EarthExplorerUse the USGS EarthExplorer (EE) to search, download, and order satellite images, aerial photographs, and cartographic products. In addition to data from the Landsat missions and a variety of other data providers, EE provides access to MODIS land data products from the NASA Terra and Aqua missions, and ASTER level-1B data products over the U.S. and Territories from the NASA ASTER mission. Registered users of EE have access to more features than guest users.Earth Explorer Distribution DownloadThe EarthExplorer user interface is an online search, discovery, and ordering tool developed by the United States Geological Survey (USGS). EarthExplorer supports the searching of satellite, aircraft, and other remote sensing inventories through interactive and textual-based query capabilities. Through the interface, users can identify search areas, datasets, and display metadata, browse and integrated visual services within the interface.The distributable version of EarthExplorer provides the basic software to provide this functionality. Users are responsible for verification of system recommendations for hosting the application on your own servers. By default, this version of our code is not hooked up to a data source so you will have to integrate the interface with your data. Integration options include service-based API's, databases, and anything else that stores data. To integrate with a data source simply replace the contents of the 'getDataset' and 'search' functions in the CWIC.php file.Distribution is being provided due to users requests for the codebase. The EarthExplorer source code is provided "As Is", without a warranty or support of any kind. The software is in the public domain; it is available to any government or private institution.The software code base is managed through the USGS Configuration Management Board. The software is managed through an automated configuration management tool that updates the code base when new major releases have been thoroughly reviewed and tested.Link: https://earthexplorer.usgs.gov/

Since 1972, the joint NASA/ U.S. Geological Survey Landsat series of Earth Observation satellites have continuously acquired images of the Earth’s land surface, providing uninterrupted data to help land managers and policymakers make informed decisions about natural resources and the environment.

Landsat is a part of the USGS National Land Imaging (NLI) Program. To support analysis of the Landsat long-term data record that began in 1972, the USGS. Landsat data archive was reorganized into a formal tiered data collection structure. This structure ensures all Landsat Level 1 products provide a consistent archive of known data quality to support time-series analysis and data “stacking”, while controlling continuous improvement of the archive, and access to all data as they are acquired. Collection 1 Level 1 processing began in August 2016 and continued until all archived data was processed, completing May 2018. Newly-acquired Landsat 8 and Landsat 7 data continue to be processed into Collection 1 shortly after data is downlinked to USGS EROS.

Acknowledgement or credit of the USGS as data source should be provided by including a line of text citation such as the example shown below. (Product, Image, Photograph, or Dataset Name) courtesy of the U.S. Geological Survey Example: Landsat-8 image courtesy of the U.S. Geological Survey

The U.S. Geological Survey (USGS) Aerial Photography data set includes over 2.5 million film transparencies. Beginning in 1937, photographs were acquired for mapping purposes at different altitudes using various focal lengths and film types. The resultant black-and-white photographs contain less than 5 percent cloud cover and were acquired under rigid quality control and project specifications (e.g., stereo coverage, continuous area coverage of map or administrative units). Prior to the initiation of the National High Altitude Photography (NHAP) program in 1980, the USGS photography collection was one of the major sources of aerial photographs used for mapping the United States. Since 1980, the USGS has acquired photographs over project areas that require photographs at a larger scale than the photographs in the NHAP and National Aerial Photography Program collections.

High resolution orthorectified images combine the image characteristics of an aerial photograph with the geometric qualities of a map. An orthoimage is a uniform-scale image where corrections have been made for feature displacement such as building tilt and for scale variations caused by terrain relief, sensor geometry, and camera tilt. A mathematical equation based on ground control points, sensor calibration information, and a digital elevation model is applied to each pixel to rectify the image to obtain the geometric qualities of a map.

A digital orthoimage may be created from several photographs mosaicked to form the final image. The source imagery may be black-and-white, natural color, or color infrared with a pixel resolution of 1-meter or finer. With orthoimagery, the resolution refers to the distance on the ground represented by each pixel.

