Geology topics

Eric Vermote

Publications and source records attributed to Eric Vermote.

7 recordsLinked to original sources

USGS2024

Need and vision for global medium-resolution Landsat and Sentinel-2 data products

Global changes in climate and land use are threatening natural ecosystems, biodiversity, and the ecosystem services people rely on. This is why it is necessary to track and monitor spatiotemporal change at a level of detail that can inform science, management, and policy development. The current constellation of multiple Landsat and Sentinel-2 satellites collecting imagery at predominantly ≤ "> ≤ 30-m spatial resolution affords an opportunity for the generation of global medium- resolution products every few days. Our goal is to both identify the information needs and provide direction towards the generation of a suite of global, high-level, systematically-generated, medium-resolution products designed for both management and science. Our vision builds on the success of the NASA MODIS/VIIRS product suite, while recognizing the unique strengths of medium-resolution satellite data given their higher spatial resolution and longer time series. We propose a suite of 13 essential products that enable the characterization of the current state and changes in the biosphere, cryosphere, and hydrosphere, and would fill information needs identified by the Committee on Earth Observation Satellites for the Global Climate Observing System and the Global Terrestrial Observing System, by the National Research Council of the US National Academies in the decadal survey, and by others. These products are: land cover, land cover change, burned area, forest loss, vegetation indices, phenology, dynamic habitat indices, albedo, land surface temperature, snow cover, ice extent, surface water extent, and evapotranspiration. Furthermore, we provide a list of desirable products poised for addition to the essential products (e.g., crop type, emissivity, and ice sheet velocity). Lastly, we suggest aspirational products requiring further algorithm development (e.g., forest structure and crop yield). For the identified essential products, algorithms are in place, making it feasible to begin generating products systematically. These products should be accompanied by quality and accuracy assessments undertaken following consensus protocols. Five decades after the first Landsat satellite, and two decades after the MODIS products were first produced, it is time now for readily available, standardized, and consistent high-level products built upon medium-resolution imagery, thereby fulfilling the promise and the vision that inspired the Landsat program since its inception.

Remote Sensing of Environment↗

USGS2023

Validity of the Landsat surface reflectance archive for aquatic science: Implications for cloud-based analysis

Originally developed for terrestrial science and applications, the US Geological Survey Landsat surface reflectance (SR) archive spanning ~ 40 yr of observations has been increasingly utilized in large-scale water-quality studies. These products, however, have not been rigorously validated using in situ measured reflectance. This letter quantifies and demonstrates the quality of the SR products by harnessing a sizeable global dataset ( N = 1100). We found that the Landsat 8/9 SR in the green and red bands marginally meet the targeted accuracy requirements (30%), whereas the uncertainties in the blue and coastal-aerosol bands ranged from 48% to 110%. We further observed > +25% biases in the visible bands of Landsat 5/7 SR, which can introduce an apparent downward trend when applied in time-series analyses combined with Landsat 8/9. Users must exercise caution when using this archive for trend analyses, and progress in atmospheric correction is required to foster advanced applications of the Landsat archive for aquatic science.

Limnology and Oceanography Letters↗

USGS2023

The 50-year Landsat collection 2 archive

The Landsat global consolidated data archive now exceeds 50 years. In recognition of the need for consistently processed data across the Landsat satellite series, the U.S. Geological Survey (USGS) initiated collection-based processing of the entire archive that was processed as Collection 1 in 2016. In preparation for the data from the now successfully launched Landsat 9, the USGS reprocessed the Landsat archive as Collection 2 in 2020. This paper describes the rationale for, and the contents and advancements provided by Collection 2, and highlights the differences between the Collection 1 and Collection 2 products. Notably, the Collection 2 products have improved geolocation and, for the first time, the USGS provides a global inventory of Level 2 surface reflectance and surface temperature products. Also for the first time, the USGS used a commercial cloud computing architecture to efficiently process the archive and enable direct cloud access of the Landsat products. The paper concludes with discussion of likely improvements expected in Collection 3 in preparation for the Landsat Next mission that is planned for launch in the early 2030s.

