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Topographic Science

The mission of U.S. Geological Survey (USGS) Earth Resources Observation and Science (EROS) Center Topographic Science is to establish partnerships and conduct research and applications that facilitate the development and use of integrated national and global topographic datasets. Topographic Science includes a wide range of research and applications that result in improved seamless topographic datasets, advanced elevation technology, data integration and terrain visualization, new and improved elevation derivatives, and development of Web-based tools. In cooperation with our partners, Topographic Science is developing integrated-science applications for mapping, national natural resource initiatives, hazards, and global change science. http://topotools.cr.usgs.gov/.

Fact Sheet

Landsat's international partners

Since the launch of the first Landsat satellite 40 years ago, International Cooperators (ICs) have formed a key strategic alliance with the U.S. Geological Survey (USGS) to not only engage in Landsat data downlink services but also to enable a foundation for scientific and technical collaboration. The map below shows the locations of all ground stations operated by the United States and IC ground station network for the direct downlink and distribution of Landsat 5 (L5) and Landsat 7 (L7) image data. The circles show the approximate area over which each station has the capability for direct reception of Landsat data. The red circles show the components of the L5 ground station network, the green circles show components of the L7 station network, and the dashed circles show stations with dual (L5 and L7) status. The yellow circles show L5 short-term ("campaign") stations that contribute to the USGS Landsat archive. Ground stations in South Dakota and Australia currently serve as the primary data capture facilities for the USGS Landsat Ground Network (LGN). The Landsat Ground Station (LGS) is located at the USGS Earth Resources Observation and Science (EROS) Center in Sioux Falls, South Dakota. The Alice Springs (ASN) ground station is located at the Geoscience Australia facility in Alice Springs, Australia. These sites receive the image data, via X-band Radio Frequency (RF) link, and the spacecraft housekeeping data, via S-band RF link. LGS also provides tracking services and a command link to the spacecrafts.

Argentina;Australia;Brazil;Canada;China;Germany;In

EROS resources for the classroom

The U.S. Geological Survey (USGS) Earth Resources Observation and Science (EROS) Center has several educational resources that demonstrate how satellite imagery is used to understand our changing world.

Fact Sheet

Enhanced canopy fuel mapping by integrating lidar data

Background The Wildfire Sciences Team at the U.S. Geological Survey’s Earth Resources Observation and Science Center produces vegetation type, vegetation structure, and fuel products for the United States, primarily through the Landscape Fire and Resource Management Planning Tools (LANDFIRE) program. LANDFIRE products are used across disciplines for a variety of applications. The LANDFIRE data retain their currency and relevancy through periodic updating or remapping. These updating and remapping efforts provide opportunities to improve the LANDFIRE product suite by incorporating data from other sources. Light detection and ranging (lidar) is uniquely suitable for gathering information on vegetation structure and spatial arrangement because it can collect data in three dimensions. The Wildfire Sciences Team has several completed and ongoing studies focused on integrating lidar into vegetation and fuels mapping.

Fact Sheet

Coastal National Elevation Database

The Coastal National Elevation Database (CoNED) Applications Project develops enhanced topographic (land elevation) and bathymetric (water depth) datasets that serve as valuable resources for coastal hazards research (Danielson and others, 2016; Thatcher and others, 2016). These datasets are used widely for mapping inundation zones from riverine flood events, hurricanes, and sea-level rise and for other Earth science applications, such as sediment transport, erosion, and storm impact models. CoNED is a U.S. Geological Survey (USGS) Coastal-Marine Hazards and Resources Program (formerly Coastal and Marine Geology Program) activity centered at the USGS Earth Resources Observation and Science Center and distributed at other USGS Science Centers. As part of the vision for a 3D Nation, the CoNED Project is working collaboratively with the USGS National Geospatial Program, the National Oceanic and Atmospheric Administration, and the U.S. Army Corps of Engineers through the Interagency Working Group on Ocean and Coastal Mapping to build integrated elevation models in the coastal zone by assimilating the land surface topography with littoral zone and continental shelf bathymetry. Several nongovernmental organizations and Federal agencies, including the Department of the Interior Pacific Islands Climate Adaptation Science Center, the National Park Service, the Nature Conservancy, the Louisiana Coastal Protection and Restoration Authority, and numerous academic institutions, partner to make CoNED a success.

