Integration of AWiFS and MODIS active fire data for burn mapping at regional level using the Burned Area Synergic Algorithm (BASA)

2009 ◽  
Vol 18 (4) ◽  
pp. 404 ◽  
Author(s):  
Federico González-Alonso ◽  
Silvia Merino-de-Miguel
Keyword(s):  
Forest Fires ◽  
Burned Area ◽  
Wide Field ◽  
Imaging Spectrometer ◽  
Area Index ◽  
North West ◽  
Active Fire ◽  
Moderate Resolution ◽  
Field Sensor ◽  
Speed Accuracy

The present paper presents an algorithm that synergistically combines data from four different parts of the spectrum (near-, shortwave, middle- and thermal infrared) to produce a reliable burned-area map. It is based on the use of a modified version of the BAIM (MODIS – Moderate Resolution Imaging Spectrometer – Burned Area Index) together with active fire information. The following study focusses in particular on an image from the AWiFS (Advanced Wide Field Sensor) sensor dated 21 August 2006 and MODIS active fires detected during the first 20 days of August as well as ancillary maps and information. The methodology was tested in Galicia (north-west Spain) where hundreds of forest fires occurred during the first 20 days of August 2006. Burned area data collected from the present work was compared with official fire statistics from both the Spanish Ministry of the Environment and the Galician Forestry Service. The speed, accuracy and cost-effectiveness of this method suggest that it would be of great interest for use at both regional and national levels.

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 Global and regional evaluation of over-land spectral aerosol optical depth retrievals from SeaWiFS

2012 ◽  
Vol 5 (2) ◽  
pp. 2169-2220 ◽  
Author(s):  
A. M. Sayer ◽  
N. C. Hsu ◽  
C. Bettenhausen ◽  
M.-J. Jeong ◽  
B. N. Holben ◽  
...  
Keyword(s):  
North America ◽  
Aerosol Optical Depth ◽  
Optical Depth ◽  
Field Of View ◽  
Wide Field ◽  
Imaging Spectrometer ◽  
Wide Field Of View ◽  
Moderate Resolution ◽  
Resolution Imaging ◽  
Multiangle Imaging

Abstract. This study evaluates a new spectral aerosol optical depth (AOD) dataset derived from Sea-viewing Wide Field-of-view Sensor (SeaWiFS) measurements over land. First, the data are validated against Aerosol Robotic Network (AERONET) direct-sun AOD measurements, and found to compare well on a global basis. If only data with the highest quality flag are used, the correlation is 0.86 and 72% of matchups fall within an expected absolute uncertainty of 0.05 + 20% (for the wavelength of 550 nm). The quality is similar at other wavelengths and stable over the 13-yr (1997–2010) mission length. Performance tends to be better over vegetated, low-lying terrain with typical AOD of 0.3 or less, such as found over much of North America and Eurasia. Performance tends to be poorer for low-AOD conditions near backscattering geometries, where SeaWiFS overestimates AOD, or optically-thick cases of absorbing aerosol, where SeaWiFS tends to underestimate AOD. Second, the SeaWiFS data are compared with midvisible AOD derived from the Moderate Resolution Imaging Spectrometer (MODIS) and Multiangle Imaging Spectroradiometer (MISR). All instruments show similar spatial and seasonal distributions of AOD, although there are regional and seasonal offsets between them. At locations where AERONET data are available, these offsets are largely consistent with the known validation characteristics of each dataset. With the results of this study in mind, the SeaWiFS over-land AOD record is suitable for quantitative scientific use.

scholarly journals Identification of Aerosol Sources in Siberia and Study of Aerosol Transport at Regional Scale by Airborne and Space-Borne Lidar Measurement

2020 ◽  
Vol 237 ◽  
pp. 02014
Author(s):  
Antonin Zabukovec ◽  
Gérard Ancellet ◽  
Jacques Pelon ◽  
J.D. Paris ◽  
Iogannes E. Penner ◽  
...  
Keyword(s):  
Forest Fires ◽  
Dispersion Model ◽  
Regional Scale ◽  
Particle Dispersion ◽  
Airborne Lidar ◽  
Orthogonal Polarization ◽  
Lidar Measurement ◽  
Imaging Spectrometer ◽  
Modis Aod ◽  
Moderate Resolution

