Burnt Area Index (BAIM) for burned area discrimination at regional scale using MODIS data

2006 ◽  
Vol 234 ◽  
pp. S221 ◽  
Author(s):  
M. Pilar Martín ◽  
Israel Gómez ◽  
Emilio Chuvieco
Keyword(s):  
Regional Scale ◽  
Burned Area ◽  
Burnt Area ◽  
Area Index ◽  
Modis Data

scholarly journals Crop specific green area index retrieval from MODIS data at regional scale by controlling pixel-target adequacy

2011 ◽  
Vol 115 (10) ◽  
pp. 2686-2701 ◽  
Author(s):  
Grégory Duveiller ◽  
Frédéric Baret ◽  
Pierre Defourny
Keyword(s):  
Regional Scale ◽  
Area Index ◽  
Modis Data ◽  
Green Area

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 A spatio-temporal active-fire clustering approach for global burned area mapping at 250 m from MODIS data

2020 ◽  
Vol 236 ◽  
pp. 111493 ◽  
Author(s):  
Joshua Lizundia-Loiola ◽  
Gonzalo Otón ◽  
Rubén Ramo ◽  
Emilio Chuvieco
Keyword(s):  
Burned Area ◽  
Modis Data ◽  
Active Fire ◽  
Burned Area Mapping ◽  
Clustering Approach ◽  
Spatio Temporal

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 Modeling long-term fire impact on ecosystem characteristics and surface energy using a process-based vegetation–fire model SSiB4/TRIFFID-Fire v1.0

2020 ◽  
Vol 13 (12) ◽  
pp. 6029-6050
Author(s):  
Huilin Huang ◽  
Yongkang Xue ◽  
Fang Li ◽  
Ye Liu
Keyword(s):  
Surface Energy ◽  
Surface Fluxes ◽  
Surface Energy Budget ◽  
Biophysical Model ◽  
Burned Area ◽  
Area Index ◽  
Fire Model ◽  
Vegetation Height ◽  
Fire Impact

Abstract. Fire is one of the primary disturbances to the distribution and ecological properties of the world's major biomes and can influence the surface fluxes and climate through vegetation–climate interactions. This study incorporates a fire model of intermediate complexity to a biophysical model with dynamic vegetation, SSiB4/TRIFFID (The Simplified Simple Biosphere Model coupled with the Top-down Representation of Interactive Foliage and Flora Including Dynamics Model). This new model, SSiB4/TRIFFID-Fire, updating fire impact on the terrestrial carbon cycle every 10 d, is then used to simulate the burned area during 1948–2014. The simulated global burned area in 2000–2014 is 471.9 Mha yr−1, close to the estimate of 478.1 Mha yr−1 in Global Fire Emission Database v4s (GFED4s), with a spatial correlation of 0.8. The SSiB4/TRIFFID-Fire reproduces temporal variations of the burned area at monthly to interannual scales. Specifically, it captures the observed decline trend in northern African savanna fire and accurately simulates the fire seasonality in most major fire regions. The simulated fire carbon emission is 2.19 Pg yr−1, slightly higher than the GFED4s (2.07 Pg yr−1). The SSiB4/TRIFFID-Fire is applied to assess the long-term fire impact on ecosystem characteristics and surface energy budget by comparing model runs with and without fire (FIRE-ON minus FIRE-OFF). The FIRE-ON simulation reduces tree cover over 4.5 % of the global land surface, accompanied by a decrease in leaf area index and vegetation height by 0.10 m2 m−2 and 1.24 m, respectively. The surface albedo and sensible heat are reduced throughout the year, while latent heat flux decreases in the fire season but increases in the rainy season. Fire results in an increase in surface temperature over most fire regions.

scholarly journals Global Analysis of Burned Area Persistence Time with MODIS Data

2018 ◽  
Vol 10 (5) ◽  
pp. 750 ◽  
Author(s):  
Andrea Melchiorre ◽  
Luigi Boschetti
Keyword(s):  
Global Analysis ◽  
Burned Area ◽  
Modis Data ◽  
Persistence Time

Landscape Biodiversity Characterization in Ecoregion 29 Using MODIS

2013 ◽  
pp. 815-831
Author(s):  
Nitin Kumar Tripathi ◽  
Aung Phey Khant
Keyword(s):  
Climate Change ◽  
Remote Sensing ◽  
Global Warming ◽  
Forest Type ◽  
Regional Scale ◽  
Remote Sensing Data ◽  
Modis Data ◽  
Moderate Resolution ◽  
Landscape Biodiversity

Biodiversity conservation is a challenging task due to ever growing impact of global warming and climate change. The chapter discusses various aspects of biodiversity parameters that can be estimated using remote sensing data. Moderate resolution satellite (MODIS) data was used to demonstrate the biodiversity characterization of Ecoregion 29. Forest type map linked to density of the study area was also developed by MODIS data. The outcome states that remote sensing and geographic information systems can be used in combination to derive various parameters related to biodiversity surveillance at a regional scale.

scholarly journals Correction of systematic model forcing bias of CLM using assimilation of cosmic-ray Neutrons and land surface temperature: a study in the Heihe Catchment, China

2015 ◽  
Vol 19 (1) ◽  
pp. 615-629 ◽  
Author(s):  
X. Han ◽  
H.-J. H. Franssen ◽  
R. Rosolem ◽  
R. Jin ◽  
X. Li ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Surface Temperature ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Regional Scale ◽  
Cosmic Ray ◽  
Systematic Bias ◽  
Area Index ◽  
Community Land Model ◽  
Independent Field

Abstract. The recent development of the non-invasive cosmic-ray soil moisture sensing technique fills the gap between point-scale soil moisture measurements and regional-scale soil moisture measurements by remote sensing. A cosmic-ray probe measures soil moisture for a footprint with a diameter of ~ 600 m (at sea level) and with an effective measurement depth between 12 and 76 cm, depending on the soil humidity. In this study, it was tested whether neutron counts also allow correcting for a systematic error in the model forcings. A lack of water management data often causes systematic input errors to land surface models. Here, the assimilation procedure was tested for an irrigated corn field (Heihe Watershed Allied Telemetry Experimental Research – HiWATER, 2012) where no irrigation data were available as model input although for the area a significant amount of water was irrigated. In the study, the measured cosmic-ray neutron counts and Moderate-Resolution Imaging Spectroradiometer (MODIS) land surface temperature (LST) products were jointly assimilated into the Community Land Model (CLM) with the local ensemble transform Kalman filter. Different data assimilation scenarios were evaluated, with assimilation of LST and/or cosmic-ray neutron counts, and possibly parameter estimation of leaf area index (LAI). The results show that the direct assimilation of cosmic-ray neutron counts can improve the soil moisture and evapotranspiration (ET) estimation significantly, correcting for lack of information on irrigation amounts. The joint assimilation of neutron counts and LST could improve further the ET estimation, but the information content of neutron counts exceeded the one of LST. Additional improvement was achieved by calibrating LAI, which after calibration was also closer to independent field measurements. It was concluded that assimilation of neutron counts was useful for ET and soil moisture estimation even if the model has a systematic bias like neglecting irrigation. However, also the assimilation of LST helped to correct the systematic model bias introduced by neglecting irrigation and LST could be used to update soil moisture with state augmentation.

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