Tree hugging Koalas

Every one knows how hot the Australian wilderness can get – here at Scantherma we’ve certainly had more than our fair share of experience. We usually slip, slop, slap and find cover to escape the heat, but what if you’re a little furry marsupial?

Most Australian fauna will hide from the sun by burrowing underground, seeking shelter in caves or invading our backyard swimming pools.

Crocodile-in-home-pool

No this is not a pool ornament or a deflated pool toy. It’s a REAL crocodile.

 

But what do you do if you live most of your life in a tree?

Koalas (Drop Bears) have until recently, been thought of as lazy, cute fuzzy little creatures that live in trees, and only come down to find another tree to climb up. They’re often seen clinging onto tree trunks, eating and sleeping. But now, thanks to research done by the University of Melbourne’s Zoology department, it turns out that there’s a deeper reason why Koalas hug trees so tight, especially in the summer. And it’s not because they’re lonely.

Sleepy Koala

During your average heat wave, the temperature in the Australian bush can reach over 50 degrees C, and around 45 degrees C in the shade.  To survive this blistering climate, Koalas do what they do best, hug trees.

The reason is simple. Depsite the unbearable heat, a large tree’s core temperature stays comparatively low. This makes it very convenient for the Koala as the tree is both its shelter and food source.

Below are some thermal images taken by Steve Griffiths that show the Koalas in action, or rather no-action and just laying there cooling down.

Scantherma_Koala_Thermal_Heat_1

It can be clearly seen here that the tree trunk in shades of purple is much, much cooler than the Koala’s body.

Scantherm_thermal-image-of-koala-tree-hugging

Both a cooler and a bed, oh and a kitchen, and maybe many other things. This tree is everything to the Koala.

 

Scantherm_thermal-image-of-koala-tree-sleeping

Looks like Koalas have the ideal life style.

So next time you see a Koala hanging out, remember that it is actually working hard to cool down by using its surroundings and conserving energy and water. Not so lazy after all!

If you would like to find out more about Thermal Imagery and how it can help you visit our Thermal Imaging page here, or come and visit us at our Perth office and one of our friendly technicians will gladly assist.

The search for Malaysian Airlines Flight MH370; an image engineering approach

Scantherma will be holding a presentation for Engineers Australia to showcase its methods using different image engineering to assist with the search for Malaysian Airlines Flight MH370. The presentation will be held at the Engineers Australia WA Division in West Perth. Details to follow:

Abstract

On the 8th of March 2014, Malaysian Flight MH370 disappeared. What followed was an un-precedent search effort involving over a dozen countries and a combined search area of over 1/10th of the Earth’s surface. At no time in modern aviation has there been such a myriad of facets in the use of technology in finding an aircraft. Scantherma was tasked  to use its “object-based image analysis” (OBIA) algorithms to comb through hundreds of satellite images containing potential wreckage in the southern Indian Ocean. This proved to be a new approach in utilising image engineering to a totally different audience. After more than 3 weeks of analysis, the search using satellite imagery was abandoned. However, the exercise proved extremely useful in not only identifying new OBIA methods; but also its application towards oceanic remote sensing in general.

Image showing velocity of currents in the eastern Indian Ocean. Overlayed is the  search areas analysed by satellite imagery over 3 weeks in March and April, 2014. The input of current velocity and direction was crucial in setting up algorithms for the use of OBIA. [Source: Scantherma 2014]

Image showing velocity of currents in the eastern Indian Ocean. Overlayed is the search areas analysed by satellite imagery over 3 weeks in March and April, 2014. The input of current velocity and direction was crucial in setting up algorithms for the use of OBIA. [Source: Scantherma 2014]

Software Used
  • Trimble eCognition
  • Mappt
  • ER Mapper
  • QGIS
Acknowledgements
  • Christian Hoffmann (Trimble)
  • Trevor Marshall
  • Michael Breen
  • JJ Rodrigues

Landsat 8: different strokes for different folks

Ever since the launch of the latest Landsat series of satellites by NASA, Landsat 8 has been actively collecting 11 bands of imagery with fantastic clarity. Landsat 8 so far has been very successful and it will soon take over in popularity of Landsat 7 as the most popular Earth imaging satellite.

