Probability based models for estimation of wildfire risk

2004 ◽  
Vol 13 (2) ◽  
pp. 133 ◽  
Author(s):  
Haiganoush K. Preisler ◽  
David R. Brillinger ◽  
Robert E. Burgan ◽  
J. W. Benoit
Keyword(s):  
Fire Risk ◽  
Small Region ◽  
The State ◽  
Grouped Data ◽  
Large Fire ◽  
Explanatory Variables ◽  
Time Period ◽  
Monthly Total ◽  
Historic Data ◽  
Large Fires

We present a probability-based model for estimating fire risk. Risk is defined using three probabilities: the probability of fire occurrence; the conditional probability of a large fire given ignition; and the unconditional probability of a large fire. The model is based on grouped data at the 1 km2-day cell level. We fit a spatially and temporally explicit non-parametric logistic regression to the grouped data. The probability framework is particularly useful for assessing the utility of explanatory variables, such as fire weather and danger indices for predicting fire risk. The model may also be used to produce maps of predicted probabilities and to estimate the total number of expected fires, or large fires, in a given region and time period. As an example we use historic data from the State of Oregon to study the significance and the forms of relationships between some of the commonly used weather and danger variables on the probabilities of fire. We also produce maps of predicted probabilities for the State of Oregon. Graphs of monthly total numbers of fires are also produced for a small region in Oregon, as an example, and expected numbers are compared to actual numbers of fires for the period 1989–1996. The fits appear to be reasonable; however, the standard errors are large indicating the need for additional weather or topographic variables.

scholarly journals Spatiotemporal mapping of soybean plantations in Rondônia, Western Brazilian Amazon

2017 ◽  
Vol 47 (1) ◽  
pp. 29-38 ◽  
Author(s):  
Olívia Bueno da COSTA ◽  
Eraldo Aparecido Trondoli MATRICARDI ◽  
Marcos Antonio PEDLOWSKI ◽  
Mark Alan COCHRANE ◽  
Luiz Cláudio FERNANDES
Keyword(s):  
Landsat Imagery ◽  
Distribution Patterns ◽  
The State ◽  
Commission Errors ◽  
Spatiotemporal Mapping ◽  
Crop Fields ◽  
Decision Tree Classification ◽  
Time Period ◽  
Global Accuracy ◽  
Spectral Mixture

ABSTRACT Although soybean production has been increasing in the state of Rondônia in the last decade, soybean planted area has been estimated indirectly using secondary datasets, which has limited understanding of its spatiotemporal distribution patterns. This study aimed to map and analyze spatial patterns of soybean expansion in Rondônia. We developed a classification technique based on Spectral Mixture Analysis (SMA) derived from Landsat imagery and Decision Tree Classification to detect and map soybean plantations in 2000, 2005, 2010, and 2014. The soybean classification map showed 93% global accuracy, 23% omission and 0% of commission errors for soybean crop fields. The greatest increases of soybean cropped area in the state of Rondônia were observed between 2000-2005 and 2005-2010 time-periods (33,239 ha and 59,628 ha, respectively), mostly located in Southern Rondônia. The expansion of soybean areas to Northern Rondônia (25,627 ha) has mostly occurred in the 2010-2014 time period. We estimate that 95.4% of all newly created soybean plantations, detected by 2014, were established on lands deforested nine or more years earlier. We concluded that the incursion of soybean plantations on lands deforested for other land uses (e.g. ranching) is contributing to their displacement (pastures) from older colonization zones toward more remote frontier areas of the Amazon, exacerbating new deforestation there.

scholarly journals Summarizing the state of the terrestrial biosphere in few dimensions

2019 ◽  
Author(s):  
Guido Kraemer ◽  
Gustau Camps-Valls ◽  
Markus Reichstein ◽  
Miguel D. Mahecha
Keyword(s):  
Data Streams ◽  
Land Surface ◽  
Principal Component ◽  
The State ◽  
Climate Indices ◽  
Surface Dynamics ◽  
Terrestrial Biosphere ◽  
Explanatory Variables ◽  
Arctic Regions ◽  
Agricultural Areas

