bluuebunny/crossref_metadata_2025 huggingface dataset:
Spontaneous resolution of ruptured dissecting anterior inferior cerebellar artery aneurysm: A rare case report
Authors: Singh Sumeet , Mittal R , Purohit Devendra , Shekhawat Jetendra
Published: November 2014

Dissecting anterior inferior cerebellar artery (AICA) aneurysms are extremely rare, and only nine cases are reported till date. We are reporting a case of ruptured dissecting distal AICA aneurysm with spontaneous resolution; first of its kind in the indexed literature.
Brain metastases in cancer patients attending a Gamma Knife Center: A study from a single institute in Iran
Authors: Azimi Parisa , Shahzadi Sohrab , Bitaraf Mohammad , Azar Maziar , Alikhani Mazdak , Zali Alireza , Sadeghi Sohrab , Montazeri Ali
Published: November 2014

Background: This study was aimed to explore data on brain metastases in cancer patients attending the Iranian Gamma Knife Center.
Meterials and Methods: This was a retrospective study. In all 5216 case records of patients who referred to the Iranian Gamma Knife Center for treatment of brain tumors during year 2003-2011 were reviewed. Data were explored to identify patients who developed brain metastases due to cancer and assessed the information as applied to cancer patients including survival analysis. Results: Two hundred and twenty patients were identified as having brain metastases due to cancer. The mean age of patients was 54.0 (standard deviation [SD] =12.7) years. Patients were followed for an average of 7 months after treatment with gamma-knife. The median survival time for different the Graded Prognostic Assessment (GPA) was: GPA: 0-1, 4.0 ± 0.4 months; GPA: 1.5-2.5, 6.0 ± 0.7 months; GPA: 3, 9.0 ± 0.9 months; and GPA: 3.5-4.0, 12.0 ± 1.8 months and the overall median survival was 7.0 (SD = 0.6) months. Conclusion: The findings suggest that many cancer patients in Iran might develop brain metastasis. Although, this is not a very high incidence compared with the existing statistics from other countries, there is an urgent need to explore the issue further.
Totally cystic intradural schwannoma in thoracic region
Authors: Kumar Sushil , Gupta Raghavendra , Handa Amit , Sinha Rohan
Published: November 2014

Spinal schwannomas are benign intradural extramedullary tumors arising from spinal nerve root sheath. They are usually solid or heterogeneously solid. Totally cystic schwannomas are rare entities. Herein, we report a 60-year-old male presenting with backache radiating along the chest wall and weakness of both lower limbs. He had spastic paraparesis. Magnetic resonance imaging revealed a cystic mass in the thoracic region. At operation, the cystic mass was seen to be attached to D4 dorsal rootlets. It was excised in toto and histopathology confirmed it to be a schwannoma. The relevant literature is reviewed.
First report of important causal relationship between the Adamkiewicz artery vasospasm and dorsal root ganglion cell degeneration in spinal subarachnoid hemorrhage: An experimental study using a rabbit model
Authors: Turkmenoglu Osman , Kanat Ayhan , Yolas Coskun , Aydin Mehmet , Ezirmik Naci , Gundogdu Cemal
Published: November 2014

Background: The blood supply of the lower spinal cord is heavily dependent on the artery of Adamkiewicz. The goal of this study was to elucidate the effects of lumbar subarachnoid hemorrhage (SAH) on the lumbar 4 dorsal root ganglion (L4DRG) cells secondary to Adamkiewicz artery (AKA) vasospasm. Materials and Methods: This study was conducted on 20 rabbits, which were randomly divided into three groups: Spinal SAH (n = 8), serum saline (SS) (SS; n = 6) and control (n = 6) groups. Experimental spinal SAH was performed. After 20 days, volume values of AKA and neuron density of L4DRG were analyzed. Results: The mean alive neuron density of the L4DRG was 15420 ± 1240/mm3 and degenerated neuron density was 1045 ± 260/mm3 in the control group. Whereas, the density of living and degenerated neurons density were 12930 ± 1060/mm3 and 1365 ± 480/mm3 in serum saline (SS), 9845 ± 1028/mm3 and 4560 ± 1340/mm3 in the SAH group. The mean volume of imaginary AKAs was estimated as 1,250 ± 0,310 mm3 in the control group and 1,030 ± 0,240 mm3 in the SF group and 0,910 ± 0,170 mm3 in SAH group. Volume reduction of the AKAs and neuron density L4DRG were significantly different between the SAH and other two groups (P < 0.05). Conclusion: Decreased volume of the lumen of the artery of Adamkiewicz was observed in animals with SAH compared with controls. Increased degeneration the L4 dorsal root ganglion in animals with SAH was also noted. Our findings will aid in the planning of future experimental studies and determining the clinical relevance on such studies.
Validation of MIPAS IMK/IAA V5R_O3_224 ozone profiles
Authors: Laeng A. , Grabowski U. , von Clarmann T. , Stiller G. , Glatthor N. , Höpfner M. , Kellmann S. , Kiefer M. , Linden A. , Lossow S. , Sofieva V. , Petropavlovskikh I. , Hubert D. , Bathgate T. , Bernath P. , Boone C. D. , Clerbaux C. , Coheur P. , Damadeo R. , Degenstein D. , Frith S. , Froidevaux L. , Gille J. , Hoppel K. , McHugh M. , Kasai Y. , Lumpe J. , Rahpoe N. , Toon G. , Sano T. , Suzuki M. , Tamminen J. , Urban J. , Walker K. , Weber M. , Zawodny J.
Published: November 2014