Airborne lidar measurements were carried out over Siberia in July 2013 and June 2017. Aerosol optical properties are derived using the Lagrangian FLEXible PARTicle dispersion model (FLEXPART) simulations and Moderate Resolution Imaging Spectrometer (MODIS) AOD. Comparison with Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) aerosol products is used to validate the CALIOP aerosol type identification above Siberia. Two case studies are discussed : a mixture of dust and pollution from Northern Kazakhstan and smoke plumes from forest fires. Comparisons with the CALIOP backscatter ratio show that CALIOP algorithm may overestimate the LR for a dusty mixture if not constrained by an independent AOD measurement.

scholarly journals Lidar profiling of aerosol optical properties from Paris to Lake Baikal (Siberia)

2015 ◽  
Vol 15 (9) ◽  
pp. 5007-5026 ◽  
Author(s):  
E. Dieudonné ◽  
P. Chazette ◽  
F. Marnas ◽  
J. Totems ◽  
X. Shang
Keyword(s):  
Optical Properties ◽  
Lake Baikal ◽  
Forest Fires ◽  
Western Europe ◽  
Lower Boundary ◽  
Aerosol Optical Properties ◽  
Imaging Spectrometer ◽  
Moderate Resolution ◽  
The Difference ◽  
First Time

Abstract. In June 2013, a ground-based mobile lidar performed the ~10 000 km ride from Paris to Ulan-Ude, near Lake Baikal, profiling for the first time aerosol optical properties all the way from western Europe to central Siberia. The instrument was equipped with N2-Raman and depolarization channels that enabled an optical speciation of aerosols in the low and middle troposphere. The extinction-to-backscatter ratio (also called lidar ratio or LR) and particle depolarization ratio (PDR) at 355 nm have been retrieved. The LR in the lower boundary layer (300–700 m) was found to be 63 ± 17 sr on average during the campaign with a distribution slightly skewed toward higher values that peaks between 50 and 55 sr. Although the difference is small, PDR values observed in Russian cities (>2%, except after rain) are systematically higher than the ones measured in Europe (<1%), which is probably an effect of the lifting of terrigenous aerosols by traffic on roads. Biomass burning layers from grassland or/and forest fires in southern Russia exhibit LR values ranging from 65 to 107 sr and from 3 to 4% for the PDR. During the route, desert dust aerosols originating from the Caspian and Aral seas regions were characterized for the first time, with a LR (PDR) of 43 ± 14 sr (23 ± 2%) for pure dust. The lidar observations also showed that this dust event extended over 2300 km and lasted for ~6 days. Measurements from the Moderate Resolution Imaging Spectrometer (MODIS) show that our results are comparable in terms of aerosol optical thickness (between 0.05 and 0.40 at 355 nm) with the mean aerosol load encountered throughout our route.

scholarly journals Near Real-Time Automated Early Mapping of the Perimeter of Large Forest Fires from the Aggregation of VIIRS and MODIS Active Fires in Mexico

2020 ◽  
Vol 12 (12) ◽  
pp. 2061 ◽  
Author(s):  
Carlos Ivan Briones-Herrera ◽  
Daniel José Vega-Nieva ◽  
Norma Angélica Monjarás-Vega ◽  
Jaime Briseño-Reyes ◽  
Pablito Marcelo López-Serrano ◽  
...  
Keyword(s):  
Real Time ◽  
Forest Fires ◽  
Large Scale ◽  
Infrared Imaging ◽  
Activity Patterns ◽  
Burned Area ◽  
Management Decision ◽  
Coarse Scale ◽  
Early Evaluation ◽  
Active Fire