Abstract. In times of global change, we must closely monitor the state of the planet in order to understand gradual or abrupt changes early on. In fact, each of the Earth's subsystems – i.e. the biosphere, atmosphere, hydrosphere, and cryosphere – can be analyzed from a multitude of data streams. However, since it is very hard to jointly interpret multiple monitoring data streams in parallel, one often aims for some summarizing indicator. Climate indices, for example, summarize the state of atmospheric circulation in a region. Although such approaches are also used in other fields of science, they are rarely used to describe land surface dynamics. Here, we propose a robust method to create indicators for the terrestrial biosphere using principal component analysis based on a high-dimensional set of relevant global data streams. The concept was tested using 12 explanatory variables representing the biophysical states of ecosystems and land-atmosphere water, energy, and carbon fluxes. We find that two indicators account for 73 % of the variance of the state of the biosphere in space and time. While the first indicator summarizes productivity patterns, the second indicator summarizes variables representing water and energy availability. Anomalies in the indicators clearly identify extreme events, such as the Amazon droughts (2005 and 2010) and the Russian heatwave (2010), they also allow us to interpret the impacts of these events. The indicators also reveal changes in the seasonal cycle, e.g. increasing seasonal amplitudes of productivity in agricultural areas and in arctic regions. We assume that this generic approach has great potential for the analysis of land-surface dynamics from observational or model data.

scholarly journals Climate change and forest management affect forest fire risk in Fennoscandia

2021 ◽  
Author(s):  
Keyword(s):  
Climate Change ◽  
Forest Management ◽  
Black Carbon ◽  
Forest Fire ◽  
Forest Fires ◽  
Fire Risk ◽  
The Arctic ◽  
Large Fires ◽  
Forest Fire Risk ◽  
Fire Ignition

Forest and wildland fires are a natural part of ecosystems worldwide, but large fires in particular can cause societal, economic and ecological disruption. Fires are an important source of greenhouse gases and black carbon that can further amplify and accelerate climate change. In recent years, large forest fires in Sweden demonstrate that the issue should also be considered in other parts of Fennoscandia. This final report of the project “Forest fires in Fennoscandia under changing climate and forest cover (IBA ForestFires)” funded by the Ministry for Foreign Affairs of Finland, synthesises current knowledge of the occurrence, monitoring, modelling and suppression of forest fires in Fennoscandia. The report also focuses on elaborating the role of forest fires as a source of black carbon (BC) emissions over the Arctic and discussing the importance of international collaboration in tackling forest fires. The report explains the factors regulating fire ignition, spread and intensity in Fennoscandian conditions. It highlights that the climate in Fennoscandia is characterised by large inter-annual variability, which is reflected in forest fire risk. Here, the majority of forest fires are caused by human activities such as careless handling of fire and ignitions related to forest harvesting. In addition to weather and climate, fuel characteristics in forests influence fire ignition, intensity and spread. In the report, long-term fire statistics are presented for Finland, Sweden and the Republic of Karelia. The statistics indicate that the amount of annually burnt forest has decreased in Fennoscandia. However, with the exception of recent large fires in Sweden, during the past 25 years the annually burnt area and number of fires have been fairly stable, which is mainly due to effective fire mitigation. Land surface models were used to investigate how climate change and forest management can influence forest fires in the future. The simulations were conducted using different regional climate models and greenhouse gas emission scenarios. Simulations, extending to 2100, indicate that forest fire risk is likely to increase over the coming decades. The report also highlights that globally, forest fires are a significant source of BC in the Arctic, having adverse health effects and further amplifying climate warming. However, simulations made using an atmospheric dispersion model indicate that the impact of forest fires in Fennoscandia on the environment and air quality is relatively minor and highly seasonal. Efficient forest fire mitigation requires the development of forest fire detection tools including satellites and drones, high spatial resolution modelling of fire risk and fire spreading that account for detailed terrain and weather information. Moreover, increasing the general preparedness and operational efficiency of firefighting is highly important. Forest fires are a large challenge requiring multidisciplinary research and close cooperation between the various administrative operators, e.g. rescue services, weather services, forest organisations and forest owners is required at both the national and international level.

scholarly journals Modeling of public transport waiting time indicator for the transport network of a large city

2018 ◽  
Vol 224 ◽  
pp. 04018 ◽  
Author(s):  
Olga Lebedeva ◽  
Marina Kripak
Keyword(s):  
Waiting Time ◽  
Large City ◽  
Distribution Functions ◽  
Weibull Function ◽  
Explanatory Variables ◽  
Transport Services ◽  
Time Period ◽  
Bus Stops ◽  
The Difference ◽  
Expected Waiting Time

The need to develop and improve public passenger transport in major cities was noted. It was reflected that waiting time at bus stops is one of the factors that have a big impact on the passenger quality assessment of transport services. The results of an empirical study of the actual and anticipated waiting time at bus stops were given. It was noted that the reliability functions were used in the field of ride duration modeling, traffic restoration time after an accident, and length of making the decision to travel. The waiting time distribution functions using the lognormal function and the Weibull function were chosen. The results of modeling were objective, the dependent variables in it were the expected waiting time of passengers and the difference between the anticipated and the actual waiting time. The explanatory variables were sex, age, time period, purpose of the trip and the actual waiting time. The results of the research showed that the age, purpose of the trip and the time period influence the waiting time perception, prolong it and lead to its reassessment.

