Automating Tropical Forest Monitoring - Improving the Record

Primary Contact

Dr. Eileen Helmer, Research Ecologist

Phone: 970-498-2644

ehelmer@usda.gov

Río Piedras, Puerto Rico, May 31, 2018 - This week scientists demonstrated for the first time a new, highly accurate, automated way to detect clouds and their shadows from satellite images over unusually cloudy places, like tropical rainforests. The method will make it possible to automatically generate, for example, maps of tropical deforestation or forest regrowth that extend back to the 1970s and that intensify coverage since 2015. Instead of using only U.S. imagery from the 1980s forward, scientists will now have an easier time using images from the 1970s, which are the earliest global imagery likely to be used for this purpose, and since 2015 from a new European satellite mission, Sentinel 2.

For decades, scientists, businesses, government agencies, universities and private organizations worldwide have relied on Landsat satellite imagery to track changes in the Earth’s forests, fields, cities, coasts and elsewhere. Landsat images were worth an estimated $2 billion to users in 2011.

With the rise of cloud computing on platforms like NASA’s Earth Exchange, Norway’s SEPAL1 and Google Earth Engine, the new norm is to apply algorithms to long time series of images. But scientists want to add to these time series older images from the 1970s and images from Sentinel 2, to extend the data record and have more frequent coverage. Combining Landsat with Sentinel 2 would give users images every 2-3 days instead of every 16 days for Landsat alone.

However, it is difficult to automatically find clouds in images from the 1970s, Landsat Multispectral Scanner imagery, and in Sentinel 2 images. With the new method, automatic, cloud-based computing to monitor the Earth with satellite images will be far more reliable in the world’s cloudiest places, and when using the huge archives of older and newer satellite images that lack a thermal channel. The method was published online this week in the journal Remote Sensing of Environment and can be downloaded here: An automatic method for screening clouds and cloud shadows in optical satellite image time series in cloudy regions

“Images from the 1970s and Sentinel 2 confound current cloud-finding methods that rely heavily on thermal bands, which these satellites don’t have,” said Dr. Eileen Helmer, an ecologist from the USDA Forest Service International Institute of Tropical Forestry, who was a co-author of the research. “With the new method, scientists can combine all of these images on these platforms. Their algorithms will only encounter the clear pixels left after removing clouds.”

Image CaptionFalse color composite of the four representative Landsat MSS images – the older images that go back to the 1970s, in Puerto Rico, and their cloud and shadow masks by ATSA (gray: clear pixels; black: shadows; white: clouds, DOY = Day of Year).

It would be great if the USGS could use ATSA2 to generate cloud masks for time series collections,” said Dr. Xiaolin Zhu, the first author of the study who is at Hong Kong Polytechnic University. “USGS” refers to the U.S. Geological Survey, which runs the Landsat program after NASA builds and launches the satellites with their on-board imaging sensors. “ATSA” refers to the new algorithm.

Automatically detecting clouds and their shadows in satellite images without a thermal channel has long been a holy grail of tracking tropical deforestation. This is especially true for tropical rainforests known as cloud forests, which get their name because they are on mountains where much of the time they are immersed in clouds and mist. One of the study’s test sites was Puerto Rico, where the U.S. National Forest known as El Yunque has extensive cloud forests.

The full importance of the new algorithm will probably come to be known over time, as scientists and others use it, and, of course, tinker with it.

1System for Earth observation data access, Preprocessing & Analysis for Land monitoring

2Automatic Time-Series Analysis


The Institute's mission is to develop and disseminate scientifically-based knowledge that contributes to the conservation of forests, wildlife, and watersheds of the American tropics in the context of environmental change.


The mission of the U.S. Forest Service, an agency of the U.S. Department of Agriculture, is to sustain the health, diversity and productivity of the nation's forests and grasslands to meet the needs of present and future generations. The agency manages 193 million acres of public land, provides assistance to state and private landowners, and maintains world-renowned forestry research and wildland fire management organizations. National forests and grasslands contribute more than $30 billion to the American economy annually and support nearly 360,000 jobs. These lands also provide 30 percent of the nation's surface drinking water to cities and rural communities; approximately 60 million Americans rely on drinking water that originated from the National Forest System.


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Page last modified: 06/02/2018





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