"Landsat data is assimilated into our estimation system and therefore provides the key constraint on our snowpack estimates. Without Landsat data this analysis would have to be done in a modeling context or using limited in situ data and therefore would have significantly higher uncertainties."

"Landsat is the only satellite data archive that allows the quantification of vegetation and flooding dynamics relationships across such a large area. Key features unique to the Landsat archive that are paramount for our work include the archive’s temporal depth and detail provided by over a quarter century of systematically acquired time series of imagery at management-relevant spatial resolution."

"We believe this type of continuous mapping of forest metrics at expansive scales would not have been possible without the excellent radiometric characteristics of Landsat 8, particularly the high level of quantization and the outstanding signal-to-noise ratio, which enables fine distinctions that were not previously possible."

"Landsat is an invaluable resource for developing these high resolution maps. Without the Landsat imagery we would not have the spectral information needed to decompose urban landscapes into Local Climate Zone types. Hence the data is at the heart of the project and it is the most critical piece—without Landsat there is no project."

"Landsat provides a global view of the the worlds alpine glaciers and enables us to track their retreat in ways that would be difficult without this important environmental time series."

"From now on, we’re going to be able to track all of the different types of changes in glaciers – there’s so much science to extract from the data."

"The resolution of Landsat imagery and the size of the Landsat database enables critical insight for scalable, high resolution flood detection in several key ways... This increased resolution is particularly critical in urban areas."

"We use Landsat 8 to document glacier velocity patterns on a mountain-range-wide scale. Mapping glacier velocity is facilitated by Landsat’s high radiometric resolution and precise geolocation."

"The 30-year record of the Landsat sensors (i.e. TM, ETM+, and OLI) provides a unique data archive for studying the impacts of climate change on ecosystems worldwide, in our case, coastal marshes."

"Landsat provides wide coverage of the Himalayas for years with spatial and spectral quality, especially now, with Landsat 8 that has enhanced spectral resolution, which enables the monitoring of glacier state."

"Landsat has been extremely beneficial as it allowed us to frequently evaluate the movement of the shoreline based on data gleaned from one consistent source over the duration of the study period. Further, the continued use of Landsat will allow for ongoing monitoring of the coastline in this region to ensure that potential infrastructural improvements are sustainable based on projections of near-term climate change."

"The relatively high spatial detail from Landsat allows differentiation of water use by crop type and individual farm field. At the moment, only Landsat can provide a consistent historical data going back to the 1980s that is long enough for trend analysis and investigate the relationships between management decisions and climatic drivers."

"This project would not have been possible without the consistent, long-term coverage provided by Landsat. The > 30-year archive of Landsat TM, ETM+, and OLI imagery enabled us to track changes in mangrove range limits on decadal scales."

"Dai Yamazaki, a hydrodynamic engineer at the Japan Agency for Marine-Earth Science and Technology, calls the new [Landsat-based] imagery collection the best understanding yet of Earth's changing surface water."

“Measuring the past contributes to our understanding of the long-term consequences of our past economic and societal choices, and contributes to more informed management decisions in the future.”

"Agricultural engineer Jean-Francois Pekel and colleagues have created a kind of virtual time machine, showing past changes in surface water and providing a baseline for charting the changing future of our watery world. To achieve this feat, Pekel and colleagues used more than 3 million Landsat images of Earth's lakes, wetlands, and rivers taken between 1984 and 2015."

"Without Landsat, 'we would be flying blind. We need those eyes in the sky to complement our ground efforts.'"

"Because of Landsat’s global coverage and long history, it has become a reference point for all Earth observation work and is considered the gold standard of natural resource satellite imagery."

“Landsat represents a public good, Earth-observation infrastructure that allows everyone to study their respective land resources and their change over time.”

"The novelty of our study lies in the bigger picture—measuring glacier change over all main glaciated ranges in Bolivia—and in the identification of potentially dangerous lakes for the first time."

“I would summarize Landsat 8’s science impacts in three ways: More data, better data, and improved, expanded applications."

“To make accurate machine learning models of major crops, we needed decades of satellite imagery from the entire globe. Thanks to Google Earth Engine hosting the entire Landsat archive publicly on Google Cloud, we can focus on algorithms instead of worrying about collecting petabytes of data. Earth observation will continue to improve with every new satellite launch and so will our ability to forecast global food supply."

