What is Layers?

Layers is a system that combines Agronomic Knowledge, Remote Sensing, and Artificial Intelligence to provide a proactive field monitoring system.

Food manufacturers and producers face three types of challenges that have a direct and significant impact on gross margins:

  • Management of your crops.

  • Production yields and supply planning.

  • Removable performance

The Layers system is the best ally of the agricultural sector for improving decision-making processes in four areas:

  1. Agronomic monitoring throughout the season

  2. Optimized application of inputs at key moments

  3. Identification of special attention areas (germination failures, crop alerts, etc.)

  4. Planning collection to streamline activities and maximize production and quality

Providing quality and updated information based on the reality of each plant or tree.

¿A quién está dirigida esta documentación?

A cualquier persona que utilice las apps web y móvil de Layers. Verás que las dos aplicaciones te resultarán muy útiles durante las distintas etapas de producción. Por eso, para que tu trabajo sea más eficiente, te recomendamos usar ambas versiones. Por ejemplo, la aplicación móvil puede serte útil para analizar rápidamente la salud de tus cultivos y agregar notas desde cualquier sitio (y añadir fotos si estás en el campo!). Por otro lado, la aplicación web puede ser más conveniente si estás trabajando en la oficina y trabajar con extractos GIS, PDF o SHP. Puedes usar esta versión para planificar el trabajo de campo relativo a la aplicación a tasa variable de fertilizantes, plaguicidas o semillas o, simplemente, cuando quieras comprobar el trabajo de algún operario.

Additionally, for those who use the data generated by Layers but consult it through the API in your ERP or similar system, here you can find answers to the most common questions.

How to use this documentation

This documentation is divided into 8 parts:

  1. Introduction

  2. Products

  3. Agronomist’s Library

  4. Pilot’s Library

  5. Protocols

  6. Developers

  7. Frequently Asked Questions

  8. References

If this is your first approach to Layers, we encourage you to check the “Introduction” section and continue to the “Products” section.

The “Agronomist’s Library” and “Pilot’s Library”, as well as the “Protocols” section and references to the “API”, are reference sections that we hope will help you learn and improve in the use of the tools available to you.

Finally, in the “Frequently Asked Questions” and “References” sections, you will find answers to the most common questions encountered by other users.

If you still have questions, we recommend that you write to the support team (support@hemav.com)

Data Sources

For the generation and updating of the crop mathematical models that Layers relies on, it is necessary to describe the boundary conditions that each plant or tree ‘experiences’ throughout the agronomic campaign.

As shown in the image, there are three groups of changing characteristics that influence growth:

  1. Climate

  2. Soil

  3. Physiology

To have this information, Layers takes data from different sources with different periodicities and resolutions. Below we describe the most relevant ones:

Field Parameters Information and Management

To keep Layers updated, it is essential to have minimum data provided by the user. These data definitively influence the evolution of the crop. Some examples are: sowing date, crop type, variety, irrigation system, fertilization, and historical data.

In order to adjust Layers to the needs of each entity, this information can be entered:

  1. Creating crop geometries and adding information manually

  2. Importing information from all plots and their history through your contact points at HEMAV, either once per season or periodically.

  3. Integrating Layers with your information management system (ERP, SAP, etc.) to ensure that the information is always the most up-to-date. This integration can be two-way, making information collection easy through our API.

Spatially and Temporally Discrete Information

Field Samples

One of the points that makes Layers more robust and complete is the combination of the visualization tool with the ability to integrate samples with field reality. Thus, for many utilities, Layers uses information related to geolocated samples that can be soil, leaf, or fruit (production or quality) and that can be incorporated into the system through the Gauging APP, import through your contact points at HEMAV, or automatically if the user already works with a sample geolocation tool.

In cases where an external entity (e.g., Laboratory) intervenes in the process, the same three types of sample updates are possible: Gauging APP, import in Excel format or similar, or automatic.

Spatially Discrete and Temporally Continuous Information

Meteorology

Meteorology is undoubtedly the set of conditions that has aroused the most interest in humanity since the beginnings of agriculture. Layers is connected to public networks of meteorological stations in all countries that have this infrastructure. In this way, it is possible to know, for example, what the accumulated temperature has been since the time of sowing, if the accumulated precipitation in the first weeks has been sufficient, or if the maximum or minimum records may have negatively affected crop development.

Remote Sensing: Low Spatial Resolution and High Temporal Resolution

Also in the sky but more recent is the use of satellites in agriculture. This technology, in constant development since the ’60s, is one of the pillars of monitoring provided by Layers. Currently, Layers works with different constellations of Sentinel-1, Sentinel-2, Landsat, and Planet.

Satellite: Sentinel-1

Sentinel-1 provides us with the information we call ‘RADAR’ and is allowing us to start overcoming the cloud barrier for some cases and applications.

Satellite: Sentinel-2

Sentinel-2, with an approximate resolution of 10m per pixel and a revisit period of approximately 5 days, provides us with RGB and multispectral information with which we perform the weekly update of crop status.

Satellite: Landsat 8-9

Landsat 8 and 9, with an approximate resolution of 15m per pixel and an approximate revisit period of 10 days, provide us with RGB and multispectral information.

Satellite: Planet

The Planet constellation is a private constellation, with a daily revisit period. The resolution of these satellites is 3.7m per pixel, featuring RGB and multispectral information.

Remote Sensing: High Spatial Resolution and Low Temporal Resolution

We perform detailed flights to obtain high-resolution data of the crop status to integrate with the rest of the input data. This information can come from HEMAV drones or external providers. These flights can occur at different times depending on the phenological phases of your crop. The number of flights depends on the crop and the type of applications to be extracted, with the usual number being between one and three flights per campaign.

The flight time may coincide with the collection of field data that helps us calibrate the system and provide increasingly accurate data.

In the case where the purpose of the flight is multispectral information collection, the three means are: . Rotary wing drone from the HAR series . Fixed wing drone from the HP-2 series . Light aircraft

In flight operations, in addition to the viewer, the pilot must interact with other tools such as Agromom and HLink. More information in Pilot’s Library.

In the case where the flight objective is the collection of high-resolution visual information for generating depopulation layers, depending on the selected package, the information may come from other systems. Ask your contact point at HEMAV if you have any questions about this.