How we process satellite imagery so that you can operate with ready-to-use data

How we process satellite imagery so that you can operate with ready-to-use data

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).

Dive into the Agro API | Part 1 – Personal account

Dive into the Agro API | Part 1 – Personal account

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.

Satellite Images API for Agriculture: NDVI, EVI, True and False colour

Satellite Images API for Agriculture: NDVI, EVI, True and False colour

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.

Weather and satellite APIs for precision farming

Weather and satellite APIs for precision farming

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.

Agro API – service for agriculture

Agro API – service for agriculture

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.

The influence of temperature on plant productivity in agriculture: Accumulated temperature

The influence of temperature on plant productivity in agriculture: Accumulated temperature

Accumulated temperature is a weather parameter that directly influences the productivity of agricultural plants. All biological and chemical processes taking place in the soil are connected with air temperature. The heat supply of crops is characterised by a sum of average daily air temperatures that are higher than a biological minimum during a vegetation period. Both too-high and too-low temperatures spoil the course of biochemical processes in cells, and irreversible changes can be caused that lead to a stoppage of growth and the death of plants.

New API for accumulated temperature and precipitation data!

New API for accumulated temperature and precipitation data!

We are happy to announce our new APIs based on historical data and focused primarily on users from the agricultural sector – API for accumulated temperature data and API for accumulated precipitation data.

Accumulated temperature data is an index that denotes an amount of warmth. It is determined as a sum of average daily air and soil temperatures that exceeds a defined threshold of 0°C, 5°C or 10°C, or a biological minimum temperature level that is crucial for some specific plant.

Accumulated precipitation data is calculated as a sum of all parameters for a particular period.

Accumulated precipitation data for agriculture

Accumulated precipitation data for agriculture

Precipitation, mostly rains, has a huge impact on agriculture. For plants to grow, they need at least a small amount of water, and rain is still one of the most effective ways of watering despite the development of modern technologies.

Too much or too little precipitation is bad and even harmful for agricultural plants. Drought can destroy the harvest and increase erosion, and overly humid weather can trigger the growth of unfavourable fungi. Also, different kinds of plants demand different amounts of precipitation. For example, some succulent species require little water, while tropical plants need hundreds of inches of rain a year just to continue living.

The fluctuation in precipitation amounts is quite substantial in continental climates. They fluctuate more in a month than during a year. A considerable variation in precipitation leads to situations where drought takes place during the years with low amounts, thus forming areas of unstable hydration. With a long absence of rains and at high temperatures, the reserves of moisture in the soil dry out due to evaporation.

A previous arid season brings a shortage of crop yield even in a humid season, as the harvest lacks enough time for ripening. Thus disadvantageous conditions for ordinary plant development are established, and the crop yield of agricultural plants decreases or perishes.

Along with precipitation amounts, the number of days with precipitation in a month or a year is also a significant climatic index. Plants are sensitive to whether a given precipitation amount falls all at once during just a few days, or it rains often and the amount is distributed comparatively evenly throughout a month. For instance, even one great downpour in a prairie area in summer has little ability to improve an arid situation.

By employing a data set of precipitation amounts and a number of days, one can calculate an accumulated precipitation amount for any region during a specific period of time.

Accumulated temperature data for agriculture

Accumulated temperature data for agriculture

Temperature, and especially accumulated temperature, is an important factor and plays a fundamental role in agricultural productivity. Plants and insects develop in accordance with the temperature. The warmer the weather, the faster they grow and reproduce; the colder it is, the more slowly these processes go.

All species have a biological minimum temperature level, below which development does not take place at all. When the temperature of the environment begins to exceed this minimum level, it gives a start to growth and reproduction. The value of this basic temperature (or a development threshold) has a crucial significance, and it differs between species of plants and insects.

Accumulated temperature (AT) represents an integrated excess or lack of temperature in relation to a fixed starting point. This index is calculated as the sum of the average daily temperatures of air and soil, above a chosen threshold of 0°C, 5°C or 10°C, or a biological minimum temperature level.

Basically, this is a way of including temperature and time into one dimension for quantitative evaluation of the speed of growth of plants and insects. Usually the index of accumulated temperature data is used to create models of crop growth.

In the near future, we will introduce our new API for accumulated temperature data. It will be based on historical data, and will be focused primarily on users in the agricultural sector.

We are happy to announce significant improvements in one of our products – API for UV-index

We are happy to announce significant improvements in one of our products – API for UV-index

We are happy to announce that one of our products – API for UV-index – has been significantly improved.

  • Now, as well as current and historical data, you can also get UVI forecasts for periods of 8 days.
  • The syntax has been made considerably easier: it has become clearer and more unified, like other API versions.
  • There is a new feature to request data for any geographic coordinates without limits on accuracy.
  • The accuracy level of the UVI modelled data has been doubled (the interpolation grid step has been reduced from 0.5 to 0.25 degrees).  
  • Soon, searching by city/town name, city/town ID and postal/ZIP code will be available.

You can find the instructions for the updated version at http://openweathermap.org/api/uvi.

Access to the UV-index data will be available for all our plans. For more information on our plans, please visit http://openweathermap.org/price.

The previous version of the API (http://openweathermap.org/api/old-uvi) will soon be announced as deprecated, and no further support will then be provided for this version.