bluuebunny/crossref_metadata_2025 huggingface dataset:
Daoism and Anarchism
Authors: Rapp John A.
Published: November 2014

This volume in the Contemporary Anarchist Studies series focuses on anti-statist critiques in ancient and modern China and demonstrates that China does not have an unchallenged authoritarian political culture.

Treating anarchism as a critique of centralized state power, the work first examines radical Daoist thought from the 4th century BCE to the 9th century CE and compares Daoist philosophers and poets to Western anarchist and utopian thinkers. This is followed by a survey of anarchist themes in dissident thought in the People's Republic of China from 1949 to the present. A concluding chapter discusses how Daoist anarchism can be applied to any anarchist-inspired radical critique today.

This work not only challenges the usual ideas of the scope and nature of dissent in China, it also provides a unique comparison of ancient Chinese Daoist anarchism to Western anarchist. Featuring previously untranslated texts, such as the 9th century Buddhist anarchist tract, the Wunengzi, and essays from the PRC press, it will be an essential resource to anyone studying anarchism, Chinese political thought, political dissent, and political history.
Variations of cloud condensation nuclei (CCN) and aerosol activity during fog–haze episode: a case study from Shanghai
Authors: Leng C. , Zhang Q. , Zhang D. , Xu C. , Cheng T. , Zhang R. , Tao J. , Chen J. , Zha S. , Zhang Y. , Li X. , Kong L. , Gao W.
Published: November 2014

Abstract. Measurements of cloud condensation nuclei (CCN), condensation nuclei (CN) and aerosol chemical composition were performed simultaneously at an urban site in Shanghai from 6 to 9 November 2010. The variations of CCN number concentration (NCCN) and aerosol activity (activated aerosol fraction, NCCN/NCN) were examined during a fog–haze co-occurring event. Anthropogenic pollutants emitted from vehicles and unfavorable meteorological conditions such as low planetary boundary layer (PBL) height exerted a great influence on PM2.5 and black carbon (BC) loadings. NCCN at 0.2% supersaturation (SS) mostly fell in the range of 994 to 6268 cm−3, and the corresponding NCCN/NCN varied between 0.09 and 0.57. NCCN and NCCN/NCN usually were usually higher in the hazy case due to increased aerosol concentration in the accumulation mode (100–500 nm), and lower in the foggy–hazy and clear cases. The BC mass concentration posed a strong positive effect on NCCN in the foggy–hazy and hazy cases, whereas it poorly correlated with NCCN in the clear case. NCCN/NCN was weakly related with BC in both foggy–hazy and hazy cases. By using a simplified particle hygroscopicity (κ), the calculated critical dry size (CDS) of activated aerosol did not exceed 130 nm at 0.2% SS in spite of diverse aerosol chemical compositions. The predicted NCCN at 0.2% SS was very successful compared with the observed NCCN in clear case (R2=0.96) and foggy–hazy/hazy cases (R2=0.91). In addition, their corresponding ratios of predicted to observed NCCNwere on average 0.95 and 0.92, respectively. More organic matter is possibly responsible for this closure difference between foggy–hazy/hazy and clear cases. These results reveal that the particulate pollutant burden exerts a significant impact on NCCN, especially NCCN/NCN promotes effectively during the polluted periods.
Sensitivity of East African savannah vegetation to historical moisture-balance variation
Authors: Ssemmanda I. , Gelorini V. , Verschuren D.
Published: November 2014

Abstract. Fossil pollen records provide key insight into the sensitivity of terrestrial ecosystems to climate change. However, tracing vegetation response to relatively modest historical climate fluctuations is often complicated by the overriding signature of anthropogenic landscape disturbance. Here we use high-resolution pollen data from a ~200-year lake-sediment record in open wooded savannah of Queen Elizabeth National Park (southwestern Uganda) to assess the sensitivity of the tropical lowland grassland–forest transition to historical, decade-scale moisture-balance fluctuations. Specifically we trace vegetation response to three episodes of higher average rainfall dated to the 1820s–1830s, ca. 1865–1890 and from 1962 to around 2000. Our pollen data indeed reveal a sequence of three wet periods, separated by two drier periods. During the inferred wetter episodes we find increases in the percent pollen abundance of trees and shrubs from moist semi-deciduous forest (Allophylus, Macaranga, Alchornea, Celtis), riparian forest (Phoenix reclinata) and wooded savannah (Acalypha, Rhus-type vulgaris, Combretaceae/Melastomataceae) as well as taxa common in the local rift-valley grasslands (Acacia, Ficus), together creating strong temporary reductions in Poaceae pollen (to 45–55% of the terrestrial pollen sum). During intervening dry periods, Poaceae pollen attained values of 65–75%, and dryland herbs such as Commelina, Justicia-type odora and Chenopodiaceae expanded at the expense of Asteraceae, Solanum-type, Swertia usambarensis-type, and (modestly so) Urticaceae. Noting that the overall richness of arboreal taxa remained high but their combined abundance low, we conclude that the landscape surrounding Lake Chibwera has been an open wooded savannah throughout the past 200 years, with historical moisture-balance variation exerting modest effects on local tree cover (mostly the abundance of Acacia and Ficus) and the occurrence of damp soil areas promoting Phoenix reclinata. The strong apparent expansion of true forest trees during wet episodes can be explained partly by enhanced pollen input via a temporarily activated upland stream. Pollen from exotic trees and cultural indicators appears from the 1970s onwards, but their combined influence fails to mask the signature of natural vegetation dynamics in the pollen record.
CREST (Climate REconstruction SofTware): a probability density function (PDF)-based quantitative climate reconstruction method
Authors: Chevalier M. , Cheddadi R. , Chase B. M.
Published: November 2014

