bluuebunny/crossref_metadata_2025 huggingface dataset:
Estimation of regional mass anomalies from Gravity Recovery and Climate Experiment (GRACE) over Himalayan region
Authors: Agrawal R. , Singh S. K. , Rajawat A. S. ,   Ajai
Published: November 2014

Abstract. Time-variable gravity changes are caused by a combination of postglacial rebound, redistribution of water and snow/ice on land and as well as in the ocean. The Gravity Recovery and Climate Experiment (GRACE) satellite mission, launched in 2002, provides monthly average of the spherical harmonic co-efficient. These spherical harmonic co-efficient describe earth’s gravity field with a resolution of few hundred kilometers. Time-variability of gravity field represents the change in mass over regional level with accuracies in cm in terms of Water Equivalent Height (WEH). The WEH reflects the changes in the integrated vertically store water including snow cover, surface water, ground water and soil moisture at regional scale. GRACE data are also sensitive towards interior strain variation, surface uplift and surface subsidence cover over a large area. GRACE data was extracted over the three major Indian River basins, Indus, Ganga and Brahmaputra, in the Himalayas which are perennial source of fresh water throughout the year in Northern Indian Plain. Time series analysis of the GRACE data was carried out from 2003–2012 over the study area. Trends and amplitudes of the regional mass anomalies in the region were estimated using level 3 GRACE data product with a spatial resolution at 10 by 10 grid provided by Center for Space Research (CSR), University of Texas at Austin. Indus basin has shown a subtle decreasing trend from 2003–2012 however it was observed to be statistically insignificant at 95 % confidence level. Ganga and Brahmaputra basins have shown a clear decreasing trend in WEH which was also observed to be statistically significant. The trend analysis over Ganga and Brahamputra basins have shown an average annual change of −1.28 cm and −1.06 cm in terms of WEH whereas Indus basin has shown a slight annual change of −0.07 cm. This analysis will be helpful to understand the loss of mass in terms of WEH over Indian Himalayas and will be crucial for hydrological and climate applications at regional scale.
Groundwater suitability recharge zones modelling – A GIS application
Authors: Dabral S. , Bhatt B. , Joshi J.P. , Sharma N.
Published: November 2014

Abstract. Groundwater quality in Gujarat state is highly variable and due to multiplicity of factors viz. influenced by direct sea water encroachment, inherent sediment salinity, water logging, overexploitation leading to overall deterioration in ground water quality, coupled with domestic and industrial pollution etc. The groundwater scenario in the state is not very encouraging due to imbalance between recharge and groundwater exploitation. Further, the demand for water has increased manifold owing to agricultural, industrial and domestic requirement and this has led to water scarcity in many parts of the state, which is likely to become more severe in coming future due to both natural and manmade factors. Therefore, sustainable development of groundwater resource requires precise quantitative assessment based on reasonably valid scientific principles. Hence, delineation of groundwater potential zones (GWPZ), has acquired great significance. The present study focuses on the integrated Geospatial and Multi-Criteria Decision Making (MCDM) techniques to determine the most important contributing factors that affect the groundwater resources and also to delineate the potential zones for groundwater recharge. The multiple thematic layers of influencing parameters viz. geology, geomorphology, soil, slope, drainage density and land use, weightages were assigned to the each factor according to their relative importance as per subject experts opinion owing to the natural setup of the region. The Analytical Hierarchy Process (AHP) was applied to these factors and potential recharge zones were identified. The study area for the assessment of groundwater recharge potential zones is Mahi-Narmada inter-stream region of Gujarat state. The study shows that around 28 % region has the excellent suitability of the ground water recharge.
Simulation Of Surface runoff For Upper Tapi Subcatchment Area (Burhanpur Watershed) Using SWAT
Authors: Shivhare V. , Goel M. K. , Singh C. K.
Published: November 2014

Abstract. Water related activity that takes place in one part of a river basin may have consequence in the other part. Any plan related to inter basin transfer of water from a water surplus basin to a deficit basin has to take into account the water availability and demands under the present and future scenarios of water use. Watershed is a hydrologic unit where all stream exit from the common outlet. In the present study, Tapi subcatchment area (Burhanpur watershed) located in inter-state basin of Madhya Pradesh and Maharashtra, India, is selected for the estimation of surface runoff using SWAT model. The SWAT works in conjunction with Arc GIS 9.3. Various parameters Digital Elevation Model (DEM), slope derived from DEM, Landuse/Landcover (LULC) and NBSSLUP soil data and temporal data for temperature and precipitation was used as input for the model to predict runoff at the catchment outlet. The model was run from the year 1992 to 1997. The performance of the model in terms of simulated runoff was evaluated using statistical method and compared simulated monthly flow with the observed monthly flow values from 1992 to 1996 to a significant extent. The coefficient of determination (R2) for the monthly runoff values for 1992 to 1996 was observed to be 0.82, 0.68, 0.92, 0.69.
Potential of thermal emissivity for mapping of greenstone rocks and associated granitoids of Hutti Maski Schist belt, Karnataka
Authors: Guha A. , Vinod Kumar K.
Published: November 2014

