How do cow herders spot water in the Sahara? With satellites, of course.

For most of his 50 years, Abdoul Ag Alwaly, a cattle herder in northern Mali, used the same way of finding water for his cows. He would pay a motorcyclist or camel driver to roam the desert surrounding the city of Gao and check the levels of scattered creeks and wells. The process was expensive, time-consuming, and risky—sometimes he’d march his herd for days only to find that he’d received a bad tip, or that another herd had gotten there first.

In recent years climate change has made the search even harder, Alwaly says. Where he lives, in the Sahel, the vast strip of arid scrubland south of the Sahara Desert, temperatures are rising faster than the global average, droughts are more frequent, and vegetation is scarcer. Erratic rainfall has made traditional watering holes unreliable. Animals frequently perish during the search, Alwaly says, and competition for water can easily turn violent.

So he’s trying a new approach. Over the last year, Alwaly, who leads a local union of livestock herders, has started to look for leads in satellite images. “With your phone and 25 francs”—about four US cents— “you’ll know, and can move with a lot more certainty,” he says.

Across the continent, rising temperatures and unpredictable rains are a serious threat to millions of small farmers and herders. Real-time, hyper-local satellite data can be used to detect early warning signs of drought and crop failure. As satellite imaging gets cheaper, more prolific, and higher in resolution, and the massive quantities of data it yields become easier for computers to manage and interpret, a growing number of private companies and nongovernmental organizations are finding ways to put it directly into the hands of people who deal with the effects of climate change every day.

Alwaly uses an experimental service offered by the telecom company Orange. It analyzes a daily feed of pictures from the European Space Agency’s Sentinel satellites to give nomadic herders in northern Mali up-to-date information about where they can find water and feed. Alwaly can call or send a text to a call center in Mali’s capital city, Bamako, and a technician will review a color-coded satellite image showing a pale landscape shot through with vegetation and offshoots of the Niger River. That will point to where the water is—no camel ride necessary.

Introduced in November 2017, the service has fielded 1,300 phone calls and 88,000 text messages from more than 50,000 users, according to SNV, a Dutch NGO that helped develop it.

Since the first Earth-observing satellite went into orbit in 1972, images taken from space have made visible humanity’s footprint on the planet. We can watch glaciers and rain forests shrink as cities and mega-farms grow, glean insights about water, soil, and other natural resources, and monitor disasters like wildfires and drought.

Today, satellite imaging can not only track these large, long-term trends but give farmers real-time information on particular parts of their farms. In the early days, the pixels in satellite images were measured in square kilometers, but now commercial satellites can reach resolutions of 30 square centimeters (one square foot), while public-access data from government agencies like NASA typically has a resolution of 10 to 100 square meters. Just as important, the number of Earth-observing satellites in orbit is increasing rapidly—it’s up to more than 700, according to a Union of Concerned Scientists database. That makes it easier to find an image of any given location taken in the last day or two.

Satellite-guided precision agriculture is already common in the US and Europe. Only just emerging in Africa, it could be particularly useful for farmers and herders who are spread over vast areas but who carry cell phones in their pockets.

Nearly 1,000 miles (1,600 kilometers) south of Gao, in central Ghana, cocoa—the country’s top cash crop—is highly vulnerable to rising temperatures, drought, and warm-weather-loving pests. Agronomists project that the land area suitable for cocoa production there could contract significantly by 2030. To help farmers boost their productivity under those conditions, agricultural field agents are using a new tablet-based app to create what are called Farm Development Plans. Launched in July by the SAT4Farming consortium, consisting of the nonprofit Rainforest Alliance and Grameen Foundation, the Netherlands-based Satelligence and Waterwatch Projects, and the French commodity crop trader Touton, the app uses machine- learning software trained to analyze satellite images of cocoa farms taken both in visible light and in the near-infrared spectrum, which documents wavelengths that plants reflect during photosynthesis. The images, combined with field-based agronomic science and farmer surveys, allow the software to generate regular checkups of tree health— based on metrics like the density of vegetation and the closeness of trees—and recommendations for how to improve it.

That kind of assessment is simple enough to do from the ground for a single farm. But a sky-high view allows farm consultants—who, in Africa, can have thousands of clients over a large area—to spot troubled farms at a glance throughout a difficult growing season. Then they can make adjustments—a different pruning pattern, or a targeted dose of fertilizer—in response to drought or other difficulties. “If I recommend that a farmer add a few hundred kilos of fertilizer, but the satellite shows that nothing has changed, then we can assess what might have gone wrong,” says Selasse Gidiglo, a SAT4Farming program officer.

Satellite images aren’t perfect. Clouds and dust often block the view, especially over desert and tropical areas. The images also don’t eliminate the need for on-the-ground surveys—they may show a herder a source of water without revealing that it’s on private property or that the vegetation is something animals can’t eat. “The fact that something is green in the satellite image doesn’t mean it’s necessarily suitable for livestock,” says Peter Hoefsloot, an Amsterdam-based analyst who helped develop the service Alwaly uses.

“The whole possibility of it is quite strange to me,” says Nana Kwame Korang, a cocoa farmer in Sunyani, Ghana, who works with SAT4Farming. “But if it can give me a higher yield during dry periods, I like it very much.”