Information note: Plantae specializes in the design, development, and marketing of wireless technology and weather stations, utilizing satellite imagery and sensors to conserve water and improve crop production. For this reason, Plantae sensors are increasingly being used in plantations in Spain, Portugal, Italy, Saudi Arabia, Morocco, and Latin America.
Agriculture faces the challenge of producing more food while using fewer resources and reducing its environmental impact. In this context, precision agriculture has become one of the main technological tools for improving production efficiency.
Satellite Imagery and Sensors Applied to Agriculture
Earth observation satellites, such as Sentinel-2, capture information invisible to the naked eye, allowing for the assessment of crop physiological status through spectral bands, with a frequency of just a few days and spatial resolutions that enable the evaluation of crop behavior at the plot scale.
The information obtained is processed using algorithms capable of generating agronomic indices that reflect the physiological state of the vegetation, water availability, and the temporal evolution of each crop.
Using vegetation indices such as NDVI (Normalized Difference Vegetation Index), Plantae technicians can identify areas with varying vegetative vigor, detect water stress, nutritional problems, or potential disease outbreaks before they become evident in the field.
This information generates variability maps that help producers understand how each sector of the plot is evolving and make data-driven decisions.
NDVI: Vegetative Vigor Assessment
One of the most widely used indicators in satellite imagery is the NDVI, calculated from the reflectance in the red and near-infrared bands.
This index provides an indirect measure of photosynthetic activity and vegetation vigor. High values are generally associated with healthy plants, high biomass, and adequate leaf development, while low values may indicate water stress, nutritional deficiencies, diseases, or developmental problems.
NDVI maps allow for:
Detecting intra-plot variability.
Identifying areas with low yield potential.
Prioritizing field inspections.
Optimizing variable-rate fertilizer application.
Monitoring crop phenology.
In thematic maps, green colors typically represent areas of high vegetative vigor, while yellow and reddish tones indicate areas with lower photosynthetic activity.
In thematic maps, green colors typically represent areas of high vegetative vigor, while yellow and reddish tones indicate areas with lower photosynthetic activity.
The NDMI (Normalized Difference Moisture Index) is one of the most widely used indices in precision agriculture to assess vegetation moisture content and detect water stress before it becomes visible in the crop.
The range is between -1 and +1:
High values (>0.6): dense and healthy vegetation.
Low values (<0.2): bare soil or severe stress.
What is the NDMI?
The NDMI is calculated using the near-infrared (NIR) and short-wave infrared (SWIR) spectral bands:
The SWIR band is particularly sensitive to the water content present in leaves, so the index provides a very useful estimate of the vegetation’s water status.
Interpretation of values ranging from -1 to +1
- NDMI > 0.4: Vegetation with good moisture content.
- NDMI between 0.2 and 0.4: Moderate moisture.
- NDMI between 0 and 0.2: Possible onset of water stress.
- NDMI < 0: Dry vegetation, bare soil, or areas with severe water deficit.
Thematic maps typically use the following:
Dark green: High moisture.
Light green: Adequate moisture.
Yellow: Limited moisture.
Orange and red: High water stress.
NDMI allows for the identification of areas within the plot where plants begin to lose moisture before visible wilting symptoms appear. This facilitates more precise irrigation scheduling.
Early detection of water stress
While NDVI indicates vegetation vigor, NDMI can detect water availability problems several days before plant vigor declines.
Irrigation Uniformity Assessment Using Satellite Imagery and Sensors
By comparing NDMI maps within the same plot, the following can be detected:
Clogged drippers.
Pressure problems in specific areas.
Areas with over- or under-irrigation.
Failures in valves or hydraulic systems.
Monitoring of Woody Crops
In crops such as olive groves, almond orchards, pistachio orchards, citrus orchards, or vineyards, NDMI is especially useful for monitoring water status during critical development and ripening phases.
NDWI: Monitoring Water Content
Additionally, the NDWI (Normalized Difference Water Index) allows for estimating the water content of vegetation and detecting water stress.
This index uses the spectral response of near-infrared and shortwave infrared bands to identify changes in crop moisture.
