Affiliation:
1. University of Veterinary and Animal Sciences, Lahore, Pakistan
2. Asia Pacific University of Technology, Malaysia
3. University of Agriculture, Faisalabad, Pakistan
4. University of Narowal, Pakistan
Abstract
Climate change poses a significant threat to global food security and environmental sustainability. Traditional agricultural practices often struggle to adapt to increasing weather variability and extreme events. This chapter explores the potential of AI and GIS technologies to build climate-resilient agriculture and promote environmental sustainability. AI algorithms can analyze vast datasets, including weather patterns, soil characteristics, and crop productivity data, to identify vulnerabilities and recommend strategies for farmers to adapt to changing conditions. Some applications that can help improve agricultural production are mapping climate risk, predicting drought, and finding the best places to put different crops. The chapter explores the context-specific solutions that combine technological innovation with traditional practices, fostering collaboration among farmers, researchers, developers, and business leaders to optimize resource use, enhance crop yields, and mitigate environmental impacts despite challenges like data availability and equitable access.