A Spatial Planning Support System for Managing Bangalore's Urban Sprawl

Urban sprawl is the outgrowth along the periphery of cities and along highways. Although an accurate definition of urban sprawl may be debated, a consensus is that urban sprawl is characterized by an unplanned and uneven pattern of growth, driven by multitude of processes and leading to inefficient resource utilization. Urbanization in India has never been as rapid as it is in recent times. As one of the fastest growing economies in the world, India faces stiff challenges in managing the urban sprawl, while ensuring effective delivery of basic services in urban areas. The urban areas contribute significantly to the national economy (more than 50% of GDP), while facing critical challenges in accessing basic services and necessary infrastructure, both social and economic. The overall rise in the population of the urban poor or the increase in travel times due to congestion along road networks are indicators of the effectiveness of planning and governance in assessing and catering for this demand. Agencies of governance at all levels: local bodies, state government and federal government, are facing the brunt of this rapid urban growth. It is imperative for planning and governance to facilitate, augment and service the requisite infrastructure over time systematically. Provision of infrastructure and assurance of the delivery of basic services cannot happen overnight and hence planning has to facilitate forecasting and service provision with appropriate financial mechanisms.

Greater Bangalore: Emerging Urban Heat Island

Bangalore is experiencing unprecedented urbanisation and sprawl in recent times due to concentrated developmental activities with impetus on industrialisation for the economic development of the region. This concentrated growth has resulted in the increase in population and consequent pressure on infrastructure, natural resources and ultimately giving rise to a plethora of serious challenges such as climate change, enhanced green-house gases emissions, lack of appropriate infrastructure, traffic congestion, and lack of basic amenities (electricity, water, and sanitation) in many localities, etc. This study shows that there has been a growth of 632% in urban areas of Greater Bangalore across 37 years (1973 to 2009). Urban heat island phenomenon is evident from large number of localities with higher local temperatures. The study unravels the pattern of growth in Greater Bangalore and its implication on local climate (an increase of ~2 to 2.5 ºC during the last decade) and also on the natural resources (76% decline in vegetation cover and 79% decline in water bodies), necessitating appropriate strategies for the sustainable management.

Geoinformatics for Urbanisation and Urban Sprawl Pattern Analysis

Urbanisation is the increase in the population of cities in proportion to the region's rural population. Urbanisation in India is very rapid with urban population growing at around 2.3 percent per annum. Urban sprawl refers to the dispersed development along highways or surrounding the city and in rural countryside with implications such as loss of agricultural land, open space and ecologically sensitive habitats. Sprawl is thus a pattern and pace of land use in which the rate of land consumed for urban purposes exceeds the rate of population growth resulting in an inefficient and consumptive use of land and its associated resources. This unprecedented urbanisation trend due to burgeoning population has posed serious challenges to the decision makers in the city planning and management process involving plethora of issues like infrastructure development, traffic congestion, and basic amenities (electricity, water, and sanitation), etc. In this context, to aid the decision makers in following the holistic approaches in the city and urban planning, the pattern, analysis, visualization of urban growth and its impact on natural resources has gained importance. This communication, analyses the urbanisation pattern and trends using temporal remote sensing data based on supervised learning using maximum likelihood estimation of multivariate normal density parameters and Bayesian classification approach. The technique is implemented for Greater Bangalore – one of the fastest growing city in the World, with Landsat data of 1973, 1992 and 2000, IRS LISS-3 data of 1999, 2006 and MODIS data of 2002 and 2007. The study shows that there has been a growth of 466% in urban areas of Greater Bangalore across 35 years (1973 to 2007). The study unravels the pattern of growth in Greater Bangalore and its implication on local climate and also on the natural resources, necessitating appropriate strategies for the sustainable management.