NDWI maps facilitate:
- Early detection of water deficits.
- Efficient irrigation scheduling.
- Evaluation of irrigation system uniformity.
- Identification of areas with excess or insufficient water.
- Reduction of losses due to over-irrigation.
Temporal comparison of NDWI images allows observation of how crops respond to irrigation events, rainfall, or periods of drought.
GNDVI (Green Normalized Difference Vegetation Index)
GNDVI replaces the red band used in NDVI with a green band, increasing its sensitivity to chlorophyll and nitrogen content.
Applications
- Nutritional assessment.
- Detection of nitrogen deficiencies.
- Optimization of variable-rate fertilization.
- Monitoring of actively growing crops.
In extensive crops, vineyards, and orchards, it often detects nutritional anomalies earlier than NDVI.
NDRE (Normalized Difference Red Edge)
NDRE uses the Red Edge band, a spectral region particularly sensitive to physiological changes in vegetation.
Applications
Early stress detection.
Advanced biomass assessment.
Monitoring of dense crops.
Identification of productivity losses.
While NDVI can become saturated when vegetation cover is very high, NDRE maintains high sensitivity in well-developed crops.
Therefore, it is widely used in:
- Vineyards.
- Intensive olive groves.
- Almond orchards.
- Pistachio orchards.
- Citrus orchards.
SAVI (Soil Adjusted Vegetation Index)
SAVI incorporates a correction factor that minimizes the spectral influence of the soil.
Applications
- Newly planted crops.
- Plots with low vegetation cover.
- Analysis in early phenological stages.
- Evaluation of germination and establishment, the phase in which seeds germinate and plants begin to emerge from the soil after sowing.
It is especially useful when a large part of the observed area is still bare soil.
RGB Images
RGB images correspond to conventional photography obtained by satellites, drones, or aircraft.
Applications
- Visual damage identification.
- Validation of spectral indices.
- Plant counting.
- Weed detection.
- Monitoring of irrigation infrastructure.
- Preparation of technical reports.
RGB images allow for on-site confirmation of anomalies detected using spectral indices.
Summary of satellite image and sensor indices used by Plantae for advanced crop monitoring
Index | What it measures | Main application |
NDVI | Vegetative vigor | General crop condition |
GNDVI | Chlorophyll and nitrogen content | Nutrition and fertilization |
NDRE | Physiological state in developed crops | Stress and productivity |
NDWI | Water content | Water management |
NDMI | Internal moisture of vegetation | Early water stress |
SAVI | Vegetation correcting soil influence | Young crops and low cover |
Satellite Imagery and Sensors to Understand Soil Conditions
Information from satellite imagery and sensors installed directly in the field records critical variables:
- Volumetric soil moisture.
- Soil and ambient temperature.
- Electrical conductivity.
- Solar radiation.
- Evapotranspiration.
- Precipitation.
- Wind speed and direction.
The data is transmitted in real time to digital platforms that provide precise information on the conditions of each plot. Integrating this information with satellite imagery provides a much more accurate view of the crops’ water and agronomic needs.
Smart Irrigation and Efficient Water Use
One of the main benefits of using satellite imagery and sensors is the optimization of irrigation. By combining sensor data with satellite information, Plantae can determine when, where, and how much to irrigate with greater precision.
This approach helps avoid both water deficits and excesses, improving plant development and reducing resource consumption. It also contributes to lowering the energy costs associated with pumping and distributing water.
In regions where water availability is limited, these tools represent a strategic solution for increasing the sustainability of agricultural production.
Benefits for Producers and the Environment
The application of precision agriculture technologies offers multiple advantages:
- Continuous monitoring of crop health.
- Early detection of anomalies and problem areas.
- Optimization of water and fertilizer use.
- Reduction of operating costs.
- Increased crop yield and quality.
- Reduction of the environmental impact associated with agricultural activity.
Intelligent Irrigation Management
- Reduction of water consumption by 20% to 40%, depending on the crop and local conditions.
- Improvement of production uniformity.
- Minimization of nutrient losses due to leaching. – Reduce energy costs associated with pumping.
- Increase the sustainability of the operation.