Abstract. We present the results of an extensive validation program of the most recent version of ozone vertical profiles retrieved with the IMK/IAA (Institute for Meteorology and Climate Research/Instituto de Astrofísica de Andalucía) MIPAS (Michelson Interferometer for Passive Atmospheric Sounding) research level 2 processor from version 5 spectral level 1 data. The time period covered corresponds to the reduced spectral resolution period of the MIPAS instrument, i.e., January 2005–April 2012. The comparison with satellite instruments includes all post-2005 satellite limb and occultation sensors that have measured the vertical profiles of tropospheric and stratospheric ozone: ACE-FTS, GOMOS, HALOE, HIRDLS, MLS, OSIRIS, POAM, SAGE II, SCIAMACHY, SMILES, and SMR. In addition, balloon-borne MkIV solar occultation measurements and ground-based Umkehr measurements have been included, as well as two nadir sensors: IASI and SBUV. For each reference data set, bias determination and precision assessment are performed. Better agreement with reference instruments than for the previous data version, V5R_O3_220 (Laeng et al., 2014), is found: the known high bias around the ozone vmr (volume mixing ratio) peak is significantly reduced and the vertical resolution at 35 km has been improved. The agreement with limb and solar occultation reference instruments that have a known small bias vs. ozonesondes is within 7% in the lower and middle stratosphere and 5% in the upper troposphere. Around the ozone vmr peak, the agreement with most of the satellite reference instruments is within 5%; this bias is as low as 3% for ACE-FTS, MLS, OSIRIS, POAM and SBUV.
Validation of SCIAMACHY HDO/H2O measurements using the TCCON and NDACC-MUSICA networks
Authors: Scheepmaker R. A. , Frankenberg C. , Deutscher N. M. , Schneider M. , Barthlott S. , Blumenstock T. , Garcia O. E. , Hase F. , Jones N. , Mahieu E. , Notholt J. , Velazco V. , Landgraf J. , Aben I.
Published: November 2014

Abstract. Measurements of the atmospheric HDO/H2O ratio help us to better understand the hydrological cycle and improve models to correctly simulate tropospheric humidity and therefore climate change. We present an updated version of the column-averaged HDO/H2O ratio dataset from the SCanning Imaging Absorption spectroMeter for Atmospheric CHartographY (SCIAMACHY). The dataset is extended with two additional years, now covering 2003–2007, and is validated against co-located ground-based total column δD measurements from Fourier-Transform Spectrometers (FTS) of the Total Carbon Column Observing Network (TCCON) and the Network for the Detection of Atmospheric Composition Change (NDACC, produced within the framework of the MUSICA project). Even though the time overlap between the available data is not yet ideal, we determined a mean negative bias in SCIAMACHY δD of −35±30‰ compared to TCCON and −69±15‰ compared to MUSICA (the uncertainty indicating the station-to-station standard deviation). The bias shows a latitudinal dependency, being largest (∼ −60 to −80‰) at the highest latitudes and smallest (∼ −20 to −30‰) at the lowest latitudes. We have tested the impact of an offset correction to the SCIAMACHY HDO and H2O columns. This correction leads to a humidity and latitude dependent shift in δD and an improvement of the bias by 27‰, although it does not lead to an improved correlation with the FTS measurements nor to a strong reduction of the latitudinal dependency of the bias. The correction might be an improvement for dry, high-altitude areas, such as the Tibetan Plateau and the Andes region. For these areas, however, validation is currently impossible due to a lack of ground stations. The mean standard deviation of single-sounding SCIAMACHY–FTS differences is ∼ 115‰, which is reduced by a factor ∼ 2 when we consider monthly means. When we relax the strict matching of individual measurements and focus on the mean seasonalities using all available FTS data, we find that the correlation coefficients between SCIAMACHY and the FTS networks improve from 0.2 to 0.7–0.8. Certain ground stations show a clear asymmetry in δD during the transition from the dry to the wet season and back, which is also detected by SCIAMACHY. This asymmetry points to a transition in the source region temperature or location of the water vapor, and shows the added information that HDO/H2O measurements provide, if used in combination with variations in humidity.
Impacts of freezing and thawing dynamics on foliar litter carbon release in alpine/subalpine forests along an altitudinal gradient in the eastern Tibetan Plateau
Authors: Fuzhong W. , Changhui P. , Jianxiao Z. , Jian Z. , Bo T. , Wanqin Y.
Published: November 2014

