bluuebunny/crossref_metadata_2025 huggingface dataset:
Increase in soil organic carbon by agricultural intensification in northern China
Authors: Liao Y. , Wu W. L. , Meng F. Q. , Smith P. , Lal R.
Published: November 2014

Abstract. Agricultural intensification has contributed greatly to the sustained food supply of China's 1.3 billion population over the 30 year period during 1982–2011. Intensification has several and widely recognized negative environmental impacts including depletion of water resources, pollution of water bodies, greenhouse gas emissions and soil acidification. However, there have been few studies over this period on the impacts of intensification on soil organic carbon (SOC) at the regional level. The present study was conducted in Huantai county, a typical intensive farming region in Northern China, to analyze the temporal dynamics of SOC influenced by climate and farming practices. The results indicate that from 1982 to 2011, SOC content and stock in the 0–20 cm layer of the cropland increased from 7.8 ± 1.6 to 11.0 ± 2.3 g kg–1 (41%) and 21 ± 4.3 to 33.0 ± 7.0 Mg ha–1 (54%), respectively. The SOC stock (0–20 cm) of the farmland for the entire county increased from 0.75 to 1.2 Tg (59%). Correlation analysis revealed that incorporation of crop residues significantly increased SOC, while increase in the mean annual temperature decreased the SOC level. Therefore, agricultural intensification has increased crop productivity and contributed to SOC sequestration in Northern China. In the near future, more appropriate technologies and practices must be developed and implemented for a maintenance or enhancement of SOC in this region and elsewhere in Northern China, that also reduce non-CO2 greenhouse gas emissions, since the climate benefit from the additional SOC storage is estimated to be smaller than the negative climate impacts of N2O from N fertilizer additions.
Effect of meteorological forcing and snow model complexity on hydrological simulations in the Sieber catchment (Harz Mountains, Germany)
Authors: Förster K. , Meon G. , Marke T. , Strasser U.
Published: November 2014

Abstract. Detailed physically based snow models using energy balance approaches are spatially and temporally transferable and hence regarded as particularly suited for scenario applications including changing climate or land use. However, these snow models place high demands on meteorological input data at the model scale. Besides precipitation and temperature, time series of humidity, wind speed, and radiation have to be provided. In many catchments these time series are rarely available or provided by a few meteorological stations only. This study analyzes the effect of improved meteorological input on the results of four snow models with different complexity for the Sieber catchment (44.4 km2) in the Harz Mountains, Germany. The Weather Research and Forecast model (WRF) is applied to derive spatial and temporal fields of meteorological surface variables at hourly temporal resolution for a regular grid of 1.1 km × 1.1 km. All snow models are evaluated at the point and the catchment scale. For catchment-scale simulations, all snow models were integrated into the hydrological modeling system PANTA RHEI. The model results achieved with a simple temperature-index model using observed precipitation and temperature time series as input are compared to those achieved with WRF input. Due to a mismatch between modeled and observed precipitation, the observed melt runoff as provided by a snow lysimeter and the observed streamflow are better reproduced by application of observed meteorological input data. In total, precipitation is simulated statistically reasonably at the seasonal scale but some single precipitation events are not captured by the WRF data set. Regarding the model efficiencies achieved for all simulations using WRF data, energy balance approaches generally perform similarly compared to the temperature-index approach and partially outperform the latter.
Monitoring seasonal progress of rice stubble burning in major rice growing districts of Haryana, India, using multidate AWiFS data
Authors: Yadav M. , Prawasi R. , Jangra S. , Rana P. , Kumari K. , Lal S. , Jakhar K. , Sharma S. , Hooda R. S.
Published: November 2014

Abstract. The present paper describes the methodology and results of assessment of seasonal progress of rice stubble burning for 10 major rice growing districts of Haryana state in India. These 10 districts contribute about 84 per cent of total rice area of the state. As the rice fields are immediately required to be vacated for the sowing of next crop the farmers opt for mechanized harvesting and easy way out of burning the stubbles in the field. Such burning result in release of polluting gases and aerosols. Besides, the heating of the soil kills the useful micro-flora of the soil causing soil degradation. Multi-date AWiFS data from Resourcesat 1 and 2 satellites acquired between October 16, 2013 to November 26, 2013 were used for estimating paddy stubble burning areas at different intervals for the year 2013 crop growing season. In season collected ground truth data using hand held GPS along with field photographs were used to identify paddy stubble burning areas and other land features. Complete enumeration approach and Iterative Self-organizing Data Analysis Technique (ISODATA) unsupervised classifier was used for digital analysis. Normalized Difference Vegetation Index (NDVI) of each date was also used with other spectral bands of temporal images. To improve the classification accuracy the non-agricultural areas were masked out. The area was estimated by computing pixels under the classified image mask. Progress of paddy stubble burning was estimated at different intervals for the year 2013 using available cloud free multi-date IRS-P6 AWiFS data to identify the crucial period when stubbles burning takes place in major area so that preventive measures can be taken to curb the menace.
A COMPARATIVE STUDY ON UTILIZATION OF MULTI-SENSOR SATELLITE DATA TO DETECT POTENTIAL FISHING ZONE (PFZ)
Authors: Balaguru B. , Ramakrishnan S. S. , Vidhya R. , Thanabalan T.
Published: November 2014

