Generation and analysis of a new global burned area product based on MODIS 250 m reflectance bands and thermal anomalies

Mapping Intimacies ◽

10.5194/essd-2018-46 ◽

2018 ◽

Cited By ~ 8

Author(s):

Emilio Chuvieco ◽

Joshua Lizundia-Loiola ◽

M. Lucrecia Pettinari ◽

Ruben Ramo ◽

Marc Padilla ◽

...

Keyword(s):

Near Infrared ◽

Error Rates ◽

Fire Disturbance ◽

Spatial Distance ◽

Burned Area ◽

Landsat Images ◽

Thermal Anomalies ◽

Global Dynamic ◽

Fire Modelling ◽

Area Product

Abstract. This paper presents a new global burned area (BA) product, generated from the MODIS red (R) and near infrared (NIR) reflectances and thermal anomalies data, thus providing the highest spatial resolution (approx. 250 m) among the existing global BA datasets. The product includes the full times series (2001–2016) of the MODIS archive. The BA detection 20 algorithm was based on temporal composites of daily images, using temporal and spatial distance to active fires. The algorithm has two steps, the first one aiming to reduce commission errors by selecting the most clearly burned pixels (seeds), and the second one aiming to reduce omission errors by applying contextual analysis around the seed pixels. The product was developed within the European Space Agency's (ESA) Climate Change Initiative programme, under the Fire Disturbance project (Fire_cci). The final output includes two types of BA products: monthly full-resolution continental tiles (http://doi.org/cpk7) and biweekly global grid files at a degraded resolution of 0.25 degrees (http://doi.org/gcx9gf). Each one includes several auxiliary variables that were defined by the climate users to facilitate the ingestion of the product into global dynamic vegetation and emission models. The validation was based on a stratified random sample of 1200 pairs of Landsat images, covering the whole globe from 2003 to 2014. The estimated commission and omission error rates of the pixel product was 0.512 (0.020) and 0.708 (0.030), respectively, lower 30 than previous ESA products but higher than the latest NASA MCD64A1 BA dataset. Examples of potential applications of this product to fire modelling based on burned patches analysis are included in this paper. They show greater sensitivity of our product to small burn patch detection than existing BA products.

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Generation and analysis of a new global burned area product based on MODIS 250 m reflectance bands and thermal anomalies

Earth System Science Data ◽

10.5194/essd-10-2015-2018 ◽

2018 ◽

Vol 10 (4) ◽

pp. 2015-2031 ◽

Cited By ~ 46

Author(s):

Emilio Chuvieco ◽

Joshua Lizundia-Loiola ◽

Maria Lucrecia Pettinari ◽

Ruben Ramo ◽

Marc Padilla ◽

...

Keyword(s):

Near Infrared ◽

Thermal Anomaly ◽

Detection Algorithm ◽

Fire Disturbance ◽

Spatial Distance ◽

Burned Area ◽

Detection Accuracy ◽

Landsat Images ◽

Full Resolution ◽

Omission Errors

Abstract. This paper presents a new global burned area (BA) product, generated from the Moderate Resolution Imaging Spectroradiometer (MODIS) red (R) and near-infrared (NIR) reflectances and thermal anomaly data, thus providing the highest spatial resolution (approx. 250 m) among the existing global BA datasets. The product includes the full times series (2001–2016) of the Terra-MODIS archive. The BA detection algorithm was based on monthly composites of daily images, using temporal and spatial distance to active fires. The algorithm has two steps, the first one aiming to reduce commission errors by selecting the most clearly burned pixels (seeds), and the second one targeting to reduce omission errors by applying contextual analysis around the seed pixels. This product was developed within the European Space Agency's (ESA) Climate Change Initiative (CCI) programme, under the Fire Disturbance project (Fire_cci). The final output includes two types of BA files: monthly full-resolution continental tiles and biweekly global grid files at a degraded resolution of 0.25∘. Each set of products includes several auxiliary variables that were defined by the climate users to facilitate the ingestion of the product into global dynamic vegetation and atmospheric emission models. Average annual burned area from this product was 3.81 Mkm2, with maximum burning in 2011 (4.1 Mkm2) and minimum in 2013 (3.24 Mkm2). The validation was based on a stratified random sample of 1200 pairs of Landsat images, covering the whole globe from 2003 to 2014. The validation indicates an overall accuracy of 0.9972, with much higher errors for the burned than the unburned category (global omission error of BA was estimated as 0.7090 and global commission as 0.5123). These error values are similar to other global BA products, but slightly higher than the NASA BA product (named MCD64A1, which is produced at 500 m resolution). However, commission and omission errors are better compensated in our product, with a tendency towards BA underestimation (relative bias −0.4033), as most existing global BA products. To understand the value of this product in detecting small fire patches (<100 ha), an additional validation sample of 52 Sentinel-2 scenes was generated specifically over Africa. Analysis of these results indicates a better detection accuracy of this product for small fire patches (<100 ha) than the equivalent 500 m MCD64A1 product, although both have high errors for these small fires. Examples of potential applications of this dataset to fire modelling based on burned patches analysis are included in this paper. The datasets are freely downloadable from the Fire_cci website (https://www.esa-fire-cci.org/, last access: 10 November 2018) and their repositories (pixel at full resolution: https://doi.org/cpk7, and grid: https://doi.org/gcx9gf).

