Vegetation Index (VI) is the transformation of two or more value multispectral bands into one value, designed to learn vegetation conditions.
Skyglyph proposes vegetation indices insights from two providers - Planet and Sentinel:
| Name of data Provider | The resolution, meters per pixel | Frequency, average | Available bands |
| Planet | 3.7 meters per pixel | 1-2 times per day | 8 spectral bands |
| Sentinel-2 | 10-60 meters per pixel (depends on spectral band) | once a week | 13 spectral channels: 4 channels (10m); 6 RE and shortwave infrared channels (20m); 3 channels (60m) |
Currently, we provide the next vegetation indices (in the process of extension):
CORE INDICES
| Name | Explanation | When to Use | Availability from Sentinel data | Availability from Planet data |
| NDVI | Normalized Difference Vegetation Index. NDVI = (NIR-R) / (NIR + R) This index is an indicator of healthy green vegetation. NDVI is used to measure biomass. However, it can be saturated in dense vegetation. Also, this vegetation index is quite sensitive to soil brightness and atmospheric effects. | NDVI is the most common vegetation index in remote sensing. It can be used throughout the whole crop production season except when vegetation cover is too scarce, so its spectral reflectance is too low. NDVI values are the most accurate in the middle of the season at the stage of active crop growth | 10m | 3m |
| gNDVI | Green Normalized Difference Vegetation Index gNDVI = (NIR-G) / (NIR + G) This index is similar to NDVI, except that it measures the green spectrum from 540 to 570 nm instead of the red spectrum. This index is more sensitive to chlorophyll concentration than NDVI | monitor vegetation with dense canopies or at maturity stages | 10m | 3m |
| yNDVI | Yellow Normalized Difference Vegetation Index yNDVI=(NIR-Yellow)/(NIR+Yellow) Uses a Yellow spectral band of 610nm. No equivalent in Sentinel-2. Not so saturated in dance vegetation and give a more "smooth" result in case of variation vegetation. Also, it reacts less sharply in comparison to NDVI in case of light atmospheric haze. | It is good for measuring the mid and later stages of vegetation. | 3m | |
| yrDVI | Yellow-Red Normalized Difference Vegetation Index yrDVI=(Yellow-Red)/(Yellow+Red) Uses Yellow and Red indexes. The index is based on the observation that the yellow spectrum reflects healthy vegetation more strongly than the red spectrum. | A positive index means vegetation, negative soil, or withered vegetation. | 3m | |
| SAVI | Soil Adjusted Vegetation Index SAVI = ((NIR-RED) / (NIR + RED + L)) * (1 + L) Designed to minimize soil impact. Suitable for analysis of young crops; for arid regions with sparse vegetation (less than 15% of the total area) and open soil surfaces. Huete (1988) proposes the optimal value of L = 0.5 to take into account fluctuations in soil background. | For analysis of young crops; for arid regions with sparse vegetation (less than 15% of total area) and exposed soil surfaces. | 10m | 3m |
| OSAVI | Optimized Soil Adjusted Vegetation Index. SAVI = (1.16) * (NIR-RED) / (NIR + RED + 0.16)) - shifted (-0.5) OSAVI reflects the variability of vegetation density. In addition, it is not sensitive to soil brightness (in the presence of different soil types). It is resistant to variability in soil brightness and has an increased sensitivity of more than 50% to vegetation. This index is best used in areas with relatively sparse vegetation, where the soil is visible through the canopy and where NDVI is saturated (high plant density) | to monitor areas with low-density vegetation with bare soil areas through the canopy. The adjustment allows greater soil variation in OSAVI compared to SAVI when canopy cover is low. OSAVI has better sensitivity to canopy cover exceeding 50%. | 10m | 3m |
| gSAVI | Green Soil Adjusted Vegetation Index gSAVI = (NIR-GREEN) * (1 + 0.5) / (NIR + GREEN + 0.5 This index was developed to determine nitrogen deficiency in corn. Similar to SAVI, but uses green spectrum instead of red | 10m | 3m | |
| gDVI | Green Difference Vegetation Index GDVI = NIR-GREEN This index was originally designed with color-infrared photography to predict nitrogen requirements for corn | 10m | 3m | |
| ARVI | Atmospherically Resistant Vegetation IndexARVI= (NIR-2*R+B)/(NIR+2*R-B) | ARVI is most useful in regions of high atmospheric aerosol content. It uses blue light reflectance measurements to correct for the atmospheric scattering effects, that also influence reflectance of red light. | 3m | |
| PRI | Photochemical Reflectance Index (PRI) PRI= (Green-Green1)/(Green+Green1) PRI measures the light-use efficiency of foliage and thus is primarily used as an indicator of water stress and for the assessment of carbon-dioxide uptake by plants. | Range: − 1 to 1 Typical healthy range: − 0.2 to 0.2 It is sensitive to variations in the leaves carotenoid pigments (for example, xanthophyll). These carotenoid pigments are involved in converting the absorbed photosynthetic radiation into fixed carbon. | 3m | |
| GLI | Gleen Leaf Index GLI = (2 x G - R - B) / (2 x G + R + B) This index was originally designed for use with a digital RGB camera to measure wheat cover, where the red, green, and blue digital numbers (DNs) range from 0 to 255. GLI values range from -1 to +1. Negative values represent soil and non-living features, while positive values represent green leaves and stems. | 10m | 3m | |
