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This April, the OpenWeather company presented a brand new product, Agro API, which was intended to change the working process of agricultural applications. Our algorithms for collecting and processing satellite scenes and weather data combined with the simplified delivery of prepared products to the end user make this product wholly unique and convenient.

 A couple of weeks ago, the OpenWeather team visited the GEO Business 2018 event at the Business Design Centre in London. As promised, we will share our impressions with you.
The exhibition had an excellent programme that included practical demonstrations of the latest research and workshops on the use of services and technology in action. We were particularly interested in the Earth Observation and Satellite Applications seminar. One of the presentations was about the use of satellite image recognition technologies to track the construction phase.

The fundamentals specific to the market are that satellite data is provided mostly for global territories and enterprises, and there are quite a few, if any, solutions for giving data for small customers.
We are happy to say that our service, Agro API , can provide satellite data for any size of customer, with on-the-fly data processing and availability. It is an intuitive, fast, and robust API to satellite imagery that is suitable for use in applications in either a large area or a small field. We provide the most useful tools for empowering applications for farmers and machine learning. There are so many spheres where environmental data is needed nowadays, and agricultural applications are among them.

The OpenWeather team visited GEO Business Show 2018  in London on 22–23 May. The show is an international exhibition for the geospatial industry that provides an excellent opportunity to communicate with experts and enthusiasts in the area of geospatial and satellite technologies, listen to nearly 200 speakers skilled in working with spatial data, and meet new companies of the industry.

We were delighted to explore stands of exhibitors who demonstrated new capabilities for the gathering, storing, processing, and delivery of satellite data. We were also thrilled to meet and talk face-to-face with exhibitors who already use our weather and other geodata in their applications.

There was a great event programme that included demonstrations, workshops, and speeches. Describing all of the impressions at once is difficult, so please stay tuned for more details.

We will share practical cases and photos in the next post.

 Satellite images API on the basis of which we calculate quantitative indices, such as NDVI, EVI, and others, and from which we also obtain ready-made images of territories in True and False color, NDVI, and EVI , along with other APIs to data such as Weather Data, Soil Data, Accumulated Temperature and Precipitation Data all go into making our new Agro API product.

TRUE Color and False Color

TRUE Color — "True color" is a rendering of red, green and blue satellite imagery spectral bands to the RGB composite image that seems to look natural.

False Color (b5 b4 b3) — "False color" is a rendering using NIR (near infrared) band which is more useful to visualize land cover and differentiate it from the urban and farmland areas. In these images it is possible to pick out different types of vegetation. Also easily discernible is the boundary between land and water, which enables changes in shorelines to be tracked.

NDVI and EVI vegetation indices

Some of the most common indices enabling quantitative assessment of vegetation cover. Convenient for tracking the growth rate of plants and monitoring any changes to them.

NDVI - This is an index calculated according to a set formula which uses near infrared and red wavelengths. Used in calculating and monitoring vegetation growth and its dynamics. NDV Index is displayed in images using the white to green palette where dark green indicates a good yield and white indicates a poor one or lack of vegetation.

EVI  -  In areas of the dense canopy where the Leaf Area Index (LAI) is high, NDVI values can be improved using information from the blue wavelength. Information in this part of the spectrum can help correct atmospheric influences and background interference caused by soil.

Today, we would like to look in more detail at one of the essential elements of our Agro API, Satellite images API. Satellite images API is the dataset from the Landsat 8 and Sentinel 2 satellites on the basis of which we calculate quantitative indices, such as NDVI, EVI, and others, and from which we also obtain ready-made images of territories in TRUE and False color, NDVI, and EVI. 

We provide a historical data as well as satellite images that are as up-to-date as possible (allowing for the data source and cloud cover) for the very nearest time period. These satellite images are available to all account users, including those who are using the free package. For non-paying users, the range for satellite data requests is 6 days.  For the paid service, it is one year.  Learn more.