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Evaluation of spectral indices for estimating burn severity in semiarid grasslands

International Journal of Wildland Fire ◽

10.1071/wf15098 ◽

2016 ◽

Vol 25 (2) ◽

pp. 147 ◽

Cited By ~ 18

Author(s):

Bing Lu ◽

Yuhong He ◽

Alexander Tong

Keyword(s):

Native Species ◽

Landsat Imagery ◽

Recovery Process ◽

Fire Disturbance ◽

Burn Severity ◽

Vegetation Recovery ◽

Grass Species ◽

Burned Area ◽

Spectral Indices ◽

Landsat Images

Using Landsat imagery, this study was conducted to evaluate a fire disturbance that occurred in Canada’s Grasslands National Park on 27 April 2013. We used spectral indices (e.g. Normalised Burn Ratio (NBR) and Mid-infrared Burn Index (MIRBI)) derived from Landsat images to evaluate burn severity and to analyse the vegetation recovery process. A field survey was conducted to assess burn severity, which we used to evaluate the performance of spectral indices. Responses of the vegetation community to the fire disturbance were also investigated during the field campaign. Results show that the selected spectral indices performed differently for evaluating burn severity, but MIRBI performed best, likely due to its ability to discriminate post-fire residuals. Severely burned areas were distributed along a river where a larger amount of senesced biomass had accumulated before the fire. The semiarid grasslands showed a strong resilience to fire disturbance, and vegetation recovery was likely influenced by burn severity and water availability. Different vegetation types (e.g. grass, trees and shrubs) had distinct recovery rates and, thus, fire influences plant community development. The fire disturbance changed the composition of grass species in the burned area and also promoted invasion by non-native species.

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Operational implementation of the burned area component of the Copernicus Climate Change Service: from MODIS 250 m to OLCI 300 m data

10.5194/essd-2020-399 ◽

2021 ◽

Author(s):

Joshua Lizundia-Loiola ◽

Magí Franquesa ◽

Martin Boettcher ◽

Grit Kirches ◽

M. Lucrecia Pettinari ◽

...

Keyword(s):

Climate Change ◽

Near Infrared ◽

Burned Area ◽

Landsat 8 ◽

Full Time ◽

Temporal Consistency ◽

Climate Data ◽

Thermal Anomalies ◽

Commission Errors ◽

Omission Errors

Abstract. This paper presents a new global, operational burned area (BA) product at 300 m, called C3SBA10, generated from Sentinel-3 Ocean and Land Colour Instrument (OLCI) near-infrared (NIR) reflectance and Moderate Resolution Imaging Spectroradiometer (MODIS) thermal anomaly data. This product was generated within the Copernicus Climate Change Service (C3S). Since C3S is a European service, it aims to use extensively the European Copernicus satellite missions, named Sentinels. Therefore, one of the components of the service is adapting previous developed algorithms to the Sentinel sensors. In the case of BA datasets, the precursor BA dataset (FireCCI51), which was developed within the European Space Agency's (ESA) Climate Change Initiative (CCI), was based on the 250 m-resolution NIR band of the MODIS sensor, and the effort has been focused on adapting this BA algorithm to the characteristics of the Sentinel-3 OLCI sensor, which provides similar spatial and temporal resolution to MODIS. As the precursor BA algorithm, the OLCI's one combines thermal anomalies and spectral information in a two-phase approach, where first thermal anomalies with a high probability of being burned are selected, reducing commission errors, and then a contextual growing is applied to fully detect the BA patch, reducing omission errors. The new BA product includes the full time-series of S3 OLCI data (2017–present). Following the specifications of the FireCCI project, the final datasets are provided in two different formats: monthly full-resolution continental tiles, and monthly global files with aggregated data at 0.25-degree resolution. To facilitate the use by global vegetation dynamics and atmospheric emission models several auxiliary layers were included, such as land cover and cloud-free observations. The C3SBA10 product detected 3.77 Mkm2, 3.59 Mkm2, and 3.63 Mkm2 of annual BA from 2017 to 2019, respectively. The quality and consistency assessment of C3SBA10 and the precursor FireCCI51 was done for the common period (2017–2019). The global spatial validation was performed using reference data derived from Landsat-8 images, following a stratified random sampling design. The C3SBA10 showed commission errors between 14–22 % and omission errors from 50 to 53 %, similar to those presented by the FireCCI51 product. The temporal reporting accuracy was also validated using 4.7 million active fires. 88 % of the detections were made within 10 days after the fire by both products. The spatial and temporal consistency assessment performed between C3SBA10 and FireCCI51 using four different grid sizes (0.05º, 0.10º, 0.25º, and 0.50º) showed global, annual correlations between 0.93 and 0.99. This high consistency between both products ensures a global BA data provision from 2001 to present. The datasets are freely available through the Copernicus Climate Data Store (CDS) repository (DOI: https://doi.org/10.24381/cds.f333cf85, Lizundia-Loiola et al. (2020a)).

