Abstract

Land use and land cover (LULC) changes induced by human or natural processes drive biogeochemistryof the Earth influencing the climate at global as well as regional scales. Drastic changes in the land cover with the decline in vegetation and water bodies due to anthropogenic activities enhances the heat emission from land surface and atmospheric temperatures Increased land surface temperature (LST) is mainly due to increase in concentrated human activities, paved land cover or barren lands. Due to complexity of landscapes the sampling was difficult to derive LST and environmental response relationships. Temporal data acquired through space borne remote sensors has bridged the gap of temporal data for the entire earth surface. The current study explores the relation between surface biophysical parameters to sub-pixel thermal variations. The thermal infrared bands of remote sensing data help to retrieve LST, which are supplemented byground based measurements. Analysis of LST with LULC indicates a negative correlation between vegetation indices and LST. The general trend in the ambient temperature of Uttara Kannada over the 31 year period was established. Itclarifies that there was a fundamental drift of temperature rise in recent years, especially during the last decade.

Abstract

: Railway is the largest undertaking in the country. A retrospective study of prevailing conditions is necessary to assimilate the progress of the sector and how far have the changes introduced in previous few years been successful. The paper examines how the proposed changes in the Indian railways have changed the face of it through rigorous spatial analysis in diversified fields. A balanced analysis of shortcomings as well as achievements has been tried to be achieved through this paper for few selected regions of India.Each year there has to be more emphasis on enhancing the services provided. The rail budgets play a vital role and are responsible for taking care of it. The numerous promises made in terms of introduction of trains, electrification of routes, gauge conversion, doubling and increasing frequency of trains are made every year, in order to keep track of fulfillment of those decisions the spatial analysis is conducted rigorously. Railway has also witnessed a number of disasters in past few years; the spatial analysis conducted brings out few major reasons of those. A section of study also covers the topographic conditions in the state of Jammu and Kashmir that have not allowed the progress of railways in these regions.

Abstract

In this work, Spatio-Temporal Data Mining of disease surveillance data is done, to describe the underlying patterns in disease occurrences across populations and to identify possible causes that could explain them; for better disease core prediction, detection and management. MiSTIC algorithm is used to determine spatial spread of disease core regions (scale of disease prevalence), and the frequency & regularity of occurrence of different locations in space as disease cores. The results show good correlation between the etiologic factors of Salmonellosis and the detected core locations, in addition to the significant observation of highly localized nature of disease prevalence.

Abstract

With major aerospace companies showing interest in certifying UAV systems for civilian airspace, their use in commercial remote sensing applications like traffic monitoring, map refinement, agricultural data collection, etc., are on the rise. But ambitious requirements like real-time geo-referencing of data, support for multiple sensor angle-of-views, smaller UAV size and cheaper investment cost have lead to challenges in platform stability, sensor noise reduction and increased onboard processing. Especially in small UAVs the geo-referencing of data collected is only as good as the quality of their localization sensors. This drives a need for developing methods that pickup spatial features from the captured video/image and aid in geo-referencing. This paper presents one such method to identify road segments and intersections based on traffic flow and compares well with the accuracy of manual observation. Two test video datasets, one each from moving and stationary platforms were used. The results obtained show a promising average percentage difference of 7.01% and 2.48% for the road segment extraction process using moving and stationary platform respectively. For the intersection identification process, the moving platform shows an accuracy of 75% where as the stationary platform data reaches an accuracy of 100%.

