More than half of the contiguous remaining forests on the mainland in Southeast Asia are found in Myanmar. These forests are home to many species of animals and plants and are a source of food and protection from flooding (among other things) for the local population. Unfortunately, the rate at which these forests are being illegally cleared is increasing. How satellite imagery can be used to fight this is something we asked Andrea Hess, who works on a project in this field.
In the last few years, clearing in the rainforests of Myanmar (formerly known as Burma) has grown significantly. This problem affects protected animals such as tigers or the Asian elephant. Via a cooperation between the Burmese NGO Ecodev, the Smithsonian Institution and the American Museum of Natural History, logging in Myanmar will now be evaluated using satellite imagery.
To get a direct insight into the project, we spoke with Andrea Hess, a young scientist who has worked on the project.
What benefits does satellite imagery offer as opposed to simple aerial shots?
A big benefit of satellite imagery is that a satellite is sent into orbit one time and then we receive regular images. Using this method in the field of land cover, we can very conveniently compare changes in recent years. Aerial shots are only possible to obtain when you deliberately fly over a specific area and take photos.
Apart from this, satellite images cover much bigger surfaces. If someone wants to examine a relatively large area, simple aerial shots are not practical. In principle, it is only possible to carry out analyses of country or continental plains via satellite imagery. For our project, we examine the development of the forest cover in the whole of Myanmar. Without satellite technology, this would be a lot more complex.
To what extent are satellite images automatically evaluated – do they still need to be looked over by human eyes?
There are definitely algorithms that can be used to completely evaluate satellite images automatically. But what is very popular is so-called supervised automatic classifications. This is virtually a semi-automated analysis whereby somebody always looks at the satellite images at the beginning and manually creates so-called training data. In this way, someone shows the program areas where, for example, natural forests or plantations occur. This information is then applied to the whole image using an algorithm. Having to specify training areas for each image is labour-intensive but the result of such a classification is utlimately better.
How do the preliminary results of your forest cartography look?
Our result looks a little sad. We are seeing an extreme amount of logging in three certain areas in Myanmar. The yearly rate of logging supercedes the global average and it is even higher in the three aforementioned regions. Occasionally, the hardest hit areas lie on the border to China and Thailand. On our map, you can clearly see how logging is increasing the further you get to these two borders. However, deforestation looks different in each region. On the border with Thailand, large areas are being cut down and converted to plantations (mainly palm oil). On the border with China, the are fewer bare surfaces to see. Here, we are monitoring more of a steady increase in forest degradation. The reason for this is that plantations are not being built in this area. Rather, a certain type of hardwood is being cut down and transported to China. No large areas are being cleared but single trees are being logged in a big way. Another factor are the many gold and jade mines that have dramatically expanded in the last 10 years. In these cases, the forest is of course cleared before construction of the mine can begin.
How do you deal with the results? Who gets the results, and what happens when illegal logging is detected?
Our results will be accessible to the public. One problem in Myanmar is that the government, or more to the point, the Forestry Office, has exact data on the conditions of the forests and the rate of deforestation but they don’t like to share it with the public. All environmental organisations that operate here in Myanmar find it difficult to access such data. We wish for our maps to be accessible to everyone and, through this, help simplify the work of other organisations. That is only one aspect.
The organisation I work for, EcoDev, is an NGO focused on collaboration with civil society. It is important to us that people living in the affected areas are informed about the extent of the deforestation in their area. Deforestation and illegal logging occurs in these communities often without residents’ knowledge or approval. And when places like this are found, where trees have been cut without anybody knowing or approving, the government itself must finally justify it. In the long-term, hopefully this leads to better legislation on issues like land grabbing (illegal land acquistion) and illegal logging and that these laws are the enforced.
Are areas with a high rate of illegal felling also often regions where the local population, on average, has a low income? Or is population density a deciding factor?
You can, of course, observe that less is cut down in sparsely-populated areas. Many areas are so remote and difficult to reach that clearing in any big way does not really occur. What we see in such areas is regular clearing of small surfaces for shifting cultivation. This consistently contributes to forest degradation but on the level at which it is currently done, it is manageable.
When it comes to illegal felling conducted on a large scale, other factors outside of population density and income are much more important. Above all is the fact that in many areas, ethnic conflicts prevail. Often illegal logging here is directly or indirectly related to armed ethnic groups that finance themselves by cutting down precious hardwood.
Is there also additional pressure because of the underhanded sale of forest clearing grants to ‘Big Players’ ?
There are other factors that are more important. One problem that involves grants and ‘Big Players’ and doesn’t deserve the title of ‘illegal logging’ is the fact that grants to set up plantations are often abused. International companies receive a grant to set up a plantation in a specific area. The surface is first cleared and the wood can then be sold as so-called ‘conversion timber’. The problem is that in some cases, the plantation is then never set up and the land lies idle because the sale of the timber is worth more than the actual plantation.
Given that your maps compare 2002/2003 and 2013/2014: is there the possibility that forest areas were cut shortly after 2003 and by 2013 primary forest is present, so the logging is obscured?
This is basically what makes it so hard for us to map out the areas where shifting cultivation is being carried out. The idea is that an area is cleared and is then left alone after use until the forest has regenerated. But this occurs over a much longer period than 10 years. According to the traditional ‘Myanmar selection system’, upon which forestry here is built, each surface is to be cleared every 30 years. In such cases, where a field has been cleared 30 years prior, we find it difficult to distinguish between primary forests and secondary forests on the basis of satellite images. An area that was deforested 10 years ago would still appear to be a quite young and degraded forest in our analysis in any case.
What do you personally hope the impact of the project might be?
I personally hope that making our data accessible leads the Forestry Office to making their data accessible. In order to efficiently fight against illegal deforestation, transparency seems to really be a sticking point. Only then is it possible for the civilian population to be on the same level as the government in the whole discussion.
What does the future of the project look like? How will you work on it further?
One big idea that is currently on the table is to use drones to help map out certain focus regions more accurately. Areas under 100 m² are poorly mapped when using the satellite images that we currently use. With permission from the Mining Ministry, we will build drones ourselves and map mines that we have previously been unable to record. We want to do this because many companies receive a ‘small scale mining’ grant and then they expand the mine without permission. With our drones, we wish to fly over single mines and record the actual size of the mining site.