Landsat Missions

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The Landsat Program provides over 40 years of calibrated medium spatial resolution data in support of a range of applications in areas such as global change research, agriculture, forestry, geology, land cover mapping, resource management, and water and coastal studies - to name a few. Below are some examples of regional and global Landsat data applications that can assist policy makers and land managers in making informative decisions about our environment and Earth resources.

Dr. Stephanie Hulina, President of Geospatial Data Analysis Corporation (GDA Corp) discusses how access to free Landsat imagery from USGS provides value-added products to her company’s clients.

Despite being a small business, Geospatial Data Analysis Corporation (GDA Corp.) is a major commercial user of Landsat imagery. Dr. Hulina notes, “The long-term continuity of the Landsat mission is essential to GDA’s ability to maintain a competitive edge in today’s global economy. The imagery has helped GDA to serve its clients, especially in the agricultural arena, some of whom were previously unaware of the tremendous value that satellite imagery and its analysis can bring to their decision-making and ultimately to their company’s bottom line. GDA agricultural analysis would not be possible without free, reliable, and high quality Landsat data offered by USGS.”

A significant part of GDA’s daily business relies on processing and analyzing large amounts of Landsat imagery from around the world. Landsat’s combination of moderate spatial resolution (60-meters and 30-meters), multispectral and thermal bands, and its long historical record all provide an ideal database for crop mapping, monitoring, assessments, and forecasting. GDA maintains an operational end-to-end automated system for continuous download, surface reflectance calibration, and mosaicking of terabytes of surface reflectance calibrated Landsat imagery. GDA calibration and mosaicking of the imagery occurs within a few hours of data acquisition and scene availability by the U.S. Geological Survey (USGS) Earth Resources Observation and Science (EROS) Center. GDA generates bi-monthly time series imagery mosaics covering all major agricultural areas of the world. For each mosaic, GDA tracks per pixel data quality, sourced sensor, and date; this information enables near real time mosaic updates as soon as new imagery becomes available from the USGS.

Extent of GDA’s continued collection of Landsat imagery for agricultural monitoring and analysis.
Figure 1: Extent of GDA’s continued collection of Landsat imagery for agricultural monitoring and analysis.
 

GDA depends on its analysis-ready time series of surface reflectance calibrated Landsat mosaics for its global crop analysis. The mosaics offer a tremendous value by enabling regional time series analysis, supporting field-to-country assessments, and reducing more than 80 percent of the imagery data volume. GDA’s current season crop assessments rely on the relationships between time series spectral properties and crop types established for the past 10-15 years. These relationships facilitate highly automated in-season field level crop mapping, which is the foundation for regional crop monitoring, frequent crop area and condition assessments, and estimations of end-of-season yields and production. The crop mapping is performed continuously and the results are updated bi-monthly.

GDA analysis-ready Landsat time series mosaics of the United States. (bi-monthly, full resolution, surface reflectance calibrated).
Figure 2. GDA analysis-ready Landsat time series mosaics of the United States. (bi-monthly, full resolution, surface reflectance calibrated).
 

GDA in-season crop type map for the United States.
Figure 3: GDA in-season crop type map for the United States.
 

GDA soybean map for Brazil compared to the source Landsat mosaic.
Figure 4: GDA soybean map for Brazil compared to the source Landsat mosaic.
 

GDA corn map for South Africa draped over the source Landsat mosaic.
Figure 5: GDA corn map for South Africa draped over the source Landsat mosaic.
 

GDA’s client interests range from detection of data gaps in the imagery, image calibration to surface reflectance, and image mosaicking to enhanced image analysis techniques to answer questions such as when, where, and how much of a particular crop is planted, and what is the expected yield of that crop.  GDA has a long-standing working relationship with the Foreign Agricultural Service (FAS) of the U.S. Department of Agriculture (USDA). Working with the Office of Global Analysis/International Production Assessment Division within FAS, GDA has used its technology alongside the expertise of the USDA/FAS to provide timely and accurate global crop intelligence while consistently covering all major agricultural regions annually. GDA analysis of Landsat imagery and the final products generated from it factor into the global agricultural production forecasts that FAS releases every month. The national importance of FAS activities is illustrated by the inclusion of its “World Agricultural Supply and Demand Estimates and World Agricultural Production (WASDE)” USDA publication in the Office of Management and Budget’s (OMB) Principal Federal Economic Indicators for the White House.

Visit the GDA Corp. web site for more information: http://www.gdacorp.com.

Satellite Forest Monitoring in Canada    

This screenshot of the Satellite Forest Monitoring in Canada interface shows an area in Central Alberta, and displays the colored points (pixels) of selected changes to the land surface. The scale showing the years changes as users zoom into areas of interest. 

   

The Canadian Forest Service of Natural Resources Canada, along with the University of British Columbia and support from the Canadian Space Agency, has been developing the science and methods to track and characterize the history of Canada’s forests.