Abstract. In the present study, different temperature-emissivity separation algorithms were used to derive emissivity images based on processing of ASTER( Advanced spaceborne thermal emission and reflection radiometer) thermal bands. These emissivity images have been compared with each other in terms of geological information for mapping of major rock types in Hutti Maski schist Belt and its associated granitoids. Thermal emissivity images are analyzed conjugately with thermal radiance image, radiant temperature image and albedo image of ASTER bands to understand the potential of thermal emissivity in delineating different rock types of Archaean Greenstone belt. The emissivity images derived using different emissivity extraction algorithms are characterised with poor data dimensionality and signal to noise ratio. Therefore, Inverse MNF false-colour composites(FCC) are derived using bands having better signal to noise(SNR)ratio to enhance the contrast in emissivity. It has been observed that inverse-MNF of emissivity image; which is derived using emissivity-normalisation method is suitable for delineating silica variations in granite and granodioritic gneiss in comparison to other inverse- MNF-emissivity composites derived using other emissivity extraction algorithms(reference channel and alpha residual method). Based on the analysis of ASTER derived emissivity spectra of each rocks, band ratios are derived(band 14/12,band 10/12) and these ratios are used to delineate the rock types based on index based FCC image. This FCC image can be used to delineate granitoids with different silica content. The geological information derived based on processing of ASTER thermal images are further compared with the image analysis products derived using ASTER visible-near-infrared(VNIR) and shortwave infrared(SWIR) bands. It has been observed that delineation of different mafic rocks or greenstone rocks(i.e. separation between chlorite schist and metabasalt) are better in SWIR composites and these composites also provide comparable results with thermal bands in terms of delineation of different types of granitoids.
Hyperspectral analysis of clay minerals
Authors: Janaki Rama Suresh G. , Sreenivas K. , Sivasamy R.
Published: November 2014

Abstract. A study was carried out by collecting soil samples from parts of Gwalior and Shivpuri district, Madhya Pradesh in order to assess the dominant clay mineral of these soils using hyperspectral data, as 0.4 to 2.5 μm spectral range provides abundant and unique information about many important earth-surface minerals. Understanding the spectral response along with the soil chemical properties can provide important clues for retrieval of mineralogical soil properties. The soil samples were collected based on stratified random sampling approach and dominant clay minerals were identified through XRD analysis. The absorption feature parameters like depth, width, area and asymmetry of the absorption peaks were derived from spectral profile of soil samples through DISPEC tool. The derived absorption feature parameters were used as inputs for modelling the dominant soil clay mineral present in the unknown samples using Random forest approach which resulted in kappa accuracy of 0.795. Besides, an attempt was made to classify the Hyperion data using Spectral Angle Mapper (SAM) algorithm with an overall accuracy of 68.43 %. Results showed that kaolinite was the dominant mineral present in the soils followed by montmorillonite in the study area.
Sub-pixel mineral mapping using EO-1 Hyperion hyperspectral data
Authors: Kumar C. , Shetty A. , Raval S. , Champatiray P. K. , Sharma R.
Published: November 2014

Abstract. This study describes the utility of Earth Observation (EO)-1 Hyperion data for sub-pixel mineral investigation using Mixture Tuned Target Constrained Interference Minimized Filter (MTTCIMF) algorithm in hostile mountainous terrain of Rajsamand district of Rajasthan, which hosts economic mineralization such as lead, zinc, and copper etc. The study encompasses pre-processing, data reduction, Pixel Purity Index (PPI) and endmember extraction from reflectance image of surface minerals such as illite, montmorillonite, phlogopite, dolomite and chlorite. These endmembers were then assessed with USGS mineral spectral library and lab spectra of rock samples collected from field for spectral inspection. Subsequently, MTTCIMF algorithm was implemented on processed image to obtain mineral distribution map of each detected mineral. A virtual verification method has been adopted to evaluate the classified image, which uses directly image information to evaluate the result and confirm the overall accuracy and kappa coefficient of 68 % and 0.6 respectively. The sub-pixel level mineral information with reasonable accuracy could be a valuable guide to geological and exploration community for expensive ground and/or lab experiments to discover economic deposits. Thus, the study demonstrates the feasibility of Hyperion data for sub-pixel mineral mapping using MTTCIMF algorithm with cost and time effective approach.
Semi-automated Technique to Extract Boundary of Valley/mountain Glaciers using Glacio-morphological Information from Digital Elevation Model
Authors: Chakraborty M. , Panigrahy S. , Kundu S.
Published: November 2014

