Examples of VANE Language: Fire detection

Detect areas that were deforested after fire by simple coding of burn index and apply it to chosen area and data of events. You can easily compare images before and after fire by getting visual result immediately.
http://owm.io/beautiful-vane

OpenWeatherMap presents the release of the VANE Language service

OpenWeatherMap presents the release of a new service the VANE Language (former imagery API) with examples: http://owm.io/vaneLanguage 
 Initially, we called it Imagery API but finally understood that this service is much bigger than just API calls. Language is a proper name for this service. It is like an SQL for satellite images. Something unique on the satellite market.The Language is entirely online service, there is no any manual procedures or presets like maps prepared in advance. One image that we receive from Landsat8 is not an image in common understanding but several layers that have to be processed and merged somehow before you can do anything with it. The weight of each unarchived number of bands is around 2 Gb, and obviously, it takes a lot of resources and time to process it. E.g to make a global map you need around 10,000 images that should be processed and merged. With VANE Language developer does not worry about time-costly pre-processing because we do it online immediately. We give him a powerful tool that is familiar to any developer and hides all complexity. In a short word VANE Language gives a full flexibility for a developer to do with images whatever they want and deploy result into applications. VANE also have a unique feature of configuring the formula of image processing. Means that developer can set up his logic of processing of the image to make specific vegetation indexes, false colors and any other images that he can use for analysis of objects, changes, yield health, etc.

Modern approach to use of weather data in effective marketing

Recently the approach to marketing has greatly changed. Simple broadcasting of information about goods and services, even in the most whimsical of forms, is getting out-of-date quickly. At the moment those companies are the most successful who experience a flexible approach towards using of information, both current and historical.
Defining a target audience is only the first step. The aim here is to understand where your consumers are, what they do during different seasons and times of the day and what probably they are going to do in the future.
The use of information about a person in his real-time contextual surroundings lets provide content exactly in that moment when the content is of the most importance and it works more effective.
Such factor as weather is the most available and universal in consumers’ decision making process regarding goods and services. Weather influences where we go, what we wear, what we eat and the most important how we feel. The theme of weather is so all-around and discussed at many levels, it’s a great way to start a conversation in a company of unfamiliar people.  
Properly speaking, weather data is practically the only set of data available for marketers in real time mode that gives a notion about consumers’ mood, their desires and intentions to purchase something at the moment or in the future.
The fact that demand for products and services is determined by weather conditions significantly has been well-known for a long time already and it is actively used, for example, in contextual advertising. However, as researches and sales practices demonstrate, the aim of more effective communication with consumer requires taking into consideration many additional factors such as dwelling location, seasons and current seasonal deviations from norms, etc.  
Basically, having weather data with this necessary additional information, marketing specialists can tune to psyche of consumer and suggest him goods in that moment when he is ripe for purchase. And the story here goes more complex and interesting than notorious umbrellas and popsicles. One should also consider such factors as local traditions, for instance, at what temperature people make picnics outside, since depending on local habits people of different climate zones can buy air conditioners or warm clothes at the same temperature. And what’s more interesting is how weather influences mood of people and their intention to purchase. It is true not only for interest in some specific products, but for overall purchasing activity.
It was proved that exposure to sunlight increases willingness to spend money on products approximately twice. Negative mood depending on bad weather can make consumers react more effectively to negative advertising messages basing, for example, on fears. This method is used by the American Dental Association which experiences that on gloomy days negative advertisements have more sale response than traditional positive ads depicting healthy teeth and beaming smiles.
All above mentioned facts show that weather data is a perfect tool for targeted advertising.
With creative approach from marketer side the use of weather data provides a truly unique opportunity for successful communication with consumers.
This is true not only for current data, but also for short- and long-term forecasts that help in decision making about expanding or changing a range of products or services. And the analysis of historical data from the point of view of consumers’ reaction to seasonal deviations and climate change is very useful in planning of future prices.

Management of power consumption basing on weather data and forecast.

The electric power industry is likely to be the most weather sensitive sector in the world modern industry. Insurance against the risk of loss caused by  natural fluctuations in weather condition has become a usual practice at the end of the last century.

Nowadays, due to the planet’s growing population the question of regulation of power consumption is started to increase its significance.

Weather risk insurance contributes to the steady economic situation while energy saving and control of power consumption provide cost saving and slow down the wasting of energy resources that all in all help to reduce the negative impact on the ecology of the planet.

One of the modern approaches to the issue of energy saving is automatic management of station load which is based on current and expected levels of consumption which in its turn is closely connected with climatic and weather factors.

Combined heat and power plants, fossil-fuel power plants and other types of thermal power stations operate in accordance with current or temporary levels of power consumption and consider temperature and wind conditions of air masses. Hydropower plants totally depend on hydrological regime of rivers.

In the case of solar power plants energy flux density is contingent on intensity of solar radiation and as a result it is determined by a season, a part of a day and weather conditions.Wind farms  directly depend on direction, speed and power of wind. Here is also a crucial issue of strong geographical irregularity of distribution of wind energy.

At the moment exactly the wind energy sector is a good example of a sphere where automatic management of load and generation of electric power is realized basing on accurate weather forecast.

