Kalpa: Empowering Artificial Intelligence-Driven Geospatial Analysis for Multidisciplinary Applications

In the age of big data, artificial intelligence (AI) is transforming Earth sciences by enabling efficient analysis and visualisation of complex datasets and fostering innovative approaches to solve age-old geoscientific challenges. Kalpa, a Python-based free and cross platform software, represents a pioneering step in this direction. Built with versatility at its core, Kalpa seamlessly integrates AI and machine learning workflows into geoscience applications, offering  customization through its Python plugin architecture. What sets Kalpa apart is its ease of use, even for non-experts. Its intuitive interface lowers the learning curve, enabling a broader audience—including researchers, professionals, and enthusiasts—to leverage advanced geospatial and AI tools without requiring extensive technical expertise.

Kalpa's capabilities span advanced 3D visualization, geospatial data processing, and machine learning model development. It supports global and regional raster and vector dataset visualisation and processing, allowing for interactive analysis in both geographic and cartesian coordinates. With tools to process satellite imagery, geological and geophysical data, uncrewed aerial vehicle (UAV) data, and digital geological maps, Kalpa caters to a wide range of applications, from mineral exploration to natural hazard forecasting. Its machine learning integration supports supervised and unsupervised algorithms for applications such as lithological mapping, mineral prospectivity mapping, land cover and land usage studies, agricultural productivity mapping and natural disaster management. In this study, we demonstrate Kalpa’s transformative potential through three case studies:

• Lithological Mapping in Ladakh, India: Utilizing LANDSAT and SRTM data, we produced accurate lithological maps for this geologically complex region.
• Copper Prospectivity Mapping in Northwest India: Combining remote sensing, geophysical, and geological data, Kalpa predicted copper mineralization zones, with all known deposits falling within areas of predicted probabilities exceeding 0.70.
• Landslide Susceptibility Mapping in Uttarakhand, India: Using remote sensing datasets, Kalpa identified high-risk landslide zones, supporting disaster management efforts.

Kalpa’s user-friendly interface, robust machine learning integration, and publication-ready export capabilities position it as a powerful tool for advancing geoscience research and practical applications. By bridging the gap between domain expertise and cutting-edge AI methodologies, Kalpa empowers Earth scientists, environmental researchers, and GIS professionals to analyze, model, and predict with unprecedented efficiency and precision. This software marks a new frontier in the application of AI to Earth sciences, enabling multidisciplinary research and fostering innovative solutions to pressing geoscientific challenges.