Abstract. A semi automated technique has been developed to extract the spatial extension of valleys and mountain glaciers. The method is based on morphological properties of glaciated area extracted from Digital Elevation Model (DEM). Identification of glacial boundary based on spectral information from optical remote sensing imageries produces errors due to misclassification of debris-covered ablation area with surrounding rocky terrain and perennially snow-covered slope with debris free glaciated area. Elevation information DEM of Shuttle Radar Topography Mission (SRTM), CartoDEM and ASTER DEM have been used. A part of western Himalayas was selected as the study area that contains large glaciated basins, e.g., Bhagirathi, Baspa, Chandra basin. First order derivatives, slope aspect, and second order derivatives like, profile and plan curvatures are computed from the DEM. The derivatives are used to quantify and characterise the morphological aspects of the glaciated area and used in the decision rule models to generate the glacial boundaries. The ridge lines of the study areas are also generated from the plan curvature and used in the model to delineate the catchments areas of the glaciers. The slope based boundary is checked for consistency with the boundary from profile curvature and combined manually to generate the final glacier boundary. Area and length under the derived boundary of Gangotri glacier of Bhagirathi catchments are 90.25 sq km and 30.5 km. The result has been checked with high resolution optical data. This objective approach is important to delineate glaciated area, measure the length, width and area and generate glacial hypsometry, concentration factor of the glaciers. Accuracy of the result depends up on the quality of the DEM. DEM generated by SAR interferometric technique is found superior over DEM generated from other interpolation techniques.
Ice calving and deformation from Antarctic Ice margins using RISAT-1 circular polarization SAR data
Authors: Jayaprasad P. , Rajak D. R. , Singh R. K. , Oza S. R. , Sharma R. , Kumar R.
Published: November 2014

Abstract. In the present study, quantification of spatial and temporal changes has been carried out between Indian Antarctic Research station Bharati and Amery ice shelf by monitoring the ice margins using RISAT-1 Synthetic Aperture Radar (SAR) data. Spatio-temporal change detection was carried out by comparing the feature's geographic locations from geometrically rectified SAR data from RISAT-1 (Dec. 2013), Radarsat-2 (Feb. 2013), and Antarctic Mapping Mission products of Radarsat-1 (1997 & 2000). We report large scale disintegrations at two prominent glacier tongues namely Polar Record Glacier (PRG) and Polar Times Glacier(PTG). The results are verified against in-situ ground observations made during Summer period of 33rd ISEA (Dec. 2013–Feb. 2014) and MODIS images from NSIDC archive. Polar Record Glacier Tongue (PRGT) was drastically deformed by 135.8 km2 and Polar Times Glacier Tongue (PTGT) was partly calved by ~195.6 km2 and moved away by ~23 km especially between February and December 2013.
Analysing agricultural drought vulnerability at sub-district level through exposure, sensitivity and adaptive capacity based composite index
Authors: Murthy C. S. , Laxman B. , Sesha Sai M. V. R. , Diwakar P. G.
Published: November 2014

Abstract. Information on agricultural drought vulnerability status of different regions is extremely useful for implementation of long term drought management measures. A quantitative approach for measuring agricultural drought vulnerability at sub-district level was developed and implemented in the current study, which was carried-out in Andhra Pradesh state, India with the data of main cropping season i.e., kharif. The contributing indicators represent exposure, sensitivity and adaptive capacity components of vulnerability and were drawn from weather, soil, crop, irrigation and land holdings related data. After performing data normalisation and variance based weights generation, component wise composite indices were generated. Agricultural Drought Vulnerability Index (ADVI) was generated using the three component indices and beta distribution was fitted to it. Mandals (sub-district level administrative units) of the state were categorised into 5 classes – Less vulnerable, Moderately vulnerable, Vulnerable, Highly vulnerable and Very highly vulnerable. Districts dominant with vulnerable Mandals showed considerably larger variability of detrended yields of principal crops compared to the other districts, thus validating the index based vulnerability status. Current status of agricultural drought vulnerability in the state, based on ADVI, indicated that vulnerable to very highly vulnerable group of Mandals represent 54 % of total Mandals and about 55 % of the agricultural area and 65 % of the rainfed crop area. The variability in the agricultural drought vulnerability at disaggregated level was effectively captured by ADVI. The vulnerability status map is useful for diagnostic analysis and for formulating vulnerability reduction plans.
An ensemble classification approach for improved Land use/cover change detection
Authors: Chellasamy M. , Ferré T. P. A. , Humlekrog Greve M. , Larsen R. , Chinnasamy U.
Published: November 2014

