- Collecting evidence of deforestation or forest degradation
- Capturing evidence of companies’ wrongdoing in how they use land
- Recording and monitoring the environmental value of land or forest areas
This introduction to satellite imagery is part of a Primer for using technology to monitor and share information on rainforest issues, land rights and indigenous rights. It is designed as a starting point for organisations and activists interested in adding technology to improve their advocacy work, and is the product of a partnership between Rainforest Foundation Norway and The Engine Room.
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What is it
- Satellites orbiting the globe take photographs of the Earth’s surface from space, which can include images of forests or community land.
- These photographs can be used to produce analysis of changes to a forest area over time, or combined with other forms of information, including other types of maps.
How it can help
Satellite imagery was once too expensive for all but large institutions, governments and big corporations. Now, it is easily accessible and free (or very cheap). Comparing regular images of the same area can provide proof of deforestation, trends like increased commercial activity, or visible results of forest destruction like monocultures (which follow planting patterns that can be seen from above).
There are very good free, open-source tools to analyse satellite imagery: QGIS is the most widely used GIS software. QGIS lets users add, edit, manipulate, and present GIS data. It has less advanced features than ArcGIS (see Mobile phone applications), takes longer to learn and is less stable – but it is free, and has an active volunteer community providing technical support. You will need to know programming languages like Python for more complex analytical processes.
Global Forest Watch (GFW) is the most comprehensive online tool for monitoring the world’s forest cover. It analyses satellite imagery for forest loss in near real-time, provides alert systems for deforestation and fires and sends emails when a selected area undergoes changes. GFW also shows the latest satellite imagery from Landsat 8 and Sentinel-2, updating as soon as new imagery is available.
Satellite imagery can be free, while commercial purchases range between $10 and $50 per square kilometer, depending on image quality. SatSummit provides a detailed breakdown of options and costs. Purchase costs aside, analysing satellite images is an expensive and labor-intensive task, requiring considerable investment in time (analysing thousands of high-resolution images), resources (fast computers) and skills (GIS experts). Global Forest Watch helps to bridge this gap, but it doesn’t always have access to the high-quality imagery needed to show change in great detail.
Risks and challenges
The main problem with satellite imagery is resolution, which currently means that image quality is too low to show change in detail. Global Forest Watch provides some imagery at 30 meters per pixel in some countries. Currently, worldwide forest change imagery at 30m resolution is only available once every year, which isn’t always fast enough to be used as proof of deforestation.
This brings us to the second problem: updates. Images are usually updated monthly, and sometimes yearly. This makes them good for historical analysis, but sometimes impractical for real-time monitoring (though DIY Aerial Photography can help get more up-to-date images). This is changing, though: Global Forest Watch’s GLAD alerts provide weekly, 30m alerts of likely tree cover loss in Peru, Republic of Congo, and Kalimantan (Indonesia). Brazil is expected to be ready by August 2016, with the rest of the pantropics available by early 2017. Libra provides an easy way to find and download Landsat data every two weeks. The MAAP project also aims to produce updates on the Andean Amazon every 1-2 weeks, while companies like Planet Labs promise to provide free daily images in the future.
Finally, cloudy weather can hide the forest areas below – it can take some time to get pictures that have been taken on a clear day.
Combining satellite data with other information sources
The Indonesian rainforest organisation Warsi combined satellite mapping data that they obtained from Landsat Thematic Mapper (Landsat TM) and Advanced Land Observation Satellite (ALOS) with other information sources to document the distribution of the Orang Rimba people and their use of natural resources.
How did it help?
- Warsi was able to combine the satellite data with GPS data and digital maps that they made by converting paper maps on natural resource concessions.
- The satellite imagery was relatively expensive for Warsi. Clouds sometimes covered crucial parts of the image, meaning that they needed to analyse a series of images to get a proper picture.
- The Bukit Duabelas national park now provides the Orang Rimba with user rights and formally protects the area, though deforestation remains a serious problem.
Using satellite data to provide evidence of illegal logging
In January 2015 Greenomics-Indonesia’s analysis of two NASA Landsat images of Pulau Pedang island, off the coast of Sumatra, identified that large areas of peat forest had been cleared.
How did it help?
- Greenomics used the information to target paper company Asia Pacific Resources International Holdings Limited (APRIL), which had publicly promised to end new plantation development by January 2014.
- Greenomics chose to release this information to the media in English, producing a statement with images of their claim. In March 2015, APRIL publicly admitted there had been a breach and suspended a contractor and a plantation manager.
- Global Forest Watch is an interactive online forest monitoring and alert system that provides satellite and other types of information
- MAAP (Monitoring of the Andean Amazon Project) is a project of Amazon Conservation Association and ACCA-Conservación Amazónica
- CLASlite is designed to provide weekly updated high-resolution mapping and monitoring of forests with satellite imagery. (English and Spanish)
- AAAS’s Geospatial Technologies Project contains detailed case studies of how satellite imagery was collected, categorised and analysed to document human rights abuses
This site was created by Rainforest Foundation Norway and The Engine Room as an introduction to using technology to monitor and share information on rainforest issues, land rights and indigenous rights. Download the whole primer here.
Rainforest Foundation Norway (RFN) is one of the world’s leading organisations in the field of rights-based rainforest protection. Its mission is to support indigenous peoples and traditional populations of the world’s rainforests in their efforts to protect their environment and fulfil their rights by assisting them in:
- Securing and controlling the natural resources necessary for their long-term well-being and managing these resources in ways which do not harm their environment, violate their culture or compromise their future;
- and developing the means to protect their individual and collective rights and to obtain, shape, and control basic services from the state.
RFN collaborates closely with more than 70 local and national environmental, indigenous and human rights organisations in 11 countries in the Amazon region, Central Africa, Southeast Asia, and Oceania.
The Engine Room is an international organisation that helps activists, social change organisations, and change agents make the most of data and technology to increase their impact. The Engine Room provides direct, project-level support for social change organisations; brings together communities to coordinate emerging ideas and collect practitioners; and documents and publishes findings to help anyone in the sector make better decisions about using data and technology.
Tom Walker and Tin Geber researched and wrote the main narrative, while Ruth Miller led work on the design and visuals creation. Vemund Olsen and Christopher Wilson provided invaluable input and editing support. The site sourcecode is available on Github. Comments or questions? Contact firstname.lastname@example.org or email@example.com.