Satellite imagery
Satellites are one of the most used means in agriculture to perform remote sensing: satellite imagery in fact allows to monitor crops remotely in a precise and efficient way.
Spatial and temporal resolution of satellites
There are many satellites that acquire multispectral images from space: the most common are Sentinel-2 and Landsat 8 (both used in Agricolus platform), PlanetScope, Iride, Sentinel-1 (work in progress).
The images obtained have a different spatial resolution: Landsat 8 provides data with a spatial resolution of 30 mt, while Sentinel-2 of 10 mt; the temporal resolution for Landsat 8 is every 16 days, while for Sentinel-2 every 3/5 days (depending on the areas).
The regular passage of the satellites determines the availability of the data in several phases of the growing season, but it is also important to underline that during the satellite transit, where the area under examination is covered by clouds, the data are not usable.
Data processing
Agricolus has developed a highly innovative proprietary technology designed to autonomously manage the entire process of acquiring and processing satellite imagery.
Raw data are downloaded directly from official sources, processed internally, and made available to the end user without the need for external services or intermediaries.
Specifically, through the Copernicus Data Space Ecosystem portal, access is granted to Sentinel-2 satellite data. Once acquired, these data are processed directly within the Agricolus infrastructure, where various vegetation indices essential for crop monitoring are calculated.
- Vigour indices: useful for assessing the overall growth of the plants
- Water stress indices: which indicate possible water deficiencies
- Chlorophyll indices: useful for estimating the crop’s nutritional status
Agricolus has developed a highly innovative proprietary technology designed to autonomously manage the entire process of acquiring and processing satellite imagery.
Raw data are downloaded directly from official sources, processed internally, and made available to the end user without the need for external services or intermediaries.
Specifically, through the Copernicus Data Space Ecosystem portal, access is granted to Sentinel-2 satellite data. Once acquired, these data are processed directly within the Agricolus infrastructure, where various vegetation indices essential for crop monitoring are calculated.
- Vigour indices: useful for assessing the overall growth of the plants
- Water stress indices: which indicate possible water deficiencies
- Chlorophyll indices: useful for estimating the crop’s nutritional status
This information is made available both on the Agricolus mobile app and on the web platform, enabling farmers to make informed, timely decisions based on objective data.
This information is made available both on the Agricolus mobile app and on the web platform, enabling farmers to make informed, timely decisions based on objective data.
The benefits offered by this technology are several:
- Creation of new customized indices, developed according to the specific needs of crops, climatic conditions, or agronomic practices;
- Advanced management of raw data, such as the ability to apply filters to eliminate images affected by clouds or other disturbances;
- Tailored processing, which can be adapted to individual farms, research projects, territorial needs, or specific crops.
This is a scalable and modular solution, applicable not only to satellite data processing but also to other types of complex data, such as weather information.
In other words, the technology developed by Agricolus provides a solid and flexible base for the autonomous and customized management of any data stream from external sources, representing a key element in the evolution of digital agriculture.
This is a scalable and modular solution, applicable not only to satellite data processing but also to other types of complex data, such as weather information.
In other words, the technology developed by Agricolus provides a solid and flexible base for the autonomous and customized management of any data stream from external sources, representing a key element in the evolution of digital agriculture.
Vegetation indices obtained from satellite
When talking about satellite images, and remote sensing in general, it is necessary to introduce the concept of vegetation index to understand how they allow the monitoring of the health of crops without the need to go to the field.
Vegetation indexes are a key tool of Digital Agriculture: the use of satellite data and their correct interpretation reduce the interventions in the field and make sustainable, from the economic point of view, the activities in the fields.
The indices can describe the vigor of the plant, providing a measure of its general health, or specific problems such as water stress or the amount of chlorophyll.
Types of vegetation indices
NDVI: it allows to evaluate the health of the vegetation, analyzing the reflectance of the vegetation in the Red and NIR bands.
SAVI: allows to evaluate the conditions of vegetation development in the emergency and early stages of development, as it applies a correction to bare soil.
LAI: leaf area index that estimates the leaf area of the plant expressed in m2 on m2.
TCARI/OSAVI: specific index that allows to identify chlorotic areas within the field.
GNDVI (Green-NDVI): it provides an indication of the health of the vegetation and reduces the saturation effect when the vegetation is particularly developed.
NDMI: specific index that evaluates the water content of the vegetation, therefore usable only with developed vegetation.
NMDI: can be used to assess the water content of the soil; in case of bare soil, a high index value indicates dry soil. In the presence of vegetation, a high index value indicates that the plant is not under water stress.
Historical and comparative data
In agriculture it is essential to monitor and compare crop development on different fileds during different years.
The four main steps for the interpretation of vegetation indices are the multi-temporal analysis and the comparison between indices:
- assessment of the phenological stage of the plant;
- analysis of the historical trend of indices to assess whether there are anomalies and whether they are related to known phenomena;
- identification of indices to be compared;
- comparison between indices to identify critical areas to be verified in the field.
The comparison of satellite images allows us to evaluate the relationships between different indices (such as low vigor and high water stress) and the possible causes of their variations.
The graph of the historical trend of vegetation indices also allows to keep track of what happens in the field and to evaluate the changes compared to the data of previous years.