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Volcanic Anomalies Monitoring System (VOLCANOMS), a Low-Cost Volcanic Monitoring System Based on Landsat Images

Remote Sensing ◽

10.3390/rs12101589 ◽

2020 ◽

Vol 12 (10) ◽

pp. 1589 ◽

Cited By ~ 2

Author(s):

Susana Layana ◽

Felipe Aguilera ◽

Germán Rojo ◽

Álvaro Vergara ◽

Pablo Salazar ◽

...

Keyword(s):

Monitoring System ◽

Seismic Data ◽

Near Infrared ◽

Landsat Imagery ◽

Low Cost ◽

Short Wave ◽

Eruptive Activity ◽

Landsat Images ◽

Thermal Anomalies ◽

Volcanic Monitoring

The practice of monitoring active volcanoes, includes several techniques using either direct or remote measurements, the latter being more important for volcanoes with limited accessibility. We present the Volcanic Anomalies Monitoring System (VOLCANOMS), a new, online, low-cost and semiautomatic system based on Landsat imagery. This system can detect permanent and/or temporal thermal anomalies in near-infrared (NIR), short-wave infrared (SWIR), and thermal infrared (TIR) bands. VOLCANOMS allows researchers to calculate several thermal parameters, such as thermal radiance, effective temperature, anomaly area, radiative, gas, convective, and total heat, and mass fluxes. We study the eruptive activity of five volcanoes including Krakatau, Stromboli, Fuego, Villarrica and Lascar volcanoes, comparing field and eruptive data with thermal radiance. In the case of Villarrica and Lascar volcanoes, we also compare the thermal radiance and eruptive activity with seismic data. The thermal radiance shows a concordance with the eruptive activity in all cases, whereas a correlation is observed between thermal and seismic data both, in Villarrica and Lascar volcanoes, especially in the case of long-period seismicity. VOLCANOMS is a new and powerful tool that, combined with other techniques, generates robust information for volcanic monitoring.

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SAFARI 2000 EMISSIONS ESTIMATES, MODIS BURNED AREA PRODUCT, DRY SEASON 2000

ORNL Distributed Active Archive Center Datasets ◽

10.3334/ornldaac/758 ◽

2004 ◽

Author(s):

C. O. JUSTICE ◽

S. KORONTZI ◽

D. P. ROY

Keyword(s):

Dry Season ◽

Burned Area ◽

Area Product

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Integrated Approach for Sclera Recognition and Eye Gaze Detection

International Journal of Emerging Research in Management and Technology ◽

10.23956/ijermt.v6i7.188 ◽

2018 ◽

Vol 6 (7) ◽

pp. 77

Author(s):

Snehal S. Rajole ◽

J. V. Shinde

Keyword(s):

Near Infrared ◽

Eye Gaze ◽

Integrated Approach ◽

Error Rates ◽

Infrared Images ◽

Scaling Method ◽

Extensive Simulation ◽

Sclera Recognition ◽

Gaze Detection ◽

Biometric Trait

In this paper we proposed unique technique which is adaptive to noisy images for eye gaze detection as processing noisy sclera images captured at-a-distance and on-the-move has not been extensively investigated. Sclera blood vessels have been investigated recently as an efficient biometric trait. Capturing part of the eye with a normal camera using visible-wavelength images rather than near infrared images has provoked research interest. This technique involves sclera template rotation alignment and a distance scaling method to minimize the error rates when noisy eye images are captured at-a-distance and on-the move. The proposed system is tested and results are generated by extensive simulation in java.

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Incorporating Sentinel-1 SAR imagery with the MODIS MCD64A1 burned area product to improve burn date estimates and reduce burn date uncertainty in wildland fire mapping

Geocarto International ◽

10.1080/10106049.2019.1608592 ◽

2019 ◽

pp. 1-21 ◽

Cited By ~ 1

Author(s):

Kristofer Lasko

Keyword(s):

Wildland Fire ◽

Burned Area ◽

Sar Imagery ◽

Area Product

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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

Proceedings of the International Association of Hydrological Sciences ◽

10.5194/piahs-371-157-2015 ◽

2015 ◽

Vol 371 ◽

pp. 157-162 ◽

Cited By ~ 1

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.

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