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New Tool Uses Satellite Data to Combat Olive Fruit Fly

Researchers have developed a tool using satellite data to combat olive fruit fly infestations in changing climates.
By Paolo DeAndreis
Apr. 23, 2025 17:47 UTC

At a recent con­fer­ence held at the European Space Agency in Frascati, Italy, researchers show­cased a tool that can help com­bat and pre­vent olive fruit fly infes­ta­tions in the face of cli­mate change.

The project stems from inte­grat­ing the bio­log­i­cal cycles of the olive tree and the olive fruit fly with rel­e­vant satel­lite data.

We should con­sider this project as a new con­tri­bu­tion to ongo­ing pest con­trol efforts,” Luigi Ponti, a researcher at the Italian National Agency for New Technologies, Energy and Sustainable Economic Development, told Olive Oil Times.

You can’t con­duct ten years of field tri­als across all of Puglia. But this model lets you do that vir­tu­ally within min­utes.- Luigi Ponti, researcher, ENEA

A cru­cial source of data for the project comes from satel­lite obser­va­tions made using mod­er­ate-res­o­lu­tion imag­ing spec­tro­ra­diome­ter (MODIS) sen­sors installed aboard two NASA satel­lites, Terra and Aqua.

Over the past two decades, these sen­sors have mea­sured sev­eral sur­face vari­ables, such as veg­e­ta­tion indices, while also pro­vid­ing highly reli­able land sur­face tem­per­a­ture data.

They mea­sured sur­face tem­per­a­ture from space with daily tem­po­ral res­o­lu­tion, also cap­tur­ing approx­i­mate daily max­i­mum and min­i­mum tem­per­a­tures thanks to their over­pass times,” Ponti said. 

See Also:Decoding the Olive Fly’s Symbiotic Secret

Previous research by Markus Neteler, founder of Mundialis, a German part­ner com­pany in the project, devised a method to extract tem­per­a­ture data from the satel­lite obser­va­tions.

Additionally, a method­ol­ogy based on sta­tis­tics and spa­tial infor­ma­tion was devel­oped to fill in the gaps caused by cloud cover, since MODIS sen­sors can­not see through clouds.

The research pre­sented by Ponti and his col­leagues aimed to link this broad dataset to a MODIS-derived veg­e­ta­tion index known as the Normalized Difference Vegetation Index (NDVI).

MODIS NDVI mea­sures the amount of green veg­e­ta­tion on Earth’s sur­face, pro­vid­ing infor­ma­tion about land cover through­out the year. That infor­ma­tion can be used to enhance tem­per­a­ture data derived from MODIS satel­lites.

The effec­tive­ness of this approach builds on ear­lier research by a team of Israeli sci­en­tists who devel­oped a method to cal­i­brate MODIS-derived land sur­face tem­per­a­tures using NDVI data.

They installed ther­mome­ters inside olive tree canopies and found that the tem­per­a­ture derived from MODIS satel­lites, once cor­rected using MODIS NDVI, esti­mated canopy tem­per­a­ture bet­ter than the near­est weather sta­tion,” Ponti said.

Thanks to these data, it is pos­si­ble to esti­mate the tem­per­a­ture expe­ri­enced by both the plant and the olive fruit fly.

If we want real agri­cul­tural impact, we need to observe what hap­pens day by day, because that’s how plants and inter­act­ing organ­isms oper­ate,” Ponti noted.

The need for highly pre­cise infor­ma­tion about agroe­cosys­tems led to the devel­op­ment of the phys­i­o­log­i­cally based demo­graphic model of the olive agroe­cosys­tem in col­lab­o­ra­tion with the non-profit sci­en­tific con­sor­tium CASAS Global.

The mod­el’s out­put is a detailed and real­is­tic bio­log­i­cal rep­re­sen­ta­tion of the life cycles of the olive tree and the olive fruit fly, includ­ing their inter­ac­tions.

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This type of mod­el­ing, which com­bines a top-down approach (using satel­lite data) with a bot­tom-up approach (bio­log­i­cal mech­a­nisms), over­comes the lim­i­ta­tions of both and pro­vides a pow­er­ful tool for strate­gic analy­sis in agri­cul­tural man­age­ment.

The com­bi­na­tion of satel­lite obser­va­tions, bio­log­i­cal mod­el­ing and open-source geo­graphic infor­ma­tion tools allows researchers to visu­al­ize and ana­lyze dynam­ics with unprece­dented tem­po­ral (daily) and spa­tial (250-meter) res­o­lu­tion.

For the plant, [the model] sim­u­lates leaf pop­u­la­tions, branch pop­u­la­tions and root pop­u­la­tions. With the same base model, it sim­u­lates birth, growth, aging and death of plant organs or insect stages,” Ponti said.

So we use the same model to describe both insects and plants in our olive – olive fruit fly sys­tem,” he added.

For the plant, the pri­mary resource is the energy in solar radi­a­tion, along with nutri­ents and water from the soil. For the fly, the resource is the plant it feeds on: how many olives it can find to lay eggs. Its vital rates (growth, repro­duc­tion) depend on olive avail­abil­ity.

This gives the mod­els a degree of bio­log­i­cal real­ism, because they’re con­strained by the real-world resource con­straints that organ­isms face,” Ponti said.

If the fly doesn’t find olives, it goes into repro­duc­tive qui­es­cence, just like in nature. So, it’s not a tool to pre­dict’ an infes­ta­tion exactly, but it can tell you that under cer­tain con­di­tions, the envi­ron­ment is suit­able for one,” he explained.

You can’t say the fly will arrive tomor­row,’ but you can say this area cur­rently has con­di­tions that would sup­port fly devel­op­ment,’” Ponti added.