Abstract. Change Detection (CD) methods based on post-classification comparison approaches are claimed to provide potentially reliable results. They are considered to be most obvious quantitative method in the analysis of Land Use Land Cover (LULC) changes which provides from - to change information. But, the performance of post-classification comparison approaches highly depends on the accuracy of classification of individual images used for comparison. Hence, we present a classification approach that produce accurate classified results which aids to obtain improved change detection results. Machine learning is a part of broader framework in change detection, where neural networks have drawn much attention. Neural network algorithms adaptively estimate continuous functions from input data without mathematical representation of output dependence on input. A common practice for classification is to use Multi-Layer-Perceptron (MLP) neural network with backpropogation learning algorithm for prediction. To increase the ability of learning and prediction, multiple inputs (spectral, texture, topography, and multi-temporal information) are generally stacked to incorporate diversity of information. On the other hand literatures claims backpropagation algorithm to exhibit weak and unstable learning in use of multiple inputs, while dealing with complex datasets characterized by mixed uncertainty levels. To address the problem of learning complex information, we propose an ensemble classification technique that incorporates multiple inputs for classification unlike traditional stacking of multiple input data. In this paper, we present an Endorsement Theory based ensemble classification that integrates multiple information, in terms of prediction probabilities, to produce final classification results. Three different input datasets are used in this study: spectral, texture and indices, from SPOT-4 multispectral imagery captured on 1998 and 2003. Each SPOT image is classified individually to produce the classified output and used for comparison. A MLP is trained with the input datasets separately using a backpropagation learning algorithm and prediction probabilities are produced for each pixel as evidence against each LU/LC class. An integration rule based on Endorsement Theory is applied to these multiple evidence by considering their individual contribution and the most probable class of a pixel is identified. Integration of the three datasets by the proposed method is found to produce 88.4 % and 84.6 % for individual image. The proposed method improves the potential of using SPOT satellite imagery for change detection.
Study of Discrimination Between Plantation and Dense Scrub Based on Backscattering Behavior of C Band SAR Data
Authors: Iyyappan M. , Ramakrishnan S. S. , Srinivasa Raju K.
Published: November 2014

Abstract. The study about on landuse and landcover classification using multi polarization and multi temporal C-band Synthetic Aperture Radar (SAR) data of recently launched multi-mode of RISAT-1 (Radar Imaging Satellite) by Indian Space Research Organization (ISRO) and European satellite, Envisat ASAR data. The backscattering coefficient were extracted for various land features from Cband SAR data. The training sample collecting from satellite optical imagery of study and field visit for verification. The training samples are used for the supervised classification technique of maximum Likelihood (ML) algorithms, Neural Network (NN) and Support Vector Machine (SVM) algorithms were applied for fourteen different polarizations combination of multi temporal and multiple polarizations. The previous study was carried only four band combination of RISAT 1 data, the continuation of work both SAR data were used in this study. The Classification results are verified with confusion matrix. The pixel based classification gives the good results in the dual polarization of CRS – HH and HV of RISAT −1 compared to dual polarization Envisat ASAR data. Meanwhile the quad Polarization combination of Envisat ASAR data got better classification accuracy. The SVM classifiers has given better classification results for all band combination followed by ML and NN. The Scrub are better identified in EnviSat ASAR – VV & VH Polarization and Plantation are better identified in EnviSat ASAR – HH, HH-HV & HV Polarization. The classification accuracy of both Scrub and Plantation is about 80 % in EnviSat ASAR – HH, VH & VV Polarization combination.
Spatio-temporal Assessment of Land Use/ Land Cover Dynamics and Urban Heat Island of Jaipur City using Satellite Data
Authors: Jalan S. , Sharma K.
Published: November 2014

Abstract. Urban Heat Island (UHI) refers to the phenomena of higher surface temperature occurring in urban areas as compared to the surrounding countryside attributable to urbanization. Spatio-temporal changes in UHI can be quantified through Land Surface Temperature (LST) derived from satellite imageries. Spatial variations in LST occur due to complexity of land surface – combination of impervious surface materials, vegetation, exposed soils as well as water surfaces. Jaipur city has observed rapid urbanization over the last decade. Due to rising population pressure the city has expanded considerably in areal extent and has also observed substantial land use/land cover (LULC) changes. The paper aims to determine changes in the LST and UHI phenomena for Jaipur city over the period from 2000 to 2011 and analyzes the spatial distribution and temporal variation of LST in context of changes in LULC. Landsat 7 ETM+ (2000) and Landsat 5 TM (2011) images of summer season have been used. Results reveal that Jaipur city has witnessed considerable growth in built up area at the cost of greener patches over the last decade, which has had clear impact on variation in LST. There has been an average rise of 2.99 °C in overall summer temperature. New suburbs of the city record 2° to 4 °C increase in LST. LST change is inversely related to change in vegetation cover and positively related to extent of built up area. The study concludes that UHI of Jaipur city has intensified and extended over new areas.
Entropy based determination of optimal principal components of Airborne Prism Experiment (APEX) imaging spectrometer data for improved land cover classification
Authors: Kallepalli A. , Kumar A. , Khoshelham K.
Published: November 2014

Abstract. Hyperspectral data finds applications in the domain of remote sensing. However, with the increase in amounts of information and advantages associated, come the "curse" of dimensionality and additional computational load. The question most often remains as to which subset of the data best represents the information in the imagery. The present work is an attempt to establish entropy, a statistical measure for quantifying uncertainty, as a formidable measure for determining the optimal number of principal components (PCs) for improved identification of land cover classes. Feature extraction from the Airborne Prism EXperiment (APEX) data was achieved utilizing Principal Component Analysis (PCA). However, determination of optimal number of PCs is vital as addition of computational load to the classification algorithm with no significant improvement in accuracy can be avoided. Considering the soft classification approach applied in this work, entropy results are to be analyzed. Comparison of these entropy measures with traditional accuracy assessment of the corresponding „hardened‟ outputs showed results in the affirmative of the objective. The present work concentrates on entropy being utilized for optimal feature extraction for pre-processing before further analysis, rather than the analysis of accuracy obtained from principal component analysis and possibilistic c-means classification. Results show that 7 PCs of the APEX dataset would be the optimal choice, as they show lower entropy and higher accuracy, along with better identification compared to other combinations while utilizing the APEX dataset.
Comparative analysis of RISAT-1 and simulated RADARSAT-2 hybrid polarimetric SAR data for different land features
Authors: Kumar V. , S Rao Y.
Published: November 2014