Landsat 8 Collection 2 Tier 1 보정된 대기 중간 (TOA) 반사율입니다. 보정 계수는 이미지 메타데이터에서 추출됩니다. TOA 계산에 관한 자세한 내용은 Chander et al. (2009)를 참고하세요. 사용 가능한 데이터 품질이 가장 우수한 Landsat 장면은 Tier 1로 분류되며 시계열 처리 분석에 적합한 것으로 간주됩니다. …

The first generation of U.S. photo intelligence satellites collected more than 860,000 images of the Earth’s surface between 1960 and 1972. The classified military satellite systems code-named CORONA, ARGON, and LANYARD acquired photographic images from space and returned the film to Earth for processing and analysis. The images were originally used for reconnaissance and to produce maps for U.S. intelligence agencies. In 1992, an Environmental Task Force evaluated the application of early satellite data for environmental studies. Since the CORONA, ARGON, and LANYARD data were no longer critical to national security and could be of historical value for global change research, the images were declassified by Executive Order 12951 in 1995. The first successful CORONA mission was launched from Vandenberg Air Force Base in 1960. The satellite acquired photographs with a telescopic camera system and loaded the exposed film into recovery capsules. The capsules or buckets were de-orbited and retrieved by aircraft while the capsules parachuted to earth. The exposed film was developed and the images were analyzed for a range of military applications. The intelligence community used Keyhole (KH) designators to describe system characteristics and accomplishments. The CORONA systems were designated KH-1, KH-2, KH-3, KH-4, KH-4A, and KH-4B. The ARGON systems used the designator KH-5 and the LANYARD systems used KH-6. Mission numbers were a means for indexing the imagery and associated collateral data. A variety of camera systems were used with the satellites. Early systems (KH-1, KH-2, KH-3, and KH-6) carried a single panoramic camera or a single frame camera (KH-5). The later systems (KH-4, KH-4A, and KH-4B) carried two panoramic cameras with a separation angle of 30° with one camera looking forward and the other looking aft. The original film and technical mission-related documents are maintained by the National Archives and Records Administration (NARA). Duplicate film sources held in the USGS EROS Center archive are used to produce digital copies of the imagery. Mathematical calculations based on camera operation and satellite path were used to approximate image coordinates. Since the accuracy of the coordinates varies according to the precision of information used for the derivation, users should inspect the preview image to verify that the area of interest is contained in the selected frame. Users should also note that the images have not been georeferenced.

Shorelines Extracted from 1984-2015 Landsat Imagery: Petit Bois Island, Mississippi (Polyline: Individual Dates) is a line shapefile representing shorelines generated from satellite imagery that was collected from 1984 to 2015. The sample frequency of satellite imagery is much higher, and the coverage much greater, than most routine high-resolution topographic surveys. Certain aspects of barrier island morphology, such as island size, shape and position, can be determined from these images and can indicate erosion, land loss, and island breakup. Studying how these characteristics evolve will help develop an understanding of how barrier islands will respond to climate change, sea level rise, and major storms in the future and that will serve to improve management of our coastal resources.

Landsat 4 TM Collection 2 Tier 1 DN values, representing scaled, calibrated at-sensor radiance. Landsat scenes with the highest available data quality are placed into Tier 1 and are considered suitable for time-series processing analysis. Tier 1 includes Level-1 Precision Terrain (L1TP) processed data that have well-characterized radiometry and are inter-calibrated across the different Landsat sensors. The georegistration of Tier 1 scenes will be consistent and within prescribed tolerances [<=12 m root mean square error (RMSE)]. All Tier 1 Landsat data can be considered consistent and inter-calibrated (regardless of sensor) across the full collection. See more information in the USGS docs.

