Have you read the top Pixalytics blogs of 2016?

Artist's rendition of a satellite - paulfleet/123RF Stock Photo

Artist’s rendition of a satellite – paulfleet/123RF Stock Photo

As this is the final blog of the year we’d like to take a look back over the past fifty-two weeks and see which blog’s captured people’s attention, and conversely which did not!

It turns out that seven of the ten most widely viewed blogs of the last year weren’t even written in 2016. Four were written in 2015, and three were written in 2014! The other obvious trend is the interest in the number of satellites in space, which can be seen by the titles of six of the ten most widely read blogs:

We’ve also found these blogs quoted by a variety of other web pages, and the occasional report. It’s always interesting to see where we’re quoted!

The other most read blogs of the year were:

Whilst only three of 2016’s blogs made our top ten, this is partly understandable as they have less time to attract the interest of readers and Google. However, looking at most read blogs of 2016 shows an interest in the growth of the Earth Observation market, Brexit, different types of data and Playboy!

We’ve now completed three years of weekly blogs, and the views on our website have grown steadily. This year has seen a significant increase in viewed pages, which is something we’re delighted to see.

We like our blog to be of interest to our colleagues in remote sensing and Earth observation, although we also touch on issues of interest to the wide space, and small business, communities.

At Pixalytics we believe strongly in education and training in both science and remote sensing, together with supporting early career scientists. As such we have a number of students and scientists working with us during the year, and we always like them to write a blog. Something they’re not always keen on at the start! This year we’ve had pieces on:

Writing a blog each week can be hard work, as Wednesday mornings always seem to come around very quickly. However, we think this work adds value to our business and makes a small contribution to explaining the industry in which we work.

Thanks for reading this year, and we hope we can catch your interest again next year.

We’d like to wish everyone a Happy New Year, and a very successful 2017!

Four Fantastic Forestry Applications of Remote Sensing

Landsat Images of the south-east area of Bolivia around Santa Cruz de la Sierra 27 years apart showing the changes in land use. Data courtesy of USGS/NASA.

Landsat Images of the south-east area of Bolivia around Santa Cruz de la Sierra 27 years apart showing the changes in land use. Data courtesy of USGS/NASA.

Monitoring forest biomass is essential for understanding the global carbon cycle because:

  • Forests account for around 45 % of terrestrial carbon, and deforestation accounts for 10% of greenhouse gas emissions
  • Deforestation and forest degradation release approximately identical amounts of greenhouse gases as all the world’s road traffic
  • Forests sequester significant amounts of carbon every year

The United Nations (UN) intergovernmental Reducing Emissions from Deforestation and forest Degradation in developing countries (REDD+) programme, was secured in 2013 during the 19th Conference of the Parties to the UN Framework Convention on Climate Change. It requires countries to map and monitor deforestation and forest degradation, together with developing a system of sustainable forest management. Remote sensing can play a great role in helping to deliver these requirements, and below are three fantastic remote sensing initiatives in this area.

Firstly, the Real Time System for Detection of Deforestation (DETER) gives monthly alerts on potential areas of deforestation within Amazon rainforests. It uses data from MODIS, at 250 m pixel resolution, within a semi-automated classification technique. A computer model detects changes in land use and cover such as forest clearing that are then validated by interpreters. It has been valuable helping Brazil to reduce deforestation rates by around 80% over the last decade; however, it takes two weeks to produce the output of this computer model.

Zoomed in Landsat Images of the south-east area of Bolivia around Santa Cruz de la Sierra 27 years apart showing the changes in land use. Data courtesy of USGS/NASA.

Zoomed in Landsat Images of the south-east area of Bolivia around Santa Cruz de la Sierra 27 years apart showing the changes in land use. Data courtesy of USGS/NASA.

A similar initiative is FORest Monitoring for Action (FORMA), which also use MODIS data. FORMA is fully automated computer model which combines vegetation reflectance data from MODIS, active fires from NASA’s Fire Information for Resource Management and rainfall figures, to identify potential forest clearing. Like DETER it produces alerts twice a month, although it works on tropical humid forests worldwide.

A third initiative aims to provide faster alerts for deforestation using the research by Hansen et al, published in 2013. The researchers used successive passes of the current Landsat satellites to monitor land cover, and when gaps appear between these passes it is flagged. These will be displayed on an online map, and the alerts will be available through the Word Resources Institute’s Global Forest Watch website, starting in March 2016. With the 30 m resolution of Landsat, smaller scale changes in land use can be detected than is possible for sensors such as MODIS. Whilst this is hoped to help monitor deforestation, it doesn’t actually determine it, as they could be other reasons for the tree loss and further investigation will be required. Being an optical mission, Landsat has problems seeing both through clouds and beneath the forestry canopy, and so it’s use will be limited in areas such as tropical rain forests.

Finally, one way of combat the weather and satellite canopy issue is to use radar to assess forests, and the current AfriSAR project in Gabon is doing just that – although it’s with flights and Unmanned Aerial Vehicles (UAV) rather than satellites. It began in the 2015 with overflights during the dry season, and the recent flights in February 2016 captured the rainy season. This joint ESA, Gabonese Space Agency and Gabon Agency of National Parks initiative aims of the project is to determine the amount of biomass and carbon stored in forests, by using the unique sensitivity of P-band SAR, the lowest radar frequency used in remote sensing at 432–438 MHz. NASA joined the recent February missions adding its Uninhabited Aerial Vehicle Synthetic Aperture Radar (UAVSAR) and the Land, Vegetation and Ice Sensor (LVIS) instrument, which are prototypes of sensors to be used on future NASA missions. Overall, this is giving a unique dataset on the tropical forests.

These are just four example projects of how remote sensing can contribute towards towards understanding what is happening in the world’s forests.