Abstract. Carbon (C) release from foliar litter is a primary component in C exchange among the atmosphere, vegetation, soil and water from respiration and leaching, but little information is currently related to the effects of freezing and thawing dynamics on C release of foliar litter in cold regions. A 2-year field litter decomposition experiment was conducted along an altitudinal gradient (~ 2700 to ~ 3600 m) to mimic temperature increases in the eastern Tibetan Plateau. C release was investigated for fresh foliar litter of spruce, fir and birch. The onset of the frozen stage, deep frozen stage and thawing stage was partitioned according to changes in the freezing and thawing dynamics of each winter. More rapid 2-year C released from fresh foliar litter at upper elevations compared to lower elevations in the alpine/subalpine region. However, high C release was observed at low altitudes during winter stages, but high altitudes exhibited high C release during growing season stages. The deep frozen stage showed higher rates of C release than other stages in the second year of decomposition. Negative-degree days showing freezing degrees were correlated to C release rates for the deep frozen stages in both years, and this relationship continued for the duration of the experiment, indicating that changes in freezing can directly modify C release from foliar litter. The results suggested that the changed freezing and thawing dynamics could delay the onset of C release in fresh litter in this cold region in the scenario of climate warming.
Does Vegetation Parameterization from EO NDVI Data Capture Grazing induced Variations in Species Composition and Biomass in Semi-Arid Grassland Savanna?
Authors: Olsen J. L. , Miehe S. , Ceccato P. , Fensholt R.
Published: November 2014

Abstract. Most regional scale studies of vegetation in the Sahel have been based on Earth observation (EO) imagery, due to the limited number of sites providing continuous and long term in situ meteorological and vegetation measurement. From long time series of coarse resolution normalized difference vegetation index (NDVI) data a greening of the Sahel since the 1980s has been identified. The greening appears highly related to a general increase in rainfall following the severe droughts of the 1970s and 80s. In the same time period the region has experienced a drastic population boom and a resulting increase in numbers of livestock. However, it is poorly understood how commonly applied remote sensing techniques reflect the extensive influence of grazing on natural rangeland vegetation. This paper analyses time series of parameterized Moderate Resolution Imaging Spectroradiometer (MODIS) NDVI data by comparison with data from the Widou Thiengoly test site in northern Senegal. Field data include grazing intensity, vegetation productivity, and species composition from sizeable areas suitable for comparison with moderate – coarse resolution satellite imagery. It is established that sampling plots excluded from grazing have higher Net Primary Production (NPP) and different species composition as compared to plots under controlled grazing or communal grazing. The seasonal small integrated NDVI, derived using absolute thresholds to estimate start and end of growing seasons, is identified as the parameter most strongly related to vegetation productivity for all grazing regimes. However plot-pixel comparisons demonstrates how the NDVI/biomass relationship changes due to grazing induced variation in annual plant species composition and the NDVI values for grazed plots are only slightly lower than the values observed for the ungrazed plots. Hence, average biomass in ungrazed plots since 2000 was 0.93 t ha−1, compared to 0.51 t ha−1 for plots subjected to controlled grazing and 0.49 t ha−1 for communally grazed plots, but the average integrated NDVI values for the same period were 1.56, 1.49, and 1.45 for ungrazed, controlled and communal respectively, i.e. a much smaller difference. This indicates that a grazing induced development towards less standing crop biomass and limited ability to turn additional water in wet years into biomass can cause neutral or even increasing NDVI trends over time. It is important to note that these findings are based on limited data and needs to be further verified, as it ultimately indicates that the greening of Sahel could partly be an indicator of increasingly intensified grazing.
Large eddy simulations of surface roughness parameter sensitivity to canopy-structure characteristics
Authors: Maurer K. D. , Bohrer G. , Ivanov V. Y.
Published: November 2014

Abstract. Surface roughness parameters are at the core of every model representation of the coupling and interactions between land-surface and atmosphere, and are used in every model of surface fluxes. However, most models assume these parameters to be a fixed property of plant functional type and do not vary them in response to spatial or temporal changes to canopy structure. In part, this is due to the difficulty of reducing the complexity of canopy structure and its spatiotemporal dynamic and heterogeneity to less than a handful of parameters describing its effects of atmosphere–surface interactions. In this study we use large-eddy simulations to explore, in silico, the effects of canopy structure characteristics on surface roughness parameters. We performed a virtual experiment to test the sensitivity of resolved surface roughness to four axes of canopy structure: (1) leaf area index, (2) the vertical profile of leaf density, (3) canopy height, and (4) canopy gap fraction. We found roughness parameters to be highly variable, but were able to find positive relationships between displacement height and maximum canopy height, aerodynamic canopy height and maximum canopy height and leaf area index, and eddy-penetration depth and gap fraction. We also found negative relationships between aerodynamic canopy height and gap fraction, and between eddy-penetration depth and maximum canopy height and leaf area index. Using a decade of wind and canopy structure observations in a site in Michigan, we tested the effectiveness of our model-resolved parameters in predicting the frictional velocity over heterogeneous and disturbed canopies. We compared it with three other semi-empirical models and with a decade of meteorological observations. We found that parameterizations with fixed representations of roughness performed relatively well. Nonetheless, some empirical approaches that incorporate seasonal and inter-annual changes to the canopy structure performed even better than models with temporally fixed parameters.
Spatial variability and temporal dynamics of greenhouse gas (CO2, CH4, N2O) concentrations and fluxes along the Zambezi River mainstem and major tributaries
Authors: Teodoru C. R. , Nyoni F. C. , Borges A. V. , Darchambeau F. , Nyambe I. , Bouillon S.
Published: November 2014