Greening India Mission

The Government of India has announced the Greening India Mission (GIM) under the National Climate Change Action Plan. The Mission aims to restore and afforest about 10 mha over the period 2010-2020 under different sub-missions covering moderately dense and open forests, scrub/grasslands, mangroves, wetlands, croplands and urban areas. Even though the main focus of the Mission is to address mitigation and adaptation aspects in the context of climate change, the adaptation component is inadequately addressed. There is a need for increased scientific input in the preparation of the Mission. The mitigation potential is estimated by simply multiplying global default biomass growth rate values and area. It is incomplete as it does not include all the carbon pools, phasing, differing growth rates, etc. The mitigation potential estimated using the Comprehensive Mitigation Analysis Process model for the GIM for the year 2020 has the potential to offset 6.4% of the projected national greenhouse gas emissions, compared to the GIM estimate of only 1.5%, excluding any emissions due to harvesting or disturbances. The selection of potential locations for different interventions and species choice under the GIM must be based on the use of modelling, remote sensing and field studies. The forest sector provides an opportunity to promote mitigation and adaptation synergy, which is not adequately addressed in the GIM. Since many of the interventions proposed are innovative and limited scientific knowledge exists, there is need for an unprecedented level of collaboration between the research institutions and the implementing agencies such as the Forest Departments, which is currently non-existent. The GIM could propel systematic research into forestry and climate change issues and thereby provide global leadership in this new and emerging science.

The status and use of tree biomass in a semi-arid village ecosystem

The status of the tree biomass resource was investigated in Ungra, a semi-arid village ecosystem in South India. There were 57 tree species with 12 trees capita−1 and 35 trees ha−1. Multiple benefit yielding local tree species dominated the village ecosystem, while fuel only or single end use trees accounted for a small proportion of trees. The standing tree biomass is adequate to meet the requirement of biomass fuels for cooking only for about two years. Village tree biomass is presently being depleted largely for export to urban areas. Tree regeneration is now characterized by transformation from multiple-use local tree species to a few single-use species. A large potential exists for tree biomass production along field boundaries (bunds), stream banks and roadsides. Biomass estimation equations were developed for 10 species.

Seismic Microzonation: Principles,Practices and Experiments

This paper presents an overview of the seismic microzonation and the grade/level based study along with methods used for estimating hazard. The principles of seismic microzonation along with some current practices are discussed. Summary of seismic microzonation experiments carried out in India is presented. A detailed work of seismic microzonation of Bangalore has been presented as a case study. In this case study, a seismotectonic map for microzonation area has been developed covering 350 km radius around Bangalore, India using seismicity and seismotectonic parameters of the region. For seismic microzonation Bangalore Mahanagar Palike (BMP) area of 220 km2 has been selected as the study area. Seismic hazard analysis has been carried out using deterministic as well as probabilistic approaches. Synthetic ground motion at 653 locations, recurrence relation and peak ground acceleration maps at rock level have been generated. A detailed site characterization has been carried out using borehole with standard penetration test (SPT) ―N‖ values and geophysical data. The base map and 3-dimensional sub surface borehole model has been generated for study area using geographical information system (GIS). Multichannel analysis of surface wave (MASW)method has been used to generate one-dimensional shear wave velocity profile at 58 locations and two- dimensional profile at 20 locations. These shear wave velocities are used to estimate equivalent shear wave velocity in the study area at every 5m intervals up to a depth of 30m. Because of wider variation in the rock depth, equivalent shear for the soil overburden thickness alone has been estimated and mapped using ArcGIS 9.2. Based on equivalent shear wave velocity of soil overburden thickness, the study area is classified as ―site class D‖. Site response study has been carried out using geotechnical properties and synthetic ground motions with program SHAKE2000.The soil in the study area is classified as soil with moderate amplification potential. Site response results obtained using standard penetration test (SPT) ―N‖ values and shear wave velocity are compared, it is found that the results based on shear wave velocity is lower than the results based on SPT ―N‖ values. Further, predominant frequency of soil column has been estimated based on ambient noise survey measurements using instruments of L4-3D short period sensors equipped with Reftek 24 bit digital acquisition systems. Predominant frequency obtained from site response study is compared with ambient noise survey. In general, predominant frequencies in the study area vary from 3Hz to 12Hz. Due to flat terrain in the study area, the induced effect of land slide possibility is considered to be remote. However, induced effect of liquefaction hazard has been estimated and mapped. Finally, by integrating the above hazard parameters two hazard index maps have been developed using Analytic Hierarchy Process (AHP) on GIS platform. One map is based on deterministic hazard analysis and other map is based on probabilistic hazard analysis. Finally, a general guideline is proposed by bringing out the advantages and disadvantages of different approaches.