Please note that there are limitations on the total area for which data can be requested as well as the number of requests that can be made per minute. However, should you exceed these figures, we will continue to provide you with the data you need so that your work is not affected and your customers do not run and hide!*

All of the details and the full set of the Agro API capabilities can be viewed here.
As always, we would be glad to hear your remarks and suggestions regarding our product!

* At the end of your billing month, we will provide you with a separate bill for any additional area, beyond the tariff limits, for which you requested data.

Objectives:
As farms mainly consist of crop fields, which can be hundreds of acres in size, much time and resources are demanded of farmers in obtaining an accurate picture of the overall condition of these farms.
Drying out of plants or, conversely, an excess of moisture and a rise in the number of pests: these can all take their toll on the size and quality of the harvest and demand a rapid response. There are also such problems as the danger of overusing fertilizers, which poses a threat not only in terms of extra costs but also in that it is harmful to the environment and primarily to the health of farmers themselves.
To maximize harvests, constant monitoring is required throughout the season; and it is not easy finding the time to keep up with changes for each crop, not to mention monitoring the condition of every single acre. When deciding on long-term plans, a comparative analysis has to be carried out for both the usual course of the seasonal cycle and, in particular, any crises that have arisen.
To assess the current situation and to keep track of changes compared with preceding seasons and with the condition of neighboring fields, accurate information on both the past and the present is needed as well as future forecasts that are as precise as possible.

Solutions:
There are currently numerous services that help with managing farms for any acreage: checking boundaries and nutrient and moisture intake, monitoring the negative effects of weather conditions and diseases, and controlling pest numbers. And this can all be done without having to visit the fields, just by using a phone or tablet screen or a PC.

It is exactly to provide these services that OpenWeather offers a wide range of APIs for different weather and satellite data combined in the one product, Agro API, with universal and simple syntax.

OpenWeatherMap team are pleased to announce that we are launching a new product aimed primarily at specialists developing agricultural services and addressing the specific requirements of this sector. This product is also geared toward the insurance and banking sector and can be used as a farm rating tool.

As part of this product, we are providing an API for receiving weather data (current weather, forecasts and history), satellite data (current and historical) and weather and vegetation indices based upon this.  As well as the data we already provide in other products, here we have added specialized agricultural indices such as soil temperature and moisture, accumulated temperature, cumulative precipitation and satellite data*: images from space and vegetation indices (EVI and NDVI) based upon them. Weather data can be requested both for a particular point and for a polygon. Find out more here.
We are offering you the chance to try out our free package. All you have to do is set up a user account** and you will receive a personal API key.

We have also put together paid services as part of which the user is provided with a wider range of functions, which you can find out about here

* Currently, as part of the existing paid packages, we are providing data that is of the utmost relevance to agribusiness. Other territories can be added upon request.
** Users who are already registered can use their username and password for their new account

We look forward to your feedback and comments! We will be glad to answer any questions you might have.

Crop farming covers around 40% of the globe and uses 85% of its fresh water.
Often, in countries where agriculture constitutes the principal occupation of farmers, due to drought and overpopulation, they find themselves in a constant battle to maintain everyday resources such as food and water etc. In such cases, productivity and crop prices assume critical importance. And they, in turn, depend primarily on atmospheric factors and soil conditions.

By the way, we really like our new office in Riga!
The view from our window to snow-covered tiled roofs of the Old City has been pleasing us even during the snowy European winter.
We have not yet managed to arrange all the furniture, but we already admire what surrounds us

During the entirety of their lifecycle, crops are affected by a whole range of factors, the greatest influence being exerted by weather events. These have a significant and occasionally decisive effect on the size, quality, and timeliness of a harvest and, consequently, on its value.
There exist a large number of indices for assessing this effect, including both direct measurements and the results of calculations.
Currently, the main source of information is complex weather models based on the mathematical processing of large amounts of data collected from tens of thousands of stations around the world as well as the data received from satellites.