Landsat 8 Collection 2 Tier 1 の地上（TOA）反射率が補正されています。キャリブレーション係数は画像メタデータから抽出されます。TOA の計算の詳細については、Chander et al.（2009）をご覧ください。利用可能なデータ品質が最も高い Landsat シーンは Tier 1 に分類され、時系列処理分析に適していると見なされます。…

Aerial imagery is a critical geospatial data component in identyfing, planning, and preparing for the protection of the US and its people. This dataset includes approximately 78,000 square miles of coverage along or near the Gulf Coast and the Atlantic coastline, terminating north of Wilmington, North Carolina. The imagery was collected in 2006 using aircraft to produce a 0.5 meter pixel reso...

Landsat 8 集合 2 第 1 层级校准的对流层顶(TOA) 反射率。校准系数会从图片元数据中提取。如需详细了解TOA 计算，请参阅Chander 等人(2009) 的论文。数据质量最高的Landsat 场景会被划分到第1 层级，并且被视为适合进行时间序列处理分析。…

This data set contains high-resolution QuickBird imagery and geospatial data for the entire Barrow QuickBird image area (156.15° W - 157.07° W, 71.15° N - 71.41° N) and Barrow B4 Quadrangle (156.29° W - 156.89° W, 71.25° N - 71.40° N), for use in Geographic Information Systems (GIS) and remote sensing software. The original QuickBird data sets were acquired by DigitalGlobe from 1 to 2 August 2002, and consist of orthorectified satellite imagery. Federal Geographic Data Committee (FGDC)-compliant metadata for all value-added data sets are provided in text, HTML, and XML formats.

Accessory layers include: 1:250,000- and 1:63,360-scale USGS Digital Raster Graphic (DRG) mosaic images (GeoTIFF format); 1:250,000- and 1:63,360-scale USGS quadrangle index maps (ESRI Shapefile format); an index map for the 62 QuickBird tiles (ESRI Shapefile format); and a simple polygon layer of the extent of the Barrow QuickBird image area and the Barrow B4 quadrangle area (ESRI Shapefile format).

Unmodified QuickBird data comprise 62 data tiles in Universal Transverse Mercator (UTM) Zone 4 in GeoTIFF format. Standard release files describing the QuickBird data are included, along with the DigitalGlobe license agreement and product handbooks.

The baseline geospatial data support education, outreach, and multi-disciplinary research of environmental change in Barrow, which is an area of focused scientific interest. Data are provided on four DVDs. This product is available only to investigators funded specifically from the National Science Foundation (NSF), Office of Polar Programs (OPP), Arctic Sciences Section. An NSF OPP award number must be provided when ordering this data. Contact NSIDC User Services at nsidc@nsidc.org to order the data, and include an NSF OPP award number in the email.

The Global Land Survey (GLS) datasets are a collection of orthorectified, cloud-minimized Landsat-type satellite images, providing near complete coverage of the global land area decadally since the early 1970s. The global mosaics are centered on 1975, 1990, 2000, 2005, and 2010, and consist of data acquired from five sensors: Operational Land Imager, Enhanced Thematic Mapper Plus, Thematic Mapper, Multispectral Scanner, and Advanced Land Imager. This newest version combines all of the GLS data into one collection which has all of the combined collections. The GLS datasets have been widely used in land-cover and land-use change studies at local, regional, and global scales. This study evaluates the GLS datasets with respect to their spatial coverage, temporal consistency, geodetic accuracy, radiometric calibration consistency, image completeness, extent of cloud contamination, and residual gaps. The datasets have been improved in order to give spatial continuity across all decadal collections. Most of the imagery (85%) having cloud cover of less than 10%, the acquisition years clustered much more tightly around their target years, better co-registration relative to GLS-2000, and better radiometric absolute calibration. Probably, the most significant impediment to scientific use of the datasets is the variability of image phenology (i.e., acquisition day of year). This collection provides end-users with an assessment of the quality of the GLS datasets for specific applications, and where possible, suggestions for mitigating their deficiencies.

