The Dashboard for Agricultural Monitoring is a service created for visual demonstration of satellite data (NDVI) and weather data (forecast, historical and accumulated parameters), which you can get for your area of interest (that is, for your polygons).

When you work with single-channel images, you need to focus in depth on a narrow range of values and clearly evaluate the researched data.

If you want to download Sentinel-2 satellite data, you’ve come to the right place! Our Satellite Images API was created exactly for this purpose.

1) Satellite data search.
1.1. Selection of suppliers or distributors of satellite data.
1.2. Data search in archives. Search is based on the following criteria: date of satellite imagery, percentage cloud coverage, type of satellite imagery system, level of data preprocessing, geographical area of interest (AOI).

An example of one of the services for agricultural applications offered by VANE has now been added to the Query Builder interface.

The Polygon tool allows you to isolate any outline you want in the photograph, process the satellite images in RGB and EVI, and arrange any colour palette with any scale for a specific area.

It is possible to edit it, obtain data on the depicted polygon and download it from the GeoJSON file.

You can then get the URL with the assembled polygon and copy it to your site.

The filter algorithm for selecting BEST coverage tiles has changed.

BEST is the method for overlaying images (parameter value order), and is the best way possible, depending on the parameters selected: date range, satellite, percentage cloud cover.

Changes to the algorithm have enabled the quality of coverage to be significantly enhanced:

Sentinel-2 - before

Sentinel-2 - after

– combined data sources Landsat 8 and Landsat 8 TOA.

Landsat 8

Landsat 8 + Landsat 8_TOA

The drawings show global coverage obtained between 1 June 2017 and 1 September 2017 using data from the MODIS spectroradiometer aboard KA Terra and Aqua.

The current cloudless coverage of the Earth by medium and low-resolution satellite images is an important element in the regional and global systems that monitor the territorial changes caused by natural and man-made factors. For example, assessing the damage inflicted by forest fires caused by deforestation, volcanic eruptions, flooding and so on. Also, such types of coverage are popular as the base layer for cartographic web services.

The main stages of creating such coverage are: the selection of images, the masking of clouded areas, tonal adjustment of images taken at different times of the year, and pasting them into single coverage using so-called “cutlines”, which enable, to a certain extent, the joins between the pasted images to be hidden. Such operations, as a rule, are carried out in semi-automatic mode and require specialised software and highly qualified experts, which substantially increases both the time taken to create such a product and its cost.

You are invited to test the new web interface Query Builder for our Vane platform.
You can use this simple tool to create your own map in just a few minutes, and with just one click receive a completed link for display on your site or app using a web map library like Leaflet, Open Layer, Mapbox and Google Map.

This version is an improvement over the previous one in terms of simplicity of use and layout. The user can select either one of the available data sources and the required combination of spectral bands or one of the derivative index products such as NDVI, EVI, etc. You can also set up display parameters, including clarity, contrast and gamma correction, or use one of the available schemes provided. After that, all you need is to get an API key and insert it in the prepared link, and you can use it in your programming product.
We are ready to answer your questions and will be glad to hear any proposals you might have.

One of the benefits of the VANE platform is that there is no need to search by scenes and footprints. It is based on a simple assumption: each location in the world has metadata – click on any location and you can get information about all pixels containing this location.

Such projects as cloudless atlases and Google base satellite maps are created according to this basic principle, stitching the best imagery pixels in one seamless mosaic. Based on the scene’s metadata, VANE can choose the best satellite cover – you need to set up a parameter “order=best” for this operation.

As well as this, the VANE language allows you to set up further requirements for your mosaic, providing appropriate parameters in your query:

no older than (“day>{yyyy-mm-dd}”)

or put all the latest imagery on the top (“order=last”)

or within a specific time interval (“between({yyyy-mm-dd}:{yyyy-mm-dd})”).

Then you can go further, applying your custom colours to the result mosaic, according to the VANE language specification.

Just to demonstrate this principle at work, we’ve launched a very basic application called Finder.

OpenWeatherMap presents the release of a new service – VANE Language (formerly Imagery API) – with examples here: http://owm.io/vaneLanguage.

We initially called this service the “Imagery API”, but later realised that it consists of much more than just API calls. “VANE Language” is a more appropriate name for it, as it is like an SQL for satellite images. It is a unique offering in the satellite market. VANE Language is an entirely online service – there are no manual procedures, or presets such as maps prepared in advance.

Each “image” that we receive from Landsat 8 is not an image as commonly understood, but several layers that have to be processed and merged in some way before you can do anything with them. Each unarchived number of bands occupies around 2 GB of storage, and it obviously takes a lot of resources and time to process it. For example, to create a global map you need around 10,000 images that need to be processed and merged.

With VANE Language, the developer does not worry about time-costly pre-processing, because we do it all online immediately. We provide a powerful tool that will be familiar to any developer and hides all the complexity. In short, VANE Language gives full flexibility for a developer to do whatever they want with images and deploy the results into applications.

It also has a unique feature: configuring the formula for image processing. This allows the developer to set up their image-processing logic to create specific vegetation indexes, false colours and any other images that they want to use for analysis of objects, changes, yield health, etc.