A Survey of Forest Monitoring Systems
This page gives a brief overview of other forest monitoring approaches.
Bunjil Forest Watch is a tool intended for one specific purpose – to alert locals when ‘illegal’ deforestation occurs. There are many other teams and organisations around the world working on related challenges for forest monitoring and conservation.
Please leave a comment if there is a system that should be added.
Brazillian Systems
Brazil has the largest and most systematic use of remote sensing for environmental protection of any country.
Some notable operational systems include DETER and PRODES by the Brazil Space Agency, INPE; SAD by Brazilian not-for-profit IMAZON; and CLASlite by the Carnegie Institution for Science which is also focused initially on the Amazon. Between 2005 and 2008, PRODES indicated deforestation in the Amazon had slowed compared to what it would have been without the detection and enforcement.
The Brazil Space Agency INPE runs DETER and PRODES. The newer DETER system can detect large scale illegal logging in near real time while PRODES has higher resolution but results are only updated annually. DETER provides an update every 15 days and sends alerts to Brazil’s Ministry of Environment enforcement agency IBAMA, and police. Loggers are fined and sometime have their property confiscated. DETER relies on a range of satellites including Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) and the China-Brazil Earth Resources Satellite CBERS-2.
CLASlite
Carnegie Landsat Analysis System Lite (CLASlite) is an automated satellite mapping approach that performs statistical analysis on raw satellite images to detect sub-pixel changes in forest cover. While broad-scale clear felling is easier to detect, CLASlite can also detect selective logging down to one or two trees. It is able to distinguish undisturbed forest from recent degradation and regrowth.
After calibration, pre-processing, atmospheric correction, and cloud masking steps, CLASlite will analyse the spectrum reflected in each pixel. Vegetation that photosynthesizes has a different spectral signal from dead trees, rocks or soil. A ‘Monte Carlo’ analysis then produces a range of possible combinations that converge on the most likely explanation for the data (Asner, 2009). By determining the fractional cover from canopy, dead wood and bare surfaces, CLASlite can provide maps of the forest’s composition, including where it has been disturbed. If a tiny red reflection is picked up indicating bare earth, and that signal forms a line over several pixels, the most likely explanation would be a road.
Detecting new logging tracks early increases the opportunity to combat deforestation and degradation, as these are often the first indication of more extensive logging to come.
For input, CLASlite can use a wide variety of satellite imagery including: Landsat 4 and 5 Thematic Mapper (TM), Landsat 7 Enhanced Thematic Mapper Plus (ETM+), ASTER, Earth Observing-1 Advanced Land Imager (ALI), Satellite pour l’Observation de la Terre 4 and 5 (SPOT), and MODIS.
Classlite recently published a free online course on forest mapping and monitoring.
IUCN Protected Planet
IUCN. World Database on Protected Areas.A joint initiative between IUCN and UNEP WCMC. www.protectedplanet.net
SAD
Brazillian System
Deforestation in Time Lapse
Global Forest Watch
Global Forest Watch is a dynamic online forest monitoring and alert system that empowers people everywhere to better manage forests.
From a partnership convened by the World Resources Institute
The app is powered by Google Earth Engine, with maps showing deforestation and real-time fires, among other maps.
The Global Forest Watch blog catalyzes conversations around improved forest management by providing timely, credible analysis on threats to global forests.
The GFW API (in beta) makes it easier to share GFW data. So far the API includes:
- University of Maryland (UMD) Tree cover loss & gain,
- FORMA alerts,
- IMAZON SAD alerts,
- QUICC alerts, and
- NASA active fires.
For one example see the anti-paoching site: www.smarconservationtools.org
Global Land Analysis and Discovery
In February 2016, GFW announced Global Land Analysis and Discovery (GLAD) alerts. It detects tree cover loss in Peru, Republic of Congo and Indonesian Borneo (Kalimantan) at 30-meter resolution.
The excellent research article is available with open access
Humid tropical forest disturbance alerts using Landsat data
Matthew C Hansen, Alexander Krylov, Alexandra Tyukavina, Peter V Potapov, Svetlana Turubanova, Bryan Zutta, Suspense Ifo, Belinda Margono, Fred Stolle and Rebecca Moore. Published 2 March 2016
Forest Maps
Forests worldwide are in a state of flux, with accelerating losses in some regions and gains in others.Hansen et al. (p. 850) examined global Landsat data at a 30-meter spatial resolution to characterize forest extent, loss, and gain from 2000 to 2012. Globally, 2.3 million square kilometres of forest were lost during the 12-year study period and 0.8 million square kilometres of new forest were gained. The tropics exhibited both the greatest losses and the greatest gains (through regrowth and plantation), with losses outstripping gains.
http://earthenginepartners.appspot.com/science-2013-global-forest
Rainforest Connection
Rainforest Connection (RFCx) transforms recycled cell-phones into autonomous, solar-powered listening devices that can monitor and pinpoint chainsaw activity at great distance.
This changes the game by providing the world’s first real-time logging detection system, pinpointing deforestation activity as it occurs, and providing the data openly, freely, and immediately to anyone around the world.