Abstract. Spanning over 3000 km in length and with a catchment of approximately 1.4 million km2, the Zambezi River is the fourth largest river in Africa and the largest flowing into the Indian Ocean from the African continent. As part of a~broader study on the riverine biogeochemistry in the Zambezi River basin, we present data on greenhouse gas (GHG, carbon dioxide (CO2), methane (CH4), and nitrous oxide (N2O)) concentrations and fluxes collected along the Zambezi River, reservoirs and several of its tributaries during 2012 and 2013 and over two climatic seasons (dry and wet) to constrain the interannual variability, seasonality and spatial heterogeneity along the aquatic continuum. All GHGs concentrations showed high spatial variability (coefficient of variation: 1.01 for CO2, 2.65 for CH4 and 0.21 for N2O). Overall, there was no unidirectional pattern along the river stretch (i.e. decrease or increase towards the ocean), as the spatial heterogeneity of GHGs appeared to be determined mainly by the connectivity with floodplains and wetlands, and the presence of man-made structures (reservoirs) and natural barriers (waterfalls, rapids). Highest CO2 and CH4 concentrations in the mainstream river were found downstream of extensive floodplains/wetlands. Undersaturated CO2 conditions, in contrast, were characteristic for the surface waters of the two large reservoirs along the Zambezi mainstem. N2O concentrations showed the opposite pattern, being lowest downstream of floodplains and highest in reservoirs. Among tributaries, highest concentrations of both CO2 and CH4 were measured in the Shire River whereas low values were characteristic for more turbid systems such as the Luangwa and Mazoe rivers. The interannual variability in the Zambezi River was relatively large for both CO2 and CH4, and significantly higher concentrations (up to two fold) were measured during wet seasons compared to the dry season. Interannual variability of N2O was less pronounced but generally higher values were found during the dry season. Overall, both concentrations and fluxes of CO2 and CH4 were well below the median/average values reported for tropical rivers, streams and reservoirs. A first-order mass balance suggests that carbon (C) transport to the ocean represents the major component (59%) of the budget (largely in the form of DIC), while only 38% of total C yield is annually emitted into the atmosphere, mostly as CO2 (98%), and 3% is removed by sedimentation in reservoirs.
The spectral element method (SEM) on variable-resolution grids: evaluating grid sensitivity and resolution-aware numerical viscosity
Authors: Guba O. , Taylor M. A. , Ullrich P. A. , Overfelt J. R. , Levy M. N.
Published: November 2014

Abstract. We evaluate the performance of the Community Atmosphere Model's (CAM) spectral element method on variable-resolution grids using the shallow-water equations in spherical geometry. We configure the method as it is used in CAM, with dissipation of grid scale variance, implemented using hyperviscosity. Hyperviscosity is highly scale selective and grid independent, but does require a resolution-dependent coefficient. For the spectral element method with variable-resolution grids and highly distorted elements, we obtain the best results if we introduce a tensor-based hyperviscosity with tensor coefficients tied to the eigenvalues of the local element metric tensor. The tensor hyperviscosity is constructed so that, for regions of uniform resolution, it matches the traditional constant-coefficient hyperviscosity. With the tensor hyperviscosity, the large-scale solution is almost completely unaffected by the presence of grid refinement. This later point is important for climate applications in which long term climatological averages can be imprinted by stationary inhomogeneities in the truncation error. We also evaluate the robustness of the approach with respect to grid quality by considering unstructured conforming quadrilateral grids generated with a well-known grid-generating toolkit and grids generated by SQuadGen, a new open source alternative which produces lower valence nodes.
Iron oxidation kinetics and phosphate immobilization along the flow-path from groundwater into surface water
Authors: van der Grift B. , Rozemeijer J. C. , Griffioen J. , van der Velde Y.
Published: November 2014

Abstract. The retention of phosphorus in surface waters through co-precipitation of phosphate with Fe-oxyhydroxides during exfiltration of anaerobic Fe(II) rich groundwater is not well understood. We developed an experimental field set-up to study Fe(II) oxidation and P immobilization along the flow-path from groundwater into surface water in an agricultural experimental catchment of a small lowland river. We physically separated tube drain effluent from groundwater discharge before it entered a ditch in an agricultural field. Through continuous discharge measurements and weekly water quality sampling of groundwater, tube drain water, exfiltrated groundwater, and surface water, we investigated Fe(II) oxidation kinetics and P immobilization processes. The oxidation rate inferred from our field measurements closely agreed with the general rate law for abiotic oxidation of Fe(II) by O2. Seasonal changes in climatic conditions affected the Fe(II) oxidation process. Lower pH and lower temperatures in winter (compared to summer) resulted in low Fe oxidation rates. After exfiltration to the surface water, it took a couple of days to more than a week before complete oxidation of Fe(II) is reached. In summer time, Fe oxidation rates were much higher. The Fe concentrations in the exfiltrated groundwater were low, indicating that dissolved Fe(II) is completely oxidized prior to inflow into a ditch. While the Fe oxidation rates reduce drastically from summer to winter, P concentrations remained high in the groundwater and an order of magnitude lower in the surface water throughout the year. This study shows very fast immobilization of dissolved P during the initial stage of the Fe(II) oxidation process which results in P-depleted water before Fe(II) is completely depleted. This cannot be explained by surface complexation of phosphate to freshly formed Fe-oxyhydroxides but indicates the formation of Fe(III)-phosphate precipitates. The formation of Fe(III)-phosphates at redox gradients seems an important geochemical mechanism in the transformation of dissolved phosphate to structural phosphate and, therefore, a major control on the P retention in natural waters that drain anaerobic aquifers.
Spatial and Temporal Variation of Japanese encephalitis Disease and Detection of Disease Hotspots: a Case Study of Gorakhpur District, Uttar Pradesh, India
Authors: Verma S. , Gupta R. D.
Published: November 2014

