Chesapeake Bay is the Nation's largest estuary and its restoration and protection is a priority. The USGS provides scientific information to help manage this vital ecosystem. As part of that role, staff at the USGS Earth Resources Observation and Science (EROS) Center created this true color composite image.
What could be causing the "seamline" in a mosaic of multiple Landsat images?
In order to obtain a "seamless" mosaic, radiance (and preferably reflectance) might need to be calculated before performing the mosaic because gain changes might occur in one or more of the scenes. When two scenes have different gain states, they have different dynamic ranges and there will be a shift in Digital Number (DN) values from one scene to the next. This can be determined by reviewing the included metadata file for each scene.
Some imaging software packages have a utility that can automatically create the radiance image, based on the gain/bias in the header file. If this is not available, a manual "band math function" might be necessary.
Learn more: Landsat Level-1 Conversion Equations
Related
Why are negative values observed over water in some Landsat Surface Reflectance products?
Landsat atmospheric correction and surface reflectance retrieval algorithms are not ideal for water bodies due to the inherently low surface reflectance of water. Similarly, surface reflectance values greater than 1.0 can be encountered over bright targets such as snow and playas. These are known computational artifacts in the Landsat surface reflectance products. Learn more Landsat Surface...
What are some known issues that users might find in Landsat data?
A number of artifacts and anomalies can happen to any remote sensing data. Banding, dropped scan lines, and detector failures are only a few of the anomalies that can be seen in Landsat data. Go to Landsat Known Issues for details about anomalies that have been discovered and investigated.
Why is there so much color variation among the Landsat browse images?
A custom color stretch is performed on the images, based on individual scene content. Scenes from within the same area and/or acquisition date might vary in band content (due to differences such as cloud content or ground moisture). This differing content will cause variation in the results of the color stretch. Pixelation is an artifact of the browse generation process and is common for scenes...
What are the band designations for the Landsat satellites?
The sensors onboard each of the Landsat satellites were designed to acquire data in different wavelengths in the electromagnetic spectrum. View Bandpass Wavelengths for all Landsat Sensors The Multispectral Scanner (MSS) carried on Landsat 1,2,3,4 and 5 collected data in four ranges (bands); the Thematic Mapper (TM) sensor on Landsat 4 and Landsat 5 included those bands found on earlier satellites...
What are the best Landsat spectral bands for use in my research?
The Spectral Characteristics Viewer is an interactive tool that can be used to visualize how the bands, or channels, of different satellite sensors measure the intensity of the many wavelengths (colors) of light. This is also known as the relative spectral response (RSR). By overlaying the spectral curves from different features (spectra), one can determine which bands of the selected sensor will...
Chesapeake Bay: A Landsat 8 Surface Reflectance Mosaic
Chesapeake Bay is the Nation's largest estuary and its restoration and protection is a priority. The USGS provides scientific information to help manage this vital ecosystem. As part of that role, staff at the USGS Earth Resources Observation and Science (EROS) Center created this true color composite image.
Landsat 8 mosaic image of the Black Hills and Badlands, South Dakota
This image showing the Black Hills and Badlands, South Dakota is a mosaic of multiple Landsat 8 scenes acquired in 2015 and 2016.
This image showing the Black Hills and Badlands, South Dakota is a mosaic of multiple Landsat 8 scenes acquired in 2015 and 2016.
Landsat Collections
Landsat Collections: Providing a Stable Environmental Record for Time Series Analysis
Landsat Collections: Providing a Stable Environmental Record for Time Series Analysis
Landsat Collections — What are Tiers?
This is the third video in a series describing the new U.S. Geological Survey (USGS) Landsat Collection 1 inventory structure. Collection 1 required the reprocessing of all archived Landsat data to achieve radiometric and geometric consistency of Level-1 products through time and across all Landsat sensors.
This is the third video in a series describing the new U.S. Geological Survey (USGS) Landsat Collection 1 inventory structure. Collection 1 required the reprocessing of all archived Landsat data to achieve radiometric and geometric consistency of Level-1 products through time and across all Landsat sensors.
Landsat Collections - RMSE
Landsat Collections: Providing a Stable Environment Record for Time Series Analysis
Landsat Collections: Providing a Stable Environment Record for Time Series Analysis
Tessera Mosaic
The Tietê River snakes across this tessera mosaic of multicolored shapes near Ibitinga, Brazil. Fields of sugarcane, peanuts, and corn vary in their stages of development. Lavender, purple, and bright blue indicate actively growing crops. Light yellow or white indicate little or no vegetation growth. The splotches of dark mustard yellow are urban areas.
The Tietê River snakes across this tessera mosaic of multicolored shapes near Ibitinga, Brazil. Fields of sugarcane, peanuts, and corn vary in their stages of development. Lavender, purple, and bright blue indicate actively growing crops. Light yellow or white indicate little or no vegetation growth. The splotches of dark mustard yellow are urban areas.
A Landsat Mosaic for Indiana’s Bicentennial
This satellite mosaic of the Hoosier State was created from several Landsat scenes stitched together to create one seamless image. Data from the National Elevation Dataset (NED) is also incorporated into the image. The names of major cities and county boundaries have been added.
