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USGS2005

Global land cover mapping and characterization: present situation and future research priorities

The availability and accessibility of global land cover data sets plays an important role in many global change studies. The importance of such science‐based information is also reflected in a number of international, regional, and national projects and programs. Recent developments in earth observing satellite technology, information technology, computer hardware and software, and infrastructure development have helped developed better quality land cover data sets. As a result, such data sets are increasingly becoming available, the user‐base is ever widening, application areas have been expanding, and the potential of many other applications are enormous. Yet, we are far from producing high quality global land cover data sets. This paper examines the progress in the development of digital global land cover data, their availability, and current applications. Problems and opportunities are also explained. The overview sets the stage for identifying future research priorities needed for operational land cover assessment and monitoring.

Geocarto International↗

USGS2018

A new 30 meter resolution global shoreline vector and associated global islands database for the development of standardized ecological coastal units

A new 30-m spatial resolution global shoreline vector (GSV) was developed from annual composites of 2014 Landsat satellite imagery. The semi-automated classification of the imagery was accomplished by manual selection of training points representing water and non-water classes along the entire global coastline. Polygon topology was applied to the GSV, resulting in a new characterisation of the number and size of global islands. Three size classes of islands were mapped: continental mainlands (5), islands greater than 1 km 2 (21,818), and islands smaller than 1 km 2 (318,868). The GSV represents the shore zone land and water interface boundary, and is a spatially explicit ecological domain separator between terrestrial and marine environments. The development and characteristics of the GSV are presented herein. An approach is also proposed for delineating standardised, high spatial resolution global ecological coastal units (ECUs). For this coastal ecosystem mapping effort, the GSV will be used to separate the nearshore coastal waters from the onshore coastal lands. The work to produce the GSV and the ECUs is commissioned by the Group on Earth Observations (GEO), and is associated with several GEO initiatives including GEO Ecosystems, GEO Marine Biodiversity Observation Network (MBON) and GEO Blue Planet.

Journal of Operational Oceanography↗

USGS2019

An introduction to the “Oceans and Society: Blue Planet” Initiative

We live on a blue planet, and Earth’s waters benefit many sectors of society. The future of our blue planet is increasingly reliant on the services delivered by marine, coastal and inland waters and on the advancement of effective, evidence-based decisions on sustainable development. “Oceans and Society: Blue Planet” (hereafter denoted as “GEO Blue Planet”) is an initiative of the Group on Earth Observations (GEO) that aims to ensure the sustained development and use of ocean and coastal observations for the benefit of society. GEO Blue Planet works to advance and exploit synergies among the many observational programmes devoted to ocean and coastal waters; to improve engagement with a variety of stakeholders for enhancing the timeliness, quality and range of information delivered; and to raise awareness of the societal benefits of ocean observations at the public and policy levels. This paper summarizes the role of GEO Blue Planet, current activities and considerations for future directions.

Journal of Operational Oceanography↗

USGS2024

Testing spatial out-of-sample area of influence for grain forecasting models

We examine the factors that determine if a grain forecasting model fit to one region can be transferred to another region. Prior research has proposed examining the area of applicability (AoA) of a model based on structurally similar characteristics in the Earth Observation predictors and weights based on the model derived feature importance. We expand on and evaluate this approach in the context of grain yield forecasting in Sub-Saharan Africa. Specifically, we evaluate an AoA methodology established for generating raster surfaces and apply it to vector supported grain data. We fit a series of ensemble tree models both within single countries and across multiple sets of countries and then test those models in countries excluded from the training set. We then calculate and decompose AoA measures and examine several different performance metrics. We find that the spatial transfer accuracy does not vary across season but does vary by average rainfall and across high, medium, and low yielding regions. In general, areas with higher yields and medium to high average rainfall tend to have higher accuracy for both model training and transfer. Finally, we find that fitting models with multiple countries provides more accurate out-of-sample estimates when compared to models fitted to a single country.