Abstract. In recent times, Japanese Encephalitis (JE) has emerged as a serious public health problem. In India, JE outbreaks were recently reported in Uttar Pradesh, Gorakhpur. The present study presents an approach to use GIS for analyzing the reported cases of JE in the Gorakhpur district based on spatial analysis to bring out the spatial and temporal dynamics of the JE epidemic. The study investigates spatiotemporal pattern of the occurrence of disease and detection of the JE hotspot. Spatial patterns of the JE disease can provide an understanding of geographical changes. Geospatial distribution of the JE disease outbreak is being investigated since 2005 in this study. The JE incidence data for the years 2005 to 2010 is used. The data is then geo-coded at block level. Spatial analysis is used to evaluate autocorrelation in JE distribution and to test the cases that are clustered or dispersed in space. The Inverse Distance Weighting interpolation technique is used to predict the pattern of JE incidence distribution prevalent across the study area. Moran's I Index (Moran's I) statistics is used to evaluate autocorrelation in spatial distribution. The Getis-Ord Gi*(d) is used to identify the disease areas. The results represent spatial disease patterns from 2005 to 2010, depicting spatially clustered patterns with significant differences between the blocks. It is observed that the blocks on the built up areas reported higher incidences.
Road Network Extraction from High Resolution Multispectral Satellite Imagery Based on Object Oriented Techniques
Authors: Kumar M. , Singh R. K. , Raju P. L. N. , Krishnamurthy Y. V. N.
Published: November 2014

Abstract. High Resolution satellite Imagery is an important source for road network extraction for urban road database creation, refinement and updating. However due to complexity of the scene in an urban environment, automated extraction of such features using various line and edge detection algorithms is limited. In this paper we present an integrated approach to extract road network from high resolution space imagery. The proposed approach begins with segmentation of the scene with Multi-resolution Object Oriented segmentation. This step focuses on exploiting both spatial and spectral information for the target feature extraction. The road regions are automatically identified using a soft fuzzy classifier based on a set of predefined membership functions. A number of shape descriptors are computed to reduce the misclassifications between road and other spectrally similar objects. The detected road segments are further refined using morphological operations to form final road network, which is then evaluated for its completeness, correctness and quality. The experiments were carried out of fused IKONOS 2 , Quick bird ,Worldview 2 Products with fused resolution’s ranging from 0.5m to 1 m. Results indicate that the proposed methodology is effective in extracting accurate road networks from high resolution imagery.
Application of Geo-Spatial Techniques for Precise Demarcation of Village/Panchayat Boundaries
Authors: Rao S. S. , Banu V. , Tiwari A. , Bahuguna S. , Uniyal S. , Chavan S. B. , Murthy M. V. R. , Arya V. S. , Nagaraja R. , Sharma J. R.
Published: November 2014

Abstract. In order to achieve the overall progress of the country with active and effective participation of all sections of society, the 12th Five Year Plan (FYP) would bring Panchayats centre-stage and achieve the inclusive growth agenda through inclusive governance. The concept of 'democratic decentralization' in the form of a three-tier administration was introduced in the name of "Panchayat Raj". Horizontally, it is a network of village Panchayats. Vertically, it is an organic growth of Panchayats rising up to national level. The Ministry of Panchayati Raj has three broad agenda: Empowerment, Enablement and Accountability. Space based Information Support for Decentralized Planning (SIS-DP) is one of the initiatives taken by Govt. of India with ISRO/DOS for generation and dissemination of spatial information for planning at the grass root level. The boundary layer for villages across different states/district/block is available with line departments. Most of these data exist at a much generalized scale. These boundaries do not overlay exactly with that of ground realities and may not be suitable for accurate analysis in terms of area, shape, position, etc. To deal with this problem, a strategy is adopted, which makes use of High Resolution Satellite Imagery (HRSI) from Indian Remote sensing satellites and cadastral maps at 1:4000 scale integrated with GIS techniques to enhance the accuracy of geo-spatial depiction of Village/Panchayat boundaries. Cadastral maps are used to depict the boundaries of land parcels and other features at the village level. These maps are registered to ortho products of HRSI using Ground Control Points. The cadastral maps are precisely overlaid on ortho-rectified HRSI and each parcel vertex is tagged with the real-world geographical coordinates. Village boundaries are extracted from the geo-referenced village cadastral maps. These boundaries are fine-tuned by considering under lap and overlap of neighboring villages and a mosaic is generated at the subdistrict and district level. Each village is coded with a unique number based on Ministry of Panchayati Raj and Census department codes. Villages are mapped to their respective Panchayat(s) directory and are dissolved in GIS environment based on code/nomenclature to obtain the final Gram Panchayat Layer. The present study attempts to showcase the methodology for deriving precise Village/Panchayat Boundaries using geo-spatial techniques. The final output will immensely help the Ministry of Panchayati Raj and Rural Development for implementing the developmental programs in tune with 73th and 74th constitutional amendments.
To examine the association between oscillations of the stratospheric aerosol layer peaks and different types of clouds
Authors: Mane P. B.
Published: November 2014