This satellite mosaic of the Hoosier State was created from several Landsat scenes stitched together to create one seamless image. Data from the National Elevation Dataset (NED) is also incorporated into the image. The names of major cities and county boundaries have been added.
Related
Why are negative values observed over water in some Landsat Surface Reflectance products?
Landsat atmospheric correction and surface reflectance retrieval algorithms are not ideal for water bodies due to the inherently low surface reflectance of water. Similarly, surface reflectance values greater than 1.0 can be encountered over bright targets such as snow and playas. These are known computational artifacts in the Landsat surface reflectance products. Learn more Landsat Surface...
What are some known issues that users might find in Landsat data?
A number of artifacts and anomalies can happen to any remote sensing data. Banding, dropped scan lines, and detector failures are only a few of the anomalies that can be seen in Landsat data. Go to Landsat Known Issues for details about anomalies that have been discovered and investigated.
Why is there so much color variation among the Landsat browse images?
A custom color stretch is performed on the images, based on individual scene content. Scenes from within the same area and/or acquisition date might vary in band content (due to differences such as cloud content or ground moisture). This differing content will cause variation in the results of the color stretch. Pixelation is an artifact of the browse generation process and is common for scenes...
What are the band designations for the Landsat satellites?
The sensors onboard each of the Landsat satellites were designed to acquire data in different wavelengths in the electromagnetic spectrum. View Bandpass Wavelengths for all Landsat Sensors The Multispectral Scanner (MSS) carried on Landsat 1,2,3,4 and 5 collected data in four ranges (bands); the Thematic Mapper (TM) sensor on Landsat 4 and Landsat 5 included those bands found on earlier satellites...
What are the best Landsat spectral bands for use in my research?
The Spectral Characteristics Viewer is an interactive tool that can be used to visualize how the bands, or channels, of different satellite sensors measure the intensity of the many wavelengths (colors) of light. This is also known as the relative spectral response (RSR). By overlaying the spectral curves from different features (spectra), one can determine which bands of the selected sensor will...
Chesapeake Bay: A Landsat 8 Surface Reflectance Mosaic
Chesapeake Bay is the Nation's largest estuary and its restoration and protection is a priority. The USGS provides scientific information to help manage this vital ecosystem. As part of that role, staff at the USGS Earth Resources Observation and Science (EROS) Center created this true color composite image.
Chesapeake Bay is the Nation's largest estuary and its restoration and protection is a priority. The USGS provides scientific information to help manage this vital ecosystem. As part of that role, staff at the USGS Earth Resources Observation and Science (EROS) Center created this true color composite image.
Landsat 8 mosaic image of the Black Hills and Badlands, South Dakota
This image showing the Black Hills and Badlands, South Dakota is a mosaic of multiple Landsat 8 scenes acquired in 2015 and 2016.
This image showing the Black Hills and Badlands, South Dakota is a mosaic of multiple Landsat 8 scenes acquired in 2015 and 2016.
Landsat Collections
Landsat Collections: Providing a Stable Environmental Record for Time Series Analysis
Landsat Collections: Providing a Stable Environmental Record for Time Series Analysis
Landsat Collections — What are Tiers?
This is the third video in a series describing the new U.S. Geological Survey (USGS) Landsat Collection 1 inventory structure. Collection 1 required the reprocessing of all archived Landsat data to achieve radiometric and geometric consistency of Level-1 products through time and across all Landsat sensors.
This is the third video in a series describing the new U.S. Geological Survey (USGS) Landsat Collection 1 inventory structure. Collection 1 required the reprocessing of all archived Landsat data to achieve radiometric and geometric consistency of Level-1 products through time and across all Landsat sensors.
Landsat Collections - RMSE
Landsat Collections: Providing a Stable Environment Record for Time Series Analysis
Landsat Collections: Providing a Stable Environment Record for Time Series Analysis
Tessera Mosaic
The Tietê River snakes across this tessera mosaic of multicolored shapes near Ibitinga, Brazil. Fields of sugarcane, peanuts, and corn vary in their stages of development. Lavender, purple, and bright blue indicate actively growing crops. Light yellow or white indicate little or no vegetation growth. The splotches of dark mustard yellow are urban areas.
The Tietê River snakes across this tessera mosaic of multicolored shapes near Ibitinga, Brazil. Fields of sugarcane, peanuts, and corn vary in their stages of development. Lavender, purple, and bright blue indicate actively growing crops. Light yellow or white indicate little or no vegetation growth. The splotches of dark mustard yellow are urban areas.
A Landsat Mosaic for Indiana’s Bicentennial
This satellite mosaic of the Hoosier State was created from several Landsat scenes stitched together to create one seamless image. Data from the National Elevation Dataset (NED) is also incorporated into the image. The names of major cities and county boundaries have been added.
This satellite mosaic of the Hoosier State was created from several Landsat scenes stitched together to create one seamless image. Data from the National Elevation Dataset (NED) is also incorporated into the image. The names of major cities and county boundaries have been added.
Updated Date: November 4, 2022