Led by Landsat Science Team Member Michael Wulder (Canadian Forest Service), the Satellite Forest Monitoring in Canada interface displays points representing locations where forest change has been observed between 1985 and 2011. Landsat data is used to detect changes, identify the year in which the changes occurred, and estimate a change type (such as harvest or wildfire).

A change detection approach was applied to annual time series data, enabling the detection of abrupt (e.g. fire) and gradual (e.g. drought) changes. From the time series, the recovery of forests after disturbances by wildfire and harvest can also be assessed. The identification of these historical changes is beneficial in trend model developments that allow scientists to anticipate and prepare for future changes of the forested areas.

Global Forest Watch (GFW) is an interactive online forest monitoring and alert system designed to empower people everywhere with the information they need to better manage and conserve forest landscapes. Global Forest Watch uses cutting-edge technology and science to provide the timeliest and most precise information about the status of forest landscapes worldwide, including near-real-time alerts showing suspected locations of recent tree cover loss.

GFW enables anyone to create custom maps, analyze forest trends, subscribe to alerts, or download data for their local area or the entire world. Users can also contribute to GFW by sharing data and stories from the ground via GFW’s crowdsourcing tools, blogs, and discussion groups.

 

Global Forest Watch (GFW)    
This screenshot of the Global Forest Watch interface shows forest change in a small area of Rondonia, Brazil. Blue areas indicate tree cover gain, while pink areas depict tree cover loss. Land cover, land use, conservation, people, stories, and country layers can also be added, by navigating the menu above the map.    

From the Global Forest Watch website, you can also access these viewers (all in Beta):

Global Forest Watch Fires
Global Forest Watch Commodities
Global Forest Watch Climate
Global Forest Watch Water

 

 

 

 

 

 

 

 

 

 

 

 

  Google Earth Engine Timelapse
 

This screenshot of Google Earth Engine’s Timelapse viewer shows the progression
of artificial archipelagos along the shoreline of Dubai, United Arab Emirates.

Google Earth Engine combines a multi-petabyte catalog of satellite imagery and geospatial datasets with planetary-scale analysis capabilities, and makes the data available for scientific analysis and visualization of geospatial datasets to detect changes, map trends, and quantify differences on the Earth's surface.

Earth Engine stores and organizes satellite imagery and makes it available for global-scale data mining. The public data archive includes historical Earth imagery going back more than 40 years, and new imagery is collected every day. Earth Engine also provides APIs in JavaScript and Python, as well as other tools, to enable the analysis of large datasets.

Google Earth Engine’s Timelapse allows easy observations to understand and appreciate how various events and decisions for growth impact the Earth’s surface over the past 32 years.  A number of areas of the world are available for selection to quickly and easily see the changes on the Earth’s surface.

The Landsat Program provides over 40 years of calibrated medium spatial resolution data in support of a range of applications in areas such as global change research, agriculture, forestry, geology, land cover mapping, resource management, and water and coastal studies - to name a few. Below are some examples of regional and global Landsat data applications that can assist policy makers and land managers in making informative decisions about our environment and Earth resources.

 

Sheridan Glacier, Alaska
Sheridan Glacier, Alaska

Glacier movement is not always easy to predict. However, new remote sensing capabilities are making it easier to map the speed and movement patterns of flowing ice in Greenland, Antarctica, and global mountain ranges.

Scientists from the NASA-funded Global Land Ice Velocity Extraction project (GoLIVE) are using remote sensing data collected by Landsat 8 to view every large glacier and ice sheet on Earth in near-real-time. By integrating atmospheric and oceanic information, researchers can better understand what causes these ice sheets to change.

Landsat 8 collects over 700 images a day and covers Earth's entire surface every 16 days. This volume of data helps researchers to generate these global maps and will be invaluable for global ice monitoring in the future. With the help of Landsat 9, scheduled for launch in 2020, this initiative will continue for years to come.

Related Links:

NASA website

NASA Landsat website

Brown Marsh in southeastern Terrebonne Basin, Louisiana
Brown Marsh - Terrebonne Basin, Louisiana

A partnership between the European Commission's Joint Research Centre and Google Earth Engine has yielded a new online interactive mapping tool that highlights changes in Earth's surface water over the past 32 years. The Global Surface Water Explorer, which consists of 3 million Landsat images collected over the last 32 years, shows that impacts on surface water occurrence can come from a variety of factors.

The information contained in this tool will improve additional surface modeling, help to mitigate flooding, and improve global policies and water-management decision making. The Global Surface Water Explorer tool is available to everyone at no charge.

Related Links:

European Commission Press Release

Research Article

About

Landsat represents the world's longest continuously acquired collection of space-based moderate-resolution land remote sensing data. Four decades of imagery provides a unique resource for those who work in agriculture, geology, forestry, regional planning, education, mapping, and global change research. Landsat images are also invaluable for emergency response and disaster relief.

 

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