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The widely used National Land Cover Database (NLCD) has long been the foundational land cover source for scientists, resource managers, and decision-makers across the United States, trusted for its accurate and unbiased data.  

Here, we’re exploring the evolution of NLCD through its reinvention this year as Annual NLCD. 

What Is NLCD? Why Do We Need It?

NLCD maps the land cover types existing across the United States, from field and forest to pasture and pavement and other developed surfaces. Landsat satellite imagery serves as the basis for determining these cover types. These categorizations inform the people who manage land, resources and even populations in many ways.

Understanding the sudden and long-term changes in the landscape provides vital information for human, economic, and ecosystem well-being. NLCD offers the basis for understanding where change happened, the drivers of change, the potential consequences of change, and the effects of management decisions, natural hazards, and climate variability.   

 

Beginning of a Landmark Project

The U.S. Geological Survey’s Earth Resources Observation and Science (EROS) Center had recognized the world’s hunger for land cover information when it began producing greenness maps with 1-kilometer resolution satellite data in the late 1980s. These maps allowed agencies to monitor vegetation and environmental conditions fairly inexpensively and efficiently from space.

In the early 1990s, USGS partnered with other government agencies to form the Multi-Resolution Land Characteristics (MRLC) consortium. The goal was to acquire 30-meter resolution Landsat satellite imagery for a variety of mapping projects. NLCD was one of those, intended to reveal the landscape of the entire United States in greater detail than ever before.

 

 

MRLC Partners

Current Multi-Resolution Land Characteristics (MRLC) Partners:   

  • Bureau of Land Management  
  • LANDFIRE  
  • National Park Service  
  • National Oceanic and Atmospheric Administration (NOAA) 
  • US Department of Agriculture (USDA) 
  • US Environmental Protection Agency  
  • US Fish and Wildlife Service  
  • USDA Forest Service  
  • USGS

In the early years, with new projects like NLCD and LANDFIRE (Landscape Fire and Resource Management Planning Tools) at the USGS, the MRLC focused on joint purchases of imagery from Landsat and high-resolution commercial satellites.

As the partnership evolved, agencies became experts in an area of land cover for NLCD: USDA in agriculture, NOAA in coastal land cover and wetlands, and the Forest Service in forest classes and later forest canopy cover. LANDFIRE and the Gap Analysis Project (GAP) provided highly detailed ecosystem information, and later a combination of Monitoring Trends in Burn Severity (MTBS) and LANDFIRE provided fire and fire fuel information.  

Wetland near Long Lake, CA

 

“At the time, it was really a groundbreaking effort to even think about trying to map land cover at Landsat scale across the entire U.S.,” said USGS EROS Integrated Science and Applications Branch Chief Terry Sohl, who participated in that early project. He and two other scientists first created a prototype of the mid-Atlantic area using mosaics of Landsat imagery.

“From an agency perspective, you can definitely see the need for it in that land cover and land use, what’s happening on the surface of the Earth, has such a huge impact on what’s happening with ecosystem processes and societal processes. If you think about things like biodiversity and habitat, carbon greenhouse gases, regional weather and climate, water quality, human health—each one of those has some impact that land use and land cover can help to address. So NLCD was really the first effort to do that in a concerted way across the whole U.S.” – Terry Sohl, EROS science branch chief

EROS was key to this effort not only because of the expertise of its scientists, but also because of its role in archiving and providing access to Landsat imagery. Before the 2008 open data policy that eliminated charges for Landsat imagery, individual scenes were expensive, and buying enough data to cover the entire country required the resources of multiple projects and agencies. The MRLC was formed to share resources and expertise.

 

NLCD 92

The first version of NLCD was released in 2000, called NLCD 92. Based on Landsat 5 imagery, the snapshot of the landscape during target year 1992 featured a more detailed look at the conterminous United States than any other national land cover effort up to that point. NLCD 92 included 21 classes of land cover.

The computing technology at the time involved a laborious process of georegistering a Landsat scene, which measures about 106 miles by 115 miles, from manually chosen ground control points—taking 2 to 4 hours per scene—and then trying to place the scene on a map grid.