Abstract. The purpose of this study is to compare the performance of first hybrid polarimetric spaceborne satellite RISAT-1 data and simulated hybrid polarimetric data from quad-pol RADARSAT-2 data for different land use land cover (LULC) classes. The present study compares Stokes (g0, g1, g2 and g3) and its decomposed parameters (m, chi, delta and CPR) for satellite data acquired from RISAT- 1 and RADARSAT-2 over Vijayawada, Andhra Pradesh, India. Further, backscattering coefficients are also compared for different LULC types. The results indicate that both the satellites are following approximately the same trend for different classes except for settlements in RISAT-1.
DEM Construction using DInSAR
Authors: Mangla R. , Kumar S.
Published: November 2014

Abstract. A digital elevation model (DEM) is a 3D visualization of a terrain surface. It can be used in various analytical studies such as topographic feature extraction, hydrology, geomorphology and landslides analysis etc. Uttrakhand region is affected with landslides, earthquake and flash flood phenomenon. Hence this study was focused on DEM generation using Differential SAR Interferometry (DINSAR) on ALOS PALSAR dataset. Two Pass DINSAR technique involves one interferometric pair in addition with an external DEM. The external DEM was used as a reference to reduce topographic errors. The data processing steps were image co-registration, interferogram generation, interferogram flattening (Differential Interferogram), interferogram filtering, coherence map, phase unwrapping, orbital refinement and re-flattening and DEM generation. Interferogram fringes observed in forest areas were due to temporal decorrelation and the fringes in mountain regions were obtained due to topography changes (may be due to landslides in rainy season). The range of elevation in generated DEM were 132 m to 2823 m and Root Mean Square Error (RMSE) error was 36.765159 m. The generated DEM was compared with ASTER DEM and variation in height was analyzed. Atmospheric effects were not removed due to geometrical and temporal decorrelation which affect the accuracy.
Target detection algorithm for airborne thermal hyperspectral data
Authors: Marwaha R. , Kumar A. , Raju P. L. N. , Krishna Murthy Y. V. N.
Published: November 2014

Abstract. Airborne hyperspectral imaging is constantly being used for classification purpose. But airborne thermal hyperspectral image usually is a challenge for conventional classification approaches. The Telops Hyper-Cam sensor is an interferometer-based imaging system that helps in the spatial and spectral analysis of targets utilizing a single sensor. It is based on the technology of Fourier-transform which yields high spectral resolution and enables high accuracy radiometric calibration. The Hypercam instrument has 84 spectral bands in the 868 cm−1 to 1280 cm−1 region (7.8 μm to 11.5 μm), at a spectral resolution of 6 cm−1 (full-width-half-maximum) for LWIR (long wave infrared) range. Due to the Hughes effect, only a few classifiers are able to handle high dimensional classification task. MNF (Minimum Noise Fraction) rotation is a data dimensionality reducing approach to segregate noise in the data. In this, the component selection of minimum noise fraction (MNF) rotation transformation was analyzed in terms of classification accuracy using constrained energy minimization (CEM) algorithm as a classifier for Airborne thermal hyperspectral image and for the combination of airborne LWIR hyperspectral image and color digital photograph. On comparing the accuracy of all the classified images for airborne LWIR hyperspectral image and combination of Airborne LWIR hyperspectral image with colored digital photograph, it was found that accuracy was highest for MNF component equal to twenty. The accuracy increased by using the combination of airborne LWIR hyperspectral image with colored digital photograph instead of using LWIR data alone.
Land Cover Change Detection Using Object-Based Classification Technique: A Case Study Along The Kosi River, Bihar
Authors: Modi M. , Kumar R. , Ravi Shankar G. , Martha T.R.
Published: November 2014

Abstract. Land use/land cover (LULC) is dynamic in nature and can affect the ability of land to sustain human activities. The Indo-Gangetic plains of north Bihar in eastern India are prone to floods, which have a significant impact on land use / land cover, particularly agricultural lands and settlement areas. Satellite remote sensing techniques allow generating reliable and near-realtime information of LULC and have the potential to monitor these changes due to periodic flood. Automated methods such as object-based techniques have better potential to highlight changes through time series data analysis in comparison to pixel-based methods, since the former provides an opportunity to apply shape, context criteria in addition to spectral criteria to accurately characterise the changes. In this study, part of Kosi river flood plains in Supaul district, Bihar has been analysed to identify changes due to a flooding event in 2008. Object samples were collected from the post-flood image for a nearest neighbourhood (NN) classification in an object-based environment. Collection of sample were partially supported by the existing 2004–05 database. The feature space optimisation procedure was adopted to calculate an optimum feature combination (i.e. object property) that can provide highest classification accuracy. In the study, for classification of post-flood image, best class separation was obtained by using distance of 0.533 for 28 parameters out of 34. Results show that the Kosi flood has resulted in formation of sandy riverine areas.
Using logit model to identify the drivers of landuse landcover change in the Lower Gangetic Basin, India
Authors: Mondal I. , Srivastava V. K. , Roy P. S. , Talukdar G.
Published: November 2014