Abstract. The satellite oceanography reveals the rolls on Potential Fishing Zone (PFZ) advisories in India is limited by the availability of the satellite data during the cloudy days and for the cloudy areas, because of the inability of the passive sensors to pass through the clouds. However, there is a huge demand from the fishermen community to provide PFZ advisories on cloudy days / monsoon period also as the period corresponds to the peak fishing season. Keeping in view of the demand and availability of the optimally interpolated merged product from Altimetry, it is proposed to utilize 4 km SST product obtained from the AVHRR. In view of this, a comparative analysis has been carried out on the feasibility of utilization of the Altimetry product for identification of PFZ Advisories. The analysis is carried out the synergize study on existing in AVHRR SST product are really matching with the high resolution EKE and SSHA products derived from Altimetry. From the analysis it was found that the Altimetry product is suitable for identifying cold core generation of waters for PFZ advisories with certain limitations. Also persistence of the ocean color environmental variables is cross-verified with catch weight observed from In-situ observation. The overall analysis derived from ocean color and altimetry products for delineating potential fishing zones enhance flawless information for future research.
Inland Water Bodies Monitoring using Satellite Altimetry over Indian Region
Authors: Chander S. , Ganguly D. , Dubey A. K. , Gupta P. K. , Singh R. P. , Chauhan P.
Published: November 2014

Abstract. Satellite altimetry for inland water applications has evolved from investigation of water height retrieval to monitoring since last two decades. Altimetry derived reservoir/ river levels can subsequently be used to deal with key inland water resources problems such as flood, rating curve generation for remote locations, reservoir operations, and calibration of river/lake models. In this work 29 inland water bodies were selected over Indian region to monitor from satellite altimetry. First cut selection of potential water bodies was based on availability of altimeter tracks and geographic locations. Then feasibility study was carried out to check the potential of availability of in-situ measurement and scope of GPS survey for final selection. An algorithm is proposed and tested for the waterlevel retrieval over the Ukai Reservoir which fulfil all the necessary requirements. The methodology is based on averaged high rate waveforms, modified retracker and range corrections. The results were then validated with the GPS survey and in-situ tide gauge dataset. SARAL derived water-level information for six different retrackers were compared with the in-situ tide-gauge dataset installed close to the Ukai Dam. Averaged high rate waveforms were analysed for better performance, i.e. single 40 Hz, and multiple 40-Hz. A field trip was conducted on 17th January 2014, same day on the SARAL pass, using two Dual frequency GPS instruments. New improved retracker work best with overall RMSE within the range of 8 cm. The results supports that AltiKa dataset can be utilized for more accurate water level information over inland water bodies.
Coastal Sediment Monitoring by Spectral Analysis
Authors: Muttitanon W.
Published: November 2014

Abstract. Water monitoring is important to environment control and ecosystem studies which not only scientifically relevant but also legally binding in several countries. Suspended sediment concentration is one of the main parameters for the water monitoring and can be roughly detected from satellite. In the present study, the Chao Phraya River mouth was used as a case study to assess the suspended measuring using water quality index with Landsat TM imagery. A turbidity map was obtain by applying band math and convert to turbidity backscattering. This solution can be used for water quality index and applying with all satellite data.
Assessment of OSCAT winds for coastal circulation on the north western continental shelf of India
Authors: Salim M. , Nagendra K. , Bansal S. , Nayak R. K. , Rao M. S. , Sasmal S. K. , Dutt C. B. S. , Rao K. H. , Dadhwal V. K.
Published: November 2014

Abstract. Winds and tides are the major driving forces of the circulation in the coastal and marginal seas. Data Interpolating Variation Analysis (DIVA) method is used to generate spatial and time series data of sea surface winds for the period 2010–2013 at daily time scale from the OSCAT observations. Validity and consistency of the data were examined against the in situ observations and ECMWF re-analysis at different time scales. Amplitude of semi-annual cycle of OSCAT winds in the coastal domain is 30 % larger than the ECMWF winds while the amplitude of annual cycle of OSCAT winds is 20 % smaller than the ECMWF winds. On the open oceans, intensity of respective semi-annual cycles are mostly similar while annual cycle of OSCAT wind is 20 % smaller than the ECMWF winds. Wind driven currents over the western continental shelf of India were simulated by forcing OSCAT and ECMWF winds to a coastal circulation model. It is observed that the mean seasonal circulations from both the simulations are identical spatial pattern however the magnitude of simulated currents based on OSCAT winds are much stronger than ECMWF wind forcing. These currents used in a lagrangian tracer transport code to model the oil-spill events occurred in this region. It revealed that OSCAT based ocean currents has performed better in simulating the trajectory than the ECMWF wind driven currents.
Automatic Image Registration Using Free and Open Source Software
Authors: Giri Babu D. , Raja Shekhar S. S. , Chandrasekar K. , Sesha Sai M. V. R. , Diwakar P. G. , Dadhwal V. K.
Published: November 2014