The USGS, in cooperation with the U.S. Bureau of Land Management (BLM), created a series of geospatial products using historic aerial imagery and Structure from Motion (SfM) photogrammetry methods. A point cloud dataset (.laz) of the South Cow Mountain Recreational Area was generated from stereo historical aerial imagery acquired in by the BLM in 1977. The aerial imagery was downloaded from the USGS Earth Resources Observation and Science (EROS) Data Center's USGS Single Aerial Frame Photo archive and the point cloud was created using USGS guidelines. Photo alignment, error reduction, and dense point cloud generation followed guidelines documented in Over, J.R., Ritchie, A.C., Kranenburg, C.J., Brown, J.A., Buscombe, D., Noble, T., Sherwood, C.R., Warrick, J.A., and Wernette, P.A., 2021, Processing coastal imagery with Agisoft Metashape Professional Edition, version 1.6— Structure from motion workflow documentation: U.S. Geological Survey Open-File Report 2021–1039, 46 p., https://doi.org/10.3133/ofr20211039. Photo-identifiable points, selected as synthetic ground-control points, followed guidelines documented in Sherwood, C.R.; Warrick, J.A.; Hill, A.D.; Ritchie, A.C.; Andrews, B.D., and Plant, N.G., 2018. Rapid, remote assessment of Hurricane Matthew impacts using four-dimensional structure-from-motion photogrammetry https://doi.org/10.2112/JCOASTRES-D-18-00016.1 Additional post-processing of the 1977 dense point cloud, using Iterative Closest Point (ICP) analysis, was used to improve the alignment with the 2015 LiDAR point cloud. The ICP analysis is explained in Low, K.L., 2004. Linear least-squares optimization for point-to-plane ICP surface registration. Chapel Hill, University of North Carolina, 4(10), pp.1-3. http://www.comp.nus.edu.sg/~lowkl/publications/lowk_point-to-plane_icp_techrep.pdf Data were processed using photogrammetry to generate a three-dimensional point cloud that identifies pixels of an object from multiple images taken from various angles and calculates the x, y, and z coordinates of that object/pixel. The point cloud was processed to create a digital surface model of the study area (57.3 cm resolution). Finally, source images were stitched together based on shared pixels and orthogonally adjusted to the digital surface model to create a high resolution (approximately 18.3 cm) orthoimage for the study area.

This joint NASA/USGS program provides the longest continuous space-based record of Earth’s land in existence. Every day, Landsat satellites provide essential information to help land managers and policy makers make wise decisions about our resources and our environment. Data is provided for Landsats 1, 2, 3, 4, 5, 7, 8, and 9 (excludes Landsat 6).As of June 28, 2023 (announcement), the previous single SNS topic arn:aws:sns:us-west-2:673253540267:public-c2-notify was replaced with three new SNS topics for different types of scenes.

Landsat 8 Collection 2 Tier 1 calibrated top-of-atmosphere (TOA) reflectance. Calibration coefficients are extracted from the image metadata. See Chander et al. (2009) for details on the TOA computation. Landsat scenes with the highest available data quality are placed into Tier 1 and are considered suitable for time-series processing analysis. Tier 1 includes Level-1 Precision Terrain (L1TP) processed data that have well-characterized radiometry and are inter-calibrated across the different Landsat sensors. The georegistration of Tier 1 scenes will be consistent and within prescribed tolerances [<=12 m root mean square error (RMSE)]. All Tier 1 Landsat data can be considered consistent and inter-calibrated (regardless of sensor) across the full collection. See more information in the USGS docs. The T1_RT collection contains both Tier 1 and Real-Time (RT) assets. Newly-acquired Landsat 7 ETM+ and Landsat 8 OLI/TIRS data are processed upon downlink but use predicted ephemeris, initial bumper mode parameters, or initial TIRS line of sight model parameters. The data is placed in the Real-Time tier and made available for immediate download. Once the data have been reprocessed with definitive ephemeris, updated bumper mode parameters and refined TIRS parameters, the products are transitioned to either Tier 1 or Tier 2 and removed from the Real-Time tier. The transition delay from Real-Time to Tier 1 or Tier 2 is between 14 and 26 days.

