Tracking Fires in India Using Advanced Along Track Scanning Radiometer (A)ATSR Data

Quantifying forest resilience post forest fire disturbances using time-series satellite data

Quantification of forest resilience will help us to manage the sustainability of the forest environment and the safety of biodiversity. Measuring forest resilience is crucial for ensuring long-term health of the forest ecosystem in the face of ongoing environmental changes and disturbances. This study focuses on providing a framework to estimate forest resilience scores to assess the vegetation condition after a disturbance. The resilience calculation framework provided uses number of recovery days, the phenological performance level of vegetation in the year when the disturbance took place, long-term mean phenological performance, and greenness levels in subsequent year to calculate the final resilience score at each pixel. Recovery of forests using Landsat data with the help of Normalized Difference Vegetation Index or Normalized Burn Ratio poses a challenge for continuous monitoring of forested landscapes due to cloud cover and availability of scenes at continuous intervals in Landsat datasets. In this regard, MODIS 16-day EVI products were used in this study (2001 to 2020) for monitoring vegetation health before, during, and after the disaster. Bandhavgarh National Park (BNP) located in Madhya Pradesh, India is considered for this study as it witnessed major forest fire breakouts in the second half of March 2018. The objectives of the study are the following: (1) to estimate post-fire recovery days and (2) to formulate new resilience index. The study revealed that the northern part of BNP is more vulnerable and shows slow recovery. The relationship between occupation of people living inside and in the neighboring area with forest resilience is also investigated in this study.

Fire alters diversity, composition, and structure of dry tropical forests in the Eastern Ghats

Fire is known to have dramatic consequences on forest ecosystems around the world and on the livelihoods of forest-dependent people. While the Eastern Ghats of India have high abundances of fire-prone dry tropical forests, little is known about how fire influences the diversity, composition, and structure of these communities. Our study aimed to fill this knowledge gap by examining the effects of the presence and the absence of recent fire on tropical dry forest communities within the Kadiri watershed, Eastern Ghats. We sampled plots with and without evidence of recent fire in the Eswaramala Reserve Forest in 2008 and 2018. Our results indicate that even though stem density increases in the recently burned areas, species richness is lower because communities become dominated by a few species with fire resistance and tolerance traits, such as thick bark and clonal sprouting. Further, in the presence of fire, the size structure of these fire-tolerant species shifts toward smaller-sized, resprouting individuals. Our results demonstrate that conservation actions are needed to prevent further degradation of forests in this region and the ecosystem services they provide.

Forest Fire Trend and Influence of Climate Variability in India: A Geospatial Analysis at National and Local Scale

Climate change and its severity play an important role in forest fire regime. Analysing the forest fires events becomes a prerequisite for safeguarding the forest from further damage. We have made an assessment of the long-term forest fire events at the district level in India and identified the forest fire hotspot districts. The spatial seasonal (January to June) district wise pattern and forest fire trend were analysed. In the second part of the study area (central part of India), we have evaluated the forest fire events in grid format with respect to the climatic/weather datasets, and the statistical analysis Cramer V coefficient (CVC) was performed to understand its association/relationship with forest fire events.

The study revealed that Karbi Anglong and North Cachar Hills districts of Assam of India have the highest forest fire percent among all districts equivalent to 3.4 and 3.2% respectively. Dantewada district of Chhattisgarh and Garhchiroli district of Maharashtra of India occupied 3rd and 4th rank with value 3.1 and 3.0% respectively. The grid-based evaluation (local scale) revealed that most of the fire equivalent of 80% was found in the month of March and April. Forest fire frequency of the month of April is spread over 88 % of the grids over the study area. The 11 years average seasonal month-wise (February to June) maximum temperature, wind velocity, relative humidity, and solar radiation were found in the range of (25.9 to 40.6), (1.69 to 2.7), (0.301 to 0.736) and (14.21 to 22.98) respectively. The percentage increase (in the month of March) of maximum temperature, wind velocity, and solar radiation were 36, 39 and 62% respectively, when compared with the preceding month; whereas, a 60% decrease to relative humidity that was observed in the same month is usually the major cause of forest fire events in the month of March onwards.