Enivronmental Research Letters↗

USGS2026

ENSO and PDO drive shoreline position anomalies in the U.S. Pacific Northwest

Sandy beaches act as buffers against various coastal hazards but are vulnerable to episodic (seasonal) and chronic (interannual) erosion. Understanding the variation of shoreline position, a key metric in coastal morphology, over a spectrum of time scales is therefore crucial in assessing hazard vulnerability. Long-standing research has investigated the role of El Niño-Southern Oscillation (ENSO), the dominant mode of climate variability in the Pacific Basin, in seasonal shoreline variability. Yet, ENSO’s chronic influence—and that of another Pacific climate mode, the Pacific Decadal Oscillation (PDO)—on shoreline anomalies remains poorly understood. Here, we examine the variability of sandy beaches in the US Pacific Northwest, a ∼750 km long coastal region on the US West Coast. We leverage 40 years (1984–2024) of shoreline data from publicly available Earth-observing (Landsat) satellite imagery at a high spatial resolution (>10,000 shore-normal transects at 50-m alongshore spacing) and employ Convergent Cross Mapping (CCM), a methodology for inferring causality in dynamical systems. We discover that strong El Niño years are signified by erosion (75.1% of transects), and strong La Niña years exhibit accretional behavior (73.4% of transects). Furthermore, we establish, for the first time, that both ENSO and PDO exert a statistically significant control on interannual shoreline variability, particularly on the alongshore component (in 95 and 100% of littoral cells, respectively), with water level fluctuations playing a critical role. This effort advances our understanding of the seasonal-to-interannual interactions between Pacific Basin climate variability and the PNW’s coastal morphodynamics, with implications for sediment management and coastal adaptation.

California, Oregon, Washington↗

USGS1998

ASTER preflight and inflight calibration and the validation of level 2 products

Describes the preflight and inflight calibration approaches used for the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER). The system is a multispectral, high-spatial resolution sensor on the Earth Observing System's EOS-AM1 platform. Preflight calibration of ASTER uses well-characterized sources to provide calibration and preflight round-robin exercises to understand biases between the calibration sources of ASTER and other EOS sensors. These round-robins rely on well-characterized, ultra-stable radiometers. An experiment field in Yokohama, Japan, showed that the output from the source used for the visible and near-infrared (VNIR) subsystem of ASTER may be underestimated by 1.5%, but this is still within the 4% specification for the absolute, radiometric calibration of these bands. Inflight calibration will rely on vicarious techniques and onboard blackbodies and lamps. Vicarious techniques include ground-reference methods using desert and water sites. A recent joint field campaign gives confidence that these methods currently provide absolute calibration to better than 5%, and indications are that uncertainties less than the required 4% should be achievable at launch. The EOS-AM1 platform will also provide a spacecraft maneuver that will allow ASTER to see the Moon, allowing further characterization of the sensor. A method for combining the results of these independent calibration results is presented. The paper also describes the plans for validating the Level 2 data products from ASTER. These plans rely heavily upon field campaigns using methods similar to those used for the ground-reference, vicarious calibration methods.

IEEE Transactions on Geoscience and Remote Sensing↗

USGS2008

Monitoring on-orbit stability of Terra MODIS and Landsat 7 ETM+ reflective solar bands using Railroad Valley Playa, Nevada (RVPN) test site

The Moderate Resolution Imaging Spectroradiometer (MODIS) Proto-Flight Model (PFM), launched on December 18, 1999, aboard NASA's Earth Observing System (EOS) Terra satellite has 20 reflective solar bands (RSB) with wavelengths ranging from 0.41 to 2.1 mum over a wide field of view (plusmn55deg). The Landsat 7 (L7) Enhanced Thematic Mapper Plus (ETM+) sensor was launched on April 15, 1999, and has six spectral bands located in the visible and shortwave infrared (SWIR) part of the electromagnetic spectrum (0.4 - 2.5 mum). The ETM+ belongs to the family of Thematic Mapper sensors flown on previous Landsat missions. In this study, over 75 cloud-free nadir near-simultaneous images over Railroad Valley Playa, Nevada (RVPN) were chosen covering entire missions of both sensors. RVPN (38.5degN and 115.7degW), located between the cities of Ely and Tonopah, Nevada, USA, is a high reflectance site with very high spatial, spectral, and temporal uniformity. It is referenced to the Worldwide Reference System-2 (WRS-2) with path 40 and row 33. Homogeneous regions of interest (ROI) were chosen and cross-calibration was performed using an image statistics approach to monitor the long-term stability of the two sensors.

