Drones Agriculture

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Drones in agriculture:applications and outlook

EXPO 2015 Salar Bybordi PhD, DEIB - Politecnico di Milano,[email protected]

Luca Reggiani PhD, Researcher, DEIB - Politecnico di [email protected]


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Outline

Drones in agricultureEXPO 2015

Unmanned Aerial VehiclesApplications

UAVs for agriculture

LimitationsFuture development

Conclusions


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Unmanned Aerial Vehicles


Unmanned Aerial Vehicles (UAVs), commonly known as drones,can beunpiloted aerial vehiclesorremotely piloted aircrafts.

Rotary wing Fixed wing

More efficient aerodynamics

longer flights, higher speedLarge space for take-off and landing

Easier to pilot, agile maneuvering

Vertical take-off and landing

[*] "Parrot AR.Drone 2.0", N. Halftermeyer Wikimedia Commons[o] "InView Unmanned Aircraft" by Fasicle, http://www.barnardmicrosystems.com/ - Wikimedia Commons

[*] [o]


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Unmanned Aerial Vehicles


UAVs are knowing a huge, increasing interest.

The worldwide marketof drones forcivilian use:

$609 million in 2014 forecast to reach$4.8 billion in 2021

Civilian sector is about 5% of the global market but the growthrate is higher.

Compound annual growth rate: CAGR= 19%The defense sector has a growth rate = 5%


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Civilian applications:filmmaking,search operations,

inspecting and surveying,delivering supplies,monitoring and data acquisition

In the following f ields:Emergency servicesSecurityEnvironmental protectionAgriculture

Engineering and architectureMediaBusiness

Applications



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Data acquisitionRemote sensing

Integration with sensor networks

Monitoring (fires, fields, animals )

Chemical and biological treatments

Precision agriculture


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Optimization of the treatments

only where and when necessary fertilizers cut down till to 20 40 %

Reduction and prevention of wastewater consumption in some cases till to almost 90 %

Reduction of labor and material costs

Reduction of pollutionSmall UAVs are electrical machines.

Reduction of the risksAutomatic and continuous analysis of the processes and field status.Prevention.

Precision agriculture: advantages


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Remote sensing

Remote sensing regards the acquisit ion of informationabout an object

or surface area by means of propagated signals(e.g. electro magneticwaves as optical or microwave signals), typically emitted and/or receivedby aerial vehicles(e.g. satellites, aircrafts, UAVs).

Main limitations of satellites and aircrafts:

expensiveneed expertiseweather dependent

resolutionavailability of multi-temporal data


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UAV low alti tude remote sensing: main technologies

Visible-band, near-infrared, multi-spectral, hyperspectral cameras

Plant and soil analysisHeight, growth, health, vegetation indexes.

Irrigation, property, moisture, erosionSpecific chemical components

Thermal imaging

Plant and soil analysisIrrigation, maturity, temperature

Laser scanners

Plant and soil analysisHeight, growth, topographical maps




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UAV low altitude remote sensing: main technologies

Data can be acquired in2D/3Dand as a function oftime

Multi-temporal analysis:

a drone can repeat the survey periodically (even everyfew hours) in order to appreciate the variations of the

field status.

Opportunity of a very advanced managementandorganizationof work, irrigation, fertilization andnecessary treatments.


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UAV low altitude remote sensing: main outputs

Vegetation indicesPlant growth, counting, diseases identificationImpact of chemical or biological treatments

Temperature and moisture

Water issues and irrigation systemsGround erosion and modifications, topography

Acquisition of data for insurance claims (e.g. afterstorms)

Of course drones usage changes with the seasons

plants

soil


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Remote sensing: examples

Plant height and growthcan be derived byLaser Scanning

3D image analysisMicrowave radars.

["Plodozmian" by Lesaw Zimny - Wikimedia Commons]

The estimated height isaffected by errorsaround few cm.

These systems areapplied to corn, wheat,rice fields.


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Moisture estimation

Thermal cameras

Visible and near-infrared

reflectance

Microwave sensors

Mult i-spectral images

["Irrigation1" by Paulkondratuk3194 - Wikimedia Commons]


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NDVI (normalized difference

vegetation index) estimation:

Spectral reflectance

measurements acquired

in the visible (red) and

near-infrared regions

Other properties can be derived fromNDVI: biomass, chlorophyll concentration

of leaves, plant productivity,

["SUAS_StardustII_Ndvi_sml" by Idetec uav - Wikimedia Commons]


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Integration with sensor networks

UAVs operations can be controlled by means of feedbacks (wirelesssignals) from asensors network deployed on the ground.

For example:the areas covered by treatments or irrigation can becontrolled by ground sensors in presence of wind or inabsence of precise flight plans.


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Limitations


Drone usage is weather dependant(in particular wind, rain)

National regulations

Italy possible till to 25 kgFrance possible till 150 kgUS new rules in 2015

ICAO (International Civil Aviation Organization) ispreparing rules for 2018.

According to EASA, (European Aviation SafetyAgency), open use could be for flights within

500 meters and maximum altitude = 150 m.


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Future development


Technological steps

Increase of UAVs autonomy: automatic piloting andoperations

Automatic analysis for real-time decisions

Increase of precision in remote sensing

Advanced integration with sensor networks and robots onthe ground


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Conclusions


Today UAVs are a reality in many fields of agriculture.

However precision agriculture is about to know a further

progress and UAVs will play a crucial role.

Important savings(20% - 90%) in terms of water, chemicaltreatments and labor are expected.

Flight regulations are an issue but UAVs, for mostagriculture applications, have low weight and fly at lowaltitudes over uninhabited and private areas


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Bibliography


[1] C. Zhang, J. M. Kovacs, The application of small unmanned aerial systems for precisionagriculture: a review, Precision Agriculture, Springer, 2012.

[2] MIT Technology Review, Agricultural Drones. Relatively cheap drones with advancedsensors and imaging capabilities are giving farmers new ways to increase yields and reduce

crop damage, http://www.technologyreview.com/featuredstory/526491/agricultural-drones/,2015.

[3] I. Colomina, P. Molina, Unmanned aerial systems for photogrammetry and remote sensing:a review, ISPRS Journal of Photogrammetry and Remote Sensing, June 2014.

[4] D. Anthony, S. Elbaum, A. Lorenz, C. Detweiler, On Crop Height Estimation with UAVs,2014 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[5] J. Primicerio, S. F. Di Gennaro, E. Fiorillo, L. Genesio, E. Lugato, A. Matese, F. P. Vaccari, Aflexible unmanned aerial vehicle for precision agriculture, Precision Agriculture, Springer, 2012.

[6] L. Hassan-Esfahani, A. Torres-Rua, A. M. Ticlavilca, A. Jensen, M. McKee, Topsoil MoistureEstimation for Precision Agriculture Using Unmanned Aerial Vehicle Multispectral Imagery,2014 IEEE InternationalGeoscience and Remote Sensing Symposium,2014.

[7] F. G. Costa, J. Ueyama, T. Braun, G. Pessin, F. S. Osorio, P. A. Vargas, The Use ofUnmanned Aerial Vehicles and Wireless Sensor Network in Agriculture Applications, 2012IEEE InternationalGeoscience and Remote Sensing Symposium,2012.

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