Abstract. Several methods currently exist to quantitatively reconstruct palaeoclimatic variables from fossil botanical data. Of these, probability density function (PDF)-based methods have proven valuable as they can be applied to a wide range of plant assemblages. Most commonly applied to fossil pollen data, their performance, however, can be limited by the taxonomic resolution of the pollen data, as many species may belong to a given pollen type. Consequently, the climate information associated with different species cannot always be precisely identified, resulting in less-accurate reconstructions. This can become particularly problematic in regions of high biodiversity. In this paper, we propose a novel PDF-based method that takes into account the different climatic requirements of each species constituting the broader pollen type. PDFs are fitted in two successive steps, with parametric PDFs fitted first for each species and then a combination of those individual species PDFs into a broader single PDF to represent the pollen type as a unit. A climate value for the pollen assemblage is estimated from the likelihood function obtained after the multiplication of the pollen-type PDFs, with each being weighted according to its pollen percentage. To test its performance, we have applied the method to southern Africa as a regional case study and reconstructed a suite of climatic variables (e.g. winter and summer temperature and precipitation, mean annual aridity, rainfall seasonality). The reconstructions are shown to be accurate for both temperature and precipitation. Predictable exceptions were areas that experience conditions at the extremes of the regional climatic spectra. Importantly, the accuracy of the reconstructed values is independent of the vegetation type where the method is applied or the number of species used. The method used in this study is publicly available in a software package entitled CREST (Climate REconstruction SofTware) and will provide the opportunity to reconstruct quantitative estimates of climatic variables even in areas with high geographical and botanical diversity.
Comparison of sampling methodologies for nutrient monitoring in streams: uncertainties, costs and implications for mitigation
Authors: Audet J. , Martinsen L. , Hasler B. , de Jonge H. , Karydi E. , Ovesen N. B. , Kronvang B.
Published: November 2014

Abstract. Eutrophication of aquatic ecosystems caused by excess concentrations of nitrogen and phosphorus may have harmful consequences for biodiversity and poses a health risk to humans via water supplies. Reduction of nitrogen and phosphorus losses to aquatic ecosystems involves implementation of costly measures, and reliable monitoring methods are therefore essential to select appropriate mitigation strategies and to evaluate their effects. Here, we compare the performances and costs of three methodologies for the monitoring of nutrients in rivers: grab sampling; time-proportional sampling; and passive sampling using flow-proportional samplers. Assuming hourly time-proportional sampling to be the best estimate of the "true" nutrient load, our results showed that the risk of obtaining wrong total nutrient load estimates by passive samplers is high despite similar costs as the time-proportional sampling. Our conclusion is that for passive samplers to provide a reliable monitoring alternative, further development is needed. Grab sampling was the cheapest of the three methods and was more precise and accurate than passive sampling. We conclude that although monitoring employing time-proportional sampling is costly, its reliability precludes unnecessarily high implementation expenses.
Glof Study in Tawang River Basin, Arunachal Pradesh, India
Authors: Panda R. , Padhee S. K. , Dutta S.
Published: November 2014

Abstract. Glacial lake outburst flood (GLOF) is one of the major unexpected hazards in the high mountain regions susceptible to climate change. The Tawang river basin in Arunachal Pradesh is an unexplored region in the Eastern Himalayas, which is impending to produce several upcoming hydro-electric projects (HEP). The main source of the river system is the snow melt in the Eastern Himalayas, which is composed of several lakes located at the snout of the glacier dammed by the lateral or end moraine. These lakes might prove as potential threat to the future scenario as they have a tendency to produce flash flood with large quantity of sediment load during outbursts. This study provides a methodology to detect the potential lakes as a danger to the HEP sites in the basin, followed by quantification of volume of discharge from the potential lake and prediction of hydrograph at the lake site. The remote location of present lakes induced the use of remote sensing data, which was fulfilled by Landsat-8 satellite imagery with least cloud coverage. Suitable reflectance bands on the basis of spectral responses were used to produce informational layers (NDWI, Potential snow cover map, supervised classification map) in GIS environment for discriminating different land features. The product obtained from vector overlay operation of these layers; representing possible water area, was further utilized in combination with Google earth to identify the lakes within the watershed. Finally those identified lakes were detected as potentially dangerous lakes based on the criteria of elevation, area, proximity from streamline, slope and volume of water held. HEC-RAS simulation model was used with cross sections from Google Earth and field survey as input to simulate dam break like situation; hydrodynamic channel routing of the outburst hydrograph along river reach was carried out to get the GLOF hydrograph at the project sites. It was concluded from the results that, the assessed GLOF would be a lead for the qualitative approximation of the amount of bed load transported along the river reach and thus hydropower project sites.
Study of Oil spill in Norwegian area using Decomposition Techniques on RISAT-1 Hybrid Polarimetric Data.
Authors: Jayasri P. V. , Usha Sundari H. S. V. , Sita Kumari E. V. S. , Prasad A. V. V.
Published: November 2014

