Articles written in Journal of Earth System Science

    • Assessing the consistency between AVHRR and MODIS NDVI datasets for estimating terrestrial net primary productivity over India

      R K Nayak N Mishra V K Dadhwal N R Patel M Salim K H Rao C B S Dutt

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      This study examines the consistency between the AVHRR and MODIS normalized difference vegetation index (NDVI) datasets in estimating net primary productivity (NPP) and net ecosystem productivity (NEP) over India during 2001–2006 in a terrestrial ecosystem model. Harmonic analysis is employed to estimate seasonal components of the time series. The stationary components (representing long-termmean) of the respective NDVI time series are highly coherent and exhibit inherent natural vegetation characteristics with high values over the forest, moderate over the cropland, and small over the grassland. Both data exhibit strong semi-annual oscillations over the cropland dominated Indo-Gangetic plains while annual oscillations are strong over most parts of the country. MODIS has larger annual amplitude than that of the AVHRR. The similar variability exists on the estimates of NPP and NEP across India. In an annual scale, MODIS-based NPP budget is 1.78 PgC, which is 27% higher than the AVHRR-based estimate. It revealed that the Indian terrestrial ecosystem remained the sink of atmospheric CO$_2$during the study period with 42 TgC y$^{−1}$ NEP budget associated with MODIS-based estimate against 18 TgC y$^{−1}$ for the AVHRR-based estimate.

    • Predictive modelling of the spatial pattern of past and future forest cover changes in India

      C Sudhakar Reddy Sonali Singh V K Dadhwal C S Jha N Rama Rao P G Diwakar

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      This study was carried out to simulate the forest cover changes in India using Land Change Modeler. Classified multi-temporal long-term forest cover data was used to generate the forest covers of 1880 and 2025. The spatial data were overlaid with variables such as the proximity to roads, settlements, water bodies, elevation and slope to determine the relationship between forest cover change and explanatory variables. The predicted forest cover in 1880 indicates an area of 10,42,008 km², which represents 31.7% of the geographical area of India. About 40% of the forest cover in India was lost during the time interval of 1880–2013. Ownership of majority of forest lands by non-governmental agencies and large scale shifting cultivation are responsible for higher deforestation rates in the Northeastern states. The six states of the Northeast (Assam, Manipur, Meghalaya, Mizoram, Nagaland, Tripura) and one union territory (Andaman & Nicobar Islands) had shown an annual gross rate of deforestation of >0.3 from 2005 to 2013 and has been considered in the present study for the prediction of future forest cover in 2025. The modelling results predicted widespread deforestation in Northeast India and in Andaman & Nicobar Islands and hence is likely to affect the remaining forests significantly before 2025. The multilayer perceptron neural network has predicted the forest cover for the period of 1880 and 2025 with a Kappa statistic of >0.70. The model predicted a further decrease of 2305 km2 of forest area in the Northeast and Andaman & Nicobar Islands by 2025. The majority of the protected areas are successful in the protection of the forest cover in the Northeast due to management practices, with the exception of Manas, Sonai-Rupai, Nameri and Marat Longri. The predicted forest cover scenario for the year 2025 would provide useful inputs for effective resource management and help in biodiversity conservation and for mitigating climate change.

    • Monitoring of fire incidences in vegetation types and Protected Areas of India: Implications on carbon emissions

      C Sudhakar Reddy V V L Padma Alekhya K R L Saranya K Athira C S Jha P G Diwakar V K Dadhwal