Classification of road damage due to earthquakes

Earthquakes cause massive road damage which in turn causes adverse effects on the society. Previous studies have quantified the damage caused to residential and commercial buildings; however, not many studies have been conducted to quantify road damage caused by earthquakes. In this study, an attempt has been made to propose a new scale to classify and quantify the road damage due to earthquakes based on the data collected from major earthquakes in the past. The proposed classification for road damage due to earthquake is called as road damage scale (RDS). Earthquake details such as magnitude, distance of road damage from the epicenter, focal depth, and photographs of damaged roads have been collected from various sources with reported modified Mercalli intensity (MMI). The widely used MMI scale is found to be inadequate to clearly define the road damage. The proposed RDS is applied to various reported road damage and reclassified as per RDS. The correlation between RDS and earthquake parameters of magnitude, epicenter distance, hypocenter distance, and combination of magnitude with epicenter and hypocenter distance has been studied using available data. It is observed that the proposed RDS correlates well with the available earthquake data when compared with the MMI scale. Among several correlations, correlation between RDS and combination of magnitude and epicenter distance is appropriate. Summary of these correlations, their limitations, and the applicability of the proposed scale to forecast road damages and to carry out vulnerability analysis in urban areas is presented in the paper.

Model projections for household energy use in India

Energy use in developing countries is heterogeneous across households. Present day global energy models are mostly too aggregate to account for this heterogeneity. Here, a bottom-up model for residential energy use that starts from key dynamic concepts on energy use in developing countries is presented and applied to India. Energy use and fuel choice is determined for five end-use functions (cooking, water heating, space heating, lighting and appliances) and for five different income quintiles in rural and urban areas. The paper specifically explores the consequences of different assumptions for income distribution and rural electrification on residential sector energy use and CO(2) emissions, finding that results are clearly sensitive to variations in these parameters. As a result of population and economic growth, total Indian residential energy use is expected to increase by around 65-75% in 2050 compared to 2005, but residential carbon emissions may increase by up to 9-10 times the 2005 level. While a more equal income distribution and rural electrification enhance the transition to commercial fuels and reduce poverty, there is a trade-off in terms of higher CO(2) emissions via increased electricity use. (C) 2011 Elsevier Ltd. All rights reserved.

Automatic road extraction using high resolution satellite images based on Level Set and Mean Shift methods

Analysis of high resolution satellite images has been an important research topic for urban analysis. One of the important features of urban areas in urban analysis is the automatic road network extraction. Two approaches for road extraction based on Level Set and Mean Shift methods are proposed. From an original image it is difficult and computationally expensive to extract roads due to presences of other road-like features with straight edges. The image is preprocessed to improve the tolerance by reducing the noise (the buildings, parking lots, vegetation regions and other open spaces) and roads are first extracted as elongated regions, nonlinear noise segments are removed using a median filter (based on the fact that road networks constitute large number of small linear structures). Then road extraction is performed using Level Set and Mean Shift method. Finally the accuracy for the road extracted images is evaluated based on quality measures. The 1m resolution IKONOS data has been used for the experiment.

Treatment of gray water using anaerobic biofilms created on synthetic and natural fibers

Gray water treatment and reuse is an immediate option to counter the upcoming water shortages in various parts of world, especially urban areas. Anaerobic treatment of gray water in houses is an alternative low cost, low energy and low sludge generating option that can meet this challenge. Typical problems of fluctuating VFA, low pH and sludge washout at low loading rates with gray water feedstock was overcome in two chambered anaerobic biofilm reactors using natural fibers as the biofilm support. The long term performance of using natural fiber based biofilms at moderate and low organic loading rates (OLR) have been examined. Biofilms raised on natural fibers (coir, ridge-gourd) were similar to that of synthetic media (PVC, polyethylene) at lower OLR when operated in pulse fed mode without effluent recirculation and achieved 80-90% COD removal at HRT of 2 d showing a small variability during start-up. Confocal microscopy of the biofilms on natural fibers indicated thinner biofilms, dense cell architecture and low extra cellular polymeric substances (EPS) compared to synthetic supports and this is believed to be key factor in high performance at low OLR and low strength gray water. Natural fibers are thus shown to be an effective biofilm support that withstand fluctuating characteristic of domestic gray water. (C) 2013 The Institution of Chemical Engineers. Published by Elsevier B.V. All rights reserved.