Abstract. Over past few years Synthetic Aperture Radar(SAR) has received a considerable attention for monitoring and detection of oil spill due to its unique capabilities to provide wide-area surveillance and day and night measurements, almost independently from atmospheric conditions. The critical part of the oil spill detection is to distinguish oil spills from other natural phenomena. Stokes vector analysis of the image data is studied to estimate the polarized circular and linear components of the backscatter signal which essentially utilize the degree of polarization(m) and relative phase (δ) of the target. In a controlled oil spill experiment conducted at Norwegian bay during 17th to 22nd June 2014, RISAT-1 hybrid polarimetry images were utilized to study the characteristics of oil spill in the sea. The preliminary results obtained by using polarimetric decomposition technique on hybrid polarimetric data to decipher the polarimetric characteristics of oil spills from natural waters are discussed in the paper.
Time Series Analysis Of Primary Productivity Along The East Coast Of India Using Oceansat-2 Ocean Colour Monitor (O cm)
Authors: Lakshmi E. , Pratap D. , Nagamani P. V. , Rao K. H. , Preethi Latha T. , Choudhury S. B.
Published: November 2014

Abstract. Primary Productivity is the ultimate source of energy for all organisms in an ecosystem. It is associated with the food production and the global carbon cycle. Sensors on remote platforms (satellites) are capable of estimating the Chlorophyll-a concentration in surface waters by measurement of spectral changes of the upwelling light. From these data, which connected with other remotely sensed data, it is possible to use algorithms to estimate the primary production. In this paper, an initial attempt is made to estimate the Primary Productivity along the east coast of India. Vertically Generalized Productivity Model (VGPM) which is a depth (euphotic depth) integrated model is used for the estimation. The common input variables or geophysical parameters used for the model are chlorophyll-a concentration (chl-a), vertically diffuse attenuation coefficient (Kd-490), Photosynthetically Available Radiation (PAR), and Sea Surface Temperature (SST). The chlorophyll-a and Kd-490 parameters were estimated using Oceansat-2 OCM data whereas PAR and SST were taken from MODIS-aqua data. Oceansat-2 Ocean Colour Monitor (OCM) data for the year 2013 is used in the analysis to compute the primary productivity using the weekly (8-day) data products of all the parameters as mentioned above. These products were inter compared with the MODIS Weekly (8-day) Primary Productivity products which were estimated at a global scale using the modified Vertically Generalized Productivity Model (VGPM) with which uses the exponential function of Sea surface temperature (SST).
Seasonal variability of phytoplankton blooms in the coastal waters along the East coast of India
Authors: Preethi Latha T. , Rao K. H. , Amminedu E. , Nagamani P. V. , Choudhury S. B. , Lakshmi E. , Sridhar P. N. , Dutt C. B. S. , Dhadwal V. K.
Published: November 2014

Abstract. Bay of Bengal (BOB) is a semi enclosed tropical basin located in the north eastern part of the Indian Ocean with high influence of fresh water discharge from major rivers and rainfall. Bay of Bengal (BOB) is highly influenced by monsoons and represents a natural laboratory to study the effect of fresh water fluxes on the marine ecosystem. Bay of Bengal (BOB) is very low in productivity often with the observations of Phytoplankton Blooms. Phytoplankton blooms are one of the prominent features of biological variability in the coastal ecosystems such as estuaries, lagoons, bays, and tidal rivers with rapid production and accumulation of phytoplankton biomass in the ocean. These blooms usually respond to changing physical forcings originating in the coastal ocean like tides, currents and river runoff and to the atmospheric forcing like wind. These physical forcings have different timescales of variability, so algal blooms can be short-term episodic events, recurrent seasonal phenomena, or rare events associated with exceptional climatic or hydrologic conditions. Bloom events and their variability on spatial & temporal scales monitoring through field measurements is difficult. Based on this key hypothesis an effort is made to understand the seasonal and spatial variability of Phytoplankton Blooms along the East Coast of India. In this paper we present the bloom dynamics in their context to the chlorophyll concentration along with species composition and abundance in estuarine and near shore coastal waters of Godavari basin using Oceansat-2 Ocean Colour Monitor (OCM). The initial results revealed that the quasi permanent phytoplankton blooms initiates in the month of mid- February and evolves for a period of two months and then slowly starts decaying by the mid of May month. The results also stand as a base for the study of influence of Phytoplankton Blooms on the carbon flux estimations and bio-geo-chemical processes in the Bay of Bengal.
Automated Registration of Images from Multiple Bands of Resourcesat-2 Liss-4 camera
Authors: Radhadevi P. V. , Solanki S. S. , Jyothi M. V. , Varadan G.
Published: November 2014