However one thing to note is that Landsat 8 has slightly different spectral wavelengths to its predecessor resulting in different combinations. For example, its been the common norm to simply choose bands 4, 3 and 2 in RGB channels to highlight vegetation in false colour (red); this has changed to 5, 4 and 3 in RGB. Its often hard to change ones routine. We’ve put together a quick cheat sheet comparing both Landsat 7 and Landsat 8 bands, and which band combinations are best suited to observing different surfaces.

Landsat 7 vs Landsat 8

Landsat 7 vs Landsat 8 band wavelengths

Furthermore, we’ve put together a quick combination matrix that summarizes the use of Landsat 8 bands in highlighting different surface types.

Landsat 8 band matrix highlighting the best combinations to use to showcase different surface types.

Landsat 8 band matrix highlighting the best combinations to use to showcase different surface types.

In conclusion, Landsat 8 is continues a terrific series of what is the earth’s longest running imaging system. The more imagery we process for our clients, particularly for those requiring geological or vegetation analysis, we get to truly appreciate how good of a job the folks at NASA have done. Keep it up girls and boys!

 

Perth remote sensing firm on MH370 mission

By Liam Croy [Story as it appeared in The West Australian – 3rd of April, 2014]

A Perth remote sensing company has been tasked with finding the wreckage of MH370. Welshpool-based Scantherma applies its mapping and imaging technologies across a range of residential, commercial, agricultural and resources projects. From iron ore exploration in the jungles of West Africa to energy efficient homes in Perth, Scantherma’s capabilities are diverse in nature and scale.

Chief executive Amir Farhand and his 11 staff do the bulk of their work in the resources industry, where they have teamed with BHP Billiton, Fortescue Metals Group and the world’s largest iron ore producer, Brazilian corporation, Vale.

They are currently working with Samsung C&T on the Roy Hill project in the Pilbara. But after a “serendipitous” meeting at a recent mining expo in Hong Kong, Scantherma took on its biggest and most unique challenge yet.

“We were contacted by a very large insurance company which might have a big bailout because of this missing plane,” he said.

The Perth company was commissioned to use its “object-based image analysis” software to comb through hundreds of satellite images containing potential wreckage. They analysed 437 images of debris in the original southern Indian Ocean search area, before shifting their focus north-east last Wednesday based on ocean current data. Two days later, the Australian Maritime Safety Authority announced a new 319,000sq km search area in the same region.

“There was plenty of debris in those first 437 images but it wasn’t from the plane,” he said. “It was mostly white caps and sea junk. Global shipping lanes pass through that area to the south of Western Australia.

“What (AMSA) is doing is terrific because they’ve only got finite resources. Our stuff is done on computer but it takes four hours just for the planes to get out there.

“It’s just such a vast area. We’re in mining so we say it’s like trying to find Lasseter’s Reef.”

Mr Farhand said the insurance company was expected to call off the search this weekend when the plane’s black box was due to run out of battery. But for now, four US and Japanese satellites are scanning a search area nearly four times larger than AMSA’s site.

He said Scantherma’s chief remote sensing analyst was stationed in Florianopolis, Brazil, ready to identify any signs of MH370 in the next set of images.

“It’s been incredible. Most of the work we do is for mining companies, so it’s been terrific to be able to use this technology for a humanitarian purpose,” he said. “As a society, I think we need to embrace these types of technologies more.”

Original Article

The FLIR ONE

As many of you may have read on our Blog a few months ago, FLIR showcased a new gadget – a FLIR thermal camera sensor and lens built into a custom iPhone case, thus creating something that had not been seen before: a mobile phone capable of capturing and editing actual thermal imagery.

Unlike many prototypes that made it no further than the concept stage, FLIR has pushed their prototype Thermal Camera iPhone case into consumer production.  The FLIR One, as it’s called, is now available for purchase for less than $350 USD.  Some may think that $350 is a lot to pay for an iPhone case with another camera on it, but compared with it’s closest living relative, the FLIR E4, which is priced at around $1600 AUD, it’s a no-brainer.

Scantherma_FLIR-one_Iphone_5

The new FLIR One iPhone case, sporting a very sleek design, thermal camera and sensor and a built in battery. Very nice!

With the FLIR One, small business owners and enthusiast now have a way to see what’s hot and what’s not without breaking the bank.  But remember, for all the big boys, FLIR has a large range of hand held and fixed thermal cameras that are sure fit your needs.

