Landsat Next | Landsat Science

Mission Objectives

Under the Sustainable Land Imaging (SLI) Program, Landsat Next will continue the long-running partnership between NASA and the USGS by acquiring high-quality, space-borne, moderate-resolution global land imaging data. The Landsat Next mission has four major objectives:

Collect and archive moderate-resolution, reflective and emissive multispectral image data affording seasonal coverage of the global land mass for a period of no less than five years.
Ensure that data are sufficiently consistent with data from earlier Landsat missions in terms of spectral and spatial characteristics, acquisition rates, geometry, calibration, product quality, and data availability.
Support critical emerging user needs and applications, as characterized by periodic assessments and identified by operational requirements.
Distribute data products to the public in a timely and dependable manner on a nondiscriminatory, unrestricted basis.

An Innovative Mission Concept

Landsat Next is an innovative mission concept that will continue the Landsat program’s legacy of global land imaging with greater temporal frequency, finer spatial resolution, and richer spectral information. The mission architecture reflects both advances in technology, in part through the NASA Sustainable Land Imaging-Technology (SLI-T) program, and user priorities for land monitoring, as reflected in the following key documents:

Landsat Next will consist of three identical satellite observatories, equally spaced in orbit. The entire constellation will be a Category 2, Class B mission with a 5-year design life, where each observatory will be composed of Class B and Class C systems. The instrument technical performance is not affected by the risk class designation, and the systems will include elements and mechanisms more typical of Class B instruments to ensure reliability, resiliency, and robustness. The key elements of the Landsat Next concept include:

Continuation of the Landsat legacy through sustainable mission operations.

Implementation of a constellation of three observatories with improved sensors to enhance reliability and systematic monitoring of the Earth.

Improvement of temporal revisit, with an aggregate 6-day repeat period, to increase cloud-free observation frequency.

Collection of bands with higher spatial resolutions, ranging from 10 to 60 meters, for improved detection, monitoring, and management.

Acquisition of 26 spectral bands to support Landsat data continuity,
Sentinel-2 compatibility, and emerging applications.

Preservation of spatial, geometric, and radiometric requirements to maintain long-term data consistency and ensure high-quality science products.

Collection of reflective and thermal infrared bands within 15 seconds of each other to allow for band-to-band georegistration and accurate observations.

Development of the Worldwide Reference System-3 (WRS-3) based on the updated orbital parameters.

Implementation of new techniques to increase the efficiency of ground system operations and improve the distribution of data products.

Video credit: NASA Scientific Visualization Studio, Goddard Space Flight Center.

More Frequent Observations

Improved temporal revisit was identified as the greatest priority by Landsat stakeholders and data users. At least weekly Landsat observations were desired to increase cloud-free image frequency and availability; enhance phenological observations and measurements; better understand landscape disturbance and recovery; advance monitoring and modeling of landscape dynamics; and support more effective mitigation strategies.

From the beginning of the Landsat program with Landsat 1 and Landsat 2 (1975-1978), near weekly revisit frequency was achievable using observations from two or more single observatory missions (except from 1993 to 1999 due to the launch failure of Landsat 6). This approach requires an observatory to perform beyond its design life and provide sufficient overlap with the following mission. Data harmonization and fusion are limited by shared heritage bands and the spatial resolutions of the overlapping observatories. For instance, Landsat 8 and Landsat 9 were separate missions, each with a 16-day repeat cycle and a 5-year mission design life. This pair of nearly identical observatories have an aggregate 8-day temporal revisit, but Landsat 9 was not launched until eight years after Landsat 8. In contrast to a single observatory mission cadence, Landsat Next will deploy three identical observatories, all at the same time.

Landsat Next will use advances in instrument and spacecraft technology to disaggregate the large, single satellite design of previous missions into a constellation of three identical observatories. The three observatories, which will be spaced 120 degrees apart in an 18-day temporal revisit, will provide an aggregate temporal revisit of 6 days at the equator. Revisit times at higher latitudes and in polar regions, where swaths have greater overlap, will be more frequent. Sub-weekly temporal revisit fulfills Landsat data user needs and will support a variety of emerging applications.