Abstract. The Lower Gangetic Basin is one of the most highly populated areas of India, covering an area of 286,899 km2 with a population density of 720 persons per km2. 64 % of the area is covered under agriculture which is supported by the highly fertile alluvial soil. Landuse and landcover (LULC) changes due to an ever increasing human population, natural disasters induced by climate change can alter agricultural productivity which in turn can affect the food security of the region. The current study found out the change in LULC over a span of 20 years (1985–2005), and identified the factors driving this change. LULC data was generated from geo-corrected satellite data of LANDSAT-MSS, IRS LISS-I and IRS LISS-III for pre monsoon and post monsoon seasons for the years 1985–86, 1994–95 and 2004–05 respectively, using onscreen visual interpretation at 1 : 250,000 scale. We used cross-tabulation matrix to investigate landuse and landcover transformation. The most significant transformation has been to built-up category, contributed by agricultural land (515 km2) and scrubland (53 km2). The other notable transformations are from agriculture to plantation (247 km2), fallow to scrubland (838 km2) and from water body to scrubland (407 km2). We generated change no-change matrix and analyzed it using logistic regression to investigate the drivers of LULC change. We identified availability of water for irrigation, literacy, sexratio and the availability of different sources of livelihoods, as the major drivers of LULC change in the Lower Gangetic Basin.
Monitoring land use with reference to aquaculture in Chinna Cherukuru village of Nellore district, Andhra Pradesh, India – A Remote Sensing and GIS Based Approach
Authors: Saxena M. R. , Ganguly K. , Sunder B. S. , Rani G. P. , Rao A. , Shankar G. R.
Published: November 2014

Abstract. The present study focuses on the dynamics of conversion of agricultural land to aquaculture over a decade from 1995 to 2013 in Chinna Cherukuru Village (Thotapalligudur Mandal) in Nellore District of Andhra Pradesh State, India. Multi temporal satellite data from 1995's medium resolution to high resolution IRS LISS IV & Cartosat of 2013 time frame was analysed and mapped using RS & GIS techniques to monitor the dynamics of land transformation from agriculture to aquaculture (1995's) and conversion back to agriculture in 2013. It was observed that, in 1995 aquaculture was practiced to an extent of 62.35 hectares which accounts to 9.48 % of the Total Geographic Area (TGA) of the village (658.01 hectares), whereas in 2001 there is a major conversion from agricultural land to aquaculture accounting to an extent of 237.01 hectares or 36.01 % of total village area . However, thereafter there was a significant conversion back to agriculture accounting to an extent of 27.23 hectares or 4.13 % of TGA in 2013. The study tries to understand the underlying reasons for conversion back to agriculture which were due to several factors that include outbreak of diseases in aquatic fauna, natural calamities, variation in production cost / selling cost and non-availability of infrastructure facilities like cold storages etc. The present village level study on LUCC database provides an answer key question about socio-economic issues, land use and cropping pattern which form important input for environmental management.
Comparative Analysis of Haar and Daubechies Wavelet for Hyper Spectral Image Classification
Authors: Sharif I. , Khare S.
Published: November 2014

Abstract. With the number of channels in the hundreds instead of in the tens Hyper spectral imagery possesses much richer spectral information than multispectral imagery. The increased dimensionality of such Hyper spectral data provides a challenge to the current technique for analyzing data. Conventional classification methods may not be useful without dimension reduction pre-processing. So dimension reduction has become a significant part of Hyper spectral image processing. This paper presents a comparative analysis of the efficacy of Haar and Daubechies wavelets for dimensionality reduction in achieving image classification. Spectral data reduction using Wavelet Decomposition could be useful because it preserves the distinction among spectral signatures. Daubechies wavelets optimally capture the polynomial trends while Haar wavelet is discontinuous and resembles a step function. The performance of these wavelets are compared in terms of classification accuracy and time complexity. This paper shows that wavelet reduction has more separate classes and yields better or comparable classification accuracy. In the context of the dimensionality reduction algorithm, it is found that the performance of classification of Daubechies wavelets is better as compared to Haar wavelet while Daubechies takes more time compare to Haar wavelet. The experimental results demonstrate the classification system consistently provides over 84% classification accuracy.
Road Detection from Remote Sensing Images using Impervious Surface Characteristics: Review and Implication
Authors: Singh P. P. , Garg R. D.
Published: November 2014