The NLCD 92 accuracy assessment was released in 2004. Accuracy assessments for each NLCD release give users reportable, statistically valid accuracies for the country that allow citing for policy, while also giving users a measure of performance for specific classes and regions.   

NLCD 1992

 

Moving NLCD Forward as a Database

List of 20 phrases with title and small rectangular colored boxes beside them

Work on the next version, NLCD 2001, represented a new generation. It used a database approach of interlinked data layers. Development for NLCD 2001, with imagery targeted for that year, began in 1999 and overhauled the methods used to make it and the land cover classes it yielded.

NLCD 2001 also added Hawaii, Puerto Rico and Alaska—the last being a significant achievement, considering Alaska is a fifth the size of the conterminous United States.

Using both Landsat 5 and Landsat 7 gave NLCD 2001 a distinct advantage over NLCD 92.  Having twice the available imagery meant a better chance of getting cloud-free imagery showing phenology, or vegetation at about the same time of year, which was essential for NLCD 2001 to use more advanced and automated interpretation techniques.

The satellite imagery was used in collaboration with aerial photos to which map attributes had been added. These photos provided training data for certain types of land cover, such as developed urban areas and forest, that could easily be identified. A significant amount of other training data required scoping out areas of land cover in person.

Alaska was another matter. With a relatively short growing season, and very active cloud layers throughout the growing season, cloud-free Landsat imagery was very rare, let alone large areas of the landscape with matched phenology. With its vast remote areas, Alaska also lacked aerial imagery for the majority of the state.  Given both of these factors, training data for the algorithms required large amounts of on-the-ground field data collection paired with extensive modeling and imagery combinations for accurate classification.  

NLCD 2001 reduced the number of land cover classes to 16 (with four additional classes in Alaska only) and retooled class definitions to align with satellite-detected land cover conditions and put less emphasis on interpreting land usage. The NLCD 2001 classes simplified the agricultural and barren categories, but also changed to four classes of developed area representing the percentage of developed impervious surfaces that water cannot penetrate, such as pavement or roads or roofs. 

EROS also developed a separate percent tree canopy data layer that categorized the different densities of forest around the nation. Used in combination with land cover and percent developed impervious surface data, this allowed users to understand, for example, the density of forest over developed areas, or low density forest encroachment into rangeland areas.  

Other federal agencies and several states helped with NLCD 2001 mapping as well. For example, NOAA and USGS’ GAP mapped the majority of the coastal regions, and Kentucky mapped the state’s impervious surfaces.

Left: The current NLCD classes, with 16 across the United States and Puerto Rico and an additional 4 for Alaska only.

 

Releases that Followed

NLCD 2006

NLCD moved to a 5-year release cycle as it aimed to help users wanting to analyze changes between the releases. NLCD 2006 for the conterminous United States was released in 2011 under similar methods and the same 16 classes as NLCD 2001. An updated version of NLCD 2001 also was released to be compatible with NLCD 2006 for land change analysis.

NLCD 2011

The NLCD 2011 release in 2013 allowed for a decade of land change comparison for the conterminous United States and Alaska using Landsat imagery from 2011. Updated versions of NLCD 2001 and 2006 were also released. The USDA Forest Service also took over production of percent tree canopy cover using their Forest inventory Analysis points (FIA) as the basis for that training. These points were also crucial for the initial development of the 2001 land cover forest classes.

NLCD 2016

This release in 2019, based on 2016 Landsat 5, 7, and 8 imagery, marked another revolution of NLCD data aimed at the development of a long-term, consistent national land cover and change product spanning 15 years. In addition to 2016, products for the years 2004, 2008 and 2013 were also released to narrow the window of change between datasets to 2-3 years. Updates, as usual, were made to already existing products with a main emphasis on removing and correcting previous errors. 

Using time series analysis for the first time facilitated these improvements. For instance, with only one or two dates of imagery, a freshly cleared forest could be interpreted as new agriculture, or a new developed area, or just grassland in a sequence of forest regeneration. The ability to analyze multiple dates and see the next progression in the land cover sequence allowed for error correction to the previous releases. This time series analysis was the foundation for accurate change through time. 