scholarly journals Verification of Red Flag Warnings across the Northwestern U.S. as Forecasts of Large Fire Occurrence

Fire ◽  
2020 ◽  
Vol 3 (4) ◽  
pp. 60
Author(s):  
Joshua Clark ◽  
John T. Abatzoglou ◽  
Nicholas J. Nauslar ◽  
Alistair M.S. Smith
Keyword(s):  
Early Warning ◽  
Warning System ◽  
Early Warning Systems ◽  
The United States ◽  
Fire Occurrence ◽  
Warning Systems ◽  
Large Fire ◽  
Fire Activity ◽  
Large Fires ◽  
Red Flag

Red Flag Warnings (RFWs) issued by the National Weather Service in the United States (U.S.) are an important early warning system for fire potential based on forecasts of critical fire weather that promote increased fire activity, including the occurrence of large fires. However, verification of RFWs as they relate to fire activity is lacking, thereby limiting means to improve forecasts as well as increase value for end users. We evaluated the efficacy of RFWs as forecasts of large fire occurrence for the Northwestern U.S.—RFWs were shown to have widespread significant skill and yielded an overall 124% relative improvement in forecasting large fire occurrences than a reference forecast. We further demonstrate that the skill of RFWs is significantly higher for lightning-ignited large fires than for human-ignited fires and for forecasts issued during periods of high fuel dryness than those issued in the absence of high fuel dryness. The results of this first verification study of RFWs related to actualized fire activity lay the groundwork for future efforts towards improving the relevance and usefulness of RFWs and other fire early warning systems to better serve the fire community and public.

scholarly journals Summarizing the state of the terrestrial biosphere in few dimensions

2020 ◽  
Vol 17 (9) ◽  
pp. 2397-2424 ◽  
Author(s):  
Guido Kraemer ◽  
Gustau Camps-Valls ◽  
Markus Reichstein ◽  
Miguel D. Mahecha
Keyword(s):  
Data Streams ◽  
Land Surface ◽  
Principal Component ◽  
The State ◽  
Climate Indices ◽  
Surface Dynamics ◽  
Terrestrial Biosphere ◽  
Explanatory Variables ◽  
Arctic Regions ◽  
Agricultural Areas

Abstract. In times of global change, we must closely monitor the state of the planet in order to understand the full complexity of these changes. In fact, each of the Earth's subsystems – i.e., the biosphere, atmosphere, hydrosphere, and cryosphere – can be analyzed from a multitude of data streams. However, since it is very hard to jointly interpret multiple monitoring data streams in parallel, one often aims for some summarizing indicator. Climate indices, for example, summarize the state of atmospheric circulation in a region. Although such approaches are also used in other fields of science, they are rarely used to describe land surface dynamics. Here, we propose a robust method to create global indicators for the terrestrial biosphere using principal component analysis based on a high-dimensional set of relevant global data streams. The concept was tested using 12 explanatory variables representing the biophysical state of ecosystems and land–atmosphere fluxes of water, energy, and carbon fluxes. We find that three indicators account for 82 % of the variance of the selected biosphere variables in space and time across the globe. While the first indicator summarizes productivity patterns, the second indicator summarizes variables representing water and energy availability. The third indicator represents mostly changes in surface albedo. Anomalies in the indicators clearly identify extreme events, such as the Amazon droughts (2005 and 2010) and the Russian heat wave (2010). The anomalies also allow us to interpret the impacts of these events. The indicators can also be used to detect and quantify changes in seasonal dynamics. Here we report, for instance, increasing seasonal amplitudes of productivity in agricultural areas and arctic regions. We assume that this generic approach has great potential for the analysis of land surface dynamics from observational or model data.

scholarly journals Trends and variability of midlatitude stratospheric water vapour deduced from the re-evaluated Boulder balloon series and HALOE

2008 ◽  
Vol 8 (5) ◽  
pp. 1391-1402 ◽  
Author(s):  
M. Scherer ◽  
H. Vömel ◽  
S. Fueglistaler ◽  
S. J. Oltmans ◽  
J. Staehelin
Keyword(s):  
Water Vapour ◽  
Linear Trend ◽  
Potential Temperature ◽  
Data Series ◽  
Explanatory Variables ◽  
Time Period ◽  
Corrected Data ◽  
Instrumental Bias ◽  
The Tropics ◽  
Stratospheric Water Vapour