Fact Sheet

Land change monitoring, assessment, and projection

There is a pressing need to monitor and understand the rapid land change happening around the world. The U.S. Geological Survey is developing a new capability, called Land Change Monitoring, Assessment, and Projection (LCMAP), to innovate the understanding of land change. This capability is the Earth Resources Observation and Science Center's foundation for an integrated U.S. Geological Survey-wide land change science framework. LCMAP supports the development of consistent data and land cover products spanning large geographic extents, over extended periods, and at a higher frequency than in the past. LCMAP provides solutions to the science and management communities’ growing need for an improved understanding of the fundamental drivers of land change, the consequences of change in human and natural systems, and feedbacks associated with land change processes.

Fact Sheet

South Dakota and Landsat

Few States derive as much of their social and economic well-being from the land as South Dakota. Agriculture is the State’s primary industry. Hunting, fishing, tourism, mining, and hydroelectric power are also important economic and cultural drivers. Data from the U.S. Geological Survey Landsat program, archived at the U.S. Geological Survey Earth Resources Observation and Science Center just outside Sioux Falls, South Dakota, has long been a boon to the monitoring, mapping, and management of the State’s land resources.

South Dakota

EarthExplorer

The EarthExplorer trifold provides basic information for on-line access to remotely-sensed data from the U.S. Geological Survey Earth Resources Observation and Science (EROS) Center archive. The EarthExplorer (http://earthexplorer.usgs.gov/) client/server interface allows users to search and download aerial photography, satellite data, elevation data, land-cover products, and digitized maps. Minimum computer system requirements and customer service contact information also are included in the brochure.

General Information Product

Land change monitoring, assessment, and projection (LCMAP) revolutionizes land cover and land change research

When nature and humanity change Earth’s landscapes - through flood or fire, public policy, natural resources management, or economic development - the results are often dramatic and lasting. Wildfires can reshape ecosystems. Hurricanes with names like Sandy or Katrina will howl for days while altering the landscape for years. One growing season in the evolution of drought-resistant genetics can transform semiarid landscapes into farm fields. In the past, valuable land cover maps created for understanding the effects of those events - whether changes in wildlife habitat, water-quality impacts, or the role land use and land cover play in affecting weather and climate - came out at best every 5 to 7 years. Those high quality, high resolution maps were good, but users always craved more: even higher quality data, additional land cover and land change variables, more detailed legends, and most importantly, more frequent land change information. Now a bold new initiative called Land Change Monitoring, Assessment, and Projection (LCMAP) promises to fulfill that demand. Developed at the U.S. Geological Survey (USGS) Earth Resources Observation and Science (EROS) Center in Sioux Falls, South Dakota, LCMAP provides definitive, timely information on how, why, and where the planet is changing. LCMAP’s continuous monitoring process can detect changes as they happen every day that Landsat satellites acquire clear observations. The result will be to place near real-time information in the hands of land and resource managers who need to understand the effects these changes have on landscapes.

General Information Product

Earth as art 5

Fanciful Fluorescence. Lurking Madness. Serene Expressions. The titles of the images in this fifth edition of Earth As Art speak to the powerfully artistic qualities of Earth’s natural features when tinged with unnatural colors. Art serves as a great partner in the communication of science, bringing emotion to the pursuit of understanding. The pieces in this collection look like abstract art but are actual satellite images. Satellite imagery has long served the rational and disciplined approaches of science to better understand our Earth. But these images can also, with a bit of creativity, excite our imaginations with the beauty and art that surround us. In this newest collection of Earth As Art, we continue to display the Earth as our eyes cannot see it—in creative combinations of visible and infrared light. Although beauty in art is often subjective, the science data provide objective views of the Earth’s changing land surface. However, we will let these images speak to you as art. Enjoy the latest additions to Earth As Art! The images in the Earth As Art 5 collection can be downloaded for free from the Earth Resources Observation and Science (EROS) Center Image Gallery at https://www.usgs.gov/centers/eros/science/earth-art-5 .

General Information Product

EarthNow!

EarthNow! displays live or recent acquisitions from the Landsat 5 and Landsat 7 satellites as they pass over North America. When these satellites pass within range of the U.S. Geological Survey (USGS) Earth Resources Observation and Science (EROS) Center, data imagery is downloaded and displayed in near-real time. When the satellites are out of range of the South Dakota ground station at the EROS Center, recent acquisitions are displayed.