Abstract. Continuous and automated co-registration and geo-tagging of images from multiple bands of Liss-4 camera is one of the interesting challenges of Resourcesat-2 data processing. Three arrays of the Liss-4 camera are physically separated in the focal plane in alongtrack direction. Thus, same line on the ground will be imaged by extreme bands with a time interval of as much as 2.1 seconds. During this time, the satellite would have covered a distance of about 14 km on the ground and the earth would have rotated through an angle of 30”. A yaw steering is done to compensate the earth rotation effects, thus ensuring a first level registration between the bands. But this will not do a perfect co-registration because of the attitude fluctuations, satellite movement, terrain topography, PSM steering and small variations in the angular placement of the CCD lines (from the pre-launch values) in the focal plane. This paper describes an algorithm based on the viewing geometry of the satellite to do an automatic band to band registration of Liss-4 MX image of Resourcesat-2 in Level 1A. The algorithm is using the principles of photogrammetric collinearity equations. The model employs an orbit trajectory and attitude fitting with polynomials. Then, a direct geo-referencing with a global DEM with which every pixel in the middle band is mapped to a particular position on the surface of the earth with the given attitude. Attitude is estimated by interpolating measurement data obtained from star sensors and gyros, which are sampled at low frequency. When the sampling rate of attitude information is low compared to the frequency of jitter or micro-vibration, images processed by geometric correction suffer from distortion. Therefore, a set of conjugate points are identified between the bands to perform a relative attitude error estimation and correction which will ensure the internal accuracy and co-registration of bands. Accurate calculation of the exterior orientation parameters with GCPs is not required. Instead, the relative line of sight vector of each detector in different bands in relation to the payload is addressed. With this method a band to band registration accuracy of better than 0.3 pixels could be achieved even in high hill areas.
Quality Metrics Evaluation of Hyperspectral Images
Authors: Singh A. K. , Kumar H. V. , Kadambi G. R. , Kishore J. K. , Shuttleworth J. , Manikandan J.
Published: November 2014

Abstract. In this paper, the quality metrics evaluation on hyperspectral images has been presented using k-means clustering and segmentation. After classification the assessment of similarity between original image and classified image is achieved by measurements of image quality parameters. Experiments were carried out on four different types of hyperspectral images. Aerial and spaceborne hyperspectral images with different spectral and geometric resolutions were considered for quality metrics evaluation. Principal Component Analysis (PCA) has been applied to reduce the dimensionality of hyperspectral data. PCA was ultimately used for reducing the number of effective variables resulting in reduced complexity in processing. In case of ordinary images a human viewer plays an important role in quality evaluation. Hyperspectral data are generally processed by automatic algorithms and hence cannot be viewed directly by human viewers. Therefore evaluating quality of classified image becomes even more significant. An elaborate comparison is made between k-means clustering and segmentation for all the images by taking Peak Signal-to-Noise Ratio (PSNR), Mean Square Error (MSE), Maximum Squared Error, ratio of squared norms called L2RAT and Entropy. First four parameters are calculated by comparing the quality of original hyperspectral image and classified image. Entropy is a measure of uncertainty or randomness which is calculated for classified image. Proposed methodology can be used for assessing the performance of any hyperspectral image classification techniques.
Socio-economic and ecological transformations of the peri-urban region of Gurgaon: an analysis of the trickle-down effect in the post globalization era
Authors: Yadav A. , Punia M.
Published: November 2014

Abstract. Economic processes are a manifestation of dynamic complex interdependent array of factors which involves resources, technology and an acting innovative human mind. Production, growth and development are the processes which has vast number of complex drivers, determinants and factors. Innovation, research, diffusion and dissemination are vital instrument of the economic processes of production, which are part of education. Whereas ecological transformations can be corroborated and analyzed by integrating remote sensing based information related to expansion of built-up area beyond city boundaries, extending to peripheries. City reflect economic, environmental, technological and social processes in their change, yet all are in turn profoundly driven by the urban spatial expansion. Metropolitan cities reflects expansion of existing urban and peri-urban areas with a significant socio-ecological transformation in terms of employment, education, and work force participation and land use changes. From the point of view of New Economic Geography (NEG) Theory 2009, the growth dynamic of metros is influenced by their proximity and dependence to a metropolis and the probable spillover effect. Entry point of discussion is the change in production of space in the post globalization era. It attempts to understand city morphology by using remote sensing datasets of LISS IV, IRS-P6 of 5.8 m spatial resolution for 2008 and 2013 and used Gurgaon Municipal Corporation's (GMC) ward boundary to represent socio-political meaning of this expansion and ways of life within the suburb. To understand how city works, detailed analysis related occupational structure, education and informality of ward 31 of Gurgaon and two villages namely Behlpa, Fazalwas and ward 11 of Nuh ( Mewat) along with the village Gabsanpur is attempted as the spatial units of study.
Operationalizing crop monitoring system for informed decision making related to food security in Nepal
Authors: Qamer F. M. , Shah S. N. Pd. , Murthy M. S. R. , Baidar T. , Dhonju K. , Hari B. G.
Published: November 2014