Abstract. The extraction of road network is an emerging area in information extraction from high-resolution satellite images (HRSI). It is also an interesting field that incorporates various tactics to achieve road network. The process of road detection from remote sensing images is quite complex, due to the presence of various noises. These noises could be the vehicles, crossing lines and toll bridges. Few small and large false road segments interrupt the extraction of road segments that happens due to the similar spectral behavior in heterogeneous objects. To achieve a better level of accuracy, numerous factors play their important role, such as spectral data of satellite sensor and the information related to land surface area. Therefore the interpretation varies on processing of images with different heuristic parameters. These parameters have tuned according to the road characteristics of the terrain in satellite images. There are several approaches proposed and implemented to extract the roads from HRSI comprising a single or hybrid method. This kind of hybrid approach has also improved the accuracy of road extraction in comparison to a single approach. Some characteristics related to impervious and non-impervious surfaces are used as salient features that help to improve the extraction of road area only in the correct manner. These characteristics also used to utilize the spatial, spectral and texture features to increase the accuracy of classified results. Therefore, aforesaid characteristics have been utilized in combination of road spectral properties to extract road network only with improved accuracy. This evaluated road network is quite accurate with the help of these defined methodologies.
Urban Mapping and Growth Prediction using Remote Sensing and GIS Techniques, Pune, India
Authors: Sivakumar V.
Published: November 2014

Abstract. This study aims to map the urban area in and around Pune region between the year 1991 and 2010, and predict its probable future growth using remote sensing and GIS techniques. The Landsat TM and ETM+ satellite images of 1991, 2001 and 2010 were used for analyzing urban land use class. Urban class was extracted / mapped using supervised classification technique with maximum likelihood classifier. The accuracy assessment was carried out for classified maps. The achieved overall accuracy and Kappa statistics were 86.33 % & 0.76 respectively. Transition probability matrix and area change were obtained using different classified images. A plug-in was developed in QGIS software (open source) based on Markov Chain model algorithm for predicting probable urban growth for the future year 2021. Based on available data set, the result shows that urban area is expected to grow much higher in the year 2021 when compared to 2010. This study provides an insight into understanding of urban growth and aids in subsequent infrastructure planning, management and decision-making.
Interpretative modelling of a geological cross section from boreholes: sources of uncertainty and their quantification
Authors: Lark R. M. , Thorpe S. , Kessler H. , Mathers S. J.
Published: November 2014

Abstract. We conducted a designed experiment to quantify sources of uncertainty in geologists' interpretations of a geological cross section. A group of 28 geologists participated in the experiment. Each interpreted borehole record included up to three Palaeogene bedrock units, including the target unit for the experiment: the London Clay. The set of boreholes was divided into batches from which validation boreholes had been withheld; as a result, we obtained 129 point comparisons between the interpreted elevation of the base of the London Clay and its observed elevation in a borehole not used for that particular interpretation. Analysis of the results showed good general agreement between the observed and interpreted elevations, with no evidence of systematic bias. Between-site variation of the interpretation error was spatially correlated, and the variance appeared to be stationary. The between-geologist component of variance was smaller overall, and depended on the distance to the nearest borehole. There was also evidence that the between-geologist variance depends on the degree of experience of the individual. We used the statistical model of interpretation error to compute confidence intervals for any one interpretation of the base of the London Clay on the cross section, and to provide uncertainty measures for decision support in a hypothetical route-planning process. The statistical model could also be used to quantify error propagation in a full 3-D geological model produced from interpreted cross sections.
Espaço livre urbano como instrumento de sustentabilidade integral e educação ambiental crítica: metodologia multidisciplinar no projeto para o Parque Municipal Marista, vila velha, Espírito Santo
Authors: Fiorotti Marcelo Seidel , Alvarez Cristina Engel , Vargas Paulo Sérgio De Paula , Vieira Jociane Florencio , Fracalossi Raissa Panetto
Published: November 2014

Este artigo aborda a importância da sustentabilidade e da educação no planejamento do espaço livre urbano. Discute uma noção mais abrangente de sustentabilidade, que inclui as dimensões cultural, ambiental, social e econômica, e uma modalidade de educação ambiental crítica, voltada para o desenvolvimento sustentável. Apresenta o projeto do Parque Municipal Marista, desenvolvido para o município de Vila Velha, localizado na Região Metropolitana da Grande Vitória (ES), Brasil, com objetivo de abordar a proteção da biodiversidade, com foco na Mata Atlântica e na mineração, e a espiritualidade-corporeidade do ser humano. A partir do desafio posto pelo plano conceitual, um processo metodológico foi delineado, no sentido de viabilizar a gênese do projeto de arquitetura e paisagismo, diferenciando-se pelo seu enfoque multidisciplinar, didático e participativo. Os resultados do projeto foram desenvolvidos no sentido de estruturar o Parque para estimular um novo olhar sobre a cidade.
Sistema Eletrônico de Revistas da UFPR
Authors: Duarte Freitas Maria do Carmo
Published: November 2014

Sistema Eletrônico de Revistas da UFPR
Temporal evolution of litterfall and potential bio-element return in a successional forest sequence of the Espinal Ecoregion, Argentina
Authors: Mendoza Carlos A. , Gallardo Lancho Juan F. , Aceñolaza Pablo G. , Turrion Maria-Belen , Pando Valentin
Published: November 2014