Abstract. Image registration is the most critical operation in remote sensing applications to enable location based referencing and analysis of earth features. This is the first step for any process involving identification, time series analysis or change detection using a large set of imagery over a region. Most of the reliable procedures involve time consuming and laborious manual methods of finding the corresponding matching features of the input image with respect to reference. Also the process, as it involves human interaction, does not converge with multiple operations at different times. Automated procedures rely on accurately determining the matching locations or points from both the images under comparison and the procedures are robust and consistent over time. Different algorithms are available to achieve this, based on pattern recognition, feature based detection, similarity techniques etc. In the present study and implementation, Correlation based methods have been used with a improvement over newly developed technique of identifying and pruning the false points of match. Free and Open Source Software (FOSS) have been used to develop the methodology to reach a wider audience, without any dependency on COTS (Commercially off the shelf) software. Standard deviation from foci of the ellipse of correlated points, is a statistical means of ensuring the best match of the points of interest based on both intensity values and location correspondence. The methodology is developed and standardised by enhancements to meet the registration requirements of remote sensing imagery. Results have shown a performance improvement, nearly matching the visual techniques and have been implemented in remote sensing operational projects. The main advantage of the proposed methodology is its viability in production mode environment. This paper also shows that the visualization capabilities of MapWinGIS, GDAL’s image handling abilities and OSSIM’s correlation facility can be efficiently integrated to effectively use in remote sensing based production environment.
Web based geoprocessing tool for coverage data handling
Authors: Kumar K. , Saran S.
Published: November 2014

Abstract. With the advancements in GIS technologies and extensive use of OGC Web Services, geospatial resources and services are becoming progressively copious and convenient over the network. The application of OGC WCS (Web Coverage Service) and WFS (Web Feature Service) standards for geospatial raster and vector data has resulted in an opulent pool of interoperable geodata resources waiting to be used for analytical or modelling purposes. The issue of availing geospatial data processing with the aid of standardised web services was attended to by the OGC WPS (Web Processing Service) 1.0.0 specifications (Schut, 2007) which elucidate WPS as a standard interface which serves for the promulgation of geo-processes and consumption of those processes by the clients. This paper outlines the design and implementation of a geo-processing tool utilizing coverage data. The geo-process selected for application is the calculation of Normalized Difference Vegetative Index (NDVI), one of the globally used indices for vegetation cover monitoring. The system is realised using the Geospatial Data Abstraction Library (GDAL) and Python. The tool accesses the WCS server using the parameters defined in the XML request. The geo-process upon execution, performs the computations over the coverage data and generates the NDVI output. Since open source technology and standards are being used more often, especially in the field of scientific research, so our implementation is also built by using open source tools only.
Space Based Information Support for Decentralised Planning (SIS-DP)-A case study in Balangir District,Odisha, India
Authors: Kumar P. , Dash S. K. , Thakur R. R. , Jonna S. , Tripathi S.
Published: November 2014

Abstract. The state government is now focusing on decentralized planning and created administrative infrastructure for Gram Panchayat (Village Community) level planning in participatory way. The people are now opening up and started taking part in planning process at grass root level. In order to involve the people and make planning exercise more effective, National Remote Sensing Centre(ISRO), Dept. of Space(DOS) have begun activities using GIS and Communication Technology(Geo-Ict). Considering the potential of Geo-Ict a project titled "Space Based Information Support for Decentralized Planning (SIS-DP)" was launched by NRSC/ISRO under PC-NNRMS, DOS, Govt. of India. Odisha Space Applications Centre as a partner institution, have ful-filled the commitment of generating thematic information on 1 : 10 K from High resolution satellite data (Ortho-Rectified Cartosat-1 & LISS-IV data) for the state of Odisha. Thematic information on Land use, Settlements, Infrastructure and drainage have been generated and started dissemination to the users. The attribute information available from line department have also been linked to spatial framework of the SIS-DP layers. In the present study Bolangir, a drought prone and backward district is taken up. Total 285 thematic maps have been prepared at Gram Panchayat level keeping a buffer of 1.5 km to locally adjust any discrepancies in the boundary. User workshop and awareness campaigns were conducted and feed backs have been collected on Land Utilization Types (LUT). It is felt that extension of these services to the entire State have a strong bearing on improved strategy and planning process by the State.
Quality Metrics of Semi Automatic DTM from Large Format Digital Camera
Authors: Narendran J. , Srinivas P. , Udayalakshmi M. , Muralikrishnan S.
Published: November 2014