In contrast with current operational products of burned area, which are generally available one month after the fire, active fires are readily available, with potential application for early evaluation of approximate fire perimeters to support fire management decision making in near real time. While previous coarse-scale studies have focused on relating the number of active fires to a burned area, some local-scale studies have proposed the spatial aggregation of active fires to directly obtain early estimate perimeters from active fires. Nevertheless, further analysis of this latter technique, including the definition of aggregation distance and large-scale testing, is still required. There is a need for studies that evaluate the potential of active fire aggregation for rapid initial fire perimeter delineation, particularly taking advantage of the improved spatial resolution of the Visible Infrared Imaging Radiometer (VIIRS) 375 m, over large areas and long periods of study. The current study tested the use of convex hull algorithms for deriving coarse-scale perimeters from Moderate Resolution Imaging Spectroradiometer (MODIS) and Visible Infrared Imaging Radiometer Suite (VIIRS) active fire detections, compared against the mapped perimeter of the MODIS collection 6 (MCD64A1) burned area. We analyzed the effect of aggregation distance (750, 1000, 1125 and 1500 m) on the relationships of active fire perimeters with MCD64A1, for both individual fire perimeter prediction and total burned area estimation, for the period 2012–2108 in Mexico. The aggregation of active fire detections from MODIS and VIIRS demonstrated a potential to offer coarse-scale early estimates of the perimeters of large fires, which can be available to support fire monitoring and management in near real time. Total burned area predicted from aggregated active fires followed the same temporal behavior as the standard MCD64A1 burned area, with potential to also account for the role of smaller fires detected by the thermal anomalies. The proposed methodology, based on easily available algorithms of point aggregation, is susceptible to be utilized both for near real-time and historical fire perimeter evaluation elsewhere. Future studies might test active fires aggregation between regions or biomes with contrasting fuel characteristics and human activity patterns against medium resolution (e.g., Landsat and Sentinel) fire perimeters. Furthermore, coarse-scale active fire perimeters might be utilized to locate areas where such higher-resolution imagery can be downloaded to improve the evaluation of fire extent and impact.

Poisson mixed models for predicting number of fires

2019 ◽  
Vol 28 (3) ◽  
pp. 237
Author(s):  
Miguel Boubeta ◽  
María José Lombardía ◽  
Manuel Marey-Pérez ◽  
Domingo Morales
Keyword(s):  
Forest Fires ◽  
Mixed Models ◽  
Mixed Model ◽  
Parametric Bootstrap ◽  
Temporal Correlation ◽  
Autoregressive Process ◽  
Burned Area ◽  
Time Effects ◽  
North West ◽  
Temporal Models

Wildfires are considered one of the main causes of forest destruction. In recent years, the number of forest fires and burned area in Mediterranean regions have increased. This problem particularly affects Galicia (north-west of Spain). Conventional modelling of the number of forest fires in small areas may have a high error. For this reason, four area-level Poisson mixed models with time effects are proposed. The first two models contain independent time effects, whereas the random effects of the other models are distributed according to an autoregressive process AR(1). A parametric bootstrap algorithm is given to measure the accuracy of the plug-in predictor of fire number under the temporal models. A significant prediction improvement is observed when using Poisson regression models with random time effects. Analysis of historical data finds significant meteorological and socioeconomic variables explaining the number of forest fires by area and reveals the presence of a temporal correlation structure captured by the area-level Poisson mixed model with AR(1) time effects.

Rapid locating of fire points from Formosat-2 high spatial resolution imagery: example of the 2007 California wildfire

2009 ◽  
Vol 18 (4) ◽  
pp. 415 ◽  
Author(s):  
Cheng-Chien Liu ◽  
An-Ming Wu ◽  
Sheng-Yun Yen ◽  
Chiung-Huei Huang
Keyword(s):  
Spatial Resolution ◽  
Near Infrared ◽  
High Spatial Resolution ◽  
Burned Area ◽  
Infrared Band ◽  
Imaging Spectrometer ◽  
Modis Image ◽  
Local Spatial Statistics ◽  
Moderate Resolution ◽  
Resolution Imaging

We report the rapid response of Formosat-2 to locate the fire points in the 2007 California wildfire. After examining the Moderate Resolution Imaging Spectrometer (MODIS) image taken and released on 23 October 2007, we used the agility of Formosat-2 to take high spatial resolution images of the wildfire front on its next overpass of the newly burned area. By calculating the local spatial statistics of the near-infrared band, fire points with a scale of a few metres can be accurately identified on the 2-m pan-sharpened Formosat-2 image. The present work suggests that the synergistic operation of MODIS and Formosat-2 would enable the rapid locating of fire points during wildfires.

Snow cover mapping using IRS-P6 AWiFS data and the relationships between some climatic factors with snowpack in the northwest of Iran

2015 ◽  
Vol 7 (2) ◽  
pp. 415-429
Author(s):  
M. Seyedielmabad ◽  
H. R. Moradi
Keyword(s):  
Snow Cover ◽  
Climatic Factors ◽  
Unsupervised Classification ◽  
Wide Field ◽  
Snow Cover Area ◽  
Multi Temporal ◽  
Moderate Resolution ◽  
Field Sensor ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Normalized Difference Snow Index