Aim of study: The aim of this work was to assess the litterfall contribution and the return of bioelements of a successional forest sequence from the Mesopotamian Espinal (Argentina) which was associated with livestock production.Area of study: Mesopotamian Espinal, Argentina.Material and methods: Litterfall samples were taken and a chemical characterization of their fractions was determined in three stages: a) in the initial successional stage (IF); b) in an intermediate secondary forest (SF); and c) in a mature forest (MF).Main results: The litterfall contribution of the three forests was 1140 ±98, 2947 ±154, and 2911 ±57 kg DM ha-1 yr-1; respectively. The IF showed a seasonal pattern of contribution with a peak occurring during summer (528 ±85 kg DM ha-1 yr-1), then decreasing during autumn, winter, and spring (241 ±30, 165 ±27, and 207 ±29 kg DM ha-1 season-1,respectively). The SF showed a rather constant seasonal pattern (about 750 kg DM season-1). The MF showed significant differences among seasons, the maximum and minimum contributions ranging between 846 ±29 and 598 ±33 kg DM ha-1 season-1 in summer and spring, respectively. The litterfall leaves/branch ratio decreased as ecological succession advanced, being lower as the forest gets more mature. As a consequence, this ratio can be used as an indicator of maturity in the sequence. The potential return of bio-elements of the successional forest sequence was proportional to the litterfall input, with a maximum amount of N in the Fabaceae species. Research highlights: The litterfall assessment and the leaves/branch ratio allowed the characterization of the successional stages in Xerophytic forest used for livestock production. Keywords: Semi-xerophytic trees; tree production pattern; plant organ contribution; leaf/branch ratio; return of bio-elements; tree nutrients.
Transferability of microsatellite markers located in candidate genes for wood properties between Eucalyptus species
Authors: Acuña Cintia V. , Villalba Pamela , Hopp H. Esteban , Marcucci Poltri Susana N.
Published: November 2014

Aim of study:  To analyze the feasibility of extrapolating conclusions on wood quality genetic control between different Eucalyptus species, particularly from species with better genomic information, to those less characterized. For this purpose, the first step is to analyze the conservation and cross-transferability of microsatellites markers (SSRs) located in candidate genes.Area of study: Eucalyptus species implanted in Argentina coming from different Australian origins.Materials and methods: Twelve validated and polymorphic SSRs in candidate genes (SSR-CGs) for wood quality in E. globulus were selected for cross species amplification in six species: E. grandis, E. saligna, E. dunnii, E. viminalis, E. camaldulensis and E. tereticornis.Main results: High cross-species transferability (92% to 100%) was found for the 12 polymorphic SSRs detected in E. globulus. These markers revealed allelic diversity in nine important candidate genes: cinnamoyl CoA reductase (CCR), cellulose synthase 3 (CesA3), the transcription factor LIM1, homocysteine S-methyltransferase (HMT), shikimate kinase (SK), xyloglucan endotransglycosylase 2 (XTH2), glutathione S-transferase (GST), glutamate decarboxylase (GAD) and peroxidase (PER).Research highlights: The markers described are potentially suitable for comparative QTL mapping, molecular marker assisted breeding (MAB) and for population genetic studies across different species within the subgenus Symphyomyrtus.Keywords: validation; cross-transferability; SSR; functional markers; eucalypts; Symphyomyrtus.
Long-term development of nursing mixtures of Sitka spruce and larch species in an experiment in northern Scotland
Authors: Mason William L.
Published: November 2014

Aim of the study: An experiment was established in 1966 to compare the growth and development of 50: 50 mixtures of Sitka spruce (Picea sitchensis) with either Japanese larch (Larix kaempferi) or tamarack (L. laricina) with that found in pure plots of Sitka spruce. The site was one of moderate nitrogen availability where the presence of heather (Calluna vulgaris) could be expected to limit the growth ofSitka spruce.Area of the study: North-east Scotland.Material and methods: There were different patterns of spruce growth in the pure plots and in the mixtures, with faster spruce growth in mixture in the years approaching and immediately following canopy closure (i.e. ages 15-25). Foliage analysis suggested that this was linked with improved nitrogen status of spruce trees in the mixed compared to the pure plots.Main results: At years 20 and 25 there were significant differences in height, diameter, and basal area between treatments, with the largest basal area being found in the Japanese larch/Sitka spruce mixtures, indicative of overyielding in the mixed plots. However, when the experiment was clearfelled at 41 years of age, all treatments had self-thinned to produce spruce dominated stands of similar height with only an occasional larch tree surviving in plots that were originally 50:50 mixtures.Research highlights: There were no differences between treatments in basal area, harvested volume or sawlog outturn after 41 years. These results can be interpreted as showing facilitation between the larch and the spruce during the establishment phase followed by competition for light once canopy closure had occurred.Keywords: Mixed stand dynamics; facilitation; nitrogen status; product outturn.