Nevada↗

USGS2009

Assessment of the short-term radiometric stability between Terra MODIS and Landsat 7 ETM+ sensors

Short-term radiometric stability was evaluated using continuous ETM+ scenes within a single orbit (contact period) and the corresponding MODIS scenes for the four matching solar reflective visible and near-infrared (VNIR) band pairs between the two sensors. The near-simultaneous earth observations were limited by the smaller swath size of ETM+ (183 km) compared to MODIS (2330 km). Two sets of continuous granules for Terra MODIS and Landsat 7 ETM+ were selected and mosaicked based on pixel geolocation information for noncloudy pixels over the African continent. The matching pixel pairs were resampled from a fine to a coarse pixel resolution, and the at-sensor spectral radiance values for a wide dynamic range of the sensors were compared and analyzed, covering various surface types. The following study focuses on radiometric stability analysis from the VNIR band-pairs of ETM+ and MODIS. The Libya-4 desert target was included in the path of this continuous orbit, which served as a verification point between the short-term and the long-term trending results from previous studies. MODTRAN at-sensor spectral radiance simulation is included for a representative desert surface type to evaluate the consistency of the results.

Conference Paper↗

USGS2010

Operational calibration and validation of landsat data continuity mission (LDCM) sensors using the image assessment system (IAS)

Systematic characterization and calibration of the Landsat sensors and the assessment of image data quality are performed using the Image Assessment System (IAS). The IAS was first introduced as an element of the Landsat 7 (L7) Enhanced Thematic Mapper Plus (ETM+) ground segment and recently extended to Landsat 4 (L4) and 5 (L5) Thematic Mappers (TM) and Multispectral Sensors (MSS) on-board the Landsat 1-5 satellites. In preparation for the Landsat Data Continuity Mission (LDCM), the IAS was developed for the Earth Observer 1 (EO-1) Advanced Land Imager (ALI) with a capability to assess pushbroom sensors. This paper describes the LDCM version of the IAS and how it relates to unique calibration and validation attributes of its on-board imaging sensors. The LDCM IAS system will have to handle a significantly larger number of detectors and the associated database than the previous IAS versions. An additional challenge is that the LDCM IAS must handle data from two sensors, as the LDCM products will combine the Operational Land Imager (OLI) and Thermal Infrared Sensor (TIRS) spectral bands.

Conference Paper↗

USGS2023

Opera Dynamic Surface Water extents for Harmonized Landsat Sentinel-2 (DSWX-HLS) validation activities

We present the validation methodology and results of Dynamic Surface Water eXtent from Harmonized Landsat Sentinel-2 (DSWx-HLS). The DSWx-HLS product is the first of the DSWx suite, comprised of products each which map water from Earth Observation optical and SAR satellites. We detail the generation of high-resolution (3 m) validation datasets from a globally-stratified sample of dry, moderate, and wet sites. We provide the precise accounting of the classification metrics used to verify the Observational Products for End-users from Remote Sensing Analysis (OPERA) project requirements. We also report broader classification metrics across the validation datasets considered. OPERA performs validation in the public domain to ensure that the validation activities are transparent and reproducible. The resulting validation datasets and provisional OPERA products are publicly available; the software used for validation is also open-source.

Conference Paper↗

USGS2004

A geometric performance assessment of the EO-1 advanced land imager

The Earth Observing 1 (EO-1) Advanced Land Imager (ALI) demonstrates technology applicable to a successor system to the Landsat Thematic Mapper series. A study of the geometric performance characteristics of the ALI was conducted under the auspices of the EO-1 Science Validation Team. This study evaluated ALI performance with respect to absolute pointing knowledge, focal plane sensor chip assembly alignment, and band-to-band registration for purposes of comparing this new technology to the heritage Landsat systems. On-orbit geometric calibration procedures were developed that allowed the generation of ALI geometrically corrected products that compare favorably with their Landsat 7 counterparts with respect to absolute geodetic accuracy, internal image geometry, and band registration.

IEEE Transactions on Geoscience and Remote Sensing↗

USGS2004

Cross calibration of the Landsat-7 ETM+ and EO-1 ALI sensor

As part of the Earth Observer 1 (EO-1) Mission, the Advanced Land Imager (ALI) demonstrates a potential technological direction for Landsat Data Continuity Missions. To evaluate ALI's capabilities in this role, a cross-calibration methodology has been developed using image pairs from the Landsat-7 (L7) Enhanced Thematic Mapper Plus (ETM+) and EO-1 (ALI) to verify the radiometric calibration of ALI with respect to the well-calibrated L7 ETM+ sensor. Results have been obtained using two different approaches. The first approach involves calibration of nearly simultaneous surface observations based on image statistics from areas observed simultaneously by the two sensors. The second approach uses vicarious calibration techniques to compare the predicted top-of-atmosphere radiance derived from ground reference data collected during the overpass to the measured radiance obtained from the sensor. The results indicate that the relative sensor chip assemblies gains agree with the ETM+ visible and near-infrared bands to within 2% and the shortwave infrared bands to within 4%.