Abstract. The high resolution digital images from Ultracam-D Large Format Digital Camera (LFDC) was used for near automatic DTM generation. In the past, manual method for DTM generation was used which are time consuming and labour intensive. In this study LFDC in synergy with accurate position and orientation system and processes like image matching algorithms, distributed processing and filtering techniques for near automatic DTM generation. Traditionally the DTM accuracy is reported using check points collected from the field which are limited in number, time consuming and costly. This paper discusses the reliability of near automatic DTM generated from Ultracam-D for an operational project covering an area of nearly 600 Sq. Km. using 21,000 check points captured stereoscopically by experienced operators. The reliability of the DTM for the three study areas with different morphology is presented using large number of stereo check points and parameters related to statistical distribution of residuals such as skewness, kurtosis, standard deviation and linear error at 90% confidence interval. The residuals obtained for the three areas follow normal distribution in agreement with the majority of standards on positional accuracy. The quality metrics in terms of reliability were computed for the DTMs generated and the tables and graphs show the potential of Ultracam-D for the generation of semiautomatic DTM process for different terrain types.
Cadastral Resurvey using High Resolution Satellite Ortho Image - challenges: A case study in Odisha, India
Authors: Parida P. K , Sanabada M. K. , Tripathi S.
Published: November 2014

Abstract. Advancements in satellite sensor technology enabling capturing of geometrically accurate images of earth's surface coupled with DGPS/ETS and GIS technology holds the capability of large scale mapping of land resources at cadastral level. High Resolution Satellite Images depict field bunds distinctly. Thus plot parcels are to be delineated from cloud free ortho-images and obscured/difficult areas are to be surveyed using DGPS and ETS. The vector datasets thus derived through RS/DGPS/ETS survey are to be integrated in GIS environment to generate the base cadastral vector datasets for further settlement/title confirmation activities. The objective of this paper is to illustrate the efficacy of a hybrid methodology employed in Pitambarpur Sasana village under Digapahandi Tahasil of Ganjam district, as a pilot project, particularly in Odisha scenario where the land parcel size is very small. One of the significant observations of the study is matching of Cadastral map area i.e. 315.454 Acres, the image map area i.e. 314.887 Acres and RoR area i.e. 313.815 Acre. It was revealed that 79 % of plots derived by high-tech survey method show acceptable level of accuracy despite the fact that the mode of area measurement by ground and automated method has significant variability. The variations are more in case of Government lands, Temple/Trust lands, Common Property Resources and plots near to river/nalas etc. The study indicates that the adopted technology can be extended to other districts and cadastral resurvey and updating work can be done for larger areas of the country using this methodology.
Assessment of coastal erosion along Indian coast on 1 : 25, 000 scaleusing satellite data
Authors: Rajawat A. S. , Chauhan H. B. , Ratheesh R. , Rhode S. , Bhanderi R. J. , Mahapatra M. , Kumar M. , Yadav R. , Abraham S. P. , Singh S. S. , Keshri K. N. ,   Ajai
Published: November 2014

Abstract. The long stretch of coastline on the either side of Indian peninsula is subjected to varied coastal processes and anthropogenic pressures, which makes the coast vulnerable to erosion. There is no systematic inventory of shoreline changes occurring along the entire Indian coast on 1:25, 000 scale, which is required for planning measures to be taken up for protecting the coast at national level. It is in this context that shoreline change mapping on 1:25, 000 scale for the entire Indian coast based on multidate satellite data in GIS environment has been carried out for 1989–91 and 2004–06 time frame. The paper discusses salient observations and results from the shoreline change inventory. The results show that 3829 km (45.5 %) of the coast is under erosion, 3004 km (35.7 %) of the coast is getting accreted, while 1581 km (18.8 %) of the coast is more or less stable in nature. Highest percentage of the shoreline under erosion is in Nicobar Islands (88.7 %), while percentage of accreting coastline is highest for Tamil Nadu (62.3 %) and the state of Goa has highest percentage of stable shoreline (52.4 %). The analysis shows that the Indian coast has lost a net area of about 73 sq km during 1989–91 and 2004–06 time frame. In Tamilnadu, a net area of about 25.45 sq km have increased due to accretion, while along Nicobar Island about 93.95 sq km is lost due to erosion. The inventory has been used to prepare “Shoreline Change Atlas of the Indian Coast”, brought out as Six Volumes for the entire Indian coast.
Automatic geolocation of targets tracked by aerial imaging platforms using satellite imagery
Authors: Shukla P. K. , Goel S. , Singh P. , Lohani B.
Published: November 2014