General Information Product

User's Guide for the MapImage Reprojection Software Package, Version 1.01

Scientists routinely accomplish small-scale geospatial modeling in the raster domain, using high-resolution datasets (such as 30-m data) for large parts of continents and low-resolution to high-resolution datasets for the entire globe. Recently, Usery and others (2003a) expanded on the previously limited empirical work with real geographic data by compiling and tabulating the accuracy of categorical areas in projected raster datasets of global extent. Geographers and applications programmers at the U.S. Geological Survey's (USGS) Mid-Continent Mapping Center (MCMC) undertook an effort to expand and evolve an internal USGS software package, MapImage, or mapimg, for raster map projection transformation (Usery and others, 2003a). Daniel R. Steinwand of Science Applications International Corporation, Earth Resources Observation Systems Data Center in Sioux Falls, S. Dak., originally developed mapimg for the USGS, basing it on the USGS's General Cartographic Transformation Package (GCTP). It operated as a command line program on the Unix operating system. Through efforts at MCMC, and in coordination with Mr. Steinwand, this program has been transformed from an application based on a command line into a software package based on a graphic user interface for Windows, Linux, and Unix machines. Usery and others (2003b) pointed out that many commercial software packages do not use exact projection equations and that even when exact projection equations are used, the software often results in error and sometimes does not complete the transformation for specific projections, at specific resampling resolutions, and for specific singularities. Direct implementation of point-to-point transformation with appropriate functions yields the variety of projections available in these software packages, but implementation with data other than points requires specific adaptation of the equations or prior preparation of the data to allow the transformation to succeed. Additional constraints apply to global raster data. It appears that some packages use the USGS's GCTP or similar point transformations without adaptation to the specific characteristics of raster data (Usery and others, 2003b). It is most common for programs to compute transformations of raster data in an inverse fashion. Such mapping can result in an erroneous position and replicate data or create pixels not in the original space. As Usery and others (2003a) indicated, mapimg performs a corresponding forward transformation to ensure the same location results from both methods. The primary benefit of this function is to mask cells outside the domain. MapImage 1.01 is now on the Web. You can download the User's Guide, source, and binaries from the following site: http://mcmcweb.er.usgs.gov/carto_research/projection/acc_proj_data.html

Open-File Report

Collection and analysis of high-resolution elevation data for the Lincoln Lidar Project, Lincoln, Nebraska, 2004

The Lincoln Lidar Project was a partnership developed between the U.S. Geological Survey National Center for Earth Resources Observations and Science (EROS), Lancaster County and the city of Lincoln, Nebraska. This project demonstrated a successful planning, collection, analysis and integration of high-resolution elevation information using Light Detection and Ranging, (Lidar) data. This report describes the partnership developed to collect local Lidar data and transform the data into information useable at local to national levels. This report specifically describes project planning, quality assurance, processing, transforming raw Lidar points to useable data layers, and visualizing and disseminating the raw and final products.

Nebraska

User's Guide for MapIMG 2: Map Image Re-projection Software Package

BACKGROUND Scientists routinely accomplish small-scale geospatial modeling in the raster domain, using high-resolution datasets for large parts of continents and low-resolution to high-resolution datasets for the entire globe. Direct implementation of point-to-point transformation with appropriate functions yields the variety of projections available in commercial software packages, but implementation with data other than points requires specific adaptation of the transformation equations or prior preparation of the data to allow the transformation to succeed. It seems that some of these packages use the U.S. Geological Survey's (USGS) General Cartographic Transformation Package (GCTP) or similar point transformations without adaptation to the specific characteristics of raster data (Usery and others, 2003a). Usery and others (2003b) compiled and tabulated the accuracy of categorical areas in projected raster datasets of global extent. Based on the shortcomings identified in these studies, geographers and applications programmers at the USGS expanded and evolved a USGS software package, MapIMG, for raster map projection transformation (Finn and Trent, 2004). Daniel R. Steinwand of Science Applications International Corporation, National Center for Earth Resources Observation and Science, originally developed MapIMG for the USGS, basing it on GCTP. Through previous and continuing efforts at the USGS' National Geospatial Technical Operations Center, this program has been transformed from an application based on command line input into a software package based on a graphical user interface for Windows, Linux, and other UNIX machines.

