Spatial pattern analysis of fire events in Central India – A case study

The impact of fires on environment can have adverse effects. To fully understand the synoptic behaviour of fire events, information on the spatial distributions and their pattern are highly important. In this study, we used 9-year (1997–2005) integrated fire count datasets derived from Along Track Scanning Radiometer (ATSR) satellite to geographically map the distribution of fire events in the Madhya Pradesh state, central India. We then used robust spatial metrics to test the spatial pattern of fire events against the hypothesis of complete spatial randomness (CSR). Specifically, we used the index of dispersion, Green's index, in addition to nearest neighbour statistic for testing CSR. Also, quantification of clustering is carried out using Ripley's K-function. To spatially map the fire events, we used Kernel density estimation that relies on bi-variate probability density functions. Results from using different spatial pattern metrics and nearest neighbour statistics suggested relatively high clustering of fire events in the study area. In addition, results from Ripley's K-function suggested the fire events to be clustered at a lag-distance of ～60 mile radius. By converting original fire ignition locations that are based on historical records to continuous density surfaces, the probability of fire events could be mapped effectively using kernel density estimation. As each fire event is the result of certain spatial process including biophysical and anthropogenic attributes, results from this study can provide useful information on fire management at a local district level. Also, the analysis presented in this study illustrates how spatial patterns in the point datasets can be quantified using different dispersion indices, clustering and density estimation techniques.     

Analysis of aerosol and carbon monoxide characteristics over Arabian Sea during crop residue burning period in the Indo-Gangetic Plains using multi-satellite remote sensing datasets

In this study, we have used multi-satellite data to retrieve aerosol loadings and carbon monoxide (CO) pollution over the Arabian Sea, caused due to anthropogenic activities over the Indo-Gangetic Plains (IGP) in India. Relatively high aerosol and CO loadings during 9–14 November 2007 over Arabian Sea were attributed to crop residues burning in the IGP and fireworks during Diwali festival. Aerosol index (AI) obtained from ozone monitoring instrument (OMI) and CO from measurements of pollution in the troposphere instrument (MOPITT). CO showed higher values over the Arabian Sea suggesting long-range transport of anthropogenic aerosols and trace gases from the continental to Arabian Sea region.     

Satellite observations of unusual dust event over North-East India and its relation with meteorological conditions

An unusual intense dust storm occurred over North-East region of India on 17 March 2009, which was analyzed using multi-satellite data sets. Terra MODIS AOD₅₅₀ showed high values on 17 March 2009 with low values of Angstrom exponent (α), suggesting coarse mode particle loading in the atmosphere. NCEP temperature and relative humidity anomalies showed high temperature and low humidity during March 2009. Dry weather conditions due to deficit rainfall during January–March 2009 and higher winds resulted in unusual dust storm over the region. Satellite observations of aerosol optical depth variations suggested increased aerosol loading in March 2009 due to dust storm.     

Spatial patterns of vegetation phenology metrics and related climatic controls of eight contrasting forest types in India – analysis from remote sensing datasets

Summary Leaf phenology describes the seasonal cycle of leaf functioning and is essential for understanding the interactions between the biosphere, the climate and the atmosphere. In this study, we characterized the spatial patterns in phenological variations in eight contrasting forest types in an Indian region using coarse resolution NOAA AVHRR satellite data. The onset, offset and growing season length for different forest types has been estimated using normalized difference vegetation index (NDVI). Further, the relationship between NDVI and climatic parameters has been assessed to determine which climatic variable (temperature or precipitation) best explain variation in NDVI. In addition, we also assessed how quickly and over what time periods does NDVI respond to different precipitation events. Our results suggested strong spatial variability in NDVI metrics for different forest types. Among the eight forest types, tropical dry deciduous forests showed lowest values for summed NDVI (SNDVI), averaged NDVI (ANDVI) and integrated NDVI (I-NDVI), while the tropical wet evergreen forests of Arunachal Pradesh had highest values. Within the different evergreen forest types, SNDVI, ANDVI and INDVI were highest for tropical wet evergreen forests, followed by tropical evergreen forests, tropical semi-evergreen forests and were least for tropical dry evergreen forests. Differences in the amplitude of NDVI were quite distinct for evergreen forests compared to deciduous ones and mixed deciduous forests. Although, all the evergreen forests studied had a similar growing season length of 270 days, the onset and offset dates were quite different. Response of vegetative greenness to climatic variability appeared to vary with vegetation characteristics and forest types. Linear correlations between mean monthly NDVI and temperature were found to yield negative relationships in contrast to precipitation, which showed a significant positive response to vegetation greenness. The correlations improved much for different forest types when the log of cumulative rainfall was correlated against mean monthly NDVI. Of the eight forest types, the NDVI for six forest types was positively correlated with the logarithm of cumulative rainfall that was summed for 3–4 months. Overall, this study identifies precipitation as a major control for vegetation greenness in tropical forests, more so than temperature.     