Rrp1B gene polymorphism (1307T > C) in metastatic progression of breast cancer

Rrp1B (ribosomal RNA processing1 homolog B) is a novel candidate metastasis modifier gene in breast cancer. Functional gene assays demonstrated that a physical and functional interaction existing between Rrp1b and metastasis modifier gene SIPA1 causes reduction in the tumor growth and metastatic potential. Ectopic expression of Rrp1B modulates various metastasis predictive extra cellular matrix (ECM) genes associated with tumor suppression. The aim of this study is to determine the functional significance of single nucleotide polymorphism (SNP) in human Rrp1B gene (1307 T > C; rs9306160) with breast cancer development and progression. The study consists of 493 breast cancer cases recruited from Nizam's Institute of Medical Sciences, Hyderabad, and 558 age-matched healthy female controls from rural and urban areas. Genomic DNA was isolated by non-enzymatic method. Genotyping was done by amplification refractory mutation system (ARMS-PCR) method. Genotypes were reconfirmed by sequencing and results were analyzed statistically. We have performed Insilco analysis to know the RNA secondary structure by using online tool m fold. The TT genotype and T allele frequencies of Rrp1B1307 T > C polymorphism were significantly elevated in breast cancer (chi (2); p = < 0.008) cases compared to controls under different genetic models. The presence of T allele had conferred 1.75-fold risk for breast cancer development (OR = 1.75; 95 % CI = 1.15-2.67). The frequency of TT genotype of Rrp1b 1307T > C polymorphism was significantly elevated in obese patients (chi (2); p = 0.008) and patients with advanced disease (chi (2); p = 0.01) and with increased tumor size (chi (2); p = 0.01). Moreover, elevated frequency of T allele was also associated with positive lymph node status (chi (2); p = 0.04) and Her2 negative receptor status (chi (2); p = 0.006). Presence of Rrp1b1307TT genotype and T allele confer strong risk for breast cancer development and progression.

Isolating the impacts of land use and climate change on streamflow

Quantifying the isolated and integrated impacts of land use (LU) and climate change on streamflow is challenging as well as crucial to optimally manage water resources in river basins. This paper presents a simple hydrologic modeling-based approach to segregate the impacts of land use and climate change on the streamflow of a river basin. The upper Ganga basin (UGB) in India is selected as the case study to carry out the analysis. Streamflow in the river basin is modeled using a calibrated variable infiltration capacity (VIC) hydrologic model. The approach involves development of three scenarios to understand the influence of land use and climate on streamflow. The first scenario assesses the sensitivity of streamflow to land use changes under invariant climate. The second scenario determines the change in streamflow due to change in climate assuming constant land use. The third scenario estimates the combined effect of changing land use and climate over the streamflow of the basin. Based on the results obtained from the three scenarios, quantification of isolated impacts of land use and climate change on streamflow is addressed. Future projections of climate are obtained from dynamically downscaled simulations of six general circulation models (GCMs) available from the Coordinated Regional Downscaling Experiment (CORDEX) project. Uncertainties associated with the GCMs and emission scenarios are quantified in the analysis. Results for the case study indicate that streamflow is highly sensitive to change in urban areas and moderately sensitive to change in cropland areas. However, variations in streamflow generally reproduce the variations in precipitation. The combined effect of land use and climate on streamflow is observed to be more pronounced compared to their individual impacts in the basin. It is observed from the isolated effects of land use and climate change that climate has a more dominant impact on streamflow in the region. The approach proposed in this paper is applicable to any river basin to isolate the impacts of land use change and climate change on the streamflow.