For instance, Xcel Energy company implemented a such project in October, 2011 and set a world record of the amount of energy generated from wind power.

"Our goal was to enable automatic management of load and generation [called “automatic dispatch], so our system could be smart about turning units on, or keeping them offline when using them would be inefficient or unnecessary. It’s enabled by an Its IT infrastructure that sends thousands of data points every five minutes in order to connect the system to real-time circumstances. The resulting cost savings were (and are) passed on to its customers, to date yielding approximately $60 million in savings for a company investment of $3.8 million. ”

http://www.forbes.com/sites/jonathansalembaskin/2016/06/30/xcel-tames-variability-of-wind-power/#43f16be42716

Weather risk management in retail

Daily news mass media readily inform people about numerous natural disasters happening throughout the world. Such extreme weather conditions as floods in India and Louisiana, severe drought in California paralyze the life of entire states and have a harmful impact on the economy.

According to Allianz Global Corporate & Specialty SE reports, only during the last three years insurers around the world paid $70 billion a year for claims related to extreme natural phenomena. In the 1980s the annual amount of payments for such claims consisted only $15 billion. By comparison, 905 natural disasters took place around the world in 2012, 93% of which were weather related ones, and they led to losses in the amount of $170 billion.

However, also less devastating in its power weather conditions have a strong impact on the economy. Furthermore, the losses emerging due to weather changes exceed the annual losses from natural disasters significantly. Even small deviations from the expected weather conditions can greatly affect the financial situation in various industries.

Retail industry is highly susceptible to risk of unstable weather. Abrupt change in the ordinary climatic conditions, such as sharp cooling or warming often turns for business into bigger losses than ones from the most serious natural disasters. For instance, an unusually mild winter provokes a drop in demand for warm clothing, and vice versa in cold summers demand for beach accessories and refreshments also falls. Excessive precipitation during weekends can result in people’s reluctance to leave their houses. Sudden pressure fluctuations negatively influence the well-being of customers who are weather dependent, and this fact can greatly affect the attendance of shops and shopping centers even in visually good weather.

Nowadays there exist solutions for weather risk management which can protect retailing companies from revenue fall in various cases when shopping centers are empty due to bad weather or in situations when demand for seasonal items is different from expected. The fact is that over the past few years the availability of weather data has increased significantly. Processing of huge amounts of data does not take a lot of time and has become much cheaper. Moreover, in modern conditions one can measure and analyze not only the basic weather parameters such as temperature, humidity, wind force and wind direction, but also intensity of rain, sunshine or snowfall. 

Modern technologies allow getting information on the current weather and providing accurate forecast not only for cities, but also for a specified place worldwide. Comparing the historical weather data with the statistics of growth and decline in demand for certain products, it is possible to anticipate the consumer involvement and to hedge weather risks in advance. Weather risk management gives opportunity for companies to perform their strategies such as diversification and adaptation of production for expected weather conditions.

Weather risk management in the electrical power industry

Risk management is an opportunity to prevent risk emergence, as well as to mitigate negative effects of different adverse situations. Weather risk is related to physical phenomena which can influence performance of a company and which cannot be controlled from company's side.

One of the industries which is mostly sensitive to weather activity is the electrical power industry.

Basically the market of insurance of weather risk was initially established for purposes of the electrical power industry. Presupposition for this establishment appeared in the mid 90s when deregulation of the energy and urban engineering industries took place. And later on the impetus for emergence of this market was unusually warm winter 1997/98 which was caused by a natural phenomenon of El Niño.

That winter many energy companies of North America experienced heavy losses due to a sharp fall in energy consumption by urban and rural populations. Since that time for insurance against risk of loss due to natural variability of weather the instrument of weather futures has been created. Nowadays for this purpose as basis asset the historical data on main parameters (temperature, wind speed, precipitation) in a specified region is applied. Modern technologies such as digital cloud storages and Big Data allow storing huge array data structures and processing them quickly and provide easy access to necessary information of any time period for any world point.

Influence of weather conditions on the electrical power industry

Weather phenomena have a substantial impact on safe operation of power systems, on modes of power generation and power consumption. 

Influence of weather conditions on the electrical power industry is diversified. Here can be mentioned power lines as quite vulnerable objects. Power lines are affected by significant fluctuations in temperature, by ice and wind loads, by rapid freezing of wet snow, by showers and thunderstorms. Due to wind and ice there were cases of wire break on long distances of tens of kilometers, and also there were collapses of power lines supporting constructions. Thunderstorms can affect operation of urban substations, putting transformers and high-voltage equipment out of action.

Besides devastating weather phenomena there also exist periods of temporary changes of weather that do not possess physical damaging power but have impact on level of power consumption and consequently on demand and price of electricity. For instance, abnormal summer heat can increase level of power consumption by population drastically and thus cause a sharp jump in prices on electricity.

The following approaches are used for weather risk management:

• use of preventive measures basing on forecasts and timely warnings about severe weather phenomena; 
• insurance against extreme weather conditions; 
• Market instruments of weather risk hedging.

Currently 74% of electrical power companies state that they evaluate influence of weather conditions on their financial flow, and 35% of companies claim that they insure against weather risk to mitigate it.