Abstract. In Nepal, two thirds of the total population depend on agriculture for their livelihoods and more than one third of Gross Domestic Product (GDP) comes from the agriculture sector. However, effective agriculture production across the country remains a serious challenge due to various factors, such as a high degree of spatial and temporal climate variability, irrigated and rain-fed agriculture systems, farmers' fragile social and economic fabric, and unique mountain practices. ICIMOD through SERVIR-Himalaya initiative with collaboration of Ministry of Agricultural Development (MoAD) is working on developing a comprehensive crop monitoring system which aims to provide timely information on crop growth and drought development conditions. This system analyzes historical climate and crop conditions patterns and compares this data with the current growing season to provide timely assessment of crop growth. Using remote sensing data for vegetation indices, temperature and rainfall, the system generated anomaly maps are inferred to predict the increase or shortfall in production. Comparisons can be made both spatially and in graphs and figures at district and Village Developmental Committee (VDC) levels. Timely information on possible anomaly in crop production is later used by the institutions like Ministry of Agricultural Development, Nepal and World Food Programme, Nepal to trigger appropriate management response. Future potential includes integrating data on agricultural inputs, socioeconomics, demographics, and transportation to holistically assess food security in the region served by SERVIR-Himalaya.
Dynamic Land Use and Coastline Changes in active Estuarine Regions – A Study of Sundarban Delta
Authors: Thomas J. V. , Arunachalam A. , Jaiswal R. K. , Diwakar P. G. , Kiran B.
Published: November 2014

Abstract. Alteration of natural environment in the wake of global warming is one of the most serious issues, which is being discussed across the world. Over the last 100 years, global sea level rose by 1.0–2.5 mm/y. Present estimates of future sea-level rise induced by climate change range from 28 to 98 cm for the year 2100. It has been estimated that a 1-m rise in sea-level could displace nearly 7 million people from their homes in India. The climate change and associated sea level rise is proclaimed to be a serious threat especially to the low lying coastal areas. Thus, study of long term effects on an estuarine region not only gives opportunity for identifying the vulnerable areas but also gives a clue to the periods where the sea level rise was significant and verifies climate change impact on sea level rise. Multi-temporal remote sensing data and GIS tools are often used to study the pattern of erosion/ accretion in an area and to predict the future coast lines. The present study has been carried out in the Indian Sundarbans area. Major land cover/ land use classes has been delineated and change analysis of the land cover/ land use feature was performed using multi-temporal satellite images (Landsat MSS, TM, ETM+) from 1973 to 2010. Multivariate GIS based analysis was carried out to depict vulnerability and its trend, spatially. Digital Shoreline change analysis also was attempted for two islands, namely, Ghoramara and Sagar Islands using the past 40 years of satellite data and validated with 2012 Resourcesat-2 LISS III data.
Efficacy of StaMPS technique for monitoring surface deformation in L'Aquila, Italy
Authors: Tiwari A. , Dwivedi R. , Narayan A. B. , Dikshit O. , Singh A. K.
Published: November 2014

Abstract. This research work investigates the efficacy of the Stanford Method for Persistent Scatterer Interferometry (StaMPS) in measuring the surface deformation over the L'Aquila region, Italy just before an event of earthquake of magnitude Mw 6.3 by using seven descending Envisat C-Band ASAR images. The results show that the StaMPS technique successfully extracted sufficient number of Persistent Scatterers (PS) to derive a one dimensional (1D) time series displacement map which shows the deformation rates up to 59 mm/year in the satellite Line of Sight (LOS) direction and 50.8 mm/year in the direction opposite to the satellite LOS. Further, several deformation gradients are also observed from this map which indicate the occurrence of multiple crustal movement mechanism. Another dataset of 14 ASAR images is processed covering a time period before and after the earthquake in the study area to validate the results obtained by the previous dataset. We observed that the generated displacement map follows the deformation characteristics of the earlier displacement map in terms of magnitude and surface movement. We conclude that the generated displacement maps validate the presence of a normal fault mechanism with a tectonic process stretching in a NW-SE direction as predicted by earlier research studies.
GIS and Remote Sensing for Malaria Risk Mapping, Ethiopia
Authors: Ahmed A.
Published: November 2014

