The DRONE with Multi-spectral Camera: the new Solution for Precision Farming accessible to everyone.

The monitoring and analysis Systems in farming essentially refer to the so called remote sensing and multispectral imaging. These systems primarily ensure the possibility to obtain multi-spectral images of vineyards with satellite optical sensors or airborne devices (DRONES). What practically happens is this: many imges in different spectral band are taken, each characterized by a different ability to reflect incident radiation from parts of objects. The most significant spectral bands for monitoring cultivations are green (555-580 nanometers), red (665-700 nm)  the near infrared (NIR, 740-900 nm).

Very interesting for the analysis of multi-spectral images are vegetative indexes, which are the different mathematical combinations of the reflectance (R) of vegetation in different spectral bands. The two most important indexes are NDVI (Normalized Difference Vegetation Index) and Red/NIR (relationship between red and near-infrared) which combine the reflectance in red and infrared bands.

NDVI: Normalized difference vegetation index
NDVI: Normalized difference vegetation index

The NDVI index is positively correlated to the quantity of plant biomass for surface unit (Lai) and consequently to the vigor of the cultivation. The index has values between -1 e +1; in particular, from 0,1 to 0,3 indicates a bare soil with little turf, while if there is plant biomass the index values are above 0,5.

Red/NIR is related to the è messo in relazione allo physiological state of the cultivation: high Red/NIR (above 1) values show indicate a worsening of the health condition of the plants.

The NDVI images can be used both directly to identify areas with different vegetative vigor or indirectly as  as the basis for subsequent processing through the construction of thematic maps as shown in the image.

Thematic maps concerning the crop yield obtained with multispectral images
Thematic maps concerning the crop yield obtained with multispectral images

The possibility to optically evaluate the cultivation physiological status  is based on the is based on changes that the light radiation suffers when affecting the plant and interacting with its fabrics. Every body, in fact, is characterized by a “spectral signature”, – which derives from the relationship between the incident radiation and the radiation reflected from the body itself – called reflectance. The spectral signature of the leaf tissue of a plant is concentrated in the range of the spectrum between 200 and 2500 nm.

The plant tissue reflects little in red, because these wavelengths are absorbed more by chlorophyll and other pigments, wheras it reflects more in green, which is why this color appears. The reflectance in the infrared is due to the cellular structure of the plant tissue and its water content. At the foliage level, however, the total reflectance is the sum of contributions due to the leaf tissue, the woody parts and the soil.

Riflettanza o "firma spettrale" della vegetazione
Vegetation reflectance or “spectral signature”

From the analysis of the variations of the reflected light in the wavelengths we can obtain important information about the state of the crop which is mainly related to the density of biomass produced (the latter used as an index of force and vigor). Starting from the reflectance data in certain wavelengths vegetation indexes can be calculated, as algebraic combination of the measured spectral values (an example of calculation of NDVI is shown in the picture).

Esempio di calcolo di NDVI
NDVI calculation example

The use of multispectral technology is spreading with increasing frequency also thanks to Solutions with the DRONE with multi-spectral cameras which ensure the most accurate analysis in the shortest time.

Drone per Agricoltura con camera Multispettrale
The Drone for Precision Farming with multi-spectral Camera

These technologies ensure the detection of optical properties of crops both with stations positioned at fixed points in particularly delicate areas, or with mobile devices mounted on dedicated vehicles (DRONES). In this last case, the UAVs must have a GPS to connect the detected data with their position in the field. Surveys with DRONES are designed for use during the course of normal mechanized field operations, so as to interfere as little as possible with the normal Farm business planning.

With Surveys with the DRONE in farming you can obtain a high spatial detail of the information, coupled with the enormous speed acquisition and analysis of the data. This way you can carry a lot of analysis in time and, perhaps, concentrate surveys in more delicate phenological phases.

These new technologies allow vegetation physiological status evaluation with a series or REAL advantages:

  • they allow non-destructive detections, which can be repeated on each plant of the vineyard at different stages of the growing season;
  • they are not in direct contact with the cultivation;
  • they are based on instantaneous phenomena, allowing rapid and appropriate measurements which can be also carried out also by moving vehicles.

Multi-spectral sensors

With regard to technologies usable in a ground sensing system for monitoring the crop, it should be specified that the tools more readily applicable in the short/medium term are those technologies based on silicon, sensitive in the spectral range from visible to near infrared (400-1100 nm).

Esempio di una mappa sullo stato di salute della Canapa
Example of a hemp health condition map

Such maps can provide the farmer diagnostic and/or prescriptive indications since they provide useful information for site-specific management of the foliage,indicating areas which need pruning and on which plants this action is needed more than on others.


Source: http://www.intersezioni.eu/?objselected=177&scheda=view_articolo
Credits: Aldo Calcante (Dottore Agronomo, Ricercatore di Meccanica agraria presso il Dipartimento di Dipartimento di Scienze agrarie e ambientali dell’Università degli studi di Milano); Aira Mena (Assegnista di ricerca presso il Dipartimento di Ingnegneria agraria dell’Università degli studi di Milano).