Abstract. Aerosol measurements have been carried out at Kolhapur (16°42′N, 74°14′E) by using newly designed Semiautomatic Twilight Photometer. The system is a ground based simple and inexpensive but very sensitive passive remote sensing technique. The altitudes of the Junge layer peaks on measurement days were derived from the aerosol vertical profiles. One attempt is made to examine the association between oscillations of the stratospheric aerosol layer peaks and different types of clouds. The values of AND for the Junge layer peaks for each observational day were also calculated. The graph between AND at peak point of Junge layer and day numbers was also studied in comparison with High, Medium and Low level clouds. There is an annual variation in the altitude of the peak of Junge layer also. Its maximum is observed during January. The annual variation of the altitude of the peak of Junge layer and the AND of Junge layer peak showed opposite phase relation.
Assessing Usefulness of High-Resolution Satellite Imagery (HRSI) for Re-Survey of Cadastral Maps
Authors: Rao S. S. , Sharma J. R. , Rajashekar S. S. , Rao D. S. P. , Arepalli A. , Arora V. ,   Kuldeep, Singh R. P. , Kanaparthi M.
Published: November 2014

Abstract. The Government of India has initiated “National Land Records Modernization Programme (NLRMP)” with emphasis to modernize management of land records, minimize scope of land/property disputes, enhance transparency in the land records maintenance system, and facilitate moving eventually towards guaranteed conclusive titles to immovable properties in the country. One of the major components of the programme is survey/re-survey and updating of all survey and settlement records including creation of original cadastral records wherever necessary. The use of ETS/GPS, Aerial or High Resolution Satellite Images (HRSI) and hybrid method of images are suggested for re-survey in the guidelines. The emerging new satellite technologies enabling earth observation at a spatial resolution of 1.0m or 0.5m or even 0.41m have brought revolutionary changes in the field of cadastral survey. The highresolution satellite imagery (HRSI) is showing its usefulness for cadastral surveys in terms of clear identification of parcel boundaries and other cultural features due to which traditional cadastre and land registration systems have been undergoing major changes worldwide. In the present research study, cadastral maps are derived from ETS/GPS, HRSI of 1.0m and 0.5m and used for comparison. The differences in areas, perimeter and position of parcels derived from HRSI are compared vis-a-vis ETS/GPS boundaries. An assessment has been made on the usefulness of HRSI for re-survey of cadastral maps vis-a-vis conventional ground survey.
Soil Moisture Model with Multi Angle and Multi Polarisation Risat-1 Data
Authors: Rao S. S. , Sahadevan D. K. , Wadodkar M. R. , Nagaraju M. S. S. , Chattaraj S. , Joseph W. , Rajankar P. , Sengupta T. , Venugopalan M. V. , Das S. N. , Joshi A. K. , Sharma J. R. , Amminedu E.
Published: November 2014

Abstract. Multi dimensional data (multi frequency, incident angle and polarisation) measurements of σ0 provided better estimates of soil moisture over those derived from single. This particular paper explains a new methodology for soil moisture estimation with the use of multi angle and multi polarisation RISAT-1 data. The roughness component was derived by correlating root mean square height with the differences of cross polarisation and like polarisation backscatter values (σ HV - σ HH) and differences of low and high incidence backscatter values (σ HH high (θ) - σ HH Low). The derived roughness was inputted to the modified dubois model (MDM). The results show both the σ HV - σ HH & σ HH high (θ) - σ HH Low are sensitive to roughness. The derived soil moisture using the MDM model is shows reasonable correlation with ground soil moisture.
A Novel Graph Based Fuzzy Clustering Technique For Unsupervised Classification Of Remote Sensing Images
Authors: Banerjee B. , Krishna Moohan B.
Published: November 2014

Abstract. This paper addresses the problem of unsupervised land-cover classification of multi-spectral remotely sensed images in the context of self-learning by exploring different graph based clustering techniques hierarchically. The only assumption used here is that the number of land-cover classes is known a priori. Object based image analysis paradigm which processes a given image at different levels, has emerged as a popular alternative to the pixel based approaches for remote sensing image segmentation considering the high spatial resolution of the images. A graph based fuzzy clustering technique is proposed here to obtain a better merging of an initially oversegmented image in the spectral domain compared to conventional clustering techniques. Instead of using Euclidean distance measure, the cumulative graph edge weight is used to find the distance between a pair of points to better cope with the topology of the feature space. In order to handle uncertainty in assigning class labels to pixels, which is not always a crisp allocation for remote sensing data, fuzzy set theoretic technique is incorporated to the graph based clustering. Minimum Spanning Tree (MST) based clustering technique is used to over-segment the image at the first level. Furthermore, considering that the spectral signature of different land-cover classes may overlap significantly, a self-learning based Maximum Likelihood (ML) classifier coupled with the Expectation Maximization (EM) based iterative unsupervised parameter retraining scheme is used to generate the final land-cover classification map. Results on two medium resolution images establish the superior performance of the proposed technique in comparison to the traditional fuzzy c-means clustering technique.
A Review On Accuracy and Uncertainty of Spatial Data and Analyses with special reference to Urban and Hydrological Modelling
Authors: Devendran A.A , Lakshmanan G.
Published: November 2014