Just like weather fore­casts, bio­log­i­cal fore­casts are chal­leng­ing. Weather fore­cast­ing itself is con­sid­ered unre­li­able beyond a short period of about three days.

Still, we use weather data as input for our bio­log­i­cal mod­els, so uncer­tainty com­pounds,” Ponti said. What our mod­els add is strate­gic infor­ma­tion.” 

Forecasting can indi­cate when to act, but it can­not tell you why some­thing is hap­pen­ing or how to pre­pare more effec­tively in a chang­ing cli­mate.

That requires under­stand­ing mech­a­nisms and dynam­ics in the field,” Ponti said. That’s the point: if the olive fly is a key pest, how can we man­age it bet­ter eco­nom­i­cally and oper­a­tionally, espe­cially under cli­mate change, where the assump­tions about cli­mate are obso­lete and the con­se­quent man­age­ment rules may no longer apply?” 

See Also:Researchers Develop Algorithm to Predict Harvest Potential from Climate Data

We showed this clearly in our work in Andalusia,” he added. For instance, in some areas, there are not enough chill­ing hours to induce flow­er­ing in olives any­more. In warmer areas, the fly pop­u­la­tion stays below thresh­old due to high tem­per­a­tures that approach or exceed the fly’s ther­mal tol­er­ance.” 

Using more pre­cise cli­mate and veg­e­ta­tive infor­ma­tion can help pol­i­cy­mak­ers reshape pest con­trol strate­gies.

Region-spe­cific inter­ven­tions and poli­cies, such as those in Andalusia, where inte­grated con­trol orga­ni­za­tions mon­i­tor and pre­scribe treat­ments, rely on ana­lyz­ing past data.

For exam­ple, mon­i­tor­ing might tra­di­tion­ally start in May, but if win­ters are warmer, it may be more use­ful to start ear­lier,” Ponti said.

The olive fruit fly has rapid pop­u­la­tion growth, is closely syn­chro­nized with the olive tree’s life­cy­cle, and can repro­duce year-round as soon as olive fruit and cli­mate are suit­able. This makes it a sig­nif­i­cant pest of olive crops world­wide.

If not mon­i­tored and con­trolled early, it gets out of hand quickly,” Ponti said. So the best approach may be to mon­i­tor even dur­ing the quiet’ sea­son, late win­ter or early spring. With future cli­mate trends, being proac­tive will be cru­cial.”

As the weather becomes increas­ingly unpre­dictable and extreme events become more com­mon, to the point where they are no longer excep­tional, agri­cul­tural insti­tu­tions find it increas­ingly chal­leng­ing to plan effec­tive pro­tec­tion ser­vices.

This mod­el­ing tool gives you a real­is­tic view of what’s hap­pen­ing in the field, some­thing you could never get through field obser­va­tions at this scale, for this dura­tion,” Ponti said.

In Puglia, we sim­u­lated 20 years of olive and fly dynam­ics on a daily timescale at 250-meter res­o­lu­tion for hun­dreds of thou­sands of loca­tions, thanks to cloud com­put­ing pro­vided by the Italian part­ner Recube,” he added.

Getting the same kind of data from field obser­va­tions would sim­ply be impos­si­ble. This kind of sys­tem gives you that field-level insight essen­tially for free,” Ponti con­tin­ued.

Since cli­mate affects plants and insects dif­fer­ently, their inter­ac­tions and bal­ance shift.

That’s impor­tant to know. You could sim­u­late dif­fer­ent man­age­ment sce­nar­ios, such as ear­lier inter­ven­tion, and eval­u­ate how ben­e­fi­cial it is,” Ponti said.

You can’t con­duct ten years of field tri­als across all of Puglia. But this model lets you do that vir­tu­ally within min­utes,” he added. So, while it’s not meant for short-term fore­cast­ing, because that would require per­fectly detailed real-time bio­log­i­cal and cli­mate data, it’s great for describ­ing and plan­ning strate­gi­cally.”

The NASA Aqua and Terra satel­lites are on track to be decom­mis­sioned. As a result, researchers are already work­ing on using other satel­lites, such as those launched by Eumetsat and the European Space Agency, that carry sim­i­lar sen­sors.

The new gen­er­a­tion of the agency’s Sentinel satel­lites has high spa­tial res­o­lu­tion and can observe sur­face tem­per­a­tures.

But they cur­rently don’t have daily tem­po­ral res­o­lu­tion, although there are plans to reach daily res­o­lu­tion in future Sentinel mis­sions,” Ponti said.

That means they can’t pro­vide daily max­i­mum and min­i­mum tem­per­a­tures, which are cru­cial for cir­ca­dian rhythms, the nat­ural cycles that reg­u­late life on Earth,” he explained.

Satellite-derived and other cli­mate data, com­bined with phys­i­o­log­i­cally based demo­graphic model intel­li­gence, may prove cru­cial in the years ahead, not just for olive groves, but for many crops that researchers have already stud­ied.

The project was car­ried out within the frame­work of the TEBAKA project and is based on the ICT infra­struc­ture devel­oped by the Med-Gold project, both of which are funded by the European Union.

For this data to inform strat­egy, pub­lic insti­tu­tions and regional orga­ni­za­tions must take action.

What’s miss­ing are the research and project resources to sup­port the required cloud com­put­ing while main­tain­ing and extend­ing the time series of the dataset we used, which cov­ers about 20 years, from 2003 to 2023. That’s a long and valu­able period,” Ponti said.

Climate change is not some­thing that will hap­pen at the end of the cen­tury. It is some­thing that is hap­pen­ing right now,” he con­cluded. Statistical analy­ses of what hap­pened in the past in a given area are a great tool, but they are no longer enough, because cli­mate is chang­ing rapidly.”


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