Science of Remote Sensing↗

USGS2022

Fifty years of Landsat science and impacts

Since 1972, the Landsat program has been continually monitoring the Earth, to now provide 50 years of digital, multispectral, medium spatial resolution observations. Over this time, Landsat data were crucial for many scientific and technical advances. Prior to the Landsat program, detailed, synoptic depictions of the Earth's surface were rare, and the ability to acquire and work with large datasets was limited. The early years of the Landsat program delivered a series of technological breakthroughs, pioneering new methods, and demonstrating the ability and capacity of digital satellite imagery, creating a template for other global Earth observation missions and programs. Innovations driven by the Landsat program have paved the way for subsequent science, application, and policy support activities. The economic and scientific value of the knowledge gained through the Landsat program has been long recognized, and despite periods of funding uncertainty, has resulted in the program's 50 years of continuity, as well as substantive and ongoing improvements to payload and mission performance. Free and open access to Landsat data, enacted in 2008, was unprecedented for medium spatial resolution Earth observation data and substantially increased usage and led to a proliferation of science and application opportunities. Here, we highlight key developments over the past 50 years of the Landsat program that have influenced and changed our scientific understanding of the Earth system. Major scientific and programmatic impacts have been realized in the areas of agricultural crop mapping and water use, climate change drivers and impacts, ecosystems and land cover monitoring, and mapping the changing human footprint. The introduction of Landsat collection processing, coupled with the free and open data policy, facilitated a transition in Landsat data usage away from single images and towards time series analyses over large areas and has fostered the widespread use of science-grade data. The launch of Landsat-9 on September 27, 2021, and the advanced planning of its successor mission, Landsat-Next, underscore the sustained institutional support for the program. Such support and commitment to continuity is recognition of both the historic impact the program, and the future potential to build upon Landsat's remarkable 50-year legacy.

Remote Sensing of Environment↗

USGS2020

Satellite and airborne remote sensing of gross primary productivity in boreal Alaskan lakes

In terrestrial and marine ecosystems, remote sensing has been used to estimate gross primary productivity (GPP) for decades, but few applications exist for shallow freshwater ecosystems.Here we show field-based GPP correlates with satellite and airborne lake color across a range of optically and limnologically diverse lakes in interior Alaska. A strong relationship between in situ GPP derived from stable oxygen isotopes (δ 18 O) and space-based lake color from satellites (e.g. Landsat-8, Sentinel-2 and CubeSats) and airborne imagery (AVIRIS-NG) demonstrates the potential power of this technique for improving spatial and temporal monitoring of lake GPP when coupled with additional field validation measurements across different systems. In shallow waters clear enough for sunlight to reach lake bottoms, both submerged vegetation (macrophytes and algae) and phytoplankton likely contribute to GPP. The stable isotopes and remotely sensed shallow lake color used here integrate both components. These results demonstrate the utility of lake color as a feasible means for mapping lake GPP from remote sensing. This novel methodology estimates GPP from remote sensing in shallow lakes by combining field measurements of oxygen isotopes with airborne, satellite and CubeSat imagery. This use of lake color for providing insight into ecological processes of shallow lakes is recommended, especially for remote arctic and boreal landscapes.

Alaska↗

USGS2013

Landsat ecosystem disturbance adaptive processing system (LEDAPS) algorithm description

The Landsat Ecosystem Disturbance Adaptive Processing System (LEDAPS) software was originally developed by the National Aeronautics and Space Administration–Goddard Space Flight Center and the University of Maryland to produce top-of-atmosphere reflectance from LandsatThematic Mapper and Enhanced Thematic Mapper Plus Level 1 digital numbers and to apply atmospheric corrections to generate a surface-reflectance product.The U.S. Geological Survey (USGS) has adopted the LEDAPS algorithm for producing the Landsat Surface Reflectance Climate Data Record.This report discusses the LEDAPS algorithm, which was implemented by the USGS.

Open-File Report↗

USGS2010

Web-enabled Landsat Data (WELD): Landsat ETM+ composited mosaics of the conterminous United States

Since January 2008, the U.S. Department of Interior / U.S. Geological Survey have been providing free terrain-corrected (Level 1T) Landsat Enhanced Thematic Mapper Plus (ETM+) data via the Internet, currently for acquisitions with less than 40% cloud cover. With this rich dataset, temporally composited, mosaics of the conterminous United States (CONUS) were generated on a monthly, seasonal, and annual basis using 6521 ETM+ acquisitions from December 2007 to November 2008. The composited mosaics are designed to provide consistent Landsat data that can be used to derive land cover and geo-physical and bio-physical products for detailed regional assessments of land-cover dynamics and to study Earth system functioning. The data layers in the composited mosaics are defined at 30 m and include top of atmosphere (TOA) reflectance, TOA brightness temperature, TOA normalized difference vegetation index (NDVI), the date each composited pixel was acquired on, per-band radiometric saturation status, cloud mask values, and the number of acquisitions considered in the compositing period. Reduced spatial resolution browse imagery, and top of atmosphere 30 m reflectance time series extracted from the monthly composites, capture the expected land surface phenological change, and illustrate the potential of the composited mosaic data for terrestrial monitoring at high spatial resolution. The composited mosaics are available in 501 tiles of 5000 × 5000 30 m pixels in the Albers equal area projection and are downloadable at http://landsat.usgs.gov/WELD.php . The research described in this paper demonstrates the potential of Landsat data processing to provide a consistent, long-term, large-area, data record.

Remote Sensing of Environment↗