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      Carbon emissions released from forest fires have been identified as an environmental issue in the context of global warming. This study provides data on spatial and temporal patterns of fire incidences, burnt area and carbon emissions covering natural vegetation types (forest, scrub and grassland) and Protected Areas of India. The total area affected by fire in the forest, scrub and grasslands have been estimated as 48765.45, 6540.97 and 1821.33 km², respectively, in 2014 using Resourcesat-2 AWiFS data. The total CO₂ emissions from fires of these vegetation types in India were estimated to be 98.11 Tg during 2014. The highest emissions were caused by dry deciduous forests, followed by moist deciduous forests. The fire season typically occurs in February, March, April and May in different parts of India. Monthly CO₂ emissions from fires for different vegetation types have been calculated for February, March, April and May and estimated as 2.26, 33.53, 32.15 and 30.17 Tg, respectively. Protected Areas represent 11.46% of the total natural vegetation cover of India. Analysis of fire occurrences over a 10-year period with two types of sensor data, i.e., AWiFS and MODIS, have found fires in 281 (out of 614) Protected Areas of India. About 16.78 Tg of CO₂ emissions were estimated in Protected Areas in 2014. The natural vegetation types of Protected Areas have contributed for burnt area of 17.3% and CO₂ emissions of 17.1% as compared to total natural vegetation burnt area and emissions in India in 2014. 9.4% of the total vegetation in the Protected Areas was burnt in 2014. Our results suggest that Protected Areas have to be considered for strict fire management as an effective strategy for mitigating climate change and biodiversity conservation.

    • Tectonic evolution of Kutch sedimentary basin, western India


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      Lithological variations, circular spectral anomalies, geological structures such as folds, faults, lineaments and shear zones of Kutch sedimentary basin were interpreted using IRS-LISS III satellite data. Aeromagnetic data was also interpreted qualitatively and quantitatively and a number of anomalous magnetic zones, faults, lineaments and domal structures were mapped. Magnetic basement depths and thickness of sediments were also computed. A number of alternate basement ridges/highs/uplifted blocks and depressions/lows/downthrown blocks were delineated. The information obtained from satellite remote sensing and aeromagnetic data were then integrated and the results were compared with published literature on gravity, magnetic (ground), magnetotelluric and seismic data, and also with field geology and well data. Structural controls in spatial domain (latitude, longitude and depth) were derived by establishing spatial relationship among different geological structures with reference to the geological time scale. Numerous horst and graben structures (ridges and sub-basins) as well as a number of master faults were delineated which serve as vital information with regard to hydrocarbon prospects and earthquake vulnerability, respectively. Based on the information obtained from this integrated study, a conceptual tectonometamorphic model along with sedimentation and igneous activity (ophiolitic and basaltic) has been constructed which has a significant bearing on the sequence of events that occurred during the deformational history of Kutch sedimentary basin resulting into the present day tectonic configuration.

    • Consistency of seasonal variability in regional CO$_2$ Cuxes from GOSAT-IM, NASA-GEOS, and NOAA-CT


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      Assessment of consistency in seasonal variability of CO$_2$ Cuxes between GOSAT-IM, NASA-GEOS, and NOAA-CT databases was carried out over major biogeographic regions across the globe. A blended data product was composited through a linear least square error optimization procedure from the weighted mean of the three datasets. The blended-product is in closer agreement with GOSAT-IM followed by NOAA-CT and NASA-GEOS for most parts of the globe; however, the blended-product was found to be closer to NASA-GEOS for the Arabian Sea and India. Comparison with limited in-situ FLUXNET observations shows NASA-GEOS has a better agreement for India, and NOAA-CT is better for Europe, Africa, and the US. The mean climatology of these datasets exhibits spatially distinct and coherent patterns of positive and negative Cuxes that characterize the source and sink of atmospheric CO$_2$ across the globe. The tropical oceanic and terrestrial regions and the southern circumpolar oceans have been playing as the sources, whereas the temperate oceanic and terrestrial ecosystems and the Eurasian Boreal are the sinks. The seasonal cycles of the Cuxes are intense over the northern temperate and boreal terrestrial and oceanic regions; wherein annual amplitudes dominate over the semi-annual amplitudes. The mean climatology varies in the range of -6 to 6 gC m$^{-2}$ month$^{-1}$ for oceans as well as continents; however, amplitudes of the seasonal cycle are one order higher for the continents (${\ge}$20 gC m$^{-2}$ month$^{-1}$) than that of the oceans (${\le}$1 gC m$^{-2}$ month$^{-1}$). The tropical desert tracts, especially Sahara and Thar, and the equatorial oceans show minima in their climatological mean with the reduced seasonal cycle. All these data, however, depict a broad agreement in their seasonal cycle and mean climatology; they exhibit significant differences in their annual budgets, amplitude, and phases of annual and semi-annual harmonics.

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