Abstract. Data quality for GIS processing and analysis is becoming an increased concern due to the accelerated application of GIS technology for problem solving and decision making roles. Uncertainty in the geographic representation of the real world arises as these representations are incomplete. Identification of the sources of these uncertainties and the ways in which they operate in GIS based representations become crucial in any spatial data representation and geospatial analysis applied to any field of application. This paper reviews the articles on the various components of spatial data quality and various uncertainties inherent in them and special focus is paid to two fields of application such as Urban Simulation and Hydrological Modelling. Urban growth is a complicated process involving the spatio-temporal changes of all socio-economic and physical components at different scales. Cellular Automata (CA) model is one of the simulation models, which randomly selects potential cells for urbanisation and the transition rules evaluate the properties of the cell and its neighbour. Uncertainty arising from CA modelling is assessed mainly using sensitivity analysis including Monte Carlo simulation method. Likewise, the importance of hydrological uncertainty analysis has been emphasized in recent years and there is an urgent need to incorporate uncertainty estimation into water resources assessment procedures. The Soil and Water Assessment Tool (SWAT) is a continuous time watershed model to evaluate various impacts of land use management and climate on hydrology and water quality. Hydrological model uncertainties using SWAT model are dealt primarily by Generalized Likelihood Uncertainty Estimation (GLUE) method.
Sensor Simulation based Hyperspectral Image Enhancement with Minimal Spectral Distortion
Authors: Khandelwal A. , Rajan K. S.
Published: November 2014

Abstract. In the recent past, remotely sensed data with high spectral resolution has been made available and has been explored for various agricultural and geological applications. While these spectral signatures of the objects of interest provide important clues, the relatively poor spatial resolution of these hyperspectral images limits their utility and performance. In this context, hyperspectral image enhancement using multispectral data has been actively pursued to improve spatial resolution of such imageries and thus enhancing its use for classification and composition analysis in various applications. But, this also poses a challenge in terms of managing the trade-off between improved spatial detail and the distortion of spectral signatures in these fused outcomes. This paper proposes a strategy of using vector decomposition, as a model to transfer the spatial detail from relatively higher resolution data, in association with sensor simulation to generate a fused hyperspectral image while preserving the inter band spectral variability. The results of this approach demonstrates that the spectral separation between classes has been better captured and thus helped improve classification accuracies over mixed pixels of the original low resolution hyperspectral data. In addition, the quantitative analysis using a rank-correlation metric shows the appropriateness of the proposed method over the other known approaches with regard to preserving the spectral signatures.
Quality assessment of TanDEM-X DEMs using airborne LiDAR, photogrammetry and ICESat elevation data
Authors: Rao Y. S. , Deo R. , Nalini J. , Pillai A. M. , Muralikrishnan S. , Dadhwal V. K.
Published: November 2014

Abstract. TanDEM-X mission has been acquiring InSAR data to produce high resolution global DEM with greater vertical accuracy since 2010. In this study, TanDEM-X CoSSC data were processed to produce DEMs at 6 m spatial resolution for two test areas of India. The generated DEMs were compared with DEMs available from airborne LiDAR, photogrammetry, SRTM and ICESat elevation point data. The first test site is in Bihar state of India with almost flat terrain and sparse vegetation cover and the second test site is around Godavari river in Andhra Pradesh (A.P.) state of India with flat to moderate hilly terrain. The quality of the DEMs in these two test sites has been specified in terms of most widely used accuracy measures viz. mean, standard deviation, skew and RMSE. The TanDEM-X DEM over Bihar test area gives 5.0 m RMSE by taking airborne LiDAR data as reference. With ICESat elevation data available at 9000 point locations, RMSE of 5.9 m is obtained. Similarly, TanDEM-X DEM for Godavari area was compared with high resolution aerial photogrammetric DEM and SRTM DEM and found RMSE of 5.3 m and 7.5 m respectively. When compared with ICESat elevation data at several point location and also the same point locations of photogrammetric DEM and SRTM, the RMS errors are 4.1 m, 3.5 m and 4.3 m respectively. DEMs were also compared for open-pit coal mining area where elevation changes from -147 m to 189 m. X- and Y-profiles of all DEMs were also compared to see their trend and differences.
Utilisation of satellite data in identification of geomorphic landform and its role in arsenic release in groundwater
Authors: Singh R.  P. , Singh N. , Shashtri S. , Mukherjee S.
Published: November 2014