"This is an example of something government can do well: investing in infrastructure that broadly benefits society, and provides a stable platform for the development of businesses and economic activity. Landsat is the data equivalent of the interstate highway system, a public good that has spawned a thriving for-profit remote sensing industry in the US and beyond."

"We use Landsat images on a daily basis at SkyTruth for environmental monitoring."

"The Deltares Aqua Monitor is the first global-scale tool that shows at 30-m resolution where water is converted to land and vice versa. With assistance from Google Earth Engine, it analyzes satellite imagery from multiple Landsat missions, which observed Earth for more than three decades, on the fly."

"Nothing is harder to image than the past. It is imperative that all Landsat observations are archived and made available to users."

“Work has begun on the next mission, Landsat 9, with launch scheduled for late 2020. Plans for the next generation of Landsat are also underway, with a series of studies leading to a decision on the Landsat 10 and beyond architecture in 2018.”

“Satellite data is revolutionizing the way we map the world and the way we understand the natural and anthropogenic processes acting on Earth.”

"This [Google Earth] update was made possible in a large part thanks to the Landsat program and its commitment to free and accessible open data. Landsat, a joint program of the USGS and NASA, has observed the Earth continuously from 1972 to the present day and offers a wealth of information on the changes to the Earth's surface over time."

"Landsat 8, which launched into orbit in 2013, is the newest sensor in the USGS/NASA Landsat Program — superior to its predecessors in many ways. Landsat 8 captures images with greater detail, truer colors, and at an unprecedented frequency — capturing twice as many images as Landsat 7 does every day."

"We knew that ice had been retreating from this region recently but now, thanks to a wealth of freely available satellite data, we know this has been occurring pervasively along the coastline for almost half a century."

“For our main aim of quantifying surface water extent dynamics during a period of high hydro-climatic variability, Landsat was the only satellite archive to meet all our criteria.”

"The primary archive available for reviewing the positions of coastlines and effects of sea-level rise is Landsat."

“Free and open access to the Landsat archive has already spurred scientific innovation and provided a foundation for REDD+ monitoring, reporting and verification.”

“An alert system operating at the scale presented here depends on systematic global acquisitions, robust preprocessing, and free and accessible data. Only Landsat has these criteria at medium spatial resolutions, with Sentinel aspiring to emulate Landsat.”

"Since the first in the line of Landsat craft entered orbit in 1972, this satellite program has proven valuable to the economy of the United States."

“With 32 years’ worth of data — and ongoing data collection — the Landsat data record (satellites 5, 7 and 8) captures the decadal and interannual variability in forest losses and gains needed to drive global carbon cycle models.”

“We basically built ... Tinder for Landsat maps: Swipe right if it’s good, swipe left if it’s bad.”

“The majority of tropical countries are using Landsat imagery as the primary source of information to support their forest change assessments.”

"The rich history of Landsat (40+ years) enables not only change detection and trend analysis, but also provides a unique oppurtunity for hydrologic model calibration and validation as shown in this application."

"Landsat enabled us to collect a multi-decadal record of the [river] reaches at almost annual resolution. By extending our record into the past we were able to examine how the reaches changed through time providing us with a truly invaluable dataset."

"The Landsat satellites have provided an unprecedented volume of high quality medium-resolution imagery spanning more than 30 years. Without this record it would be exceedingly difficult to place presently observed changes in ice discharge into a longer-term context."

"Landsat offers a globally consistent data set with a short enough revisit time to allow us to consider the percent of time that surface water is present on an annual and seasonal basis, while its 30 meter resolution also enables detection of smaller ponds and rivers, providing greater connectivity."

"In order to produce a rock outcrop map for the entire Antarctic continent, we required a freely available georeferenced multispectral dataset. The dataset needed to cover the high latitudes; be recently acquired; be of a high enough resolution to identify individual outcrops and geomorphological features; and have suitable coverage of the continent. On this basis, the Landsat 8 multispectral satellite data was chosen for analysis as no other platform met these requirements. It would not have been possible, or at least would have been prohibitively expensive, to carry out this study without Landsat data."