Abstract. Integrating malaria data into a decision support system (DSS) using Geographic Information System (GIS) and remote sensing tool can provide timely information and decision makers get prepared to make better and faster decisions which can reduce the damage and minimize the loss caused. This paper attempted to asses and produce maps of malaria prone areas including the most important natural factors. The input data were based on the geospatial factors including climatic, social and Topographic aspects from secondary data. The objective of study is to prepare malaria hazard, Vulnerability, and element at risk map which give the final output, malaria risk map. The malaria hazard analyses were computed using multi criteria evaluation (MCE) using environmental factors such as topographic factors (elevation, slope and flow distance to stream), land use/ land cover and Breeding site were developed and weighted, then weighted overlay technique were computed in ArcGIS software to generate malaria hazard map. The resulting malaria hazard map depicts that 19.2 %, 30.8 %, 25.1 %, 16.6 % and 8.3 % of the District were subjected to very high, high, moderate, low and very low malaria hazard areas respectively. For vulnerability analysis, health station location and speed constant in Spatial Analyst module were used to generate factor maps. For element at risk, land use land cover map were used to generate element at risk map. Finally malaria risk map of the District was generated. Land use land cover map which is the element at risk in the District, the vulnerability map and the hazard map were overlaid. The final output based on this approach is a malaria risk map, which is classified into 5 classes which is Very High-risk area, High-risk area, Moderate risk area, Low risk area and Very low risk area. The risk map produced from the overlay analysis showed that 20.5 %, 11.6 %, 23.8 %, 34.1 % and 26.4 % of the District were subjected to very high, high, moderate, low and very low malaria risk respectively. This help to plan valuable measures to be taken in early warning, monitor, control and prevent malaria epidemics.
Analytical Hierarchy Process modeling for malaria risk zones in Vadodara district, Gujarat
Authors: Bhatt B. , Joshi J. P.
Published: November 2014

Abstract. Malaria epidemic is one of the complex spatial problems around the world. According to WHO, an estimated 6, 27, 000 deaths occurred due to malaria in 2012. In many developing nations with diverse ecological regions, it is still a large cause of human mortality. Owing to the incompleteness of epidemiological data and their spatial origin, the quantification of disease incidence burdening basic public health planning is a major constrain especially in developing countries. The present study focuses on the integrated Geospatial and Multi-Criteria Evaluation (AHP) technique to determine malaria risk zones. The study is conducted in Vadodara district, including 12 Taluka among which 4 Taluka are predominantly tribal. The influence of climatic and physical environmental factors viz., rainfall, hydro geomorphology; drainage, elevation, and land cover are used to score their share in the evaluation of malariogenic condition. This was synthesized on the basis of preference over each factor and the total weights of each data and data layer were computed and visualized. The district was divided into three viz., high, moderate and low risk zones .It was observed that a geographical area of 1885.2sq.km comprising 30.3% fall in high risk zone. The risk zones identified on the basis of these parameters and assigned weights shows a close resemblance with ground condition. As the API distribution for 2011overlaid corresponds to the risk zones identified. The study demonstrates the significance and prospect of integrating Geospatial tools and Analytical Hierarchy Process for malaria risk zones and dynamics of malaria transmission.
Geomatics Approach for Assessment of respiratory disease Mapping
Authors: Pandey M. , Singh V. , Vaishya R. C.
Published: November 2014

Abstract. Air quality is an important subject of relevance in the context of present times because air is the prime resource for sustenance of life especially human health position. Then with the aid of vast sums of data about ambient air quality is generated to know the character of air environment by utilizing technological advancements to know how well or bad the air is. This report supplies a reliable method in assessing the Air Quality Index (AQI) by using fuzzy logic. The fuzzy logic model is designed to predict Air Quality Index (AQI) that report monthly air qualities. With the aid of air quality index we can evaluate the condition of the environment of that area suitability regarding human health position. For appraisal of human health status in industrial area, utilizing information from health survey questionnaire for obtaining a respiratory risk map by applying IDW and Gettis Statistical Techniques. Gettis Statistical Techniques identifies different spatial clustering patterns like hot spots, high risk and cold spots over the entire work area with statistical significance.
Geospatial modelling for groundwater quality mapping: a case study of Rupnagar district, Punjab, India
Authors: Sahoo S. , Kaur A. , Litoria P. , Pateriya B.
Published: November 2014

Abstract. Over period of time, the water usage and management is under stress for various reasons including pollution in both surface and subsurface. The groundwater quality decreases due to the solid waste from urban and industrial nodes, rapid use of insecticides and pesticides in agricultural practices. In this study, ground water quality maps for Rupnagar district of Punjab has been prepared using geospatial interpolation technique through Inverse Distance Weighted (IDW) approach. IDW technique has been used for major ground water quality parameters observed from the field samples like Arsenic, Hardness, pH, Iron, Fluoride, TDS, and Sulphate. To assess the ground water quality of the Rupnagar district, total 280 numbers of samples from various sources of tubewells for both pre and post monsoon have collected. Out of which, 80 to 113 samples found Iron with non potable limits ranging 0.3–1.1mg/l and 0.3–1.02mg/l according to BIS standard for both the seasons respectively. Chamkaur Sahib, Rupnagar, Morinda blocks have been found non potable limit of iron in both pre & post-monsoon. 11 to 52 samples in this region have sulphate with permissible limits in both the season ranging 200–400mg/l and 201–400mg/l. But arsenic had acceptable limit in both the season. Various parameters-wise ground water quality map is generated using the range values of drinking water quality to know the distribution of different parameters and diversification in the concentration of different elements. These maps are very much needful for human being to expand awareness among the people to maintain the Cleanness of water at their highest quality and purity levels to achieve a healthy life.
Evaluation of operational INSAT-3D UTH product, using Radiosonde, Meteosat-7 and NCEP Analysis
Authors: Dey I. , Shukla M. V. , Thapliyal P. K. , Kishtawal C. M.
Published: November 2014