| rSIPI | Reverse Structure Insensitive Pigment Index rSIPI=(NIR-Red)/(NIR-Cobalt Blue) | SIPI є хорошим індексом для використання в районах з високою мінливістю структури пологу або індексу площі листя. Цей індекс максимізує чутливість до співвідношення масових каротиноїдів і хлорофілу, мінімізуючи при цьому вплив змінної структури покриву. | 3m | |
| VARI | Visible Atmospherically Resistant Index. VARI = (GR) / (G + RB) the index of visual resistance to the atmosphere is minimally sensitive to atmospheric influences. VARI strongly correlates with vegetation fraction (crop density, biomass | This index estimates the fraction of vegetation in an image with low sensitivity to atmospheric effects. | 10m | 3m |
| NDRE | Normalized Difference Red Edge Index NDRE = (NIR + RedEdge) / (NIR + RedEdge) very sensitive to medium and high chlorophyll content in leaves (how green the leaf looks), variability in leaf area, and soil background. High NDRE values represent a higher level of chlorophyll in the leaf than lower values. Hence, red-edge is a good indicator of crop health in the mid to late-stage crops where the chlorophyll concentration is relatively higher. Also, the NDRE could be used to map the within-field variability of foliar nitrogen to understand the fertilizer requirements of the crops. | NDRE is typically used to monitor crops that have reached the maturity stage NDRE is typically used to monitor crops that have reached the maturity stage | 20m | 3m |
| EVI | Enhanced Vegetation Index EVI = 2.5 * (NIR-RED) / (NIR + 6 * RED-7.5 * BLUE + 1)) The Improved Vegetation Index (EVI) is an "optimized" vegetation index designed to enhance the vegetation signal with improved sensitivity in regions with high biomass and improved vegetation monitoring by dissociating the background signal and reducing atmospheric exposure. Uses blue display area to correct background soil signals and reduce weathering, including aerosol scattering | large amounts of chlorophyll, and preferably with minimum topographic effects (non-mountainous regions)large amounts of chlorophyll, and preferably with minimum topographic effects (non-mountainous regions) | 10m | |
| NGRDI | Normalized Difference Green/Red difference Index Visual NDVI = (Green-Red) / (Green + Red) | 10m | 3m |
CHLOROPHYLL GROUP OF INDICES
| Name | Explanation | When to Use | Availability from Sentinel data | Availability from Planet data |
| LCI | Leaf Chlorophyll Index LCI = (NIR-RedEdge) / (NIR + RED) Index for estimating chlorophyll content in full leaf cover areas. | 20m | 3m | |
| CLg | Green Chorpphill Index) or CLg (Chlorophyll green) CLg = NIR / Green - 1 is used to estimate the content of leaf chlorophyll in various species of plants. The chlorophyll content reflects the physiological state of vegetation; it decreases in stressed plants and can therefore be used as a measurement of vegetation health. This index estimates the chlorophyll content of leaves in a wide range of plant species. A wide wavelength of the near-infrared and green color provides a better prediction of chlorophyll content while providing greater sensitivity and a higher signal-to-noise ratio. GCI-based areas distinguish high biomass spots better than NDVI. | To monitor the impact of seasonality, environmental stresses, or applied pesticides on vegetation health. | 10m | 3m |
| CLr | Red Chlorophyll Index or CLr (Chlorophyll red) CLg = NIR / Red - 1 Uses the red multispectral band. Because chlorophyll content directly depends on nitrogen level in plants, responsible for their “greenness”, this vegetation index in remote sensing helps detect areas with yellow or shed foliage. | CLrI values are most useful at the stage of active vegetation development but are not suitable for the season of harvesting. | 10m | 3m |
| CLre | Chlorophyll red-edge CLre = NIR / red_edge - 1 Sensitive to small fluctuations in chlorophyll content and is constant for most vegetation species. | CIre values are most useful at the stage of active vegetation development but are not suitable for the season of harvesting. | 20m | 3m |
WATER GROUP OF INDICES
| Name | Explanation | When to Use | Availability from Sentinel data | Availability from Planet data |
| NDWI | Normalized Difference Water Index NDWI = (G – NIR) / (G + NIR) NDWI = (B03 - B08) / (B03 + B08) proposed by McFeeters, 1996. initially elaborated to outline open water bodies and assess their turbidity, mitigating the reflectance of soil and land vegetation cover | Detection of flooded agricultural lands; allocation of flooding on the field; detection of irrigated farmland; allocation of wetlands. 0.2 – 1 – Water surface, 0.0 – 0.2 – Flooding, humidity, -0.3 – 0.0 – Moderate drought, non-aqueous surfaces, -1 – -0.3 – Drought, non-aqueous surfaces | 20m | 3m |
| NDWIL | Normalized Difference Water Index in Leaves. ndwil = (B08-B11) / (B08 + B11) water content of leaves, proposed by Gao the water content of leaves NDWI uses SWIR (Short Wave Infrared) and NIR channels. NIR reflectance allows analyzing dry matter content in vegetation foliage and internal leaf structure, while SWIR reflectance shows the changes in plant water content and mesophyll structure. When combined, NIR and SWIR bands give a better idea of plant water content because the water in the internal leaf structure impacts the spectral reflectance in SWIR. | 20m | ||
| Moisture Sentinel Index | (B8A-B11) / (B8A + B11) Soil moisture index | 20m |