Abstract. This paper presents an updated trend analysis of water vapour in the lower midlatitude stratosphere from the Boulder balloon-borne NOAA frostpoint hygrometer measurements and from the Halogen Occulation Experiment (HALOE). Two corrections for instrumental bias are applied to homogenise the frostpoint data series, and a quality assessment of all soundings after 1991 is presented. Linear trend estimates based on the corrected data for the period 1980–2000 are up to 40% lower than previously reported. Vertically resolved trends and variability are calculated with a multi regression analysis including the quasi-biennal oscillation and equivalent latitude as explanatory variables. In the range of 380 to 640 K potential temperature (≈14 to 25 km), the frostpoint data from 1981 to 2006 show positive linear trends between 0.3±0.3 and 0.7±0.1%/yr. The same dataset shows trends between −0.2±0.3 and 1.0±0.3%/yr for the period 1992 to 2005. HALOE data over the same time period suggest negative trends ranging from −1.1±0.2 to −0.1±0.1%/yr. In the lower stratosphere, a rapid drop of water vapour is observed in 2000/2001 with little change since. At higher altitudes, the transition is more gradual, with slowly decreasing concentrations between 2001 and 2007. This pattern is consistent with a change induced by a drop of water concentrations at entry into the stratosphere. Previously noted differences in trends and variability between frostpoint and HALOE remain for the homogenised data. Due to uncertainties in reanalysis temperatures and stratospheric transport combined with uncertainties in observations, no quantitative inference about changes of water entering the stratosphere in the tropics could be made with the mid latitude measurements analysed here.

Ending Grand Alliance Politics in Western Europe: US Anti-communism in France and Italy, 1944–7

2017 ◽  
Vol 53 (1) ◽  
pp. 134-157 ◽  
Author(s):  
Alessandro Brogi
Keyword(s):  
Cold War ◽  
Western Europe ◽  
The State ◽  
Alliance Politics ◽  
Time Period ◽  
The Us ◽  
The Usa ◽  
Grand Alliance ◽  
The Cold War ◽  
Transitional Phase

The postwar ascendancy of the French and Italian Communist Parties (PCF and PCI) as the strongest ones in the emerging Western alliance was an unexpected challenge for the USA. The US response during this time period (1944–7) was tentative, and relatively moderate, reflecting the still transitional phase from wartime Grand Alliance politics to Cold War. US anti-communism in Western Europe remained guarded for diplomatic and political reasons, but it never mirrored the ambivalence of anti-Americanism among French and especially Italian Communist leaders and intellectuals. US prejudicial opposition to a share of communist power in the French and Italian provisional governments was consistently strong. A relatively decentralized approach by the State Department, however, gave considerable discretion to moderate, circumspect US officials on the ground in France and Italy. The subsequent US turn toward an absolute struggle with Western European communism was only in small part a reaction to direct provocations from Moscow, or the PCI and PCF. The two parties and their powerful propaganda appeared likely to undermine Western cohesion; this was the first depiction, by the USA and its political allies in Europe, of possible domino effects in the Cold War.

scholarly journals "DEPUTIES CARTOGRAPHY" ON THE MATERIAL OF THE STENOGRAMS OF THE SITTINGS OF THE STATE DUMA

2020 ◽  
Vol 14 (4) ◽  
pp. 138-152
Author(s):  
Konstantin Belousov ◽  
◽  
Konstantin Ryabinin ◽  
Ilya Labutin ◽  
Konstantin Sulimov ◽  
...  
Keyword(s):  
Russian Federation ◽  
Visual Analytics ◽  
Text Processing ◽  
Interdisciplinary Approach ◽  
Federal District ◽  
Semantic Space ◽  
The State ◽  
Natural Language Text ◽  
Time Period ◽  
Reported Study

Public speeches of the deputies of the Russian Federation State Duma represent productive empirical material that requires an interdisciplinary approach to its analysis. The goal of the reported study is defining the degree of the concord regarding the future of Russia among deputies and the localization of this agreement in the semantic space (equilibrium point). The empirical base under consideration comprises the transcripts of Russian Federation State Duma sittings. This dataset covers time period from 1994 to mid-2020 and includes 324 thousand phrases (27 million words) from 2773 deputies and other people. The paper presents the general design of the study of the State Duma deputies discourse using the "Semograph" information system, the SlovNet library for natural language text processing based on deep learning, the SciVi visual analytics platform, the map visualization module based on the Leaflet library, the geocoding of geographic objects based on the OpenStreetMap map provider and other tools. The application of the approach showed the importance of the institutional foundations of the symbolic deputies' mapping of the regions of the Volga Federal District (the electoral connection of a deputy with the region – deputies elected by party list or pluralist rule).

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