Open-File Report

Users Manual for the Geospatial Stream Flow Model (GeoSFM)

The monitoring of wide-area hydrologic events requires the manipulation of large amounts of geospatial and time series data into concise information products that characterize the location and magnitude of the event. To perform these manipulations, scientists at the U.S. Geological Survey Center for Earth Resources Observation and Science (EROS), with the cooperation of the U.S. Agency for International Development, Office of Foreign Disaster Assistance (USAID/OFDA), have implemented a hydrologic modeling system. The system includes a data assimilation component to generate data for a Geospatial Stream Flow Model (GeoSFM) that can be run operationally to identify and map wide-area streamflow anomalies. GeoSFM integrates a geographical information system (GIS) for geospatial preprocessing and postprocessing tasks and hydrologic modeling routines implemented as dynamically linked libraries (DLLs) for time series manipulations. Model results include maps that depicting the status of streamflow and soil water conditions. This Users Manual provides step-by-step instructions for running the model and for downloading and processing the input data required for initial model parameterization and daily operation.

Open-File Report

Technical Manual for the Geospatial Stream Flow Model (GeoSFM)

The monitoring of wide-area hydrologic events requires the use of geospatial and time series data available in near-real time. These data sets must be manipulated into information products that speak to the location and magnitude of the event. Scientists at the U.S. Geological Survey Earth Resources Observation and Science (USGS EROS) Center have implemented a hydrologic modeling system which consists of an operational data processing system and the Geospatial Stream Flow Model (GeoSFM). The data processing system generates daily forcing evapotranspiration and precipitation data from various remotely sensed and ground-based data sources. To allow for rapid implementation in data scarce environments, widely available terrain, soil, and land cover data sets are used for model setup and initial parameter estimation. GeoSFM performs geospatial preprocessing and postprocessing tasks as well as hydrologic modeling tasks within an ArcView GIS environment. The integration of GIS routines and time series processing routines is achieved seamlessly through the use of dynamically linked libraries (DLLs) embedded within Avenue scripts. GeoSFM is run operationally to identify and map wide-area streamflow anomalies. Daily model results including daily streamflow and soil water maps are disseminated through Internet map servers, flood hazard bulletins and other media.