The evaluation of Cramer V coefficient (CVC) values of rainfall, relative humidity, potential evapotranspiration, maximum temperature, wind velocity, and solar radiation were in decreasing order and in the range of 0.778 to 0.293. The highest value of rainfall (0.778) showed its strongest association with the forest fire events. In the month of June, these areas receive adequate rainfall, which leads to an increase in the soil moisture and a reduction in forest fuel burning capacity by absorbing the moisture and it is a strong reason for less forest fire events during this month. Geospatial technology provides an opportunity to evaluate large datasets over various spatial and temporal scales and help in decision making/formulating various policies.

Geospatial monitoring and prioritization of forest fire incidences in Andhra Pradesh, India

Forest fire has been identified as one of the key environmental issue for long-term conservation of biodiversity and has impact on global climate. Spatially multiple observations are necessary for monitoring of forest fires in tropics for understanding conservation efficacy and sustaining biodiversity in protected areas. The present work was carried out to estimate the spatial extent of forest burnt areas and fire frequency using Resourcesat Advanced Wide Field Sensor (AWiFS) data (2009, 2010, 2012, 2013 and 2014) in Andhra Pradesh, India. The spatio-temporal analysis shows that an area of 7514.10 km(2) (29.22% of total forest cover) has been affected by forest fires. Six major forest types are distributed in Andhra Pradesh, i.e. semi-evergreen, moist deciduous, dry deciduous, dry evergreen, thorn and mangroves. Of the total forest burnt area, dry deciduous forests account for >75%. District-wise analysis shows that Kurnool, Prakasam and Cuddapah have shown >100 km(2) of burnt area every year. The total forest burnt area estimate covering protected areas ranges between 6.9 and 22.3% during the study period. Spatial burnt area analysis for protected areas in 2014 indicates 37.2% of fire incidences in the Nagarjunasagar Srisailam Tiger Reserve followed by 20.2 % in the Sri Lankamalleswara Wildlife Sanctuary, 20.1% in the Sri Venkateswara Wildlife Sanctuary and 17.4% in the Gundla Brahmeswaram Wildlife Sanctuary. The analysis of cumulative fire occurrences from 2009 to 2014 has helped in delineation of conservation priority hotspots using a spatial grid cell approach. Conservation priority hotspots I and II are distributed in major parts of study area including protected areas of the Nagarjunasagar Srisailam Tiger Reserve and Gundla Brahmeswaram Wildlife Sanctuary. The spatial database generated will be useful in studies related to influence of fires on species adaptability, ecological damage assessment and conservation planning.

Decadal time-scale monitoring of forest fires in Similipal Biosphere Reserve, India using remote sensing and GIS

Analyzing the spatial extent and distribution of forest fires is essential for sustainable forest resource management. There is no comprehensive data existing on forest fires on a regular basis in Biosphere Reserves of India. The present work have been carried out to locate and estimate the spatial extent of forest burnt areas using Resourcesat-1 data and fire frequency covering decadal fire events (2004-2013) in Similipal Biosphere Reserve. The anomalous quantity of forest burnt area was recorded during 2009 as 1,014.7 km(2). There was inconsistency in the fire susceptibility across the different vegetation types. The spatial analysis of burnt area shows that an area of 34.2 % of dry deciduous forests, followed by tree savannah, shrub savannah, and grasslands affected by fires in 2013. The analysis based on decadal time scale satellite data reveals that an area of 2,175.9 km(2) (59.6 % of total vegetation cover) has been affected by varied rate of frequency of forest fires. Fire density pattern indicates low count of burnt area patches in 2013 estimated at 1,017 and high count at 1,916 in 2004. An estimate of fire risk area over a decade identifies 12.2 km(2) is experiencing an annual fire damage. Summing the fire frequency data across the grids (each 1 km(2)) indicates 1,211 (26 %) grids are having very high disturbance regimes due to repeated fires in all the 10 years, followed by 711 grids in 9 years and 418 in 8 years and 382 in 7 years. The spatial database offers excellent opportunities to understand the ecological impact of fires on biodiversity and is helpful in formulating conservation action plans.