Sentinel 1 Synthetic Aperture Radar Based Flood Mapping in Punjab Pakistan From 2015 to 2025 for Livestock Disaster Preparedness

In the vast, flat plains of Punjab, Pakistan, the monsoon season brings life-giving rain to crops and livestock, but it also brings a recurring threat: flooding. For the farmers who raise cattle, goats, and sheep in these riverine areas, a flood is not just a temporary inconvenience; it is a disaster that can wash away food, destroy shelters, and scatter herds, leaving families without their primary source of income or food security. To protect these animals and the people who depend on them, officials need to know exactly where the water goes, how often it returns to the same spots, and which communities are most at risk. This is where modern technology steps in, offering a way to see the landscape through the clouds. Satellites equipped with a special kind of radar can "see" the ground even when the sky is overcast and rainy, a time when traditional cameras are blinded. By tracking these radar signals over many years, scientists can map the history of floods, distinguishing between permanent rivers and the temporary, dangerous sheets of water that spread across farmland.

A team of researchers, working with veterinary experts and government officials, used this technology to create a detailed, ten-year history of flooding across Punjab, from 2015 to 2025. They focused on the province's most vulnerable regions, using a cloud-based system to process thousands of images from the Sentinel-1 satellite. This satellite sends out radar waves that bounce off the Earth's surface; when the waves hit smooth, standing water, they bounce away differently than they do when hitting dry land or crops. By setting a specific rule to identify these smooth, wet surfaces, the team could automatically draw maps of where floodwaters had spread each year. They did not just look at one bad year; they built a timeline to see which areas were hit repeatedly. Their maps revealed that flooding in Punjab is not uniform. While some years saw relatively small areas covered in water, others were much more severe. In 2017, the mapped flood area was about 2,869 square kilometers, but by 2025, that number had more than doubled to 7,044 square kilometers. The most severe years, including 2015, 2016, 2023, and 2025, saw massive inundation, while years like 2017, 2018, and 2021 saw significantly less.

The maps showed a clear pattern: the water does not spread randomly. Instead, it concentrates in specific corridors, particularly in the southern and southwestern parts of the province. Districts like Rajanpur, Dera Ghazi Khan, and Muzaffargarh emerged as the most frequently affected areas, sitting in low-lying river valleys where water naturally pools. These are the places where the same land gets flooded year after year, creating a cycle of risk for the livestock that graze there. The researchers also identified "recurrent flood zones," areas that were underwater in at least two different years during the decade. These zones are critical because they represent the places where farmers and their animals are most likely to face repeated trauma, loss of feed, and displacement. By pinpointing these locations, the study provides a spatial guide for where emergency planning should be focused, rather than guessing where the next flood might strike.

To ensure these radar maps were accurate, the team cross-checked their findings with optical images from another satellite, Sentinel-2, which takes standard photographs. They compared the radar maps of the 2025 floods with clear photos taken before and after the water arrived. The two sources matched up, confirming that the radar was correctly identifying the flooded areas. This validation gave the team confidence that their maps were reliable enough to be used for real-world decision-making. However, the study also acknowledged that while the maps show where the water was, they do not automatically tell the whole story of what happened to the animals. The radar cannot count the number of goats or cattle, nor can it measure the specific diseases that might spread after a flood. This is where human experience becomes essential.

To bridge the gap between satellite data and the reality on the ground, the researchers spoke with representatives from ten livestock-owning families living in the Sutlej River floodplain, an area known for its recurring floods. These conversations revealed the specific challenges that data alone cannot capture. The farmers described how difficult it is to move animals when water rises quickly, often leaving them tied up and unable to reach higher ground. They spoke of the loss of stored feed and the struggle to find clean drinking water when everything is contaminated. They also highlighted the fear of disease, noting that when animals are crowded together on small patches of high ground to escape the water, they become more susceptible to infections and parasites. The farmers explained that they often have to sell their surviving animals at low prices just to survive, which makes it nearly impossible to rebuild their herds afterward.

The insights from these families were combined with the satellite maps to create a practical guide for disaster preparedness. The researchers identified ten key areas where action is needed, ranging from better evacuation plans to improved storage for animal feed. They suggested that farmers should identify safe, high-ground shelters in advance and move their animals there as soon as warnings are issued. They also emphasized the need for pre-flood vaccinations to protect against diseases that thrive in wet conditions, and the importance of having emergency feed ready when normal grazing lands are underwater. The study proposed that local officials should create digital maps that link flood-prone areas with the locations of livestock owners, veterinary clinics, and roads, so that help can be directed exactly where it is needed most.

This work represents a new way of thinking about disaster management in Pakistan, one that combines the broad, objective view of space with the intimate, practical knowledge of the people living on the land. The maps provide a reproducible, scientific basis for understanding where floods happen, while the community input ensures that the solutions are relevant to the lives of the farmers. The researchers noted that while their maps are a powerful tool, they are not a complete solution on their own. To be truly effective, these flood layers need to be combined with up-to-date information about how many animals live in each area, where the veterinary services are located, and what specific diseases are present. Without this local data, the maps remain a general guide rather than a precise plan.

The study concludes that while the technology to map floods is now available and proven, the real challenge lies in using that information to protect the most vulnerable. The maps show that the southern and southwestern parts of Punjab are the most at risk, and the conversations with farmers show exactly what those risks look like in daily life. By bringing these two perspectives together, the researchers have provided a foundation for better planning. They have shown that knowing where the water will go is only the first step; the next step is using that knowledge to ensure that when the water rises, the animals and the people who depend on them are not left behind. The work serves as a reminder that effective disaster preparedness requires both the high-tech view from above and the grounded wisdom of those who live through the floods.