IEEE Transactions on Geoscience and Remote Sensing↗

USGS2013

Assessment of spectral, misregistration, and spatial uncertainties inherent in the cross-calibration study

Cross-calibration of satellite sensors permits the quantitative comparison of measurements obtained from different Earth Observing (EO) systems. Cross-calibration studies usually use simultaneous or near-simultaneous observations from several spaceborne sensors to develop band-by-band relationships through regression analysis. The investigation described in this paper focuses on evaluation of the uncertainties inherent in the cross-calibration process, including contributions due to different spectral responses, spectral resolution, spectral filter shift, geometric misregistrations, and spatial resolutions. The hyperspectral data from the Environmental Satellite SCanning Imaging Absorption SpectroMeter for Atmospheric CartograpHY and the EO-1 Hyperion, along with the relative spectral responses (RSRs) from the Landsat 7 Enhanced Thematic Mapper (TM) Plus and the Terra Moderate Resolution Imaging Spectroradiometer sensors, were used for the spectral uncertainty study. The data from Landsat 5 TM over five representative land cover types (desert, rangeland, grassland, deciduous forest, and coniferous forest) were used for the geometric misregistrations and spatial-resolution study. The spectral resolution uncertainty was found to be within 0.25%, spectral filter shift within 2.5%, geometric misregistrations within 0.35%, and spatial-resolution effects within 0.1% for the Libya 4 site. The one-sigma uncertainties presented in this paper are uncorrelated, and therefore, the uncertainties can be summed orthogonally. Furthermore, an overall total uncertainty was developed. In general, the results suggested that the spectral uncertainty is more dominant compared to other uncertainties presented in this paper. Therefore, the effect of the sensor RSR differences needs to be quantified and compensated to avoid large uncertainties in cross-calibration results.

IEEE Transactions on Geoscience and Remote Sensing↗

USGS2022

Global genetic diversity status and trends: Towards a suite of Essential Biodiversity Variables (EBVs) for genetic composition

Biodiversity underlies ecosystem resilience, ecosystem function, sustainable economies, and human well-being. Understanding how biodiversity sustains ecosystems under anthropogenic stressors and global environmental change will require new ways of deriving and applying biodiversity data. A major challenge is that biodiversity data and knowledge are scattered, biased, collected with numerous methods, and stored in inconsistent ways. The Group on Earth Observations Biodiversity Observation Network (GEO BON) has developed the Essential Biodiversity Variables (EBVs) as fundamental metrics to help aggregate, harmonize, and interpret biodiversity observation data from diverse sources. Mapping and analyzing EBVs can help to evaluate how aspects of biodiversity are distributed geographically and how they change over time. EBVs are also intended to serve as inputs and validation to forecast the status and trends of biodiversity, and to support policy and decision making. Here, we assess the feasibility of implementing Genetic Composition EBVs (Genetic EBVs), which are metrics of within-species genetic variation. We review and bring together numerous areas of the field of genetics and evaluate how each contributes to global and regional genetic biodiversity monitoring with respect to theory, sampling logistics, metadata, archiving, data aggregation, modeling, and technological advances. We propose four Genetic EBVs: ( i ) Genetic Diversity; ( ii ) Genetic Differentiation; ( iii ) Inbreeding; and ( iv ) Effective Population Size ( N e ). We rank Genetic EBVs according to their relevance, sensitivity to change, generalizability, scalability, feasibility and data availability. We outline the workflow for generating genetic data underlying the Genetic EBVs, and review advances and needs in archiving genetic composition data and metadata. We discuss how Genetic EBVs can be operationalized by visualizing EBVs in space and time across species and by forecasting Genetic EBVs beyond current observations using various modeling approaches. Our review then explores challenges of aggregation, standardization, and costs of operationalizing the Genetic EBVs, as well as future directions and opportunities to maximize their uptake globally in research and policy. The collection, annotation, and availability of genetic data has made major advances in the past decade, each of which contributes to the practical and standardized framework for large-scale genetic observation reporting. Rapid advances in DNA sequencing technology present new opportunities, but also challenges for operationalizing Genetic EBVs for biodiversity monitoring regionally and globally. With these advances, genetic composition monitoring is starting to be integrated into global conservation policy, which can help support the foundation of all biodiversity and species' long-term persistence in the face of environmental change. We conclude with a summary of concrete steps for researchers and policy makers for advancing operationalization of Genetic EBVs. The technical and analytical foundations of Genetic EBVs are well developed, and conservation practitioners should anticipate their increasing application as efforts emerge to scale up genetic biodiversity monitoring regionally and globally.

