Blog

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).

This April, OpenWeather presented a brand new product, the 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 very convenient.

In this article, we would like to look in more detail at one of the essential elements of our Agro API: the Satellite Images API. The 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 colour, NDVI and EVI.

We provide 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 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. You can learn more about our pricing plans here.

Please note that there are limits to the total area for which you can request data, and to the number of requests that you can make 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 will not run and hide!*

You can find all the details and the full set of the Agro API‘s capabilities here.

As always, we would be glad to hear your comments 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 a great deal of 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 fertilisers, 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 maximise 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 neighbouring 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, the Agro API, with universal and simple syntax.

The OpenWeather 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 sectors and can be used as a farm rating tool.

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

So the, new year, 2018, has come, and it’s time to sum up the results of the past year for our company, OpenWeatherMap (UK, US and Latvia), developers of one of the best weather APIs in the world. A lot has happened and much has changed.

During the year, our number of users grew from 600,000 to 1 million. We participated in the Startup Grind Global Conference in Silicon Valley, where the team from OpenWeatherMap was named in the top 50 Startup Exhibitions of 2017. Our mature team was filled up with excellent professionals and wonderful people.

We did a lot of new things and qualitatively improved our current developments. In 2017, we were pleased to present to you:

Weather data: API and Weather Maps

• The Open Dashboard for Agricultural Monitoring can help give you an idea of the possible use for meteorological and satellite data in your agricultural applications.
• Specially for the agriculture sector, we launched an API for accumulated temperature data and another for accumulated precipitation data.
• The Weather Historical Bulk service. Now you can simply choose a city/town (or several cities/towns) and download an archive, which contains a bulk file with the weather history for up to 5 years – any day or week, or even several years.
• A new and improved version of an API for UV-index.
• Throughout the entire year, we worked constantly on our history weather API. During the year, the amount of data supplied and the speed of processing that data increased significantly. Also, we made it possible to quickly upload data in a format that doesn’t require additional processing and can be understood by any user.
• Our Weather Maps app changed qualitatively in 2017. We added the ability to switch the layers of weather and satellite maps, create various combinations with them, and connect them to mobile and web apps.

Satellite data: VANE platform

In 2017, we significantly improved our satellite platform. Our team undertook a huge amount of work and in June were able to present a new version of the satellite image processing platform VANE.

Based on the VANE platform, we developed a new product called Global Satellite Base Map, which uses visual tools and query language to generate a map from satellite images. The uniqueness of the product is that all data processing is done on the fly, and there are no presets or pre-made calculations. The user defines the parameters for a calculation and image processing and immediately receives a result for any territory. This capability was only possible thanks to VANE, our super-powerful data processing platform.

We recently presented you with Query Builder, our new interface for the VANE platform. Now you can use this simple tool to create your own map in just a few seconds, 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 Maps.

We are grateful to everyone that worked with us for all this time. We thank you for all your feedback and for not getting bored by our tech support.

We have a ton of plans for the coming year. Stay tuned, and you will see a lot of the new and interesting things to come. Subscribe to our Telegram Channel https://t.me/openweathermap and get news first about our updates and new products!

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.

We invite anyone wishing to do so to try out our weather widget’s new geolocation and weather map functionality – https://openweathermap.org (please note that ‘https://’ is required in the URL), which can be targeted to your specific location.