Abstract. Tracking of targets from aerial platforms is an important activity in several applications, especially surveillance. Knowled ge of geolocation of these targets adds additional significant and useful information to the application. This paper determines the geolocation of a target being tracked from an aerial platform using the technique of image registration. Current approaches utilize a POS to determine the location of the aerial platform and then use the same for geolocation of the targets using the principle of photogrammetry. The constraints of cost and low-payload restrict the applicability of this approach using UAV platforms. This paper proposes a methodology for determining the geolocation of a target tracked from an aerial platform in a partially GPS devoid environment. The method utilises automatic feature based registration technique of a georeferenced satellite image with an ae rial image which is already stored in UAV's database to retrieve the geolocation of the target. Since it is easier to register subsequent aerial images due to similar viewing parameters, the subsequent overlapping images are registered together sequentially thus resulting in the registration of each of the images with georeferenced satellite image thus leading to geolocation of the target under interest. Using the proposed approach, the target can be tracked in all the frames in which it is visible. The proposed concept is verified experimentally and the results are found satisfactory. Using the proposed method, a user can obtain location of target of interest as well features on ground without requiring any POS on-board the aerial platform. The proposed approach has applications in surveillance for target tracking, target geolocation as well as in disaster management projects like search and rescue operations.
Knowledge based system for Satellite data product selection
Authors: Goyal R. , Jayasudha T. , Pandey P. , Rama Devi D. , Rebecca A. , Manju Sarma M. , Lakshmi B.
Published: November 2014

Abstract. In recent years, the use of satellite data for geospatial applications has multiplied and contributed significantly towards development of the society. Satellite data requirements, in terms of spatial and spectral resolution, periodicity of data, level of correction and other parameters, vary for different applications. For major applications, remote sensing data alone may not suffice and may require additional data like field data. An application user, even though being versatile in his application, may not know which satellite data is best suited for his application, how to use the data and what information can be derived from the data. Remote sensing domain experts have the proficiency of using appropriate data for remote sensing applications. Entrenching domain expertise into the system and building a knowledge base system for satellite data product selection is vital. Non specialist data users need a user-friendly software which guides them to the most suitable satellite data product on the basis of their application. Such tool will aid the usage for apt remote sensed data for various sectors of application users. Additionally, the consumers will be less concerned about the technical particulars of the platforms that provide satellite data, instead focusing on the content and values in the data product, meeting the timelines and ease of access. Embedding knowledge is a popular and effective means of increasing the power of using a system. This paper describes a system, driven by the built-in knowledge of domain experts, for satellite data products selection for geospatial applications.
Geospatial Modelling Approach for Interlinking of Rivers: A Case Study of Vamsadhara and Nagavali River Systems in Srikakulam, Andhra Pradesh
Authors: Swathi Lakshmi A. , Saran S. , Srivastav S. K. , Krishna Murthy Y. V. N.
Published: November 2014

Abstract. India is prone to several natural disasters such as floods, droughts, cyclones, landslides and earthquakes on account of its geoclimatic conditions. But the most frequent and prominent disasters are floods and droughts. So to reduce the impact of floods and droughts in India, interlinking of rivers is one of the best solutions to transfer the surplus flood waters to deficit/drought prone areas. Geospatial modelling provides a holistic approach to generate probable interlinking routes of rivers based on existing geoinformatics tools and technologies. In the present study, SRTM DEM and AWiFS datasets coupled with land-use/land -cover, geomorphology, soil and interpolated rainfall surface maps have been used to identify the potential routes in geospatial domain for interlinking of Vamsadhara and Nagavali River Systems in Srikakulam district, Andhra Pradesh. The first order derivatives are derived from DEM and road, railway and drainage networks have been delineated using the satellite data. The inundation map has been prepared using AWiFS derived Normalized Difference Water Index (NDWI). The Drought prone areas were delineated on the satellite image as per the records declared by Revenue Department, Srikakulam. Majority Rule Based (MRB) aggregation technique is performed to optimize the resolution of obtained data in order to retain the spatial variability of the classes. Analytical Hierarchy Process (AHP) based Multi-Criteria Decision Making (MCDM) is implemented to obtain the prioritization of parameters like geomorphology, soil, DEM, slope, and land use/land-cover. A likelihood grid has been generated and all the thematic layers are overlaid to identify the potential grids for routing optimization. To give a better routing map, impedance map has been generated and several other constraints are considered. The implementation of canal construction needs extra cost in some areas. The developed routing map is published into OGC WMS services using open source GeoServer and proposed routing service can be visualized over Bhuvan portal (http://www.bhuvan.nrsc.gov.in/).Thus the obtained routing map of proposed canals focuses on transferring the surplus waters to drought prone areas to solve the problem of water scarcity, to properly utilize the flood waters for irrigational purposes and also help in recharging of groundwater. Similar methodology can be adopted in other interlinking of river systems.
Understanding Dynamics of Himalayan Glaciers: Scope and Challenges of Remote Sensing
Authors: Bajracharya S. R. , Maharjan S. B. , Shrestha F.
Published: November 2014