For the first time on a scalable level, responsible agents can arrive on the scene in time to interrupt the perpetrators and stop the damage, and the world can listen in as it occurs.
Planet Labs
The company is launching a swarm of nano imaging satelites. It aims for daily updates at 5m resolution.
ForWarn
Satellite-Based Change Recognition and Tracking for the US.
http://forwarn.forestthreats.org/
FMASK
Cloud and cloud shadow detection in Landsat imagery,
https://code.google.com/p/fmask/
Zhu, Z. and Woodcock, C. E., Object-based cloud and cloud shadow detection in Landsat imagery, Remote Sensing of Environment (2012), doi:10.1016/j.rse.2011.10.028 (This paper explains the 1.6.0 version of Fmask in great details)
FMASK is expected to be made available in Google Earth Engine.
ForestWatchers
http://forestwatchers.net/mission.html
The latest remote sensing image of a forested area are then classified into forest or non-forest with a suitable automated classification algorithm and the accuracy of the resulting map can be further improved by volunteer observation on the Web, or even by addition information provided by volunteers in the field.
Errors and even fraud are naturally handled by the inherent redundancy of the system. For this, it is crucial to attract and retain a large number of volunteers. One hundred thousand volunteers watching over an area of 100,000 hectares each, with a redundancy factor of 20, can survey an area of 500 million hectares, roughly 40 to 50% of the estimated area of world’s tropical forests.
Development Alert!
Development Alert! is an online tool for increasing transparency and public engagement on projects that impact the environmental and public health.
It is not a forest monitoring tool but a citizen activism tool to monitor developments that impact the environment.
The public can:
- submit reports on projects they are concerned about
- track information about new and existing high-impact developments
- get involved by submitting comments or concerns online or directly to officials
- learn about public hearings for proposed developments
As at Jan 2015 only Jamaica is supported.
Open Foris
Open Foris, United Nations Food & Agriculture Organisation (FAO)
IIASA – The International Institute for Applied Systems Analysis
Citizen scientists map global forests
New global forest maps combine citizen science with multiple data sources, for an unprecedented level of accuracy about the location and extent of forestland worldwide.
http://www.iiasa.ac.at/web/home/about/news/150330-ForestMap.html
Transparent Forests
Forest Stewardship Council (FSC) provides certifications for forest based products. It is a continuous challenge to make sure the forestry certification process remains efficient, effective and transparent. The TransparentForests© feasibility study builds on previous European Space Agency-funded Earth Observation Market Development activities, in which FSC evaluated the potential for Earth Observation (EO) to provide accurate and valuable data for forest management and certification
Nature Serve
Biodiversity Indicators Dashboard displays trends in biodiversity, ecosystem services, threats, and conservation actions. Data is provided as an interactive map and in API’s
Geo-Wiki
Engaging Citizens in Environmental Monitoring
Crowdsourcing the Earth’s surface
2015-03-30 Citizen scientists map global forests
New global forest maps combine citizen science with multiple data sources, for an unprecedented level of accuracy about the location and extent of forestland worldwide. New maps of global forest cover from IIASA’s Geo-Wiki team provide a more accurate view of global forests. The maps were published in the journal Remote Sensing of the Environment, and are freely available for exploration and download on the Geo-Wiki web site. More on iiasa.ac.at, ibtimes.co.uk,
Terra-i
http://www.terra-i.org/terra-i/about-us.html
“Terra-i detects land-cover changes resulting from human activities in near real-time, producing updates every 16 days. It currently runs for the whole of Latin America and is being expanded over the next year to cover the entire tropics. Terra-i is a collaboration between the International Center for Tropical Agriculture (CIAT – DAPA, based in Colombia), The program on Forestry, Trees and Agroforestry (FTA) ,The Nature Conservancy (TNC, global environmental organization), the School of Business and Engineering (HEIG-VD, based in Switzerland) and King’s College London (KCL, based in the UK). The system is based on the premise that natural vegetation follows a predictable pattern of changes in greenness from one date to the next brought about by site-specific land and climatic conditions over the same period. A so-called computational neural network is ‘trained’ to understand the normal pattern of changes in vegetation greenness in relation to terrain and rainfall for a site and then marks areas as changed where the greenness suddenly changes well beyond these normal limits. Running on many computers this analysis is refreshed with new imagery every 16 days and for every 250m square of land.”
The site’s Publications page contains links to research papers such as How-can-the-shapes-and-distribution-of-deforested-areas-inform-us-about-the-agents-of-changes-on-the-ground.html and Land and Forest Degradation inside Protected Areas in Latin America.
Terra-i alerts can be accessed via a Global Forest Watch API.
MAAP – Monitoring of the Andean Amazon Project
The Monitoring of the Andean Amazon Project (MAAP) is a web portal dedicated to presenting novel technical information and analysis pertaining to one of the most ecologically and socially important regions on the planet: the Andean Amazon (defined here as the sections of Bolivia, Colombia, Ecuador, and Peru within the Amazon watershed).
MAAP is a project of Amazon Conservation Association and Conservación Amazónica-ACCA.
See Mongabay’s profile Platform provides near real time analysis of deforestation in non brazilian amazon.
Community Forest Watch 