Open-File Report

Users and uses of Landsat 8 satellite imagery—2014 survey results

Executive Summary In 2013, Landsat 8 began adding high quality, global, moderate-resolution imagery to the more than 40-year archive of Landsat imagery. To assess the potential effects of the availability of Landsat 8 imagery on users and their work, the U.S. Geological Survey (USGS) Land Remote Sensing Program (LRS) initiated a survey of Landsat users. The objectives of the survey were to 1. Characterize various Landsat user groups, such as United States (U.S.) and international users and Landsat 8 and non-Landsat 8 users; 2. Identify any differences among user groups in uses and preferences; 3. Measure the importance of and satisfaction with Landsat 8 attributes; 4. Assess the importance to users of the frequency of usable imagery; and 5. Determine any challenges in using Landsat 8. The online survey was sent to 51,617 Landsat users registered with USGS in May 2014. Almost 13,000 people responded to the survey for a response rate of 25 percent (n = 12,966). Current Landsat users (users who had used Landsat in their work in the year prior to the survey) composed 89 percent of the sample (n = 11,549) and past Landsat users composed 11 percent (n = 1,417). The results reported here apply to current Landsat users registered with the USGS Earth Resources Observation and Science (EROS) Center. Users from 161 countries responded to the survey. Of those, 19 percent were citizens or permanent residents of the United States and 81 percent resided in other countries. More than 70 percent of current users had used Landsat 8 in the year prior to the survey. The majority of Landsat 8 users (65 percent) were established users who used Landsat imagery regularly both before and after Landsat 8 imagery became available. The average current Landsat user was male, 36 years old, and highly educated, with 9 years of experience using satellite imagery or geographic information system (GIS) software. Landsat 8 users had, on average, two more years of experience than non-Landsat 8 users. Users were employed predominantly by academic institutions (65 percent), followed by private businesses (13 percent), Federal governments (10 percent), State and local governments (6 percent), and nonprofit organizations (6 percent). Of the Landsat imagery obtained in the past year by current users, on average 31 percent came from a Landsat 8 sensor. An equivalent amount came from the Landsat 7 ETM+ sensor (33 percent); slightly less came from Landsats 4 and 5 TM sensors (27 percent). Much less came from Landsats 1 through 5 MSS sensors (5 percent). Overall, more than a third of users’ work used Landsat imagery (38 percent). Of this work, on average, 37 percent of the work was operational. Landsat 8 users considered a greater proportion of their work operational than non-Landsat 8 users (39 percent compared with 29 percent). Environmental sciences and management were the most commonly selected primary applications (selected by 42 percent of users). Land use/land cover (23 percent) was the second most commonly selected primary application, followed by education (12 percent), agriculture (9 percent), and planning and development (6 percent). Landsat 8 users were asked to rank the importance of certain attributes in determining whether to use Landsat 8 imagery in their work. The archive was ranked most important, followed by cost, spatial resolution, extent of coverage, data quality, and frequency of revisit. Users were asked how satisfied they were with these same attributes as they currently apply to Landsat 8 imagery. On average, users were most satisfied with lack of cost, extent of coverage, data quality, and the archive, but they were satisfied with all attributes. Users were asked how often they needed Landsat imagery to meet various requirements for their primary application. The survey question specifically asked how often users needed usable imagery, which differs from how often they would like the Landsat satellites to acquire an image. Users were asked to identify their needed frequency of usable imagery for the following levels: 1. Threshold level—the minimum frequency of usable imagery needed to be of any value to their primary application. 2. Breakthrough level—the frequency of usable imagery that would result in a significant improvement for their primary application of the imagery. 3. Target level—the frequency of usable imagery that would only provide a limited additional increase in the expected performance for their primary application. To meet the threshold level, three-quarters of users needed usable imagery every 17 days or less frequently. At the breakthrough level, two-thirds of users (64 percent) needed a usable image every 5–16 days. The current constellation of two satellites (Landsat 7 and 8) is capable of meeting the threshold and breakthrough needs of most users at least some of the time, but a single satellite would be highly unlikely to do so. Two-fifths of users (40 percent) felt that usable imagery provided every 4 days or more frequently would meet their target level which the current Landsat constellation cannot provide. Landsat 8 users were significantly more likely than non-Landsat 8 users to need usable imagery more frequently to meet their target levels. Additionally, U.S. Landsat 8 users were significantly more likely than other Landsat users to need usable imagery more frequently in order meet both their breakthrough and target levels. To explore the effect of the availability of Landsat 8 imagery on Landsat imagery use in general, established users (those who had consistently used Landsat imagery both before and after Landsat 8 imagery became available) using Landsat 8 imagery were asked about changes in the amount of Landsat imagery they used. The majority of established users using Landsat 8 imagery (60 percent) reported an average increase of 51 percent in the number of scenes obtained after Landsat 8 imagery became available. Landsat 8 users were asked if they had encountered challenges in using Landsat 8 whereas non-Landsat 8 users were asked if such challenges had played a role in why they were not using Landsat 8 imagery. Although many users did not encounter challenges when using or trying to use Landsat 8 data, slightly less than 30 percent did encounter issues with processing the data to a usable point. The most common issue reported was not being able to create or have access to a surface reflectance corrected product. Other challenges were related to the file sizes of images being too large to download, store, or analyze. There were no statistically significant differences between Landsat 8 and non-Landsat 8 users in terms of challenges encountered when using or trying to use the imagery, which indicates that users were not unduly discouraged by the challenges they may have encountered. When asked about potential consequences of not using Landsat 8, more than half of the non-Landsat 8 users did not report detrimental effects on their work from not using the imagery. Of those who did report detrimental effects, decreased quality of work, decreased scope of work, and increased time spent on work were the most common.

Open-File Report

Tree Cover Mapping Tool—Documentation and user manual

The Tree Cover Mapping (TCM) tool was developed by scientists at the U.S. Geological Survey Earth Resources Observation and Science Center to allow a user to quickly map tree cover density over large areas using visual interpretation of high resolution imagery within a geographic information system interface. The TCM tool uses a systematic sample grid to produce maps of tree cover. The TCM tool allows the user to define sampling parameters to estimate tree cover within each sample unit. This mapping method generated the first on-farm tree cover maps of vast regions of Niger and Burkina Faso. The approach contributes to implementing integrated landscape management to scale up re-greening and restore degraded land in the drylands of Africa. The TCM tool is easy to operate, practical, and can be adapted to many other applications such as crop mapping, settlements mapping, or other features. This user manual provides step-by-step instructions for installing and using the tool, and creating tree cover maps. Familiarity with ArcMap tools and concepts is helpful for using the tool.

Open-File Report