For more information on the professional thermal imaging solutions Scantherma offers from FLIR please visit our Thermal Camera website here, or drop in to our Perth office for a free consultation.

Cooler Roofs Reduce CO2 Emissions

As cool as a shiny new black sports car is there is wisdom in choosing one with a white paint job. With the sun bombarding the cars body the black paint will naturally absorb more of that energy and the white car will reflect it. This for some is a matter of life and death in the middle of summer as the inside of their cars transform into state of the art pizza ovens while they’re parked.

Slowly a similar and common theme is becoming apparent with in the building construction industry. More and more new buildings are having light coloured roofs installed instead of the standard darker colours.

Common sense seems to be prevailing at last and now also backed up with research. Lighter coloured roofs reflect more sunlight there fore keeping the building interior cooler. Coupled with ceiling and wall insulation, blinds and properly treated windows the air-conditioner will be under less stress in the middle of summer thereby cutting down usage leading to the drop in CO2 emissions. In fact white coloured roofs are possibly the quickest and cheapest way to start reducing house hold CO2 emissions. Along with cooling the interior of the building by reflecting heat radiation they also reduce what is called the urban heat island effect. This effect can be caused by such things as darker coloured roofs absorbing heat and retaining it through out the day and slowly releasing that energy into the air thereby raising the ambient temperature of that area. Entire cities can become heated this way and this can be detrimental for the energy efficiency of the city as a hole.

Scantherma_Cool Roofs_02

Aerial Thermal images showing the cooler roofs in shades of blue reflecting the heat. Note that most other house roofs are almost as hot as the road surface which is by far the hottest.

Scantherma_Cool Roofs_01

Same as above, the houses with the lighter coloured roofs reflect more heat than those with darker colours.

Scantherma_Cool Roofs_03

Not as many light coloured roofs in this area. Although coolour matters most, material is also a vital factor. Metal roofs will reflect more than tile or slate.

Extensive studies, especially in the United States, have now caused governments to act. For instance in the US Energy Secretary Steven Chu announced a series of initiatives at the Department of Energy to more broadly implement cool roof technologies on DOE facilities and buildings across the federal government. Other governments have also taken action and have started encouraging local builders to start installing white roofs along with light coloured exterior finishes.

Scantherma_Santorini

The people of the Island of Santorini have the idea.

 

Landsat Satellites catch deforestation red handed

Illegal deforestation can no longer remain hidden

The World’s forests are shrinking at an alarming and uncontrollable rate. There are of course a wide rage of causes ranging from cleared land for farming and ranching to mining and timber cultivation. Many of these take place within the some times thin and dotted boundaries of local and international law, but there are so many that slip past and go unseen. Thanks to the ever advancing technology of remote sensing these areas of illegal deforestation are slowly emerging out of the fog of corruption and ignorance.

Below images show a section of the Amazon forest near Tamshiyacu in Peru being illegally cleared for Palm Oil plantation. Many areas of the Amazon basin are completely cleared each year to make room for Palm, Soya and other plantations destroying entire ecosystems and endangering the survival of many plant and animal species, some of which have not yet been formally discovered.

The Palm trees planted are by no means a viable replacement for the natural habitat lost to hundreds of species and after cultivation Soya plantations just expand having depleted all the nutrients in the ground making the land completely useless. There are ways to make the land fertile again after the plantations have moved on but at great costs.

 

Scantherma_tamshiyacu_2012

Tamshiyacu Peru showing the Amazon River on the left of the image. Landsat Image acquired October 5, 2012.

Scantherma_tamshiyacu_oil_2013

The same area as above showing the massive deforested area to the right. This area has been cleared to make way for an Oil Palm plantation. Landsat Image acquired August 28, 2013.

The Palm Oil industry has already left a great scar on the face of some of Earths most important and diverse rain-forests in Malaysia and Indonesia. Now the Palm Oil boom has started in Brazil and with carefully controlled sustainable cultivation it can greatly benefit the local industry and people as it should. If planted on the degraded pasture land that is becoming increasingly plentiful, oil palm could generate more jobs and higher incomes for locals than the dominant form of land use in the region: low intensity cattle ranching. Rather than destroying more rain-forest for more cattle pasture, local farmers could go into the oil palm business and benefit from its higher returns.