A New Worldwide Reference System

Each Landsat Next observatory will occupy a sun-synchronous orbit at an altitude of 653 kilometers (406 miles), have an inclination of ~98 degrees, and image the ground track at the equator at 10:10 am ± 5 minutes (mean local time at descending node). For a single observatory to achieve an 18-day temporal revisit based on the field-of-view requirements, a lower orbital altitude than previous Landsat satellites was required. Images, or scenes, acquired by the former Landsat missions were cataloged and referenced using previous Worldwide Reference System (WRS) grids (i.e., WRS-1 and WRS-2).

To accommodate the Landsat Next repeating ground track and global revisit cycle, a new global grid reference system called WRS-3 was established to acquire, catalog, and distribute Landsat Next scenes. Preserving the previous global reference system and heritage view angle geometry was considered less critical to the overall Landsat Next mission architecture, since science applications are increasingly moving from scene- to pixel-based analysis using BRDF-normalized data.

Under WRS-3, global acquisitions will be completed in 265 orbits (i.e., paths), compared to the 233 orbits associated with WRS-2. The orbits are numbered sequentially with path numbers increasing from east to west. The row indexing system will be the same as WRS-2, with the orbital paths being segmented into 248 equally scene centers based on lines of latitude, but the swath size will be slightly narrower. The rows are indexed so that the numbers of the descending (daytime) path increase in the along-track direction.

The number of unique ground tracks means that adjacent tracks are approximately 151 kilometers (94 miles) apart at the equator. Therefore, the minimum swath width, after adding 10 kilometers for ground track error and 3 kilometers for margin, is 164 kilometers (102 miles). The along-track scene length, which includes a combined 3% in-track overlap with adjacent scenes, is 168 kilometers (104 miles).

WRS-3 PARAMETER	VALUE
Equatorial Altitude	653 km
Inclination	97.9835 degrees
Mean Local Time (Descending Node)	10:10 am ± 5 minutes
Number of Paths	265
Number of Rows	248
Repeat Cycle	18 days
Descending Node Row	60
Longitude of Path 001, Row 060	-65.2 degrees (65.2 W)
Swath Width	164 km
Along-Track Scene Length	168 km
Scene Size	164 km x 168 km

Improved Spatial Resolutions

A user needs survey (Wu et al., 2019) revealed that Landsat reflective and thermal infrared emission band data could be better optimized and harmonized with Sentinel-2 data by increasing the spatial resolution of bands for future Landsat missions. Finer spatial resolutions better characterize surface features and dynamics, particularly in heterogenous landscapes with complex structural and compositional variability, such as those in urban environments and coastal ecosystems. They also facilitate the detection and mapping of smaller features, such as woodlots, streams, riparian corridors, and agricultural fields.

Landsat Next will collect all 26 spectral bands at improved spatial resolutions, with ground sample distances (GSD) of 10 to 20 meters for the VSWIR (visible to shortwave infrared) bands and 60 meters for the atmospheric and TIR (thermal infrared) bands. Five fundamental bands, including Red 2, Green, Blue, NIR Broad, and SWIR 1, will have a GSD of 10 meters. These bands will facilitate considerable advancements in land cover mapping and enable the calculation of spectral indices (e.g., NDVI, NDMI, MSAVI, SAVI, NDSI) with finer spatial resolutions.

Enhanced Spectral Capabilities

Over the course of five decades, the number of spectral bands acquired by Landsat sensors has increased as technological advancements have been made. Landsat 1, with its Multispectral Scanner (MSS), collected four broad, visible and near infrared (NIR) bands. Landsat 8 and Landsat 9 each acquire 11 spectral bands with their Operational Land Imager (OLI/OLI-2) and Thermal Infrared Sensor (TIRS/TIRS-2) instruments. The addition of new bands, including thermal emission bands, with each successive generation of Landsat satellites has supported novel and emerging scientific applications and permitted a greater understanding of global ecosystems and processes, all while maintaining the long-term “heritage” bands to ensure consistency with data from earlier missions.

