Satellite images using Sentinel 2, Landsat 8, МODIS and VIIRS

The products shown on this website are derived from high-resolution and low-resolution satellite images. For high-resolution products, we combined Sentinel 2 and Landsat 8 data, while for the low-resolution ones we used MODIS and VIIRS data. Where resolution is the smallest dimension of a feature or detail that appears in a satellite image.


Sentinel 2 and Landsat 8
These are considered high-resolution satellites with a maximum resolution of 10 m for Sentinel 2 and 30 m for Landsat 8. These satellites are designed to monitor the use of land, vegetation, forest and water resources, as well as natural disasters.
The majority of the high-resolution products available are generated every 10 days, using the images acquired during the last month. New high resolution images are acquired by the satellites every 5 days, however often the ground is obscured by cloud cover, which is why composite images are created using the best data collected over a monthly period. The first products at 20 m resolution are derived from data acquired in 2013 and are being added to on a regular basis. While the optical image (RGB) is derived using only Sentinel 2 images at 10 m resolution.

These are considered as low-resolution satellites with a maximum resolution of 250 m for MODIS and 375 m for VIIRS. The products are produced combining data from MODIS and VIIRS together. One of the advantages of these satellites is the higher frequency with which they acquire images compared to the higher resolution satellites. There are 3 images per day from MODIS and from VIIRS. All the products are generated every 10 days, and their exact resolution depends on the specific product.


Optical (RGB)
The RGB product, a “real colour” product, is a combination of the red, green and blue bands to produce an image of what the Earth’s surface looks like.
The data are cloud masked across the time period, which means that there should not be any visible clouds in the images. However, it may sometimes be possible to see strange features in the images due to small imperfections from the cloud mask algorithm and solar illumination.

Vegetation Index (NDVI) (Normalized Difference Vegetation Index)
The Normalised Difference Vegetation Index (NDVI) is a proxy for how much vegetation is present on the ground. The index is calculated by the absorption and reflection of the red and near-infrared bands by plants.
The NDVI is scaled between -1 and 1, with 1 describing very high vegetation and 0 describing no vegetation at all (bare land). Values less than 0 are usually water, snow, cloud or other non-vegetative phenomena.

Pasture Anomaly
The Pasture Anomaly product compares the pasture biomass values from a given time period to the historic time-averaged values from the same time period. It produces a product as a percentage of the pasture biomass currently compared to the long term historical values.
This product shows the percentage of how much the pasture has improved or degraded. It goes from -100% which means that there is 100% less current pasture than the long term average, to 100% more current pasture than the long term average. If the pasture biomass is the same as the long term average, a value of 0 will be returned. Sometimes values outside this range can be returned, but these outlier values are cropped to either -100% or 100%, depending on whether it is extremely low or high. White pixels represent where the snow is.

Pasture Biomass
The Pasture Biomass product is the conversion of NDVI data to pasture biomass in kg/ha using an equation obtained comparing NDVI with ground measurement data. This should only be considered as an indication of the amount of pasture biomass that is present on the ground.

Pasture Trend
The Pasture Trend product compares the pasture biomass values from a given time period to the previous time period. As a result, it produces a product which shows the difference in pasture biomass (measured in kg/ha) of the current time period compared to the previous time period.

Snow Percentage
Using the Snow Mask product, the Snow Percentage product gives an estimation of the percentage of snow in a pixel for the time period considered. For example, if the snow percentage is 50, it means that there was snow for 50% of the time.

NDSI (Normalized Difference Snow Index)
The Normalised Difference Snow Index (NDSI) is used to display where snow is present. It is calculated using the green band and a short wave infrared band.
This index is scaled between -1 and 1, with full snow cover for values greater than 0.4 and no snow cover for values lower than 0.

NDDI (Normalized Difference Drought Index)
The Normalised Difference Drought Index (NDDI) is a combination of NDVI (vegetation) and NDWI (water content), and it is used to determine the level of drought in a specific area.
The index is scaled between -∞ and ∞, where low positive values indicate no drought conditions and high positive values indicate drought conditions. Negative values generally indicate areas which don’t correspond to pasture, due to having either a negative NDVI or NDWI value.

VHI (Vegetation Health Index (VHI))
The Vegetation Health Index (VHI) combines the TCI and VCI to create a drought index which uses information both about the vegetation levels and temperature.

NDWI (Normalized Difference Water Index)
The Normalized Differential Water Index is used to monitor changes of water content in leaves, using infrared and shortwave infrared bands.
The index is scaled between -1 and 1, where values less than 0.3 indicate no water being present and values greater than 0.3 indicate the presence of water. Usually, green vegetation has values between -0.1 and 0.4.

VCI (Vegetation Condition Index (VCI))
The Vegetation Condition Index (VCI) is an indicator of the current status of the vegetation relative to the historical values.
VCI values range from 0 to 1, reflecting changes in vegetation conditions, from dry to wet. For VCI greater than 0.7 the vegetation is in good condition, values between 0.3 and 0.7 reflect moisture conditions close to normal, while values less than 0.3 signal that vegetation is in a stress state or drought condition.

LST (Land Surface Temperature)
The Land Surface Temperature (LST) product measures the temperature at the surface of the Earth. It is a relatively good proxy of - but not the same as - the air temperature at the Earth’s surface. The LST is closely related to the humidity, vegetation cover, air temperature wind and other factors affecting the temperature balance.