This collections contains 161 1992 | 1995 1-meter black & white digital orthorectified images of multiple non-contiguous locations in Idaho. These data were acquired from July 26, 1992 to September 12, 1995, These data are sourced from the U.S. Geological Survey and commonly referred to as a DOQ (Digital Orthophoto Quadrangle).Some DOQs in this collection are made up of source images from just the most recent year. But, some DOQs in this collection were created from source images from more then one year. Regardless, every DOQ in this collection will be made up of at least one source image from the most recent year.Refer to the .hdr file associated with each DOQ for specific image dates. The .hdr file contains a list of all source image dates (SOURCE_IMAGE_DATE) for a DOQ. The source data for this service are available for download from USGS EarthExplorer.Individual image tiles can be downloaded using the Idaho Aerial Imagery Explorer.These data can be bulk downloaded from a web accessible folder.Users should be aware that temporal changes may have occurred since these data were collected and that some parts of these data may no longer represent actual surface conditions. Users should not use these data for critical applications without a full awareness of the limitations of these data as described in the lineage or elsewhere.

This collections contains 408 1997 | 1998 | 1999 | 2000 1-meter black & white digital orthorectified images of multiple non-contiguous locations in Idaho. These data were acquired from July 8, 1997 to November 22, 2000, These data are sourced from the U.S. Geological Survey and commonly referred to as a DOQ (Digital Orthophoto Quadrangle).Some DOQs in this collection are made up of source images from just the most recent year. But, some DOQs in this collection were created from source images from more then one year. Regardless, every DOQ in this collection will be made up of at least one source image from the most recent year.Refer to the .hdr file associated with each DOQ for specific image dates. The .hdr file contains a list of all source image dates (SOURCE_IMAGE_DATE) for a DOQ. The source data for this service are available for download from USGS EarthExplorer.Individual image tiles can be downloaded using the Idaho Aerial Imagery Explorer.These data can be bulk downloaded from a web accessible folder.Users should be aware that temporal changes may have occurred since these data were collected and that some parts of these data may no longer represent actual surface conditions. Users should not use these data for critical applications without a full awareness of the limitations of these data as described in the lineage or elsewhere.

This data release contains Uncrewed Aircraft System (UAS) imagery from three data collection campaigns (flights) over the Pepperwood Preserve in Sonoma County, California. Each child item contains: 1) Orthophoto, 2) Thermal, 3) Normalized Difference Vegetation Index (NDVI), 4) L-band microwave brightness temperature (Tb), 5) Estimated soil moisture, and 6) Digital elevation model from orthoimagery. The overall footprint varies depending on the flight, and the third flight in May 2023 contains an additional set of high-resolution Tb and calculated soil moisture maps for a smaller footprint. The first two flights were performed using a BlackSwift S2, which is a fixed-wing UAS with a 3-meter wingspan, and the third flight was performed using a BlackSwift E2 multirotor UAS, which contained the same instruments as the S2. All files are raster (*.tif) files that can be visualized and edited by geospatial software including ArcGIS, QGIS, Python, and R. The spatial resolution of each raster is dependent on the instrument, type of UAS, and the UAS altitude during data collection. The UAS equipment was operated by personnel from BlackSwift Technologies, LLC, and data were provided to the U.S. Geological Survey.

These digital images were taken over an area of the Potomac River in White's Ferry, Maryland using 3DR Solo unmanned aircraft systems (UAS) on October 23, 2019. These images were collected for the purpose of evaluating UAS assessment of river habitat data such as water depth, substrate type, and water clarity. Each UAS was equipped with a MicaSense RedEdge multi-spectral camera that captures five specific bands of the visible spectrum (blue, green, red, red edge, and near-infrared), which can be used to classify vegetation. Some photographs contain black and white targets used as ground control points (GCPs), which were surveyed by a field crew with a high-precision (GNSS) Global Navigation Satellite System and/or containing internal post processing kinematic (PPK) GPS system. This data release includes the original images from the MicaSense RedEdge multi-spectral camera of the Potomac River in White's Ferry, Maryland.