Map Viewer and Download Platform4 contains data available via EarthExplorer but also contains data from the National Agriculture Imagery Program. LandsatLook5 is a map-based interface where a user can search scene availability and view candidate scenes. Web-Enabled Landsat Data (WELD6) are obtainable from yet another website and include atmospherically corrected Landsat images. Landsat data are available from,7 which is operated by Michigan State University, and from the Global Land Cover Facility at the University of Maryland.8

Moreover, several commercial companies also serve high-resolution aerial and spaceborne images, Landsat imagery, and products based on imagery (e.g., ESRI, Google, Microsoft, and Yahoo). While these sites and services offer innovative ways to search for, display, and provide images and products based on them, they lack the comprehensive access to land imaging archives that can only be offered to the public from an authoritative federal government source. These programs and others like them could be better integrated to form the basis for a coherent land imaging program.

Benefits of the current open-access policy are significant and have allowed use of the federal investment in Landsat by a vastly larger user base, including all sectors—from basic research, land management research and applications, education, citizen use, and use by the value-added sector. Maintaining open access is critical. Moving toward the future, the use of land imagery can be further increased, and additional value can be gained by enhancing the suite of data products, improving their documentation through metadata and uncertainty tracking, and developing even more advanced data discovery and distribution channels.


The Landsat series of satellites provides the required long-term continuity of imaging for scientific and societal benefit purposes. However, the Landsat sensor, by its nature, cannot provide all information required for land science and management. Investment in new data products must be balanced between additional advanced data products from Landsat and new data products from other emerging data sources, such as airborne LiDAR and other airborne and spaceborne sensors. Large quantities of novel data are being collected: critical near-term decisions will need to be made about investment levels to access, process, document, and distribute them. The Sustained and Enhanced Land Imaging Program (SELIP) will benefit from an effective user-oriented mechanism, through advisory committees or other structures, to prioritize different data sets and evaluate the relative importance of enhanced data products from legacy sensors compared to new techniques.

There is potential for a far greater array of derived products than are currently available. If appropriately defined and funded, sustained land imaging capabilities would enable a myriad of products and services, including many essential climate variables and climate data records. Most of the products would be difficult for users to code themselves. The complexity of the transformations needed to render some observations into useful products—which in extreme cases are millions of lines of code requiring high-performance computing—makes better infrastructure imperative. With the availability of baseline products, the population of users would also expand, driving demand for successively higher level products. The situation is not unlike the supply of “app” products for cell phones; however, without a sustained land imaging program, the product stream will diminish.

As part of an evolving imaging system, SELIP could identify critical data products and drive requirements for future missions. Because the knowledge and technology needed to produce land-surface information from imagery are sometimes formidable, it makes sense to provide such information from a data system rather than require users to undertake the transformations. Focusing on specific data products can add a great deal of rigor to the requirements definition process for follow-on missions. Management and funding models are part of ensuring that the products are produced, validated, and available for use.

USGS already distributes valuable data products derived from land imagery—for example, the National Land Cover Dataset, LANDFIRE, the Global Land Survey, and Land Surface Reflectance. The Land Surface Reflectance


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