Fusion of multi resolution remote sensing data for urban sprawl analysis

Urban population is growing at around 2.3 percent per annum in India. This is leading to urbanisation and often fuelling the dispersed development in the outskirts of urban and village centres with impacts such as loss of agricultural land, open space, and ecologically sensitive habitats. This type of upsurge is very much prevalent and persistent in most places, often inferred as sprawl. The direct implication of such urban sprawl is the change in land use and land cover of the region and lack of basic amenities, since planners are unable to visualise this type of growth patterns. This growth is normally left out in all government surveys (even in national population census), as this cannot be grouped under either urban or rural centre. The investigation of patterns of growth is very crucial from regional planning point of view to provide basic amenities in the region. The growth patterns of urban sprawl can be analysed and understood with the availability of temporal multi-sensor, multi-resolution spatial data. In order to optimise these spectral and spatial resolutions, image fusion techniques are required. This aids in integrating a lower spatial resolution multispectral (MSS) image (for example, IKONOS MSS bands of 4m spatial resolution) with a higher spatial resolution panchromatic (PAN) image (IKONOS PAN band of 1m spatial resolution) based on a simple spectral preservation fusion technique - the Smoothing Filter-based Intensity Modulation (SFIM). Spatial details are modulated to a co-registered lower resolution MSS image without altering its spectral properties and contrast by using a ratio between a higher resolution image and its low pass filtered (smoothing filter) image. The visual evaluation and statistical analysis confirms that SFIM is a superior fusion technique for improving spatial detail of MSS images with the preservation of spectral properties.

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.

Biofuel production and implications for land use, food production and environment in India

There is a large interest in biofuels in India as a substitute to petroleum-based fuels, with a purpose of enhancing energy security and promoting rural development. India has announced an ambitious target of substituting 20% of fossil fuel consumption by biodiesel and bioethanol by 2017. India has announced a national biofuel policy and launched a large program to promote biofuel production, particularly on wastelands: its implications need to be studied intensively considering the fact that India is a large developing country with high population density and large rural population depending upon land for their livelihood. Another factor is that Indian economy is experiencing high growth rate, which may lead to enhanced demand for food, livestock products, timber, paper, etc., with implications for land use. Studies have shown that area under agriculture and forest has nearly stabilized over the past 2-3 decades. This paper presents an assessment of the implications of projected large-scale biofuel production on land available for food production, water, biodiversity, rural development and GHG emissions. The assessment will be largely focused on first generation biofuel crops, since the Indian program is currently dominated by these crops. Technological and policy options required for promoting sustainable biofuel production will be discussed. (C) 2010 Elsevier Ltd. All rights reserved.

Potential of biomass energy for electricity generation in sub-Saharan Africa

The paper explores the biomass based power generation potential of Africa. Access to electricity in sub-Saharan Africa (SSA) is about 26% and falls to less than 1% in the rural areas. On the basis of the agricultural and forest produce of this region, the residues generated after processing are estimated for all the countries. The paper also addresses the use of gasification technology - an efficient thermo-chemical process for distributed power generation - either to replace fossil fuel in an existing diesel engine based power generation system or to generate electricity using a gas engine. This approach enables the implementation of electrification programs in the rural sector and gives access to grid quality power. This study estimates power generation potential at about 5000 MW and 10,000 MW by using 30% of residues generated during agro processing and 10% of forest residues from the wood processing industry, respectively. A power generation potential of 15000 MW could generate 100 terawatt-hours (TWh), about 15% of current generation in SSA. The paper also summarizes some of the experience in using the biomass gasification technology for power generation in Africa and India. The paper also highlights the techno economics and key barriers to promotion of biomass energy in sub-Saharan Africa. (C) 2011 International Energy Initiative. Published by Elsevier Inc. All rights reserved.

Operational experience on a grid connected 100 kWe biomass gasification power plant in Karnataka, India

The paper reports the operational experience from a 100 kWe gasification power plant connected to the grid in Karnataka. Biomass Energy for Rural India (BERI) is a program that implemented gasification based power generation with an installed capacity of 0.88 MWe distributed over three locations to meet the electrical energy needs in the district of Tumkur. The operation of one 100 kWe power plant was found unsatisfactory and not meeting the designed performance. The Indian Institute of Science, Bangalore, the technology developer, took the initiative to ensure the system operation, capacity building and prove the designed performance. The power plant connected to the grid consists of the IISc gasification system which includes reactor, cooling, cleaning system, fuel drier and water treatment system to meet the producer gas quality for an engine. The producer gas is used as a fuel in Cummins India Limited, GTA 855 G model, turbo charged engine and the power output is connected to the grid. The system has operated for over 1000 continuous hours, with only about 70 h of grid outages. The total biomass consumption for 1035 h of operation was 111 t at an average of 107 kg/h. Total energy generated was 80.6 MWh reducing over loot of CO(2) emissions. The overall specific fuel consumption was about 1.36 kg/kWh, amounting to an overall efficiency from biomass to electricity of about 18%. The present operations indicate that a maintenance schedule for the plant can be at the end of 1000 h. The results for another 1000 h of operation by the local team are also presented. (C) 2011 International Energy Initiative. Published by Elsevier Inc. All rights reserved.

