Remote Sensing
Introduction
Welcome to the documentation for INVISION Remote Sensing Variables. INVISION, a product of INTENT, offers advanced remote sensing capabilities through a partnership with Planet Labs. When subscribing to satellite imagery through INVISION, users gain access to various remote sensing variables crucial for monitoring and managing agricultural fields. This documentation provides detailed explanations of each variable, their significance in agriculture, and the different types of imagery available.
1. NDRE (Normalized Difference Red Edge)
Description: The Normalized Difference Red Edge (NDRE) index is a spectral index sensitive to changes in the chlorophyll content of leaves. It uses the red edge and near-infrared bands of the electromagnetic spectrum.
Importance in Agriculture:
- Chlorophyll Monitoring: NDRE is particularly effective for monitoring chlorophyll content, which correlates with plant health and nitrogen levels.
- Early Detection: It helps in early detection of stress in crops, allowing for timely intervention.
- Precision Agriculture: Assists in making informed decisions about fertilization and other agricultural inputs.
2. NDVI (Normalized Difference Vegetation Index)
Description: The Normalized Difference Vegetation Index (NDVI) is a widely used index for quantifying vegetation health. It utilizes the red and near-infrared bands.
Importance in Agriculture:
- Vegetation Health: NDVI provides a clear indication of vegetation vigor and density.
- Crop Monitoring: Helps in assessing crop growth stages and biomass production.
- Yield Prediction: Useful for predicting crop yields based on vegetative growth patterns.
3. SAVI (Soil Adjusted Vegetation Index)
Description: The Soil Adjusted Vegetation Index (SAVI) is similar to NDVI but includes a correction factor to minimize the influence of soil brightness in areas with sparse vegetation.
Importance in Agriculture:
- Soil Influence Reduction: Reduces soil brightness impact, providing more accurate vegetation monitoring in sparse vegetation areas.
- Improved Accuracy: Enhances the accuracy of vegetation indices in arid and semi-arid regions.
4. EVI (Enhanced Vegetation Index)
Description: The Enhanced Vegetation Index (EVI) improves upon NDVI by reducing atmospheric influences and soil background signals, enhancing sensitivity to high biomass regions.
Importance in Agriculture:
- High Biomass Sensitivity: Better captures variations in dense vegetation areas.
- Atmospheric Correction: Provides more reliable data under varying atmospheric conditions.
- Detailed Analysis: Useful for detailed vegetation studies and monitoring.
5. RGB (Red, Green, Blue)
Description: RGB imagery captures visible light in the red, green, and blue bands, providing images that resemble what the human eye sees.
Importance in Agriculture:
- Visual Assessment: Allows for visual inspection of crop conditions and field status.
- Communication: Facilitates easy communication of field conditions to stakeholders.
- Baseline Monitoring: Serves as a baseline for comparing other remote sensing data.
6. Biomass
Description: Biomass estimation from satellite imagery measures the total mass of living plants in a given area, providing insights into crop productivity and health.
Importance in Agriculture:
- Productivity Assessment: Indicates overall crop productivity and potential yield.
- Nutrient Management: Helps in managing nutrient applications based on biomass data.
- Sustainable Practices: Supports sustainable agriculture practices by monitoring crop growth and health.
Key Differences and Importance
- Bands Used: Different indices and imagery types use varying combinations of spectral bands, which influence their sensitivity to specific plant characteristics and environmental conditions.
- Spatial Resolution: All types provided by PlanetScope offer high spatial resolution of 3 meters, enabling detailed field analysis.
- Temporal Resolution: The daily revisit rate ensures that changes and trends can be detected promptly, which is critical for time-sensitive applications like agriculture.
- Applications: Each imagery type has unique applications in agriculture, from monitoring chlorophyll content (NDRE) to providing visual assessments (RGB) and estimating biomass (Biomass).
| Imagery Type | Description | Bands Used | Spatial Resolution | Temporal Resolution | Key Applications |
|---|---|---|---|---|---|
|
ND RE |
Measures chlorophyll content using red edge and NIR bands | Red Edge, NIR | 3 meters | Daily | Chlorophyll monitoring, early stress detection, precision agriculture |
| NDVI | Quantifies vegetation health using red and NIR bands | Red, NIR | 3 meters | Daily | Vegetation health, crop monitoring, yield prediction |
| SAVI | Adjusted vegetation index minimizing soil brightness impact | Red, NIR (+ correction factor) | 3 meters | Daily | Accurate vegetation monitoring in sparse areas, arid region analysis |
| EVI | Enhanced vegetation index reducing atmospheric and soil influences | Red, NIR, Blue | 3 meters | Daily | High biomass sensitivity, reliable under varying atmospheric conditions, detailed vegetation analysis |
| RGB | Captures visible light, similar to human vision | Red, Green, Blue | 3 meters | Daily | Visual assessment, communication of field conditions, baseline monitoring |
| Biomass | Estimates total mass of living plants | Multi-spectral (varies) | 3 meters | Daily | Productivity assessment, nutrient management, sustainable practices |
Sources:
- PlanetScope data specifications and product details (Sentinel Hub) (Planet Developer Center) (Planet) (cloudeo AG).