пятница, 21 октября 2016 г.




Examples of VANE Language:
13 October 2016. Burning oil wells, Iraq, Al-Qayyara.(Via  http://edition.cnn.com/2016/10/12/world/burning-oil-wells-isis-iraq/)
"ISIS militants had set the wells on fire hoping to obscure the view of Iraqi and coalition warplanes".

The usual view from space: RGB(b2-b3-b4)

четверг, 20 октября 2016 г.

Examples of VANE Language: RGB



One of the simplest operations is to generate RGB map. Here an image consists of Bands 4-3-2 which correspond to the well-known RGB color model. Red, green and blue spectra combine together for creation of full color images.

http://owm.io/beautiful-vane

среда, 12 октября 2016 г.

Financial impact of changing climate on agriculture


Recent years agriculture experiences much heavier losses caused by changing climate and alterations in global middle-season temperature. Even a small rise or drop of usual temperature takes a toll on yield, productivity and profitability of agricultural sector. In such situations both manufacturers and consumers of products undergo some difficulties.  
Profit and losses of manufacturers and consumers differ significantly depending on their location; mostly this burden comes to developing countries since they have much dependence on yield productivity and it’s more difficult for them to adopt changes.    
Dense population in the regions whose economics are in direct correlation with agricultural productivity, low income, lack of social protection, and limited opportunities of risk management – all these factors make the consequences of climatic change really devastating: thousands of people can lose their livelihoods, and the threat of famine for the whole countries is no longer the illusory in the coming decades.
However it would be a big mistake to consider that this disaster can happen only to agrarian countries. Shortage of crop can affect the entire agricultural supply chain and bring substantial losses to companies and corporations throughout the world:
  • bulk companies may not be able to use its infrastructure to the full capacity, as a result, they will be likely to face a reduction in operating income, and in severe cases, they will be unable to cover their fixed costs;
  • providers of logistics services may be unable to generate enough revenue to cover their fixed costs;
  • manufacturers may get non-fulfillment of sale contracts in a supply chain since they cannot provide previously agreed amount of agricultural products, and as a result, traders will have to purchase additional amount of  products at market prices;
  • due to a drop in sale volume manufacturers of agricultural equipment may suffer as  agricultural manufacturers cannot afford to invest in more modern technologies.  
And as an overall result, the majority of costs have to be covered by ordinary consumers who will have to pay more for food basket.

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

вторник, 11 октября 2016 г.

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.

понедельник, 3 октября 2016 г.

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.

понедельник, 5 сентября 2016 г.

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