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.

Decision support system for regional electricity planning

Electricity appears to be the energy carrier of choice for modern economics since growth in electricity has outpaced growth in the demand for fuels. A decision maker (DM) for accurate and efficient decisions in electricity distribution requires the sector wise and location wise electricity consumption information to predict the requirement of electricity. In this regard, an interactive computer-based Decision Support System (DSS) has been developed to compile, analyse and present the data at disaggregated levels for regional energy planning. This helps in providing the precise information needed to make timely decisions related to transmission and distribution planning leading to increased efficiency and productivity. This paper discusses the design and implementation of a DSS, which facilitates to analyse the consumption of electricity at various hierarchical levels (division, taluk, sub division, feeder) for selected periods. This DSS is validated with the data of transmission and distribution systems of Kolar district in Karnataka State, India.

Comparison of 10 Multi-Sensor Image Fusion Paradigms for IKONOS Images

Fusion of multi-sensor imaging data enables a synergetic interpretation of complementary information obtained by sensors of different spectral ranges. Multi-sensor data of diverse spectral, spatial and temporal resolutions require advanced numerical techniques for analysis and interpretation. This paper reviews ten advanced pixel based image fusion techniques – Component substitution (COS), Local mean and variance matching, Modified IHS (Intensity Hue Saturation), Fast Fourier Transformed-enhanced IHS, Laplacian Pyramid, Local regression, Smoothing filter (SF), Sparkle, SVHC and Synthetic Variable Ratio. The above techniques were tested on IKONOS data (Panchromatic band at 1 m spatial resolution and Multispectral 4 bands at 4 m spatial resolution). Evaluation of the fused results through various accuracy measures, revealed that SF and COS methods produce images closest to corresponding multi-sensor would observe at the highest resolution level (1 m).

Spatio-temporal landscape modelling for natural hazard vulnerability analysis in select watersheds of Central Western Ghats

Natural hazards such as landslides are triggered by numerous factors such as ground movements, rock falls, slope failure, debris flows, slope instability, etc. Changes in slope stability happen due to human intervention, anthropogenic activities, change in soil structure, loss or absence of vegetation (changes in land cover), etc. Loss of vegetation happens when the forest is fragmented due to anthropogenic activities. Hence land cover mapping with forest fragmentation can provide vital information for visualising the regions that require immediate attention from slope stability aspects. The main objective of this paper is to understand the rate of change in forest landscape from 1973 to 2004 through multi-sensor remote sensing data analysis. The forest fragmentation index presented here is based on temporal land use information and forest fragmentation model, in which the forest pixels are classified as patch, transitional, edge, perforated, and interior, that give a measure of forest continuity. The analysis carried out for five prominent watersheds of Uttara Kannada district– Aganashini, Bedthi, Kali, Sharavathi and Venkatpura revealed that interior forest is continuously decreasing while patch, transitional, edge and perforated forest show increasing trend. The effect of forest fragmentation on landslide occurrence was visualised by overlaying the landslide occurrence points on classified image and forest fragmentation map. The increasing patch and transitional forest on hill slopes are the areas prone to landslides, evident from the field verification, indicating that deforestation is a major triggering factor for landslides. This emphasises the need for immediate conservation measures for sustainable management of the landscape. Quantifying and describing land use - land cover change and fragmentation is crucial for assessing the effect of land management policies and environmental protection decisions.

Influence of planning and governance on the level of urban services

A theoretical framework to analyse the interaction of planning and governance on the extent of outgrowth and level of services is proposed. An indicator framework for quantifying sprawl is also proposed and the same is operationalised for Bangalore. The indicators comprise spatial metrics (derived from temporal satellite remote sensing data) and other metrics obtained from a house-hold survey. The interaction of different indicators with respect to the core city and the outgrowth is determined by multi-dimensional scaling. The analysis reveals the underlying similarities (and dissimilarities) that relate with the different governance structures that prevail here. The paper concludes outlining the challenges in addressing urban sprawl while ensuring adequate level of services that planning and governance have to ensure towards achieving sustainable urbanisation.

Biofuel Prospects of Microalgal Community in Urban Wetlands

Microalgae are emerging as one of the most promising sources of biofuel because of their high photosynthetic efficiency and faster replication as compared to any other energy crops. Although, the concept of using microalgal lipid as a source of fuel is very mature, its approach in benefiting both environmental and energy-related is a frontier research area today. Algal community for the production of lipid depends on the physical, chemical as well as biological variables of aquatic ecosystems. This communication focuses on achieving the lipid haracterization of the microalgal community collected from four wetlands and one agricultural field of Bangalore, Karnataka with a wide range of environmental characteristics. Results reveal significant change in lipid component with change in algal community and chlorophyll content which was explained by community structure analysis and chlorophyll estimation. The presence of Triacyl glycerol (TAG) was examined through thin layer chromatography (TLC). The profile of TAG was further confirmed through Gas chromatography – mass spectroscopy (GC-MS). This study confirms the potential of algal community towards meeting growing demand for alternate sustainable fuel.