Weather news

Queries for satellite images with VANE SQL v 0.2: Tiles or polygons

Queries for satellite images with VANE SQL v 0.2: Tiles or polygons

Combination of satellite imagery and weather maps

Combination of satellite imagery and weather maps

Weather maps: Rain modeling areas rendered by the VANE openweathermap platform

Maps is a very visually intuitive way for analyzing large-scale weather phenomena like cloudiness, pressure, rains, observing it in dynamic etc.
Maybe you’ve already tried to play out with our “Map Editor” tool - custom styled maps renderer that provides tile layers based on every 3 hr constantly updatable weather data sets.

We have just launched beta Jupyter notebooks on our VANE platform!

We have just launched beta Jupyter notebooks on our VANE platform!

We have just launched beta Jupyter notebooks on our VANE platform! Now you can test your data science algorithms on Landsat8 satellite imagery. Weather and IoT are coming soon! http://owm.io/jupyter/start

Weather risk management on agricultural market through index-based insurance and weather data

Weather risk management on agricultural market through index-based insurance and weather data

In recent years, the problem of decreasing productivity of agriculture has arisen sharper due to climate change and long-term weather fluctuations; there is even the threat of famine in some countries, which are more dependable on crop productivity. This problem can be solved with traditional and known for centuries tools, i.e. by expansion of sowed land through deforestation.

Simultaneously, the intensification of manufacturing or the expansion of cultivated land into previously wild areas can lead to additional emission of greenhouse gases due to the removal of trees and also these processes can increase the amount of used fertilizers. These both actions are factors contributing to climate change and appearance of negative weather phenomena such as drought.

OpenWeatherMap @ Lisbon Web Summit

OpenWeatherMap @ Lisbon Web Summit

Olga Ukolova, CEO of OpenWeatherMap Inc., pitches the new VANE platform for operating with weather data and satellite images @ Lisbon Web Summit https://websummit.net

OpenWeatherMap @ Lisbon Web Summit

OpenWeatherMap @ Lisbon Web Summit

Our booth is A191

Let's meet at Web Summit in Lisbon!

Let's meet at Web Summit in Lisbon!

Let's meet at Web Summit in Lisbon https://websummit.net

See you on OpenWeatherMap stand A 191 in the Big Data Exhibition Area of Pavilion 3 on Wednesday, November 9.



Examples of VANE Language: False color

Examples of VANE Language: False color

These are maps, which you can compose by a combination of any three bands. For instance, use SWIR (band 7) instead of the red spectrum (band 4) and use NIR (band 5) instead of the green one (band 3), then you will get a map of land victimized by fire (See Fire detection, above).
 To get a map of a necessary color, just choose a combination of bands and you will find out what it looks like to see the world through eagle or wolf eyes.
http://owm.io/sql-viewer?select=b7,b4,b3&where=day=2016-275&op=rgb&color=brightness>6000,brightness<12000&lon=-121.2337&lat=37.6281&zoom=12

Examples of VANE Language: Custom NDVI

Examples of VANE Language: Custom NDVI

The NDVI is a major vegetation index for the agricultural industry and farming, and with VANE Language you can customize a colour scheme to get a proper picture. Here in contrast to just the NDVI option a user can set a color scale and define the colors of zones. 

Examples of VANE Language: NDVI

Examples of VANE Language: NDVI

The NDVI, i.e. the normalized difference vegetation index, is a simple graphical indicator of biomass active photosynthetically.The NDVI is one of the most common and widely used indexes for evaluation of vegetated areas, their quality and quantity. Using the NDVI it is possible to detect presence of plants, its dynamics of emergence and growth. For getting of this index there is Band 5 which measures the near infrared spectrum, or NIR (Near Infrared). This part of the spectrum is reflected by water in leaves of healthy plants. Maps of the NDVI with dynamics (in various seasons) let tracing peculiar features and deviations of seasonal vegetation.