Landsat Next’s 26 superspectral bands reflect user needs for data continuity and new sources of Earth observation data to address emerging challenges in land, water, and climate science. These enhanced capabilities are made possible by recent advances in instruments, sensors, and observatory components. “Superspectral” refers to a greater number of bands than the previous multispectral Landsat missions. Similar to former Landsat missions, the bands were preselected by the user community based on science needs and previous laboratory, field, airborne, or space-based studies, and were carefully aligned to minimize absorption by the atmosphere (i.e., bands are located in “atmospheric windows“).

Landsat Next will acquire refined versions of the 11 Landsat “heritage” bands, which includes subdividing broad broads for emerging applications and adding TIR bands for temperature and emissivity separation. To support synergy and data fusion with Sentinel-2 data, five new bands with similar spatial and spectral characteristics were included. Ten new spectral bands were added to support evolving and emerging applications, including detection of harmful algal blooms (HABs); snow/ice grain size retrieval and monitoring of melt dynamics; and quantification of crop residue and non-photosynthetic vegetation for agricultural management and soil conservation. An infrared water vapor band was also added to retrieve total column water vapor and remove residual atmospheric absorption and scattering effects in Landsat image data without requiring ancillary data from other Earth observing satellites.

BANDS		GSD (m)	WAVELENGTH RANGE (nm)	RATIONALE
1	Violet	60	402 - 422	Aerosol retrieval, atmospheric correction, detection of colored dissolved organic matter
2	Coastal/Aerosol	20	433 - 453	Landsat heritage, Sentinel-2 synergy, vegetation health and plant vigor assessments
3	Blue	10	457.5 - 522.5	Landsat heritage, Sentinel-2 synergy, bathymetry, soil/vegetation mapping, detection of snow impurities
4	Green	10	542.5 - 577.5	Landsat heritage, Sentinel-2 synergy, vegetation health and plant vigor assessments
5	Yellow	20	585 - 615	Detection of leaf chlorosis and vegetation stress, aquatic health and water quality assessments
6	Orange	20	610 - 630	Phycocyanin (cyanobacteria) detection
7	Red 1	20	640 - 660	Landsat heritage, phycocyanin flourescence (cyanobacteria) detection, chlorophyll content mapping
8	Red 2	10	650 - 680	Landsat heritage, Sentinel-2 synergy, chlorophyll content and vegetation mapping, vegetation differentiation
9	Red Edge 1	20	697.5 - 712.5	Sentinel-2 synergy, leaf area index mapping, chlorophyll content and plant stress mapping
10	Red Edge 2	20	732.5 - 747.5	Sentinel-2 synergy, leaf area index mapping, chlorophyll content and plant stress mapping
11	NIR Broad	10	784.5 - 899.5	Sentinel-2 synergy, 10 meter NDVI, biomass content and shoreline detection
12	NIR 1	20	855 - 875	Landsat heritage, Sentinel-2 synergy, biomass content and shoreline detection
13	Water Vapor	60	935 - 955	Sentinel-2 synergy, atmospheric correction for land surface temperature, surface reflectance
14	Liquid Water	20	975 - 995	Liquid water and water surface state detection, vegetation water content mapping
15	Snow/Ice1	20	1025 - 1045	Snow grain size mapping
16	Snow/Ice 2	20	1080 - 1100	Ice absorption, snow grain size mapping
17	Cirrus	60	1360 - 1390	Landsat heritage, Sentinel-2 synergy, detection of cirrus (high-altitude) clouds
18	SWIR 1	10	1565 - 1655	Landsat heritage, Sentinel-2 synergy, detection of non-photosynthetic vegetation, fuel moisture mapping
19	SWIR 2a	20	2025.5 - 2050.5	Cellulose/crop residue mapping
20	SWIR 2b	20	2088 - 2128	Landsat heritage, cellulose/crop residue and soil moisture content mapping, fire scar detection
21	SWIR 2c	20	2191 - 2231	Landsat heritage, cellulose/crop residue and soil moisture content mapping, fire scar detection
22	TIR 1	60	8175 - 8425	ASTER synergy, mineral and surface composition mapping
23	TIR 2	60	8425 - 8775	ASTER synergy, emissivity separation, volcano/sulfur dioxide emissions mapping
24	TIR 3	60	8925 - 9275	ASTER synergy, mineral and surface composition mapping
25	TIR 4	60	11025 - 11575	Landsat heritage, surface temperature retrieval, carbonate mineral mapping
26	TIR 5	60	11725 - 12275	Landsat heritage, surface temperature retrieval, snow grain size and moisture content mapping