Abstract. remote-sensing based consistent semi-automated glacier mapping methodology with minimum manual intervention has been developed at ICIMOD. Using this methodology the glaciers of Hindu Kush Himalayan region were mapped in 2011 and continuously used for glacier mapping and monitoring in the region. These data were freely available to download from ICIMOD portal and GLIMS database. These comprehensive glacier information are the only data which is being used for research and development projects for countries like Bhutan, Nepal and Pakistan. Recently decadal glacier change from 1980 to 2010 of Nepal and Bhutan were published to understand the glacier change in the Himalaya. The decadal change assessment will be continued in other basins of HKH region to understand the glacier change. Due to rugged terrain, remote access, and logistic hindrance field verification is a challenging task and can be limited only in selected glaciers. Geodetic mass balance study in the selected glaciers like in Yala of Langtang basin and Rikha Samba of Hidden valley are on progress complement to field validation. High resolution images, lack of hydro-meteorological stations near to the glacier and limited competent manpower are another hindrance in the study of glacier change of the HKH region.
Effective Management of Trans boundary Landscapes – Geospatial Applications
Authors: Kotru R. , Rawal R. S. , Mathur P. K. , Chettri N. , Chaudhari S. A. , Uddin K. , Murthy M. S. R. , Singh S.
Published: November 2014

Abstract. The Convention on Biological Diversity advocates the use of landscape and ecosystem approaches for managing biodiversity, in recognition of the need for increased regional cooperation. In this context, ICIMOD and regional partners have evolved Transboundary Landscape concept to address the issues of conservation and sustainable use of natural resources and systems (e.g., biodiversity, rangelands, farming systems, forests, wetlands, and watersheds, etc.). This concept defines the landscapes by ecosystems rather than political/administrative boundaries. The Hindu Kush Himalayan (HKH) region is extremely heterogeneous, with complex inter linkages of biomes and habitats as well as strong upstream-downstream linkages related to the provisioning of ecosystem services. Seven such transboundary landscapes, identified across west to east extent of HKH, have been considered for programmatic cooperation, include: Wakhan, Karakoram-Pamir, Kailash, Everest, Kangchenjunga, Brahmaputra-Salween, and Cherrapunjee- Chittagong. The approach is people centered and considers the cultural conservation as an essential first step towards resource conservation efforts in the region. Considering the multi-scale requirements of study, the geospatial technology has been effectively adopted towards: (i) understanding temporal changes in landscapes, (ii) long term ecological and social monitoring, (ii) identifying potential bio corridors, (iii) assessing landscape level vulnerability due to climatic and non-climatic drivers, and (iv) developing local plans on extractions of high value economic species supporting livelihoods, agroforestry system and ecotourism, etc. We present here our recent experiences across different landscapes on assessment of three decadal changes, vegetation type mapping, assessment of socio-ecological drivers, corridor assessment, ecosystem services assessment, models for optimal natural resource use systems and long term socio-ecological monitoring.
Integrated flood disaster management and spatial information: Case studies of Netherlands and India
Authors: Zlatanova S. , Ghawana T. , Kaur A. , Neuvel J. M. M.
Published: November 2014

Abstract. Spatial Information is an integral part of flood management practices which include risk management & emergency response processes. Although risk & emergency management activities have their own characteristics, for example, related to the time scales, time pressure, activities & actors involved, it is still possible to identify at least one common challenge that constrains the ability of risk & emergency management to plan for & manage emergencies effectively and efficiently i.e. the need for better information. Considering this aspect, this paper explores flood management in Netherlands& India with an emphasis on spatial information requirements of each system. The paper examines the activities, actors & information needs related to flood management. Changing perspectives on flood management in Netherlands are studied where additional attention is being paid to the organization and preparation of flood emergency management. Role of different key actors involved in risk management is explored. Indian Flood management guidelines, by National Disaster Management Authority, are analyzed in context of their history, institutional framework, achievements and gaps. Flood Forecasting System of Central Water Commission of India is also analyzed in context of spatial dimensions. Further, information overlap between risk & emergency management from the perspectives of spatial planners & emergency responders and role of GIS based modelling / simulation is analyzed. Finally, the need for an integrated spatial information structure is explained & discussed in detail. This examination of flood management practices in the Netherlands and India with an emphasis on the required spatial information in these practices has revealed an increased recognition of the strong interdependence between risk management and emergency response processes. Consequently, the importance of an integrated spatial information infrastructure that facilitates the process of both risk and emergency management is addressed.
Characterization of the Temporal and Spatial Dynamics of the Dengue Epidemic in Northern Sri Lanka
Authors: Anno S. , Imaoka K. , Tadono T. , Igarashi T. , Sivaganesh S. , Kannathasan S. , Kumaran V. , Surendran S.
Published: November 2014

