Abstract:
Livestock farming in South Asia, including Sri Lanka, is vital for food security, rural livelihoods
and economic stability. However, it faces escalating challenges such as climate variability, land
degradation and disease outbreaks, leading to notable declines in global livestock productivity
and resource efficiency. Traditional animal husbandry methods often lack precision, contributing
to unsustainable practices and lower outputs. This study explores the integration of Global
Positioning System (GPS) and remote sensing technologies to establish a sustainable framework
for livestock management. The applied research methodology highlights a mixed-methods
approach applied across varied agro-ecological zones, incorporating satellite imagery, GPS-based
animal tracking and spatial analysis of grazing patterns, water access, vegetation coverage and
land use trends. Analysis revealed strong links between livestock well-being and proximity to
water sources and vegetation-rich areas, while movement data highlighted optimal grazing
routes. Remote sensing also enabled early identification of overgrazed zones and potential
disease-risk areas, supporting targeted interventions such as rotational grazing and stress
mitigation strategies. These findings demonstrate how geospatial tools can support evidence
based decision-making, enhance resource allocation and improve animal welfare by reducing
environmental impact. By applying geospatial analysis, livestock systems can shift toward
precision farming models that are both economically and ecologically sustainable. The study
underscores the importance of adopting digital tools in animal husbandry to boost productivity
and resilience. Policymakers and stakeholders are encouraged to invest in affordable geospatial
technologies, capacity building and open-access data systems to scale these innovations across
rural livestock communities. This research contributes to the growing body of knowledge on
digital agriculture and highlights the transformative potential of geospatial innovation in
fostering resilient and data-driven livestock farming systems.