Abstract

Rapid urbanization is resulting in the irreversible land use and land cover (LULC) changes, which is the prime driver of global warming and consequent climate changes. This communication investigates landscape dynamics assessed through spatio-temporal pattern analysis using free and open source softwares [FOSS, http://ces. iisc. ernet. in/foss]. Bangalore has been experiencing urbanization tide since globalisation era and is one of the fastest growing cities in India. Migration and policy decision of setting up major facilities and industries seem to be the reason for rapid urbanisation with impacts on the local ecology and natural resources. As the city centre has reached the threshold of urbanisation, intense sprawl has been noticed at outskirts. In order to understand the urbanisation and sprawl dynamics, spatio-temporal analysis has been done in the city administrative region with 10 km buffer. To understand the dynamics at local level with drivers, spatial metrics is computed for the study region, which is divided into eight zones (radial), 13 circles of 2 km incrementing radius. The results show that extensive land conversion to urban utility has occurred since 1992 within the city and from 2000 conversion started at periphery, especially by industrialisation activities. The land scape metrics exhibited remarkable spatial and temporal variations and urban sprawl. Overall changes in the land use from 1973 to 2012 shows the increase in the built-up (paved surface) area from 1.87% to 29.33% and decrease in vegetation cover from 62.38% to 33.68%. The landscape metrics depicts the city is more concentrated at center and fragmented towards its …

Abstract

Tropical islands are special and sensitive ecosystems which are subjected to various disturbances imposed by human activities and natural disasters. A detailed study about the changing landscape scenarios of these fragile island systems induced by various driving factors could be used for setting up measurements in support of conservation and sustainable development projects. The current research is a meta-analysis of the studies carried out in Andaman and Nicobar islands which analyzed the impact of tsunami of 2004 using geospatial tools. Based on the analysis, it was observed that the Nicobar islands were more affected compared to the Andaman islands. The majority of the researchers used pre- and post-tsunami satellite imagery and adopted visual interpretation method to delineate the changed classes. The study infers uplift of land in Andaman (exposing) and subsidence in Nicobar islands …

Abstract

One of the challenges in risk analysis has been that the determinants which are identified are based on a causality-driven approach drawn largely from the correlation studies of underlying factors. These approaches not only require numerous thematic information layers-spatial and non-spatial, that may potentially represent the factors of interest, but also tend to ignore the spatial and temporal variability of the outcome itself (say, disease incidence). On the other hand, owing to the advances in surveillance and monitoring systems resulting in enhanced availability of spatially explicit data over the last 25 years, there is a need to use these effectively at understanding or explaining the phenomenon itself. In this paper, we propose a method to leverage the observed event data-both spatial and temporal characterizations of disease occurrences, to generate a risk map that will provide valuable insights into its

Abstract

Advances in sensing and data gathering technologies have resulted in an explosion in the volume of data that is being generated, processed, and archived. In particular, this information overload calls for new methods for querying large spatial datasets, since users are often not interested in merely retrieving a list of all data items satisfying a query, but would, instead, like a more informative \summary" of the retrieved items. An example is the so-called top-k problem, where the goal is to retrieve from a set of n weighted points in IRd the k most signicant points, ranked by their weights, that lie in an orthogonal query box in IRd (rather than get a list of all points lying in the query box). In this paper, ecient and output-sensitive solutions are presented for this problem in two settings. In the rst setting, the k points are reported in arbitrary order and the underlying set can be updated dynamically through insertions and deletions of points. In the second setting, the k points are reported in sorted order of their weights.

Abstract

In this paper we consider range-aggregate query problems wherein we wish to preprocess a set S of geometric objects such that given a query orthogonal range q, a certain aggregation function on the objects S0 = S \ q can be answered eciently. Range-aggregate version of point enclosure queries, 1-d segment intersection, 2-d orthogonal seg- ment intersection (with/without distance constraint) are revisited and we improve the existing results for these problems. We also provide semi- dynamic (insertions) solutions to some of these problems. This paper is the rst attempt to provide dynamic solutions to problems involving geometric aggregation operations.

Abstract

Hierarchical Ring Networks are widely used in communication systems, logistics and shared multiprocessors. It is hence imperative that efficient design of these structures has to be carried out, to reduce costs of their installation and help increase the ease of management. In this paper, we look at the problem of designing efficient 2- level Hierarchical Ring Networks, in the context of link costs optimization. 2-level HRNs only have two kinds of rings - local rings to connect disjoint sets of nodes and a global ring to interconnect all the local rings. We present an algorithm that is based on Simulated Annealing. We present results for scenarios containing upto 300 nodes. The results obtained from the algorithm are most encouraging.