In the end education is key. Teaching the local peoples of affected countries how best to utilize the resources of their lands to prosper and advance, at the same time safe keeping it for future generations.

To find out more about Scantherma’s remote sensing services and how it can help your project please go here.

Is Your Home Energy Efficient?

As our society advances we become a little wiser and learn from our mistakes. We also learn more about our environment and how we fit in it. The Earth’s population is rising rapidly and at this point in time it can be said that humankind is directly impacting the environment more than ever before. As one can imagine this impact is mostly negative. You may look at this and ask your self what you can do.

Well there are many things we can all do at the grass roots to make a positive change. To slow down and eventually halt this negative impact. One of the many things that we can do is to make our homes energy efficient. This will reduce the carbon footprint of our homes thereby reducing greenhouse gases.

At Scantherma we conduct Energy Audits using state of the art Thermal Imaging equipment. These inspections along with the accompanying reports have helped countless homes and business save money and lower their carbon footprint. The following are some areas we look at when inspecting buildings for energy efficiency using our thermal imaging cameras.

Insulation

Scantherma_missing_insulation

Missing insulation can be clearly seen here as the warmer orange to yellow colours.

Scantherma_missing_insulation 2

Again there is some areas with missing roof insulation in the corner of the room as seen in yellow.

Scantherma_damaged_insulation

Here we can see some damaged roof insulation in yellow. The exposed tin roof is radiating heat into the roof space thus elevating the ambient temperature. This will in turn reflect the overall temperature of the building interior.

Air Leeks (infiltration – exfiltration)

Scantherma_Air_infiltration4

Here we can see the effects of air infiltration by the blue tones in the image. The room behind this door is air-conditioned and the cool air is pushing through micro-gaps at the bottom of the door.

Scantherma_Air_infiltration 2

Cool air is pushing through gaps behind the garage roller door represented by dark blue.

Moisture

Scantherma_moisture_damage 1

In this image we can see an area with severe moisture damage in purple. This area was inundated by rain water pushing through small gaps in the exterior structure of the building.

Scantherma_moisture_damage 2

Structural damage in the building roof has allowed rain water to enter in and heavily damage this wall corner.

Heating / Cooling

Scantherma_aircon_ducted

This image shows the flow of cool air from the ducted air-conditioner vents. As can be seen the cool air flow is concentrated in one direction.

Scantherma_aircon_ducted 2

Cool air flow can be seen here in dark purple in the air vent.

Scantherma_heeting_vent

Heating vent can be seen here in yellow.

Scantherma_Cooling_Heeting 2

Image of wall mounted reverse cycle air-conditioner unit after service. The blue shows unobstructed cold air flow.

Lighting

Scantherma_Lighting 2

Here we can clearly see a conventional down-light that has just been turned on.

Scantherma_Lighting

The same down-light after a few minutes of use. The core has heated up a fair amount and now shows the light at it’s optimum temperature range. Many similar lights heated up to above 80 degrees. These were later found to be faulty.

 

 Our FLIR Building Inspection Video.

You can find more of our FLIR videos on our YouTube channel here. Or if you would like to find out more about our Thermal Imaging services visit us here. Alternatively you can visit us at our Perth office here and one of our friendly technicians will be glad to help.

 

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.

Mappt v1.4.3.7 Now Available

Merry Christmas from the Mappt team!  We are pleased to announce the release of version 1.4.3.7 of Mappt for Android.

You can download the latest version of Mappt from the Google Play store:

Link to download Mappt from the Google Play store

Read below for the new features in this version!

Classifications

 Mappt now has the ability to style your features according to their attribute data, making it far easier to distinguish things at a glance!

We have written a detailed blog post about it, here.  Or, if you’d rather see it in action here, in this very page, behold!

Aloha!

Hawaiian volcanoes, coloured according to elevation!

Mappt now attempts to determine feature names when importing shapefiles.

When importing data from shapefile, we have taught Mappt to guess the names of features from the attributes.  We’ve had a pretty good success rate with this quick fix, testing it against public and private datasets.  Who’s a good good boy!

Bug Fixes

As always, we have squashed a few bugs in this release.

Don't worry, Mappt has less bugs than this.

Yep, it’s the same picture as last time.  I can’t stop staring at it.