In this study, we explored the potential of the multispectral and multi-temporal IRS Advanced Wide Field Sensor (AWiFS) data for mapping of the snow cover in the northwest regions of Iran. The AWiFS snow cover maps, based on the unsupervised classification method, were compared with the estimates of snow cover area derived from the moderate resolution imaging spectroradiometer (MODIS) images based on the normalized difference snow index. Good concurrence was observed with respect to the snow area between the AWiFS features and the MODIS features; however, the snow spatial distribution of the AWiFS features differed from those of the MODIS based on the nonentity of the temporal accordance between two types of features. Also, we explored the relationships between some climatic and topographic factors with the snowpack in the northwest part of Iran. Relationships between some climatic factors with snowpack specifications were obtained, which showed significant correlation only between the components of daily temperature and snow density. The other results showed that the amounts of snowpack depth have significant correlations with the height of the stations and the height classes in 1% surface and snowpack depths showed significant differences together within the different height classes.

scholarly journals Fire Activity and Their Relationship with the Global Fire Weather Index Database Components in Guinea

2019 ◽  
Vol 8 (2) ◽  
pp. 18
Author(s):  
Mamadou Baïlo Barry ◽  
Daouda Badiane ◽  
Saïdou Moustapha Sall ◽  
Moussa Diakhaté ◽  
Habib Senghor
Keyword(s):  
Statistical Analysis ◽  
Fire Behavior ◽  
Burned Area ◽  
Fire Weather ◽  
Weather Index ◽  
Fire Weather Index ◽  
Burned Areas ◽  
Active Fire ◽  
Moderate Resolution ◽  
Moderate Resolution Imaging Spectroradiometer

The relationships between the Canadian Fire Weather Index (FWI) System components and the monthly burned area as well as the number of active fire which has taken from Moderate Resolution Imaging Spectroradiometer (MODIS) Aqua/TERRA were investigated in 32 Guinean stations between 2003 and 2013. A statistical analysis based on a multi-linear regression model was used to estimate the skills of FWI components on the predictability of burned area and active fire. This statistical analysis gave performances explaining between 16 to 79% of the variance for the burned areas and between 29 and 82% of the variance for the number of fires (P<0.0001) at lag 0. Respectively 16 to 79 % and 29 to 82 % of the variance of the burned areas and variance for the number of fires (P<0.0001) at lag0 can be explained based on the same statistical analysis. All the combinations used gave significant performances to predict the burned areas and active fire on the monthly timescale in all stations excepted Fria and Yomou where the predictability of the burned areas was not obvious. We obtained a significant correlation between the average over all of the stations of burned areas, active fires and FWI composites with percentage of variance between (75 to 84% and 29 to 77%) for active fires and burned areas at lag0 respectively. While for burned area peak (January), the skill of the predictability remains significant only one month in advance, for the active fires, the model remains skilful 1 to 3 months in advance. Results also showed that active fires are more related to fire behavior indices while the burned areas are related to the fine fuel moisture codes. These outcomes have implications for seasonal forecasting of active fire events and burned areas based on FWI components, as significant predictability is found from 1 to 3 months and one month before respectively.

Fire danger estimation from MODIS Enhanced Vegetation Index data: application to Galicia region (north-west Spain)

2011 ◽  
Vol 20 (3) ◽  
pp. 465 ◽  
Author(s):  
M. M. Bisquert ◽  
J. M. Sánchez ◽  
V. Caselles
Keyword(s):  
Forest Fires ◽  
Vegetation Index ◽  
Estimation Error ◽  
Fire Danger ◽  
Enhanced Vegetation Index ◽  
North West ◽  
Remote Sensing Technique ◽  
Moderate Resolution ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Terra Satellite

Galicia, in north-west Spain, is a region especially affected by devastating forest fires. The development of a fire danger prediction model adapted to this particular region is required. In this paper, we focus on changes in the condition of vegetation as an indicator of fire danger. The potential of the Enhanced Vegetation Index (EVI) together with period-of-year to monitor vegetation changes in Galicia is shown. The Moderate Resolution Imaging Spectroradiometer (MODIS), onboard the Terra satellite, was chosen for this study. A 6-year dataset of EVI images, from the product MOD13Q1 (16-day composites), together with fire data in a 10 × 10-km grid basis, were used. Logistic regression was used to assess the relationship between the percentage of fire activity and EVI variations together with period-of-year. The results show the ability of the model obtained to discriminate different levels of fire occurrence danger, with an estimation error of ~5%. This remote sensing technique may contribute to improving the efficiency of the currently used fire prevention systems.

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