Identification and characterization of spatio-temporal hotspots of forest fires in South Asia.

Forest fire is considered as one of the major threats to global biodiversity and a significant source of greenhouse gas emissions. Rising temperatures, weather conditions, and topography promote the incidences of fire due to human ignition in South Asia. Because of its synoptic, multi-spectral, and multi-temporal nature, remote sensing data can be a state of art technology for forest fire management. This study focuses on the spatio-temporal patterns of forest fires and identifying hotspots using the novel geospatial technique "emerging hotspot analysis tool" in South Asia. Daily MODIS active fire locations data of 15 years (2003-2017) has been aggregated in order to characterize fire frequency, fire density, and hotspots. A total of 522,348 active fire points have been used to analyze risk of fires across the forest types. Maximum number of forest fires in South Asia was occurring during the January to May. Spatial analysis identified areas of frequent burning and high fire density in South Asian countries. In South Asia, 51% of forest grid cells were affected by fires in 15 years. Highest number of fire incidences was recorded in tropical moist deciduous forest and tropical dry deciduous forest. The emerging hotspots analysis indicates prevalence of sporadic hotspots, followed by historical hotspots, consecutive hotspots, and persistent hotspots in South Asia. Of the seven South Asian countries, Bangladesh has highest emerging hotspot area (34.2%) in forests, followed by 32.2% in India and 29.5% in Nepal. Study results offer critical insights in delineation of fire vulnerable forest landscapes which will stand as a valuable input for strengthening management of fires in South Asia.

Inter-comparison of water balance components of river basins draining into selected delta districts of Eastern India.

Quantification of hydrological components in-terms of surface runoff, stream flow and evapotranspiration is important and useful in planning and management of water resources across the river basin, including downstream delta regions. River deltas water availability; management and related disaster risk are largely influenced by the hydrological state of upstream river basins. The paper presents the results of hydrological modelling (SWAT) based long-term water balance components in river basins draining into selected delta Districts of Eastern India. Mahanadi, Brahmani-Baitarani river basins and Hooghly river and adjacent small river basins are considered. The long-term water balance components of Mahanadi and Brahmani-Baitarani river basins are similar and significantly different in Hooghly river and adjacent small river basins. The runoff coefficient is significantly higher in Hooghly river and adjacent small river basins at 0.39 compared to other two river basins (0.247 & 0.256). The evapotranspiration component is relatively low in Hooghly river and adjacent small river basins with smaller range of long-term variation. The time-series model outputs brought out the basin-specific hydrological response variations in low and high rainfall years such as changes in fraction of evapotranspiration and surface runoff. Mahanadi and Brahmani-Baitarani river basins exhibit large inter-annual variation in evapotranspiration, surface runoff fractions. The developed hydrological modelling framework is capable of incorporating future climate data and to predict the basin-scale future water availability, demand, use and to bring out resulting water scenarios that would impact river deltas in-terms of their exposure towards water related adversities, such as drought and flood.

Development of deforestation and land cover database for Bhutan (1930-2014).

Bhutan is a mountainous country located in the Himalayan biodiversity hotspot. This study has quantified the total area under land cover types, estimated the rate of forest cover change, analyzed the changes across forest types, and modeled forest cover change hotpots in Bhutan. The topographical maps and satellite remote sensing images were analyzed to get the spatial patterns of forest and associated land cover changes over the past eight decades (1930-1977-1987-1995-2005-2014). Forest is the largest land cover in Bhutan and constitutes 68.3% of the total geographical area in 2014. Subtropical broad leaved hill forest is predominant type occupies 34.1% of forest area in Bhutan, followed by montane dry temperate (20.9%), montane wet temperate (18.9%), Himalayan moist temperate (10%), and tropical moist sal (8.1%) in 2014. The major forest cover loss is observed in subtropical broad leaved hill forest (64.5 km2) and moist sal forest (9.9 km2) from 1977 to 2014. The deforested areas have mainly been converted into agriculture and contributed for 60.9% of forest loss from 1930 to 2014. In spite of major decline of forest cover in time interval of 1930-1977, there is no net rate of deforestation is recorded in Bhutan since 1995. Forest cover change analysis has been carried out to evaluate the conservation effectiveness in "Protected Areas" of Bhutan. Hotspots that have undergone high transformation in forest cover for afforestation and deforestation were highlighted in the study for conservation prioritisation. Forest conservation policies in Bhutan are highly effective in controlling deforestation as compared to neighboring Asian countries and such service would help in mitigating climate change.

Nationwide classification of forest types of India using remote sensing and GIS.

India, a mega-diverse country, possesses a wide range of climate and vegetation types along with a varied topography. The present study has classified forest types of India based on multi-season IRS Resourcesat-2 Advanced Wide Field Sensor (AWiFS) data. The study has characterized 29 land use/land cover classes including 14 forest types and seven scrub types. Hybrid classification approach has been used for the classification of forest types. The classification of vegetation has been carried out based on the ecological rule bases followed by Champion and Seth's (1968) scheme of forest types in India. The present classification scheme has been compared with the available global and national level land cover products. The natural vegetation cover was estimated to be 29.36% of total geographical area of India. The predominant forest types of India are tropical dry deciduous and tropical moist deciduous. Of the total forest cover, tropical dry deciduous forests occupy an area of 2,17,713 km(2) (34.80%) followed by 2,07,649 km(2) (33.19%) under tropical moist deciduous forests, 48,295 km(2) (7.72%) under tropical semi-evergreen forests and 47,192 km(2) (7.54%) under tropical wet evergreen forests. The study has brought out a comprehensive vegetation cover and forest type maps based on inputs critical in defining the various categories of vegetation and forest types. This spatially explicit database will be highly useful for the studies related to changes in various forest types, carbon stocks, climate-vegetation modeling and biogeochemical cycles.