scholarly journals Evaluation of short-term changes of hydrological response in mountainous basins of the Vitim Plateau (Russia) after forest fires based on data analysis and hydrological modelling

2015 ◽  
Vol 371 ◽  
pp. 157-162 ◽  
Author(s):  
O. M. Semenova ◽  
L. S. Lebedeva ◽  
N. V. Nesterova ◽  
T. A. Vinogradova
Keyword(s):  
Forest Fires ◽  
Model Performance ◽  
Burned Area ◽  
Model Parameters ◽  
Hydrological Response ◽  
Short Term ◽  
Burnt Area ◽  
Area Product ◽  
Induced Changes ◽  
Fire Impact

Abstract. Twelve mountainous basins of the Vitim Plateau (Eastern Siberia, Russia) with areas ranging from 967 to 18 200 km2 affected by extensive fires in 2003 (from 13 to 78% of burnt area) were delineated based on MODIS Burned Area Product. The studied area is characterized by scarcity of hydrometeorological observations and complex hydrological processes. Combined analysis of monthly series of flow and precipitation was conducted to detect short-term fire impact on hydrological response of the basins. The idea of basin-analogues which have significant correlation of flow with "burnt" watersheds in stationary (pre-fire) period with the assumption that fire impact produced an outlier of established dependence was applied. Available data allowed for qualitative detection of fire-induced changes at two basins from twelve studied. Summer flow at the Amalat and Vitimkan Rivers (22 and 78% proportion of burnt area in 2003, respectively) increased by 40–50% following the fire.The impact of fire on flow from the other basins was not detectable.The hydrological model Hydrograph was applied to simulate runoff formation processes for stationary pre-fire and non-stationary post-fire conditions. It was assumed that landscape properties changed after the fire suggest a flow increase. These changes were used to assess the model parameters which allowed for better model performance in the post-fire period.

scholarly journals Fractal properties of forest fires in Amazonia as a basis for modelling pan-tropical burned area

2013 ◽  
Vol 10 (8) ◽  
pp. 14141-14167 ◽  
Author(s):  
I. N. Fletcher ◽  
L. E. O. C. Aragão ◽  
A. Lima ◽  
Y. Shimabukuro ◽  
P. Friedlingstein
Keyword(s):  
Forest Fires ◽  
Fire Spread ◽  
Burned Area ◽  
Burnt Area ◽  
Pareto Model ◽  
Fractal Properties ◽  
Vegetation Models ◽  
Area Product ◽  
Global Vegetation ◽  
Tapered Pareto

Abstract. Current methods for modelling burnt area in Dynamic Global Vegetation Models involve complex fire spread calculations, which rely on many inputs, including fuel characteristics, wind speed and countless parameters. They are therefore susceptible to large uncertainties through error propagation. Using observed fractal distributions of fire scars in Brazilian Amazonia, we propose an alternative burnt area model for tropical forests, with fire counts as sole input and few parameters. Several parameterizations of two possible distributions are calibrated at multiple spatial resolutions using a satellite-derived burned area map, and compared. The tapered Pareto model most accurately simulates the total area burnt (only 3.5 km2 larger than the recorded 16 387 km2) and its spatial distribution. When tested pan-tropically using MODIS MCD14ML fire counts, the model accurately predicts temporal and spatial fire trends, but produces generally higher estimates than the GFED3.1 burnt area product, suggesting higher pan-tropical carbon emissions from fires than previously estimated.

scholarly journals MODIS Reflectance and Active Fire Data for Burn Mapping in Colombia

2011 ◽  
Vol 15 (10) ◽  
pp. 1-17 ◽  
Author(s):  
Silvia Merino-de-Miguel ◽  
Federico González-Alonso ◽  
Margarita Huesca ◽  
Dolors Armenteras ◽  
Carol Franco
Keyword(s):  
Terrestrial Ecosystem ◽  
Fire Detection ◽  
Cost Effective ◽  
Burned Area ◽  
Remotely Sensed Data ◽  
Burnt Area ◽  
Ecosystem Monitoring ◽  
Active Fire ◽  
Burned Area Mapping ◽  
Area Product

Abstract Satellite-based strategies for burned area mapping may rely on two types of remotely sensed data: postfire reflectance images and active fire detection. This study uses both methods in a synergistic way. In particular, burned area mapping is carried out using MCD43B4 [Moderate Resolution Imaging Spectrometer (MODIS); Terra + Aqua nadir bidirectional reflectance distribution function (BRDF); adjusted reflectance 16-day L3 global 1-km sinusoidal grid V005 (SIN)] postfire datasets and MODIS active fire products. The developed methodology was tested in Colombia, an area not covered by any known MODIS ground antenna, using data from 2004. The resulting burned area map was validated using a high-spatial-resolution Landsat-7 Enhanced Thematic Mapper Plus (ETM+) image and compared to two global burned area products: L3JRC (terrestrial ecosystem monitoring global burnt area product) and MCD45A1 (MODIS Terra + Aqua burned area monthly global 500-m SIN grid V005). The results showed that this method would be of great interest at regional to national scales because it proved to be quick, accurate, and cost effective.