Abstract. Dengue outbreaks are affected by biological, ecological, socio-economic and demographic factors that vary over time and space. These factors have been examined separately, with limited success, and still require clarification. The present study aimed to investigate the spatial and temporal relationships between these factors and dengue outbreaks in the northern region of Sri Lanka. Remote sensing (RS) data gathered from a plurality of satellites: TRMM TMI, Aqua AMSR-E, GCOM-W AMSR2, DMSP SSM/I, DMSP SSMIS, NOAA-19 AMSU, MetOp-A AMSU and GEO IR were used to develop an index comprising rainfall. Humidity (total precipitable water, or vertically integrated water vapor amount) and temperature (surface temperature) data were acquired from the JAXA Satellite Monitoring for Environmental Studies (JASMES) portal which were retrieved and processed from the Aqua/MODIS and Terra/MODIS data. RS data gathered by ALOS/AVNIR-2 were used to detect urbanization, and a digital land cover map was used to extract land cover information. Other data on relevant factors and dengue outbreaks were collected through institutions and extant databases. The analyzed RS data and databases were integrated into geographic information systems, enabling both spatial association analysis and spatial statistical analysis. Our findings show that the combination of ecological factors derived from RS data and socio-economic and demographic factors is suitable for predicting spatial and temporal patterns of dengue outbreaks.
Landscape Heterogeneity mapping for Access to Tribal health care in Nilgiris District of Tamil Nadu, India
Authors: Brindha B. , Prashanthi Devi M.
Published: November 2014

Abstract. The Nilgiris district in Tamilnadu has a rich biodiversity in terms of flora, fauna and ethnic population. The district is basically a mountainous region, situated at an elevation of 2000 to 2,600 meters above MSL and constituting of several hill and Steep Mountain valleys. This region houses six tribes who are mainly forest dwellers and live in close settlements depending on the forest resources for their livelihood. The Tribes of Nilgiris have been diagnosed and monitored for Sickle cell Anemia which is a disease of major concern among these ethnic populations. This genetic disorder developed due to the sickling of Red Blood Cells has increased during the past few decades. The Tribes, as they live in close encounter with the forest regions and have strict social cultural barriers, face difficulty in availing treatment or counseling from the Sickle Cell Research Center (SCRC) and other NGOs like NAWA and AHWINI in the region. It was observed that many factors such as landscape terrain, climatic conditions and improper roads tend to hinder the access to appropriate health care. The SCRC in Gudalur region is a facility established to monitor the disease cases inspite of these influencing factors. On analyzing the year bound age wise classification among male and female patients, certain dropouts in cases were observed which may be due to inaccessible condition or migration of the patient. In our study, Landscape heterogeneity mapping for different climatic seasons was done in ArcGIS 10.1. For this, contour and terrain maps, road networks and villages were prepared and factors that determine Terrain Difficulty were assessed. Vegetation mapping using IRS satellite images for the study region was attempted and associated with the landscape map. A risk analysis was proposed based on terrain difficulty and access to the nearest Health care Center. Based on this, the above factors alternate routes were suggested to access the difficult areas.
Multinomial Logistic Regression Predicted Probability Map To Visualize The Influence Of Socio-Economic Factors On Breast Cancer Occurrence in Southern Karnataka
Authors: Madhu B. , Ashok N. C. , Balasubramanian S.
Published: November 2014

Abstract. Multinomial logistic regression analysis was used to develop statistical model that can predict the probability of breast cancer in Southern Karnataka using the breast cancer occurrence data during 2007–2011. Independent socio-economic variables describing the breast cancer occurrence like age, education, occupation, parity, type of family, health insurance coverage, residential locality and socioeconomic status of each case was obtained. The models were developed as follows: i) Spatial visualization of the Urban- rural distribution of breast cancer cases that were obtained from the Bharat Hospital and Institute of Oncology. ii) Socio-economic risk factors describing the breast cancer occurrences were complied for each case. These data were then analysed using multinomial logistic regression analysis in a SPSS statistical software and relations between the occurrence of breast cancer across the socio-economic status and the influence of other socio-economic variables were evaluated and multinomial logistic regression models were constructed. iii) the model that best predicted the occurrence of breast cancer were identified. This multivariate logistic regression model has been entered into a geographic information system and maps showing the predicted probability of breast cancer occurrence in Southern Karnataka was created. This study demonstrates that Multinomial logistic regression is a valuable tool for developing models that predict the probability of breast cancer Occurrence in Southern Karnataka.
Mathematical Modeling of spatial disease variables by Spatial Fuzzy Logic for Spatial Decision Support Systems
Authors: Platz M. , Rapp J. , Groessler M. , Niehaus E. , Babu A. , Soman B.
Published: November 2014