Investigation of the ozone and trace gases contribution to the total optical depth in the polluted urban environment of Athens

This study focuses on the determination of optical depths caused by ozone and trace gases absorption in the Chappuis band, 500–700 nm, and the contribution to the Total Minus Rayleigh Optical Depth (TMROD). The optical depths were derived using the transmission functions implemented in the SMARTS parametric model, while the Total Optical Depths (TODs) were derived by solar extinction measurements obtained in Athens during May 1995. From the data analysis it is obvious that both the ozone and trace gases contribute significantly to TMROD in the Chappuis band. More specifically, the trace gases contributions are higher for air with high pollution levels, while ozone's contribution can be significant under clear-sky conditions. Therefore, the correction in TMROD due to ozone and trace gases optical depths is necessary for an accurate determination of the Aerosol Optical Depth (AOD) in the Chappuis band. The optical depth of ozone is generally removed during the process of the AOD retrievals, since the significance of its absorption in the Chappuis band is well understood. Nevertheless, the optical depth of the trace gases (mainly NO₂) is not always taken into account in the AOD retrievals, though its contribution can be significant in urban polluted atmospheres. In this respect, the present study attempts to quantify the ozone and trace gases contributions in an urban environment and to provide some new functions that help estimate the contribution of ozone to the TMROD in the Chappuis band.     

Emissions from grassland burning in Kaziranga National Park,India – analysis from IRS-P6 AWiFS satellite remote sensing datasets

Biomass burning from vegetation fires is an important source of greenhouse gas emissions. In this study, we quantify biomass burning emissions from grasslands from the highly sensitive Kaziranga National Park, Assam, Northeast India. Most of the fires in the park are ‘controlled burning fires’ set by the park officials for management purposes. We evaluated the short-term impacts of fires and the resulting air pollution through integrating biomass burnt information from satellite remote sensing datasets. IRS-P6 Advanced Wide Field Sensor (AWiFS) data during March and April corresponding to dry season were evaluated to delineate the burnt areas. These burnt area estimates were then integrated with biomass data and emission factors for quantifying the greenhouse gas emissions. Results suggested that of the total study area of 37,822 ha, nearly 3163.282 ha has been burnt during March, 2005. Within one month, the burnt area increased to 7443.92 ha by April, i.e., from 8.36% to 19.68%. In total, biomass burning from the grasslands contributed to 29.65 Tg CO₂, 1.19 Tg CO, 0.071 Tg NOx, 0.042 Tg CH₄, 0.0625 Tg total non-methane hydrocarbons, 0.152 Tg of particulate matter, and 0.062 Tg of organic carbon and 0.008 Tg of black carbon during April. The importance of ‘fire’ as a management tool for maintaining the wildlife habitat has been highlighted in addition to some of the adverse affects of air pollution resulting from such management practices. The results from this study will be useful to forest officials as well as policy makers to undertake some sustainable forest management practices to maintain an ideal habitat for Kaziranga's wildlife.     

Impact of aerosols on total columnar ozone measurements—a case study using satellite and ground-based instruments

Long-term record of global distribution of ozone during 1979 to 2001, from Total Ozone Mapping Spectrometer (TOMS), over a tropical urban environment has been analyzed and compared with ground measurements. Increase in atmospheric UV-absorbing aerosol loading has been observed after 1991. TOMS columnar ozone during 1979 to 2001 suggested a clear Gaussian pattern of minimum concentration in winter months and maximum in summer months. TOMS ozone showed good correlation with the ground measured columnar ozone during winter months and negative correlation with Sunburning Ultraviolet (SUV) (280–370 nm), UVA and aerosol optical depth (AOD).     

Correlation between black carbon aerosols, carbon monoxide and tropospheric ozone over a tropical urban site

Black carbon aerosols plays an important role in the earth's radiative balance and little is known of their concentrations, distributions, source strength, and especially the aerosol chemistry of the developing world. The present study addresses the impact of back carbon aerosols on different atmospheric species like CO and tropospheric ozone over an urban environment, namely Hyderabad, India. Ozone concentration varies from 14 to 63 ppbv over the study area. Diurnal variations of ozone suggest that ozone concentration starts increasing gradually after sunrise, attaining a maximum value by evening time and decreasing gradually thereafter. Black carbon (BC) aerosol mass concentrations varies from 1471 to 11,175 ng m⁻³. The diurnal variations of BC suggest that the concentrations are increased by a factor of 2 during morning (06:00–09:00 h) and evening hours (18:00 to 22:00 h) compared to afternoon hours. Positive correlation has been observed between BC and CO (r²=0.74) with an average slope of 6.4×10⁻³ g BC/g CO. The slope between black carbon aerosol mass concentration and tropospheric ozone suggests that every 1 μg m⁻³ increase in black carbon aerosol mass concentration causes a 3.5 μg m⁻³ reduction in tropospheric ozone. The results have been discussed in detail in the paper.     

Studies on urban heat islands using envisat AATSR data

Urbanization has significant effects on local weather and climate and among these effects one of the most familiar is the urban heat island, for which the temperatures of the central urban locations are several degrees higher than those of nearby rural areas of similar elevation. Satellite data provides important inputs for estimating regional surface albedo and evapotranspiration required in the studies related to surface energy balance. Present study describes the analysis of day and night ENVISAT-AATSR satellite data for Urban heat island and surface thermal inertia. Field campaigns have been conducted in synchronous with the satellite data over pass for validating the surface temperature estimated from AATSR data. Satellite derived surface temperature values are within ±1° C from ground measured values. Heat island formations in urban regions of Hyderabad and environs can be clearly seen in the night time data with core urban regions showing high temperatures. Apparent thermal inertia derived from AATSR day and night data sets have shown typical variations over urban regions.