Robust Radiometric and Geometric Performance

The Landsat program has an extensive historical record of highly calibrated data and has served as a gold standard of global land imaging for more than five decades. These elevated standards have permitted time-series analyses and quantitative assessments; enabled the development of higher-level science products; and supported commercial and international sectors through cross-sensor calibration. Rigorous calibration and correction methods have also been applied to provide consistency to a time series that was acquired through different atmospheric conditions using eight different instruments with slightly different spatial, spectral, and view angle characteristics.

"Landsat is the gold standard calibration reference because the Landsat program has committed to world-class radiometric and geometric calibration standards."

Julia A. Barsi

NASA Landsat Calibration Scientist

"Landsat, with its five-decade record of robust collection, calibration, and archiving, and its longstanding service as a global reference to cross-calibrate other missions, improves not only the quality of those systems but the overall quality of the global 'system of systems'."

Kevin T. Gallagher

USGS Associate Director Core Science Systems

The Landsat Next mission will continue the vision of calibration and validation associated with the Landsat program. Radiometric requirements will be aligned with Landsat 8 and Landsat 9 heritage bands, and georegistration requirements will be adjusted to match the finer GSD of Landsat Next bands.

The radiometric requirements for Landsat Next include:

The geometric requirements for Landsat Next include:

To ensure band-to-band alignment and allow accurate cloud screening and science data product generation, each Landsat Next Instrument Suite (LandIS) will acquire all bands for a scene within a 15-second period. Band-to-band co-registration will be 2, 3, and 6 meters for the 10-, 20-, and 60-meter solar reflective bands, respectively, and 15 meters between the reflective and TIR bands.

Data Volumes, Storage, and Computing

Landsat Next, with its three observatories, will acquire significantly more data than prior Landsat missions. In terms of scene acquisitions, the triplet observatories will collect an estimated 2,220 scenes per day. With each scene measuring 164 kilometers by 168 kilometers, this equates to the daily acquisition of roughly 60 million square kilometers or an area comparable to two African continents.

Landsat Next will obtain approximately 10 times more data volume than either Landsat 8 or Landsat 9. Compressed Level-1 Landsat Next data products, assuming 14-bit depth for reflective bands and 12-bit depth for thermal bands, are currently estimated to be 3.7 gigabytes per scene. Given that the three observatories will acquire 2,220 scenes each day, greater than 8.2 terabytes of data will be added to the Landsat archive on a daily basis. This is equivalent to 33 250-gigabyte hard drives or 128 64-gigabyte cell phones. Every four months in operation, Landsat Next will contribute an additional petabyte of data to the archive.

Graphic displaying data acquisitions for Landsat 7, 8, 9 and Next. — Scene and data acquisitions for four Landsat missions. Landsat Next will acquire close to three times as many scenes and 10 times the amount of data than either Landsat 8 or Landsat 9. Notes: 1) Daily scenes are based on the average number of scenes per day. Data estimates are based on the size of compressed Level-1 scene bundles. 2) Landsat 7 is operating at a lower orbit during its extended science mission. It is still collecting 415 scenes per day. When Landsat 7 was first launched, it collected an average of 250 scenes per day. The numbers used in this graphic are an average of daily scenes collected over the lifespan of Landsat 7. 3) Landsat Next numbers are based on current estimates and have some built-in assumptions. Credits: Graphics - NASA Landsat Communications and Public Engagement Team (Ross Walter); Data numbers and calculations – USGS EROS Center (Linda Owen and Esad Micijevic).

The growing volume of data highlights the need to implement new and improved techniques to simplify the management and distribution of data and science products. Cloud storage and computing platforms have and will enable Landsat data to be stored, managed, and analyzed in a cost-effective, scalable, secure, and reliable manner. These services effectively address the challenges of big data storage, facilitate geoprocessing and analysis of large areas over long periods of time, and provide opportunities to explore the growing record of Landsat observations.