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Mobile Thermal Cameras

Just like all things technology, Thermal Imagery is advancing rapidly. In the past year alone there have been some considerable breakthroughs with thermal cameras. As most electronics advance, shrink, become faster and more affordable, so has the thermal camera. Last year in 2014 FLIR discretely unveiled its concept and prototype for a mobile phone mounted miniature thermal camera, the FLIR One.

The world was excited by this news but we all know that when something like this occurs it’s quickly followed by competition. Late last year a new mobile mounted thermal camera was announced called the SEEK Thermal. There are other devices under development but at this stage we have decided to review and compare the FLIR One and SEEK Thermal as they are the only publicly available mobile thermal cameras on the market.

 

FLIR One

After the buzz that came about the revelation of perhaps the world’s first mobile mounted thermal sensor FLIR released the FLIR One consumer model in 2014. It comes in the form of a two step iPhone 5 or 5s case. The first case is much like a standard hard case (with a FLIR logo) and the second stage a clip on unit that contains the camera sensors and extended power supply for the camera. This duel case system makes it a little clumsy and bulky but you have the choice of only attaching the Thermal Lens unit when required, although this requires you to carry it around with you everywhere, separately.

When operating the thermal camera, the image is visible directly on the iPhone screen. You will need to download the FLIR One app from the Apple app store in order to use it of course.

The app is a breeze to use and is very similar and in-line with other FLIR software. There are all the basic settings such as colour pallet, emissivity settings and basic analysis tools including a lens calibration tool. You can also take thermal imagery in a number of different ways. Still image, time-lapse and video. Although the video will contains no radiometric information.

Flir-one V1

The FLIR One. iPhone 5 / 5s thermal camera case attachment.

 

Below are some technical specifications of the FLIR One

Scene range temperature: 32 °F to 212 °F (O °C to 100 °C)
Operating temp: 32° to 95° F (0° to 35° C)
Weight: 3.9oz, 110grams
Dimensions: L 5.5 inches (140 mm) x W 2.4 inches (61 mm) x H .85 inches (22 mm)
Battery capacity: 1400 mA/h (maximum thermal imager battery life is approximately four hours continuous use. FLIR ONE does not consume power from the iPhone battery, nor does it charge the iPhone battery)
Core: FLIR Lepton thermal camera core
Visible camera: VGA (used for FLIR® MSX® blending)
Sensitivity: ability to detect temperature differences as small as 0.18 °F (0.1°C)
Charging method: micro USB and 1A wall charger (charges FLIR ONE but not the iPhone)
iPhone compatibility: iPhone5, iPhone5S running iOS 7 or above
The FLIR ONE app is available for download from the Apple App Store.
Included accessories: USB charging cable, iPhone case, and jack audio adapter.
Certifications and standards: FCC, CE, RoHS, CAN ICES-3 (B)/NMB-3(B), UL

 

For a first to market tech product the FLIR One preforms very well. Although as one may guess it has a lot of  space for improvement. Many of these improvements have already been made. FLIR has announced that it will be releasing the second generation FLIR One sometime in mid to late 2015.

Sacntherma Flir-One-iPhone_Android

The new 2015 FLIR One thermal camera dongle.

 

Some of the improvements are:

  • More powerful thermal sensor able to capture thermal images four times the resolution of the old FLIR One Leptom sensor.
  • Compact attachable unit that supports Lighting jack and MicroUSB connections. This makes it compatible with a wide range of phones including android smartphones.
  • Pricing to be lower than original release price. Also the original FLIR One will have its price lowered.

 

Seek Thermal

The Seek Thermal was released into the consumer market at the end of Q3 2014 and was met with positive reviews. It was one of the first competitors to the FLIR One and brought with it some enhancements that are worth serious consideration when deciding to purchase a mobile thermal device.

Scantherm seek-thermal

The Seek Thermal mobile dongle.

The first thing one notices is the different form factor of the two cameras. The Seek Thermal has been released as a dongle little larger than the average human adult thumb, where as the FLIR One is a bulky two stage extension iPhone case.

Another positive for the Seek Thermal is the thermal sensor, which is called the “True Thermal Sensor,” it’s in fact a vanadium oxide microbolometer which is capable of detecting long-wave infra-red between 7.2 and 13 microns. This gives you a thermal sensor with a total of 32,136 “Thermal Pixels” spread across a 206-by-156 pixel array. This is a far larger sensor than that of the Lepton sensor in the FLIR One which is a mere 80 x 60 thermal pixels. This means that the overall thermal image is more prises as there are more points of measurement.

