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Examples of VANE Language: False color

Examples of VANE Language: False color

These are maps, which you can compose by a combination of any three bands. For instance, use SWIR (band 7) instead of the red spectrum (band 4) and use NIR (band 5) instead of the green one (band 3), then you will get a map of land victimized by fire (See Fire detection, above).
 To get a map of a necessary color, just choose a combination of bands and you will find out what it looks like to see the world through eagle or wolf eyes.
http://owm.io/sql-viewer?select=b7,b4,b3&where=day=2016-275&op=rgb&color=brightness>6000,brightness<12000&lon=-121.2337&lat=37.6281&zoom=12

Examples of VANE Language: Custom NDVI

Examples of VANE Language: Custom NDVI

The NDVI is a major vegetation index for the agricultural industry and farming, and with VANE Language you can customize a colour scheme to get a proper picture. Here in contrast to just the NDVI option a user can set a color scale and define the colors of zones. 

Examples of VANE Language: NDVI

Examples of VANE Language: NDVI

The NDVI, i.e. the normalized difference vegetation index, is a simple graphical indicator of biomass active photosynthetically.The NDVI is one of the most common and widely used indexes for evaluation of vegetated areas, their quality and quantity. Using the NDVI it is possible to detect presence of plants, its dynamics of emergence and growth. For getting of this index there is Band 5 which measures the near infrared spectrum, or NIR (Near Infrared). This part of the spectrum is reflected by water in leaves of healthy plants. Maps of the NDVI with dynamics (in various seasons) let tracing peculiar features and deviations of seasonal vegetation.

How to use OpenWeatherMap UV index

How to use OpenWeatherMap UV index

Thank you for the article  Francesco Azzola
  http://www.survivingwithandroid.com
 @survivingwithan
  https://it.linkedin.com/in/francescoazzola

This post describes how to use OpenWeatherMap UV index. This is an interesting API because we can use it to explore some important aspects about Android and location aware API. Openweathermap provides this API for free! As you may already know, OpenWeatherMap provides also a full set of API about weather information: you can get current weather conditions, forecast, historical information and so on. This information is free and we can use OpenWeatherMap API free of charge.

Focusing on this article, at its end, we will build an Android app that gets UV index and show it using Material design guidelines.

Before diving into the app details is useful to have an idea about UV index.

Examples of VANE Language: Burning oil wells

Examples of VANE Language: Burning oil wells

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

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

Satellite image in the thermal bands: False color (b10 TIR - b7 SWIR - b5 NIR)

Satellite image in the thermal range


Examples of VANE Language: RGB

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.

Examples of VANE Language: Fire detection

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 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.

Financial impact of changing climate on agriculture

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.      

Modern approach to use of weather data in effective marketing

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.