Chaitanya Baliram Pande – författare

This book presents a case study on a semi-arid region, Maharashtra State, India, and discusses problems concerning a broad range of areas: sustainable watershed development; watershed management; groundwater condition; land and resource development plans; thematic maps on e.g. land use, soil types and soil erosion; groundwater recharge site selection; remote sensing and GIS; and soil and water conservation structures. The book’s focus is on creating a land and water resource development plan and environmental management for groundwater recharge development using remote sensing and GIS technology in the case study region, which is situated in the Akola and Buldhana districts of Maharashtra. Its goal is to promote awareness for sustainable watershed development and planning in semi-arid regions by highlighting the problems of, and plans for, groundwater and surface water pollution and sustainable watershed development. These aspects are of great importance to watershed and natural resources planning and management, and need to be exploited and managed sustainably.   

Given its scope, the book will be of interest to all scientists, research scholars and graduate students of remote sensing, hydrology, hydrogeology, water resource engineering, agricultural engineering and related areas who want to acquire detailed information on watershed planning and sustainable water resource planning in semi-arid regions, or to find new methodologies and techniques for studying the feedback mechanisms between forms and processes. 

The book provides an in-depth analysis of the major issues related to the conservation of threatened medicinal plants in the Indian Himalayan region. The book is a comprehensive resource and sustainability of challenges and conservation strategies that highlights the critical role of medicinal plants in traditional healthcare systems and identifies the significant threats that these plants face due to various anthropogenic and natural factors. The book covers ten major themes that are critical to understanding the sustainability conservation of threatened medicinal plants in the Indian Himalayan region. It provides an essential resource for researchers, policymakers, and practitioners interested in the sustainability conservation of threatened medicinal plants in the Himalayan area. The book provides an overview of the major issues related to medicinal plant sustainability conservation and suggests strategies for the sustainable management of these plants. The authors have provideda comprehensive and insightful analysis of the sustainability conservation status of medicinal plants in the region, highlighting the urgent need for concerted efforts to conserve these valuable resources.

With rapid urbanization defining the 21st Century, cities face mounting challenges in achieving sustainability, equity, and functionality. This book explores how innovative technologies such as Artificial Intelligence (AI) and Large Language Models (LLMs) can transform urban development by offering intelligent, data-driven solutions. LLMs go beyond automation, acting as co-creators in addressing environmental sustainability, resource management, and equitable development. By analyzing regulations, best practices, and real-time data on phenomena such as air pollution and traffic, these models empower urban planners to design smarter, more sustainable cities while fostering collaboration across disciplines.

Divided into five sections, the book explores the diverse applications of LLMs, from optimizing renewable energy systems and enhancing urban planning to revolutionizing construction practices and improving resource efficiency. It highlights case studies on integrating AI with smart infrastructure, ecological balance, and disaster resilience. While underscoring their transformative potential, the book also examines ethical considerations such as bias, privacy, and environmental impact. More than a collection of research, this work is a call to action for urban planners, data scientists, policymakers, and researchers to harness AI responsibly in building greener, more equitable urban futures.