Abstract. Recently available satellite observations from the water vapor channel (6.5–7.1 μm) of the Imager on-board India's geostationary satellite, INSAT-3D have been used to estimate Upper Tropospheric Humidity (UTH). In this study, operationally retrieved UTH product has been compared and validated for the period of Jan–Jun, 2014, using in-situ and satellite measurements. In-situ measurements of UTH have been indirectly derived using humidity profiles obtained from a network of radiosonde stations from NOAA/ESRL database. Meteosat-7 UTH products have been used as satellite measurements. The validation of INSAT-3D UTH against UTH derived from radiosonde profiles shows reasonable agreement, with linear correlation coefficients ranging from 0.78 to 0.87 and the slope of the regression line ranging from 0.52 to 0.77. The UTH tends to overestimate observed humidity by ~4 % with RMS difference of ~12 %. Comparison of INSAT-3D UTH product with Meteosat-7 UTH product suggests a good match with RMS difference of 7.61% and a mean bias of −0.43 %, linear correlation coefficients varying from 0.88 to 0.93 and slope of the regression line varying from 0.64 to 1.08. The UTH products from INSAT-3D and Meteosat-7 have also been inter-compared by validating the two against the UTH derived from a set of collocated radiosonde observations. INSAT-3D UTH shows a RMSD of 10.65 % and bias of 0.78 % which matches very well with Meteosat-7 UTH with a RMSD of 10.31 % and bias of −0.53 %.
Lidar Studies on The Optical Characteristics of High Altitude Cirrus Clouds at A Low Latitiude Station, Gadanki (13.5°N , 79.2°E ) India
Authors: Jayeshlal G. S. , Satyanarayana M. , Motty G. S. , Dhaman R. K. , Krishnakumar V. , Mahadevan Pillai V. P. , Ramakrishnarao D. , Sudhakar P. , Kalavathi P.
Published: November 2014

Abstract. Light Detection and Ranging (LIDAR) which is analogous to Radio Detection And Ranging (RADAR), has become an important and unique technology for atmospheric research and applications. The technology is widely used for the remote sensing of the Earth’s atmosphere, oceans, vegetation and the characteristics of Earth’s topography. Remote sensing of atmosphere, for its structure, composition and dynamics, is one of the proven applications of the lidar systems. More importantly the lidar technique is applied for the study of clouds, aerosols and minor constituents in the atmosphere. It provides the information on the above with good spatial and temporal resolutions and accuracy. The high altitude cirrus clouds which play an important role in the Earth’s radiative budget and global climate can be studied by using the LIDAR system. These clouds absorb long-wave outgoing radiation from Earth’s surface while reflecting part of the incoming short-wave solar radiation. Lidar measurements are useful in deriving the altitude, top height, bottom height and the optical properties of cirrus clouds, which are essential in understanding the cloud-radiation effects. The optical depth, the effective lidar ratio and the depolarization of the clouds are also derived by inverting the lidar signals from the cirrus clouds. In this paper we present the results on the lidar derived optical and microphysical properties of the cirrus clouds at a tropical station Gadanki (13.5°N, 79.2°E) India during two year period from 2009 to210. The seasonal variations of the cloud properties during the observation period are presented and discussed with reference to earlier period.
INSAT-3D Quality Analysis System (i3dQAS)
Authors: Jindal D. , Prakash S. , Sanghvi J. , Kartikeyan B. , Gopala Krishna B.
Published: November 2014

Abstract. INSAT-3D, an advanced meteorological satellite of ISRO carrying Imager and Sounder payloads is designed for acquiring data required for detailed climatological applications. At established data centres, Raw (L-0) data is processed to generate systematically corrected (Level-1) and geo-physical (Level-2) products which are further disseminated for use in climate related studies. Data quality evaluation (DQE) of basic data products of INSAT-3D is being operationally carried out at MOSDAC, Ahmedabad to monitor in-orbit sensor health, quantify data quality and provide feedback to various missions teams for corrective actions. DQE methodology and quality parameters have been defined keeping in view repeatability of data acquisition and quality requirements of meteorological data. In this paper, we have described INSAT-3D Quality Analysis System (i3dQAS) designed to facilitate effective data quality monitoring through web based portal. Overall context of i3dQAS in a typical data centre set-up, major objectives and design aspects to highlight the architectural and functional view of system are described. Utility of i3dQAS for mission monitoring is described through analysis scenarios for monitoring payload health and geometric accuracy of Imager.
Operational Retrieval of aerosol optical depth over Indian subcontinent and Indian Ocean using INSAT-3D/Imager product validation
Authors: Mishra M. K. , Rastogi G. , Chauhan P.
Published: November 2014

