CHANDAN M C
Sessions
Over recent years, Mysore, a district in Karnataka, India, has seen remarkable urban growth and infrastructural development, transforming its landscape significantly. This study examines how this urban expansion influences property values, using data from 2014 and 2024 to forecast property values for 2034 with a Random Forest regression model. We focus on 110 key locations, looking at factors such as closeness to the central business district, railway station, bus stand, and local amenities like schools and hospitals. By finding the strongest correlations between these elements, we establish a relationship between property values and these factors to predict future values.
Our findings highlight Mysore's vibrant economic growth and its potential for sustained progress. These insights are crucial for the real estate market, providing valuable information to make informed decisions about future property values amid ongoing urban development. By analyzing how urban growth impacts property values through sophisticated statistical models, this study sheds light on how infrastructural improvements and strategic locations drive real estate trends. The expected significant rise in property values by 2034 underscores Mysore's economic dynamism and its appeal as an emerging urban hub.
We conducted a thorough analysis of various factors affecting property values, focusing on proximity to essential services and transportation hubs. These elements significantly influence property desirability and accessibility. Our use of the Random Forest regression model enables accurate predictions of future property values by understanding complex relationships between these variables. The strong correlation between guideline values and market values provides a reliable basis for predicting future real estate trends. This correlation is essential for stakeholders, including developers, investors, and policymakers, as it supports strategic decision-making based on market projections.
The expected significant rise in property values indicates that Mysore is poised for considerable growth, driven by strategic developments and improved infrastructure. By understanding these trends, stakeholders can make informed decisions to capitalize on Mysore’s ongoing urban expansion, ensuring that investments and development strategies align with the city's projected economic vitality and growth potential. Our analysis highlights that proximity to the central business district, bus stops, and railway stations are key determinants of property values, greatly influencing market prices. We project a significant increase in property values, estimating a 118% rise by 2034.
To visualize these future values, we employ Voronoi polygons, which offer a clear spatial representation of the predicted property value distribution. This approach provides stakeholders, including developers, investors, and policymakers, with valuable insights into future market trends. By understanding the impact of these location factors, they can make informed decisions regarding investments and development strategies. The anticipated rise in property values underscores the ongoing urban development and economic growth in Mysore, highlighting its potential as a thriving urban center.
In summary, this study provides an in-depth analysis of the relationship between urban growth and property values in Mysore. By employing advanced regression models and detailed location-based data, we have developed a robust forecast for property values in 2034. Our findings indicate a significant projected increase in property values, highlighting Mysore's continuous development and potential for future growth. These insights are essential for the real estate market, offering valuable guidance for future investments and development strategies in Mysore. The study emphasizes the impact of key factors such as proximity to the central business district, bus stops, and railway stations on property values. By understanding these dynamics, stakeholders, including developers, investors, and policymakers, can make informed decisions to navigate the evolving real estate landscape. The anticipated rise in property values underscores Mysore’s economic vitality and its promise as a thriving urban center, driven by strategic infrastructure development.
Keywords: Mysore, Urban growth, Property values, Regression model, Infrastructure, Stakeholders
Reservoirs play a crucial role in global water resource management, hydroelectric power generation, and flood control. However, their construction often entails significant ecological and socio-economic impacts, necessitating thorough environmental assessments. The Mekedatu Reservoir Project, situated on the Cauvery River in the Ramanagar district of Karnataka, India, holds paramount significance. Aimed at supplying the Bengaluru Metropolitan Region and its surroundings with drinking water, the project also endeavors to generate 400 MW of renewable energy annually. Despite its benefits, the project comes with ecological costs, as approximately 5252.40 hectares of revenue, forest, and wildlife land will be submerged. This necessitates a detailed evaluation of its potential environmental consequences.
This study identifies a knowledge gap in the existing literature regarding the ecological implications of the Mekedatu Reservoir Project. It seeks to fill this void by forecasting land use and land cover (LULC) changes for the years 2000, 2010, and 2020 using the Random Forest method, and assessing the submergence area for different levels of the proposed reservoir. Catchment delineation is performed using the Soil and Water Assessment Tool (SWAT). Additionally, the Cellular Automaton-Markov Chain technique is employed to predict land use and land cover changes for the year 2030. Integrating these methodologies, the research provides a holistic understanding of the project's environmental footprint.
The land use and land cover analysis revealed significant shifts from 2000 to 2020, with forest cover decreasing from 71.54% to 60.71% and barren land increasing from 19.55% to 29.56%. The projected land use and land cover for 2030 shows further forest reduction to 58.28% and barren land increasing to 31.11%. These changes highlight a trend towards deforestation and land degradation, posing severe ecological threats. The submergence area at the proposed reservoir Full Reservoir Level is estimated to be 5252.4 hectares, distributed as 6.62% water, 19.55% barren land, 71.54% forest area, and 2.29% built-up area for the year 2000. The inundation of these areas will lead to significant biodiversity loss, affecting numerous plant and animal species.
In line with Sustainable Development Goals, which advocates for sustainable water management, this study emphasizes the importance of informed decision-making and sustainable development practices. The findings underscore the need for new ecologically sensitive areas and the establishment of wildlife corridors, conservation zones, and afforestation programs to mitigate the adverse impacts. Continuous environmental monitoring and research are essential to track biodiversity impacts and adjust conservation strategies accordingly.
Policy implications of this study suggest that due process of law, linked with the principle of natural justice, must be adhered to in ensuring environmental balance. Recommendations from the World Commission on Dams (WCD) highlight the need to reduce the negative impacts of dams by increasing the efficiency of existing assets and minimizing ecosystem impacts. Policymakers must understand the long-term ecological consequences of such mega projects and explore alternatives. Sustainable development models must be based on equality and natural justice.
Future research should focus on the socio-economic impacts of the Mekedatu Reservoir Project, particularly the displacement of local communities. This includes conducting detailed socio-economic assessments, inclusive resettlement planning, livelihood restoration programs, and initiatives to preserve cultural heritage. Continuous monitoring and long-term studies are crucial to ensure the well-being of resettled populations and to balance development with environmental and social sustainability.
In summary, this study advances the understanding of environmental impact assessment in reservoir projects, providing valuable insights for stakeholders and policymakers. It highlights the critical need for sustainable development practices that ensure equitable access to water resources while preserving environmental integrity.
Keywords: Environmental Impact Assessment, Reservoir Project, Machine Learning, Random Forest, Markov Chain, Cellular Automaton, Land Use Changes, Submergence Area, Sustainable Development Goals, Water Resource Management.