Spatial Data Mining and Modeling for visualisation of Rapid Urbanisation

Rapid urbanisation in India has posed serious challenges to the decision makers in regional planning involving plethora of issues including provision of basic amenities (like electricity, water, sanitation, transport, etc.). Urban planning entails an understanding of landscape and urban dynamics with causal factors. Identifying, delineating and mapping landscapes on temporal scale provide an opportunity to monitor the changes, which is important for natural resource management and sustainable planning activities. Multi-source, multi-sensor, multi-temporal, multi-frequency or multi-polarization remote sensing data with efficient classification algorithms and pattern recognition techniques aid in capturing these dynamics. This paper analyses the landscape dynamics of Greater Bangalore by: (i) characterisation of direct impervious surface, (ii) computation of forest fragmentation indices and (iii) modeling to quantify and categorise urban changes. Linear unmixing is used for solving the mixed pixel problem of coarse resolution super spectral MODIS data for impervious surface characterisation. Fragmentation indices were used to classify forests – interior, perforated, edge, transitional, patch and undetermined. Based on this, urban growth model was developed to determine the type of urban growth – Infill, Expansion and Outlying growth. This helped in visualising urban growth poles and consequence of earlier policy decisions that can help in evolving strategies for effective land use policies.

On the Limits of Spatial Reuse and Cooperative Communication for Dense Wireless Networks

We consider a dense ad hoc wireless network comprising n nodes confined to a given two dimensional region of fixed area. For the Gupta-Kumar random traffic model and a realistic interference and path loss model (i.e., the channel power gains are bounded above, and are bounded below by a strictly positive number), we study the scaling of the aggregate end-to-end throughput with respect to the network average power constraint, P macr, and the number of nodes, n. The network power constraint P macr is related to the per node power constraint, P macr, as P macr = np. For large P, we show that the throughput saturates as Theta(log(P macr)), irrespective of the number of nodes in the network. For moderate P, which can accommodate spatial reuse to improve end-to-end throughput, we observe that the amount of spatial reuse feasible in the network is limited by the diameter of the network. In fact, we observe that the end-to-end path loss in the network and the amount of spatial reuse feasible in the network are inversely proportional. This puts a restriction on the gains achievable using the cooperative communication techniques studied in and, as these rely on direct long distance communication over the network.

An algebraic formulation of exact force-, moment-isotropy in spatial parallel manipulators

In this paper, we present an algebraic method to study and design spatial parallel manipulators that demonstrate isotropy in the force and moment distributions.We use the force and moment transformation matrices separately,and derive conditions for their isotropy individually as well as in combination. The isotropy conditions are derived in closed-form in terms of the invariants of the quadratic forms associated with these matrices. The formulation has been applied to a class of Stewart platform manipulators. We obtain multi-parameter families of isotropic manipulator analytically. In addition to computing the isotropic configurations of an existing manipulator,we demonstrate a procedure for designing the manipulator for isotropy at a given configuration.

VLSI Implementation of Spatial prediction Based Image Compression Scheme

We propose the design and implementation of hardware architecture for spatial prediction based image compression scheme, which consists of prediction phase and quantization phase. In prediction phase, the hierarchical tree structure obtained from the test image is used to predict every central pixel of an image by its four neighboring pixels. The prediction scheme generates an error image, to which the wavelet/sub-band coding algorithm can be applied to obtain efficient compression. The software model is tested for its performance in terms of entropy, standard deviation. The memory and silicon area constraints play a vital role in the realization of the hardware for hand-held devices. The hardware architecture is constructed for the proposed scheme, which involves the aspects of parallelism in instructions and data. The processor consists of pipelined functional units to obtain the maximum throughput and higher speed of operation. The hardware model is analyzed for performance in terms throughput, speed and power. The results of hardware model indicate that the proposed architecture is suitable for power constrained implementations with higher data rate

Distributed load adaptive scheduling for throughput and delay guarantees in fading wireless LANs

We consider a problem of providing mean delay and average throughput guarantees in random access fading wireless channels using CSMA/CA algorithm. This problem becomes much more challenging when the scheduling is distributed as is the case in a typical local area wireless network. We model the CSMA network using a novel queueing network based approach. The optimal throughput per device and throughput optimal policy in an M device network is obtained. We provide a simple contention control algorithm that adapts the attempt probability based on the network load and obtain bounds for the packet transmission delay. The information we make use of is the number of devices in the network and the queue length (delayed) at each device. The proposed algorithms stay within the requirements of the IEEE 802.11 standard.

Evaluation of spatial variation of peak horizontal acceleration and spectral acceleration for south India: a probabilistic approach

In this work, an attempt has been made to evaluate the spatial variation of peak horizontal acceleration (PHA) and spectral acceleration (SA) values at rock level for south India based on the probabilistic seismic hazard analysis (PSHA). These values were estimated by considering the uncertainties involved in magnitude, hypocentral distance and attenuation of seismic waves. Different models were used for the hazard evaluation, and they were combined together using a logic tree approach. For evaluating the seismic hazard, the study area was divided into small grids of size 0.1A degrees A xA 0.1A degrees, and the hazard parameters were calculated at the centre of each of these grid cells by considering all the seismic sources within a radius of 300 km. Rock level PHA values and SA at 1 s corresponding to 10% probability of exceedance in 50 years were evaluated for all the grid points. Maps showing the spatial variation of rock level PHA values and SA at 1 s for the entire south India are presented in this paper. To compare the seismic hazard for some of the important cities, the seismic hazard curves and the uniform hazard response spectrum (UHRS) at rock level with 10% probability of exceedance in 50 years are also presented in this work.

Influence of Spatial Scales on the Performance of Saturated Subsurface Flow and Transport Models

Numerical modeling of saturated subsurface flow and transport has been widely used in the past using different numerical schemes such as finite difference and finite element methods. Such modeling often involves discretization of the problem in spatial and temporal scales. The choice of the spatial and temporal scales for a modeling scenario is often not straightforward. For example, a basin-scale saturated flow and transport analysis demands larger spatial and temporal scales than a meso-scale study, which in turn has larger scales compared to a pore-scale study. The choice of spatial-scale is often dictated by the computational capabilities of the modeler as well as the availability of fine-scale data. In this study, we analyze the impact of different spatial scales and scaling procedures on saturated subsurface flow and transport simulations.

Spatial Decision Support System for Assessing Micro, Mini and Small Hydel Potential

This study describes the design and implementation of DSS for assessment of Mini, Micro and Small Schemes. The design links a set of modelling, manipulation, spatial analyses and display tools to a structured database that has the facility to store both observed and simulated data. The main hypothesis is that this tool can be used to form a core of practical methodology that will result in more resilient in less time and can be used by decision-making bodies to assess the impacts of various scenarios (e.g.: changes in land use pattern) and to review, cost and benefits of decisions to be made. It also offers means of entering, accessing and interpreting the information for the purpose of sound decision making. Thus, the overall objective of this DSS is the development of set of tools aimed at transforming data into information and aid decisions at different scales.