Abstract. Aerosol optical depth (AOD) over Indian subcontinent and Indian Ocean region is derived operationally for the first time from the geostationary earth orbit (GEO) satellite INSAT-3D Imager data at 0.65 μm wavelength. Single visible channel algorithm based on clear sky composites gives larger retrieval error in AOD than other multiple channel algorithms due to errors in estimating surface reflectance and atmospheric property. However, since MIR channel signal is insensitive to the presence of most aerosols, therefore in present study, AOD retrieval algorithm employs both visible (centred at 0.65 μm) and mid-infrared (MIR) band (centred at 3.9 μm) measurements, and allows us to monitor transport of aerosols at higher temporal resolution. Comparisons made between INSAT-3D derived AOD (τI) and MODIS derived AOD (τM) co-located in space (at 1° resolution) and time during January, February and March (JFM) 2014 encompasses 1165, 1052 and 900 pixels, respectively. Good agreement found between τI and τM during JFM 2014 with linear correlation coefficients (R) of 0.87, 0.81 and 0.76, respectively. The extensive validation made during JFM 2014 encompasses 215 co-located AOD in space and time derived by INSAT 3D (τI) and 10 sun-photometers (τA) that includes 9 AERONET (Aerosol Robotic Network) and 1 handheld sun-photometer site. INSAT-3D derived AOD i.e. τI, is found within the retrieval errors of τI = ±0.07 ±0.15τA with linear correlation coefficient (R) of 0.90 and root mean square error equal (RMSE) to 0.06. Present work shows that INSAT-3D aerosol products can be used quantitatively in many applications with caution for possible residual clouds, snow/ice, and water contamination.
Absolute Vicarious Calibration of recently launched Indian Meteorological Satellite: INSAT-3D imager
Authors: Patel P. , Bhatt H. , Shukla A. K.
Published: November 2014

Abstract. Looking towards the advancements and popularity of remote sensing and an ever increasing need for the development of a variety of new and complex satellite sensors, it has become even more essential to continually upgrade the ability to provide absolute calibration of sensors. This article describes a simple procedure to implement post-launch calibration for VIS and SWIR channels of INSAT-3D imager over land site (Little Rann of Kutch (ROK), Gujarat) on three different days to account for characterization errors or undetermined post-launch changes in spectral response of the sensor. The measurements of field reflectance of study site (of extent ~6 km x 6 km) in the wavelength range 325–2500 nm, along with atmospheric parameters (Aerosol Optical Depth, Total Columnar Ozone, Water Vapor) and sensor spectral response functions, were input to the 6S radiative transfer model to simulate radiance at top of the atmosphere (TOA) for VIS and SWIR bands. The uncertainty in vicarious calibration coefficients due to measured spatial variability of field reflectance along with due to aerosol types were also computed for the INSAT-3D imager. The effect of surface anisotropy on TOA radiance was studied using a MODIS Bidirectional Reflectance Distribution Function (BRDF) product covering the experimental site. The results show that there is no indication of change in calibration coefficients in INSAT- 3D imager, for VIS and SWIR band over Little ROK. Comparison made between the INSAT-3D imager measured radiance and 6S simulated radiance. Analysis shows that for clear sky days, the INSAT-3D imager overestimates TOA radiance in the VIS band by 5.1 % and in the SWIR band by 11.7 % with respect to 6S simulated radiance. For these bands, in the inverse mode, the 6S corrected surface reflectance was closer to field surface reflectance. It was found that site spatial variability was a critical factor in estimating change in sensor calibration coefficients and influencing uncertainty in TOA radiance for Little ROK.
MOPITT total column CO over the Indian Subcontinent: Spatial variability and long term trend
Authors: Srivastava S.
Published: November 2014

Abstract. Total column carbon monoxide (CO) concentration obtained from MOPITT (Measurement Of Pollution In The Troposphere) have been analyzed over the Indian subcontinent for a period of March, 2000 to December, 2010. Average monthly variation of columnar CO is investigated over the eastern and western coasts of India (latitude > 18°N). The columnar CO concentration is found to be larger over the east coast than the west coast. The higher columnar CO concentrations (2.3–2.8 x 1018 molec/cm2) occur during November to April months over both the coastal regions. The lower columnar CO concentrations (1.6–1.7 x 1018 molec/cm2) occur during July-August months over these coastal regions when air blows from the Bay of Bengal towards the east coast and from the Arabian Sea towards the west coast. The latitudinal variations of ten year averaged columnar CO are also investigated over the eastern and western coastlines of India (23.5°N to 8.5°N). The latitudinal gradient is stronger over the eastern coast (3.2 x 1016 molec/cm2/°N) with respect to the western coast (8.6 x 1015 molec/cm2/°N) due to injection of highly polluted air mass from the Indo-Gangetic Plain over the northern part of Bay of Bengal. In order to investigate the source of pollution, variation of columnar CO concentration over the 11 polluted cities situated in the Indo-Gangetic plain has been examined. Columnar CO concentrations are found to be significantly higher over the southeast Indo-Gangetic plain and show a linear decreasing tendency from southeast to northwest cities. The maximum columnar CO concentration is observed over Patna (~ 2.48 x 1018 molec/cm2) and minimum over Multan (~ 2.19 x 1018 molec/cm2). This indicates that south-eastern part of Indo-Gangetic plain is mainly contributing towards enhancement in columnar CO concentration over the eastern coast. Columnar CO concentration showed an increasing trend during 2000 to 2010 over all the 11 cities. This increasing tendency is stronger over the cities situated in the southeast part of Indo-Gangetic plain.