Abstract. The present study was conducted to explore the influence of geomorphic features of the area on the mobilization of arsenic in groundwater. In this study, remote sensing and GIS techniques were used to prepare the geomorphic and slope map of the area. Different geomorphic features were identified on the basis of spectral signature on the LISS III and Landsat satellite image and field survey. Groundwater samples were collected from each representative geomorphic feature to inspect the arsenic contamination in the area. The study area is drained by the Brahmaputra river and its tributaries and contain mainly fluvial geomorphic units especially older flood plain, palaeochannels, oxbow lakes, channel islands; and hilly areas at some of the places. In this study it was observed that enrichment of arsenic in groundwater varies along the geomorphic units in following trends Paleochannel> Younger alluvial plain> Active flood plain> channel island > dissected hills. The above trend shows that a higher concentration of arsenic is found in the groundwater samples collected from the fluvial landforms as compared to those collected from structural landforms. Brahmaputra River and its tributaries carry the sediment load from the Himalayan foothills, which get deposited in these features during the lateral shift of the river’s courses. Arsenic bearing minerals may get transported through river and deposit in the geomorphological features along with organic matter. The flat terrain of the area as seen from the slope map provides more residence time to water to infiltrate into the aquifer. The microbial degradation of organic matter generates the reducing environment and facilitates the dissolution of iron hydroxide thus releasing the adsorbed arsenic into the groundwater.
Species Discrimination of Mangroves using Derivative Spectral Analysis
Authors: Arun Prasad K. , Gnanappazham L.
Published: November 2014

Abstract. Mangroves are salt tolerant trees or shrubs commonly seen in mudflats of intertidal regions of tropical and subtropical coastlines. Recent advances in field spectroscopic techniques enabled the species level discrimination among closely related vegetation types. In this study we have analysed the laboratory spectroscopy data collected from eight species of Rhizophoraceaea family of mangroves. The spectral data ranges between the wavelength of 350 nm and 2500 nm at a very narrow bandwidth of 1 nm. Preprocessing techniques including smoothing were done on the spectra to remove the noise before compiling it to a spectral library. Derivative analysis of the spectra was done and its corresponding first and second derivatives were obtained. Statistical analysis such as parametric and non-parametric tests were implemented on the original processed spectra as well as their respective first and second order derivatives for the identification of significant bands for species discrimination. Results have shown that red edge region (680 nm – 720 nm) and water vapour absorption region around 1150 nm and 1400 nm are optimal as they were consistent in discriminating species in reflectance spectra as well as in its first and second derivative spectra. C. decandra species is found to be discriminable from other species while reflectance and its derivative spectra were used. Non-parametric statistical analysis gave better results than that of parametric statistical analysis especially in SWIR 2 spectral region (1831 nm – 2500 nm).
Improved adaptive Markov random field based super-resolution mapping for mangrove tree identification
Authors: Aghighi H. , Trinder J. , Lim S. , Tarabalka Y.
Published: November 2014

Abstract. Traditionally, forest tree crowns are extracted using airborne or spaceborne hyper-/multi-spectral remotely sensed images or pansharpened images. However, these medium/low spatial resolution images suffer from the mixed pixel problem, and the cost to collect very high resolution image collection is high. Moreover, existing feature extraction techniques cannot extract local patterns from medium/low resolution images. Therefore, super-resolution mapping (SRM) techniques, which generate land-cover maps with finer spatial resolution than the original remotely sensed image, can be beneficial for the extraction of forest trees. The SRM methods can improve the quality of information extraction by combining spectral information and spatial context into image classification problems. In this paper we have improved an adaptive Markov random field approach for super-resolution mapping (MRF-SRM) based on spatially adaptive MRF-SPM to overcome the limitation of equal covariance matrices assumption for all classes. We applied the developed method for mangrove tree identification from multispectral image recorded by QuickBird satellite, where we generated a super-resolution map with the panchromatic image spatial resolution of 0.6 m. Moreover, the performance of the proposed technique is evaluated by employing the simulated image with different covariance matrices for each class. Our experimental results have demonstrated that the new adaptive MRF-SRM method has increased the overall accuracy by 5.1% and the termination conditions of this method were satisfied three times faster when compared to the state-of-the-art methods.
Status and future transition of rapid urbanizing landscape in central Western Ghats - CA based approach
Authors: Bharath S.. , Rajan K.S. , Ramachandra T.V.
Published: November 2014

Abstract. The land use changes in forested landscape are highly complex and dynamic, affected by the natural, socio-economic, cultural, political and other factors. The remote sensing (RS) and geographical information system (GIS) techniques coupled with multi-criteria evaluation functions such as Markov-cellular automata (CA–Markov) model helps in analysing intensity, extent and future forecasting of human activities affecting the terrestrial biosphere. Karwar taluk of Central Western Ghats in Karnataka state, India has seen rapid transitions in its forest cover due to various anthropogenic activities, primarily driven by major industrial activities. A study based on Landsat and IRS derived data along with CA–Markov method has helped in characterizing the patterns and trends of land use changes over a period of 2004–2013, expected transitions was predicted for a set of scenarios through 2013-2022. The analysis reveals the loss of pristine forest cover from 75.51% to 67.36% (1973 to 2013) and increase in agriculture land as well as built-up area of 8.65% (2013), causing impact on local flora and fauna. The other factors driving these changes are the aggregated level of demand for land, local and regional effects of land use activities such as deforestation, improper practices in expansion of agriculture and infrastructure development, deteriorating natural resources availability. The spatio temporal models helped in visualizing on-going changes apart from prediction of likely changes. The CA-Markov based analysis provides us insights into the localized changes impacting these regions and can be useful in developing appropriate mitigation management approaches based on the modelled future impacts. This necessitates immediate measures for minimizing the future impacts.