GIS-based Decision Support System (DSS) for Recommending Retail Outlet Locations

Many Information Technology (IT) tools play a vital role in the business world due to their wider applicability. Extremely competitive retail environment necessitates retailers to choose new store locations strategically. GIS with its capability to manage, display and analyze business information spatially, is emerging as one of the powerful location intelligence IT tool.  The purpose of this paper is to explore the possibility of strategic retail outlet location through online Decision Support System (DSS) in Hyderabad Metropolitan city, India. The procedure makes use of data, information and software from Web-based Geographical Information Systems (GIS) to generate online analysis, mapping and visualization systems. These procedures are integrated and synchronized with appropriate data layers (multi data layer system) to arrive at better decisions.  This DSS combines different data layers through spatial methodological analysis to arrive at possible solution for ideal retail store location. Keywords: Retail store site selection; spatial data layers; open source web GIS; DSS

Spatial Decision Support System for Managing Agricultural Experimental Farms

Developing Geospatial Experimental Agricultural Farm

Climate Change and Indian Agriculture: Challenges and Adaptation Strategies

Not AvailableClimate change reflects long term changes in temperature, relative humidity, rainfall and other climate variables. The factors causing climate change include both natural as well as human factors. Agriculture in India is predominantly monsoon dependent. However, the rise in temperature, uneven rainfall distribution and delayed onset of monsoon have led to drought or flood across different parts of the country. The horticulture crops are exceedingly prone to climate change owing to long economic life of the plant which requires huge initial investment and cultivating these crops has made farmers more vulnerable to climate change. There is a demand for climate smart horticultural practices or interventions which are customized to suit local needs. Strategies like conservation agriculture, natural resources conservation, reforestation, checks on population growth and pollution, reduction of greenhouse gas emissions, breeding drought resistant crops, tolerant to pests and diseases, early maturity, etc. are the need of the hour. Use of hi-tech horticulture practices will have to be implemented to meet the ever-changing dynamic challenges that emerged due to climate change. Identi cation of socio-economic factors that affect the adoption of the adaptation and mitigation strategies will help in formulating location specific strategies.Not Availabl

Revisão: Modelos de otimização-simulação para a gerenciamento e monitoramento de aquíferos costeiros

The literature on the application of simulation-optimization approaches for management and monitoring of coastal aquifers is reviewed. Both sharp- and dispersive-interface modeling approaches have been applied in conjunction with optimization algorithms in the past to develop management solutions for saltwater intrusion. Simulation-optimization models based on sharp-interface approximation are often based on the Ghyben-Herzberg relationship and provide an efficient framework for preliminary designs of saltwater-intrusion management schemes. Models based on dispersive-interface numerical models have wider applicability but are challenged by the computational burden involved when applied in the simulation-optimization framework. The use of surrogate models to substitute the physically based model during optimization has been found to be successful in many cases. Scalability is still a challenge for the surrogate modeling approach as the computational advantage accrued is traded-off with the training time required for the surrogate models as the problem size increases. Few studies have attempted to solve stochastic coastal-aquifer management problems considering model prediction uncertainty. Approaches that have been reported in the wider groundwater management literature need to be extended and adapted to address the challenges posed by the stochastic coastal-aquifer management problem. Similarly, while abundant literature is available on simulation-optimization methods for the optimal design of groundwater monitoring networks, applications targeting coastal aquifer systems are rare. Methods to optimize compliance monitoring strategies for coastal aquifers need to be developed considering the importance of monitoring feedback information in improving the management strategies