Methods were also improved for handling Landsat imagery, assembling high-quality specialized training data from local and federal partners, and modeling all of these things into a unified land cover and land change product. As one example, rangeland categorization was improved by incorporating percentages of shrub, bare ground and grassland areas in the western United States from a new EROS project, Rangeland Condition Monitoring Assessment and Projection (RCMAP), into NLCD’s thematic cover types.

NLCD 2019

NLCD 2019, released in 2021, had a faster turnaround time than any release up to that point. It also included updates for the seven prior releases, a 2001-2019 land cover change index and more detail about urban imperviousness.

NLCD 2021

Released in 2023, NLCD 2021 served as the last legacy NLCD release until the debut of the NLCD transformation the following year. This release was built on NLCD 2019 change products and did not include updates to prior releases, as NLCD prepared for substantial changes ahead.

For the releases above, many datasets from MRLC partners also were integrated into NLCD to improve its accuracy.   

Expanding Suburbs

 

Complementary Efforts 

While NLCD is widely used as a foundational land cover resource, other specialized efforts at USGS EROS have come alongside, including RCMAP, LANDFIRE and LCMAP.

RCMAP: Rangeland Condition Monitoring Assessment and Projection (RCMAP) is a partnership with the Bureau of Land Management that characterizes land cover in detail for western U.S. rangeland, including shrubs and grasses, over nearly four decades and also models projections into the future.

LANDFIRE: The LANDFIRE (Landscape Fire and Resource Management Planning Tools) program produces a variety of land cover and biological/ecological data related to wildland fire management, including numerous vegetation classes, disturbances to the landscape, surface and canopy fire fuels and more. LANDFIRE is a production partnership among the USDA Forest Service, DOI, USGS, and The Nature Conservancy. 

 

LCMAP

The Land Change Monitoring, Assessment, and Projection (LCMAP) program began in 2014 as an effort to mine the Landsat archive and provide a year-by-year look at changing conditions in land cover since 1985.

LCMAP released its first suite of annual land cover and land change products for the conterminous United States in 2019, spanning the years 1985-2017. In 2021, LCMAP updated its product suite to include the years 2018-2020, with 2021 released the following year.

LCMAP represented a significant achievement in scale and precision. Using the Landsat archive as fully as possible, enabled by the EROS-produced Landsat Analysis Ready Data (ARD) scenes and a change detection algorithm, yielded land cover change identified within a target year. In addition, a reference dataset contained 25,000 plots across the United States, all analyzed to verify multiple decades of map accuracy.

In 2023, an announcement was made that LCMAP’s strengths would be combined with those of NLCD to create a reinvented land cover resource. And that brings us to Annual NLCD. 

The LCMAP project has generated an integrated suite of annual land coverage

 

 

Defining the Next Generation of NLCD

Changes on the landscape can happen suddenly, such as a raging storm or a devastating wildfire. Or they can happen relatively slowly, like a sprawling city eating into the farmland or forest around it.

Graphic showing a mix of facts and figures
A glance at the impact the National Land Cover Database (NLCD) has had since its beginnings.

The United States needs land cover and land change products that span large geographic areas over long time periods. Scientists, land managers and the general public need information on land change that’s more frequent and consistent than ever before. 

Annual NLCD aims to take its definitive land cover source and enhance it with far more historical data to show change within a year and also spanning decades. Annual NLCD harnesses the Landsat record beginning with Landsat 4 in the early 1980s. 

The first release, in 2024—called Annual NLCD Collection 1—encompasses land cover and land change for the years 1985-2023. New artificial intelligence and machine learning methods have been developed to help process this much data more efficiently, helped also by a shift to cloud-based computing.

Annual NLCD is providing information that includes types of land cover nationwide, landscape changes over nearly four decades, the percentage of impervious surfaces such as pavement or roads, and the timing of relatively sudden changes in the landscape. 

“Our job is to give an unbiased perspective and to really follow the best scientific practices, regardless of who’s using the data.” – Jon Dewitz on the NLCD team

NLCD traditionally has offered meaningful data for addressing some of society’s biggest concerns. Just a few examples among many: NLCD helps cities identify their residents’ vulnerability to extreme heat. It helps a state understand where and why its farmland is disappearing. It helps insurers model the risks of hurricane losses.

With Annual NLCD, the possibilities will soar for even more. 

 

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