Comparison of forest burned areas in mainland China derived from MCD45A1 and data recorded in yearbooks from 2001 to 2011

2015 ◽  
Vol 24 (1) ◽  
pp. 103 ◽  
Author(s):  
Jianfeng Li ◽  
Yu Song ◽  
Xin Huang ◽  
Mengmeng Li
Keyword(s):  
Forest Fires ◽  
Mainland China ◽  
Burned Area ◽  
Burned Areas ◽  
North East ◽  
China Forestry ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Area Product ◽  
Regional Forest ◽  
Official Data

Forest burning, which emits large amounts of trace gases and particulate matter into the atmosphere, produces great impacts on air quality and climate change. In this study, the MODIS (Moderate-Resolution Imaging Spectroradiometer) burned area product (MCD45A1) and GlobCover land-cover product were integrated to estimate the forest burned areas in mainland China from 2001 to 2011. The results were compared with the official data from China Forestry Yearbooks and China Forestry Statistical Yearbooks. On the national scale, the MCD45A1 data were comparable with the official data. However, great gaps exist between the MCD45A1-derived provincial and regional forest burned areas and the corresponding values from the Forestry Statistical Yearbooks. In particular, the MCD45A1-derived areas were higher than the Forestry Statistical Yearbooks in north-east China and significantly lower in south-west China. Moreover, it was indicated that the MCD45A1 algorithm was unsuitable for retrieving the burned areas of small forest fires. Nevertheless, the MCD45A1 exhibited excellent performance in retrieving seasonal patterns of forest fire, with high fire occurrence in spring and autumn. On balance, more studies are required to assess and improve the MCD45A1 product and more precise data on forest burned areas in China are urgently needed.

scholarly journals Short-Term Effects of Fire Severity on Vegetation Based on Sentinel-2 Satellite Data

2021 ◽  
Vol 13 (1) ◽  
pp. 432
Author(s):  
Aru Han ◽  
Song Qing ◽  
Yongbin Bao ◽  
Li Na ◽  
Yuhai Bao ◽  
...  
Keyword(s):  
Forest Fire ◽  
Forest Fires ◽  
Vegetation Change ◽  
Fire Severity ◽  
Dynamic Change ◽  
Burned Area ◽  
Fire Event ◽  
Vegetation Dynamic ◽  
Area Index ◽  
Sentinel 2

An important component in improving the quality of forests is to study the interference intensity of forest fires, in order to describe the intensity of the forest fire and the vegetation recovery, and to improve the monitoring ability of the dynamic change of the forest. Using a forest fire event in Bilahe, Inner Monglia in 2017 as a case study, this study extracted the burned area based on the BAIS2 index of Sentinel-2 data for 2016–2018. The leaf area index (LAI) and fractional vegetation cover (FVC), which are more suitable for monitoring vegetation dynamic changes of a burned area, were calculated by comparing the biophysical and spectral indices. The results showed that patterns of change of LAI and FVC of various land cover types were similar post-fire. The LAI and FVC of forest and grassland were high during the pre-fire and post-fire years. During the fire year, from the fire month (May) through the next 4 months (September), the order of areas of different fire severity in terms of values of LAI and FVC was: low > moderate > high severity. During the post fire year, LAI and FVC increased rapidly in areas of different fire severity, and the ranking of areas of different fire severity in terms of values LAI and FVC was consistent with the trend observed during the pre-fire year. The results of this study can improve the understanding of the mechanisms involved in post-fire vegetation change. By using quantitative inversion, the health trajectory of the ecosystem can be rapidly determined, and therefore this method can play an irreplaceable role in the realization of sustainable development in the study area. Therefore, it is of great scientific significance to quantitatively retrieve vegetation variables by remote sensing.

scholarly journals Tendencies of Fire Development in the Forests of Ukraine

2020 ◽  
Vol 3 (1) ◽  
pp. 106
Author(s):  
Yevhen Melnyk ◽  
Vladimir Voron
Keyword(s):  
Forest Management ◽  
Forest Fires ◽  
Necessary Conditions ◽  
Climatic Conditions ◽  
Anthropogenic Factors ◽  
Burned Area ◽  
Fire Occurrence ◽  
Management Zones ◽  
Wildfire Occurrence ◽  
Management Zone

Preservation and increase of forest area are necessary conditions for the biosphere functioning. Forest ecosystems in most parts of the world are affected by fires. According to the latest data, the forest fire situation has become complicated in Ukraine, and this issue requires ongoing investigation. The aim of the study was to analyse the dynamics of wildfires in Ukrainian forests over recent decades and to assess the complex indicator of wildfire occurrence in various forest management zones and administrative regions. The average annual complex indicator of fire occurrence, in terms of wildfire number and burned area, was studied in detail in the forests of various administrative regions and forest management zones in Ukraine from 1998 to 2017. The results show that fire occurrence in both the number and area of fires can vary significantly in various forest management zones. There is a very noticeable difference in these indicators in some administrative regions within a particular forest management zone. The data show that the number of forest fires depends not only on the natural and climatic conditions of such regions, but also on anthropogenic factors.

