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.

Abstract

t 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 preand 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 (inundation) with severe damage to the coastal elements like mangroves, coral reefs, plantations and in few cases interior forest. The analysis showed there were no records of the damage for some small islands. Finally, it is concluded that utility of microwave satellite data for change analysis will prove better in regions like Andaman and Nicobar where it is difficult to get cloud free optical data because of the high monsoon periods in these islands. It is also suggested that future work utilizing suitable temporal satellite imagery should focus on the extent of recovery of vegetation and other coastal elements which suffer the impact of disaster.

Abstract

We are given a set S of n points in a d-dimensional space. Given a query orthogonal box q=d i=1[ai; bi] or a semi-innite query box q=d i=1[ai;1), a One- reporting query reports YES if S q6=, else reports NO. The data structures introduced in this paper do not have their query time exponentially dependent on the dimension size, d, if the points are assumed to be randomly generated. Hence we partially break the curse of dimensionality" with which almost all the data structures for range searching sufer. The model of computation assumed is word-RAM

Abstract

Increasingly in the recent past, the focus on climate change is moving towards the understanding of the occurrence, both in magnitude and frequency, of extreme climatic events like droughts and floods. In this paper, an effort has been made towards identification of spatial co-occurrence of droughts across various subdivisions of India, based on the historical climatological data of the past century. The results show that similarities in the climate forcing factors have a role in spatio-temporal correlation of events. Also, from the results, it is seen that the well-known spatial autocorrelations measures, such as Moran Index, are not sufficient to explain such cooccurrences of events.

Abstract

Phytodiversity is affected both by natural and anthropogenic factors and in Island ecosystems these impacts can devastate or reduce diversity, if the native vegetation is lost. In addition to rich species richness and diversity, Island systems are the sites of high endemism and any threat to these ecosystems will consequently lead to loss and extinction of species. To understand the dynamics including feedbacks of these changes in phytodiversity of North Andaman Islands, a conceptual framework is proposed which focuses on understanding the land-use and land-cover changes and its impact with phytodiversity. In considering land-use and land-cover changes this work highlights the direct and indirect drivers of changes—socio-economic, biophysical and climatic factors. Migration of population, their socio economic needs and government policies were identified as major driving forces threatening the phytodiversity of these Islands. Apart from human beings, natural disasters like tsunami and introduced herbivorous animals like elephants also contributed to forest destruction in these Islands. The integrated analysis based on such framework will provide insights for holistic resource management including ecological conservation.