Although the thermal image is higher in accuracy and sharper than the FLIR One images, the FLIR One attempts to step around this with FLIR’s MSX feature. MSX artificially enhances the thermal image by combining the thermal image with a higher resolution digital image to output a clearer and easier to interpret thermal image, albeit not as accurate.

One last thing that may put the SEEK Thermal a little further ahead of the FLIR One (first generation 2014) is the price tag at almost half the price.

Scantherma SEEK Thermal XR

The new and improved Seek Thermal XR seen paired with both iPhone and Android Phone

Much like the FLIR One, SEEK Thermal is soon releasing its own new and improved version with the SEEK Thermal XR. The new model will showcase a manual focus lens as well as the ability to optically zoom in on your targets, something even some high end thermal cameras lack.

Something tells me that this is just the beginning, competition is always good for advancement.

 

If you would like to know more about our range of FLIR products you can visit our Perth office here, or visit our thermal cameras website here.

You can find out more about the FLIR One here and the new Seek Thermal here.

Visually Classifying Your Maps by Attributes

Tired of staring at the same, drab, mess of lines and polygons? Having trouble finding the shapes you want? Mappt now has support for Classifications, allowing you to style your features according to the numeric or text values in the layer’s attributes.

Here we have some geological zones. As is typical with datasets, it’s not very pretty to look at. Worse, we can’t really tell much by just glancing at it!

Mmm, red.

Mmm, red.

Looking at the attributes defined in the layer, we can see there is an AREA key defined.

The list of attributes values for one of the zones.

The list of attribute values for one of the zones.

Let’s say we want to easily see the zones with the smallest areas. To do this, we open the layer’s properties, then navigate to the Classifications tab. Here, we can specify how we want to classify the data. In this case, we want to find highlight the features with the smallest AREA attribute value. Let’s do some experimenting!

First, we’ll try to classify the AREA by “Distinct Values”, which will give us a class for every unique AREA value in the layer.

The Classifications screen, showing how to classify an attribute by Distinct Value.

The Classifications screen, showing how to classify by Distinct Value.

When we hit Apply, the classes are generated, and we are taken to the Class Styles tab, which shows the styling applied to each of the determined classes. In the screenshot below, we can see that there were quite a few unique values, so much so that we haven’t really achieved anything by classifying them!  Perhaps Distinct Values wasn’t such a great choice!

There are too many classes to fiddle with.  We can see that classifying a numeric attribute by Distinct Value was a bad idea!

There are too many classes to fiddle with. We can see that classifying a numeric attribute by Distinct Value was a bad idea!

Let’s try again, this time using “Equal Intervals”, which instructs Mappt to classify the features into x number of classes, with x being chosen by us. So, let’s try Equal Intervals.

Let's try that again, this time with Equal Intervals.

Let’s try that again, this time with Equal Intervals.

This will give us 5 nice classes, evenly spread across the range of values found in the AREA attribute of the features in the layer.  We can apply styling to each class, as seen in the screenshot below, where I have used the colour blue to denote the lowest-range class, and yellow for the rest.  Also note that Mappt shows us the range of each class, as well as how many feature are in it, which is handy when fine-tuning your classification parameters.

Geology zones classification equal styles

Highlighting the lower-fifth zones by area in blue.

Closing the layer properties dialog, we can see the styling has been applied to the map. Because of the settings we choose, we have effectively highlighted, in blue, the zones that are in the lower 20% of overall zone sizes.

The smallest fifth of the zones, by area, can now easily be seen!

The smallest fifth of the zones, by area, can now easily be seen!

Using another example, here I have taken a dataset of the world’s volcanoes and classified them by elevation, using Manual Breaks defined at -4000, -2000, 0, 2000 and 4000 feet, allowing me to see which volcanoes are the highest, with increasing blue being below sea level, and increasing red being above sea level.

Blue because water is blue, red because... just because.

Blue because water is blue, red because… just because.

On the map, we can easily see which volcanoes are above or below sea level, as well as how far above or below, simply from their colour.

Aloha!

Aloha!

One last example shows the path of hurricanes in the Atlantic, coloured by wind speed, with redder being faster.

Red always gets such a bad rap in these things.

Red always gets such a bad rap in these things.

So in summary:

Classifications: Mappt, pretty.