scholarly journals Enhanced Neural Network Model for Worldwide Estimation of Weighted Mean Temperature

2021 ◽  
Vol 13 (12) ◽  
pp. 2405
Author(s):  
Fengyang Long ◽  
Chengfa Gao ◽  
Yuxiang Yan ◽  
Jinling Wang
Keyword(s):  
Neural Network ◽  
Real Time ◽  
Model Performance ◽  
Global Scale ◽  
Radiosonde Data ◽  
Model Parameters ◽  
Measured Temperature ◽  
Weighted Mean ◽  
Weighted Mean Temperature ◽  
Application Scope

Precise modeling of weighted mean temperature (Tm) is critical for realizing real-time conversion from zenith wet delay (ZWD) to precipitation water vapor (PWV) in Global Navigation Satellite System (GNSS) meteorology applications. The empirical Tm models developed by neural network techniques have been proved to have better performances on the global scale; they also have fewer model parameters and are thus easy to operate. This paper aims to further deepen the research of Tm modeling with the neural network, and expand the application scope of Tm models and provide global users with more solutions for the real-time acquisition of Tm. An enhanced neural network Tm model (ENNTm) has been developed with the radiosonde data distributed globally. Compared with other empirical models, the ENNTm has some advanced features in both model design and model performance, Firstly, the data for modeling cover the whole troposphere rather than just near the Earth’s surface; secondly, the ensemble learning was employed to weaken the impact of sample disturbance on model performance and elaborate data preprocessing, including up-sampling and down-sampling, which was adopted to achieve better model performance on the global scale; furthermore, the ENNTm was designed to meet the requirements of three different application conditions by providing three sets of model parameters, i.e., Tm estimating without measured meteorological elements, Tm estimating with only measured temperature and Tm estimating with both measured temperature and water vapor pressure. The validation work is carried out by using the radiosonde data of global distribution, and results show that the ENNTm has better performance compared with other competing models from different perspectives under the same application conditions, the proposed model expanded the application scope of Tm estimation and provided the global users with more choices in the applications of real-time GNSS-PWV retrival.

scholarly journals Evolution of Burned Area in Forest Fires under Climate Change Conditions in Southern Spain Using ANN

2019 ◽  
Vol 9 (19) ◽  
pp. 4155
Author(s):  
Pérez-Sánchez ◽  
Jimeno-Sáez ◽  
Senent-Aparicio ◽  
Díaz-Palmero ◽  
de Dios Cabezas-Cerezo
Keyword(s):  
Climate Change ◽  
Forest Fires ◽  
Southern Spain ◽  
Burned Area ◽  
Change Scenario ◽  
Absolute Deviation ◽  
Average Temperature ◽  
Mediterranean Regions ◽  
Artificial Neural Network Ann ◽  
Absolute Percent Error

Wildfires in Mediterranean regions have become a serious problem, and it is currently the main cause of forest loss. Numerous prediction methods have been applied worldwide to estimate future fire activity and area burned in order to provide a stable basis for future allocation of fire-fighting resources. The present study investigated the performance of an artificial neural network (ANN) in burned area size prediction and to assess the evolution of future wildfires and the area concerned under climate change in southern Spain. The study area comprised 39.41 km2 of land burned from 2000 to 2014. ANNs were used in two subsequential phases: classifying the size of the wildfires and predicting the burned surface for fires larger than 30,000 m2. Matrix of confusion and 10-fold cross-validations were used to evaluate ANN classification and mean absolute deviation, root mean square error, mean absolute percent error and bias, which were the metrics used for burned area prediction. The success rate achieved was above 60–70% depending on the zone. An average temperature increase of 3 °C and a 20% increase in wind speed during 2071–2100 results in a significant increase of the number of fires, up to triple the current figure, resulting in seven times the average yearly burned surface depending on the zone and the climate change scenario.

Development of an Inverse Plume Model for Mass Eruption Rate in Unsteady Conditions

2021 ◽  
Author(s):  
Stephen A Solovitz
Keyword(s):  
Laboratory Data ◽  
Model Performance ◽  
Volcanic Eruptions ◽  
Reynolds Numbers ◽  
Model Parameters ◽  
Plume Height ◽  
Eruption Rate ◽  
Mass Eruption Rate ◽  
Downstream Effects ◽  
Order Of Magnitude

Abstract Following volcanic eruptions, forecasters need accurate estimates of mass eruption rate (MER) to appropriately predict the downstream effects. Most analyses use simple correlations or models based on large eruptions at steady conditions, even though many volcanoes feature significant unsteadiness. To address this, a superposition model is developed based on a technique used for spray injection applications, which predicts plume height as a function of the time-varying exit velocity. This model can be inverted, providing estimates of MER using field observations of a plume. The model parameters are optimized using laboratory data for plumes with physically-relevant exit profiles and Reynolds numbers, resulting in predictions that agree to within 10% of measured exit velocities. The model performance is examined using a historic eruption from Stromboli with well-documented unsteadiness, again providing MER estimates of the correct order of magnitude. This method can provide a rapid alternative for real-time forecasting of small, unsteady eruptions.

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