Abstract. A Spatial Decision Support System (SDSS) provides support for decision makers and should not be viewed as replacing human intelligence with machines. Therefore it is reasonable that decision makers are able to use a feature to analyze the provided spatial decision support in detail to crosscheck the digital support of the SDSS with their own expertise. Spatial decision support is based on risk and resource maps in a Geographic Information System (GIS) with relevant layers e.g. environmental, health and socio-economic data. Spatial fuzzy logic allows the representation of spatial properties with a value of truth in the range between 0 and 1. Decision makers can refer to the visualization of the spatial truth of single risk variables of a disease. Spatial fuzzy logic rules that support the allocation of limited resources according to risk can be evaluated with measure theory on topological spaces, which allows to visualize the applicability of this rules as well in a map. Our paper is based on the concept of a spatial fuzzy logic on topological spaces that contributes to the development of an adaptive Early Warning And Response System (EWARS) providing decision support for the current or future spatial distribution of a disease. It supports the decision maker in testing interventions based on available resources and apply risk mitigation strategies and provide guidance tailored to the geo-location of the user via mobile devices. The software component of the system would be based on open source software and the software developed during this project will also be in the open source domain, so that an open community can build on the results and tailor further work to regional or international requirements and constraints. A freely available EWARS Spatial Fuzzy Logic Demo was developed wich enables a user to visualize risk and resource maps based on individual data in several data formats.
Ontology-Driven Knowledge-Based Health-Care System, An Emerging Area – Challenges And Opportunities – Indian Scenario
Authors: Sunitha A. , Suresh Babu G.
Published: November 2014

Abstract. Recent studies in the decision making efforts in the area of public healthcare systems have been tremendously inspired and influenced by the entry of ontology. Ontology driven systems results in the effective implementation of healthcare strategies for the policy makers. The central source of knowledge is the ontology containing all the relevant domain concepts such as locations, diseases, environments and their domain sensitive inter-relationships which is the prime objective, concern and the motivation behind this paper. The paper further focuses on the development of a semantic knowledge-base for public healthcare system. This paper describes the approach and methodologies in bringing out a novel conceptual theme in establishing a firm linkage between three different ontologies related to diseases, places and environments in one integrated platform. This platform correlates the real-time mechanisms prevailing within the semantic knowledgebase and establishing their inter-relationships for the first time in India. This is hoped to formulate a strong foundation for establishing a much awaited basic need for a meaningful healthcare decision making system in the country. Introduction through a wide range of best practices facilitate the adoption of this approach for better appreciation, understanding and long term outcomes in the area. The methods and approach illustrated in the paper relate to health mapping methods, reusability of health applications, and interoperability issues based on mapping of the data attributes with ontology concepts in generating semantic integrated data driving an inference engine for user-interfaced semantic queries.
Forest fire scenario and challenges of mitigation during fire season in North East India
Authors: Chakraborty K. , Mondal P. P , Chabukdhara M. , Sudhakar S.
Published: November 2014

Abstract. Forest fires are a major environmental problem in North East Region (NER) with large tracts of forest areas being affected in every season. Forest fires have become a major threat to the forest ecosystems in the region, leading to loss of timber, biodiversity, wildlife habitat and loss to other natural resources. Studies on forest fire have reported that about 50% of forest fire in the country takes place in NE region. The forest fire in NER is anthropogenic in nature. The forest fire hazard map generated based on appropriate weightage given to the factors affecting fire behavior like topography, fuel characteristic and proximity to roads, settlements and also historical fire locations helped to demarcate the fire prone zones. Whereas, during fire season the weather pattern also governs the fire spread in the given area. Therefore, various data on fuel characteristics (land use/land cover, forest type map, forest density map), topography (DEM, slope, aspect) proximity to settlement, road, waterbodies, meteorological data from AWS on wind speed, wind direction, dew point have been used for each fire point to rank its possible hazard level. Near real time fire location data obtained from MODIS/FIRMSwere used to generate the fire alerts. This work demonstrates dissemination of information in the form of maps and tables containing information of latitude and longitude of fire location, fire occurrence date, state and district name, LULC, road connectivity, slope and aspect, settlements/water bodies and meteorological data and the corresponding rating of possibility of fire spread to the respective fire control authorities during fire season.