated. Finally, the impact of the wildfire to soil erodibility estimates derived from the Revised Universal Soil Loss Equation (RUSLE) model implemented to the available Sentinel images was explored. In overall, the Support Vector Machines (SVM) classifier obtained the most accurate burned area mapping, with a derived accuracy of 99.38%. An object-based SVM classification using as input both optical and radar data was the most effective approach of delineating burn severity, achieving an overall accuracy of 92.97%. Soil erosion mapping predictions allowed quantifying the impact of wildfire to soil erosion at the studied site, suggesting the method could be potentially of a wider use. Our results contribute to the understanding of wildland fire dynamics in the context of the Mediterranean ecosystem, demonstrating the usefulness of Sentinels and their derived products in wildfire mapping and assessment.

scholarly journals Exploring the Potential of Sentinels-1 & 2 of the Copernicus Mission in Support of Rapid and Cost-effective Wildfire Assessment

2020 ◽  
Author(s):  
Alexander R. Brown ◽  
George Petropoulos ◽  
Konstantinos P. Ferentinos
Keyword(s):  
Soil Erosion ◽  
Wildland Fire ◽  
Burn Severity ◽  
Burned Area ◽  
Mediterranean Ecosystem ◽  
Support Vector ◽  
Fire Dynamics ◽  
Burnt Area ◽  
The Impact ◽  
Sentinel 2

The present study explores the use of the recently launched Sentinel-1 and -2 data of the Copernicus mission inwildfire mapping with a particular focus on retrieving information on burnt area, burn severity as well as inquantifying soil erosion changes. As study area, the Sierra del Gata wildfire occurred in Spain during the summerof 2015 was selected. First, diverse image processing algorithms for burnt area extraction from Sentinel-2 datawere evaluated. In the next step, burn severity maps were derived from Sentinel-2 data alone, and the synergybetween Sentinel-2 & Sentinel-1 for this purpose was evaluated. Finally, the impact of the wildfire to soilerodibility estimates derived from the Revised Universal Soil Loss Equation (RUSLE) model implemented to theacquired Sentinel images was explored. In overall, the Support Vector Machines (SVMs) classifier obtained themost accurate burned area mapping, with a derived accuracy of 99.38%. An object-based SVMs classificationusing as input both optical and radar data was the most effective approach of delineating burn severity,achieving an overall accuracy of 92.97%. Soil erosion mapping predictions allowed quantifying the impact ofwildfire to soil erosion at the studied site, suggesting the method could be potentially of a wider use. Our resultscontribute to the understanding of wildland fire dynamics in the context of the Mediterranean ecosystem, demonstratingthe usefulness of Sentinels and of their derived products in wildfire mapping and assessment.

Effect of repeated fires on land-cover change on peatland in southern Central Kalimantan, Indonesia, from 1973 to 2005

2011 ◽  
Vol 20 (4) ◽  
pp. 578 ◽  
Author(s):  
Agata Hoscilo ◽  
Susan E. Page ◽  
Kevin J. Tansey ◽  
John O. Rieley
Keyword(s):  
Land Cover ◽  
Fire Regime ◽  
Fire Frequency ◽  
Selective Logging ◽  
Woody Vegetation ◽  
Burned Area ◽  
Swamp Forest ◽  
Peat Swamp Forest ◽  
Central Kalimantan ◽  
Peat Swamp

Fire plays an increasingly important role in deforestation and degradation of carbon-dense tropical peatlands in South-east Asia. In this study, analysis of a time-series of satellite images for the period 1973–2005 showed that repeated, extensive fires, following drainage and selective logging, played an important role in land-cover dynamics and forest loss in the peatlands of Central Kalimantan, Indonesia. A study of peatlands in the former Mega Rice Project area revealed a rising trend in the rate of deforestation and identified fire as the principal factor influencing subsequent vegetation succession. A step change in fire regime was identified, with an increase in burned area and fire frequency following peatland drainage. During the 23-year pre-Mega Rice Project period (1973–1996), peat swamp forest was the most extensive land-cover class and fires were of relatively limited extent, with very few repeated fires. During the 9-year post-Mega Rice Project period (1997–2005), there was a 72% fire-related loss in area of peat swamp forest, with most converted to non-woody vegetation, dominated by ferns or mosaics of trees and non-woody vegetation, rather than cultivated land.

Evaluation of the Aging Behavior of High Density Polyethylene in Thermal Oxidative Environment by Principal Component Analysis

2017 ◽  
Vol 727 ◽  
pp. 447-449 ◽  
Author(s):  
Jun Dai ◽  
Hua Yan ◽  
Jian Jian Yang ◽  
Jun Jun Guo
Keyword(s):  
Principal Component Analysis ◽  
Impact Strength ◽  
High Density Polyethylene ◽  
Tensile Modulus ◽  
Principal Component ◽  
Component Analysis ◽  
High Density ◽  
Aging Behavior ◽  
Data Set ◽  
The Impact

To evaluate the aging behavior of high density polyethylene (HDPE) under an artificial accelerated environment, principal component analysis (PCA) was used to establish a non-dimensional expression Z from a data set of multiple degradation parameters of HDPE. In this study, HDPE samples were exposed to the accelerated thermal oxidative environment for different time intervals up to 64 days. The results showed that the combined evaluating parameter Z was characterized by three-stage changes. The combined evaluating parameter Z increased quickly in the first 16 days of exposure and then leveled off. After 40 days, it began to increase again. Among the 10 degradation parameters, branching degree, carbonyl index and hydroxyl index are strongly associated. The tensile modulus is highly correlated with the impact strength. The tensile strength, tensile modulus and impact strength are negatively correlated with the crystallinity.

Sign in / Sign up

Export Citation Format

Share Document