Biological Reviews↗

USGS2002

Operating the EOSDIS at the land processes DAAC managing expectations, requirements, and performance across agencies, missions, instruments, systems, and user communities

NASA developed the Earth Observing System (EOS) during the 1990'S. At the Land Processes Distributed Active Archive Center (LP DAAC), located at the USGS EROS Data Center, the EOS Data and Information System (EOSDIS) is required to support heritage missions as well as Landsat 7, Terra, and Aqua. The original system concept of the early 1990'S changed as each community had its say - first the managers, then engineers, scientists, developers, operators, and then finally the general public. The systems at the LP DAAC - particularly the largest single system, the EOSDIS Core System (ECS) - are changing as experience accumulates, technology changes, and each user group gains influence. The LP DAAC has adapted as contingencies were planned for, requirements and therefore plans were modified, and expectations changed faster than requirements could hope to be satisfied. Although not responsible for Quality Assurance of the science data, the LP DAAC works to ensure the data are accessible and useable by influencing systems, capabilities, and data formats where possible, and providing tools and user support as necessary. While supporting multiple missions and instruments, the LP DAAC also works with and learns from multiple management and oversight groups as they review mission requirements, system capabilities, and the overall operation of the LP DAAC. Stakeholders, including the Land Science community, are consulted regularly to ensure that the LP DAAC remains cognizant and responsive to the evolving needs of the user community. Today, the systems do not look or function as originally planned, but they do work, and they allow customers to search and order of an impressive amount of diverse data.

Conference Paper↗

USGS2005

Sharpening advanced land imager multispectral data using a sensor model

The Advanced Land Imager (ALI) instrument on NASA's Earth Observing One (EO-1) satellite provides for nine spectral bands at 30m ground sample distance (GSD) and a 10m GSD panchromatic band. This report describes an image sharpening technique where the higher spatial resolution information of the panchromatic band is used to increase the spatial resolution of ALI multispectral (MS) data. To preserve the spectral characteristics, this technique combines reported deconvolution deblurring methods for the MS data with highpass filter-based fusion methods for the Pan data. The deblurring process uses the point spread function (PSF) model of the ALI sensor. Information includes calculation of the PSF from pre-launch calibration data. Performance was evaluated using simulated ALI MS data generated by degrading the spatial resolution of high resolution IKONOS satellite MS data. A quantitative measure of performance was the error between sharpened MS data and high resolution reference. This report also compares performance with that of a reported method that includes PSF information. Preliminary results indicate improved sharpening with the method reported here.

Conference Paper↗

USGS2007

The CEOS constellation for land surface imaging

A constellation of satellites that routinely and frequently images the Earth's land surface in consistently calibrated wavelengths from the visible through the microwave and in spatial detail that ranges from sub-meter to hundreds of meters would offer enormous potential benefits to society. A well-designed and effectively operated land surface imaging satellite constellation could have great positive impact not only on the quality of life for citizens of all nations, but also on mankind's very ability to sustain life as we know it on this planet long into the future. The primary objective of the Committee on Earth Observation Satellites (CEOS) Land Surface Imaging (LSI) Constellation is to define standards (or guidelines) that describe optimal future LSI Constellation capabilities, characteristics, and practices. Standards defined for a LSI Constellation will be based on a thorough understanding of user requirements, and they will address at least three fundamental areas of the systems comprising a Land Surface Imaging Constellation: the space segments, the ground segments, and relevant policies and plans. Studies conducted by the LSI Constellation Study Team also will address current and shorter-term problems and issues facing the land remote sensing community today, such as seeking ways to work more cooperatively in the operation of existing land surface imaging systems and helping to accomplish tangible benefits to society through application of land surface image data acquired by existing systems. 2007 LSI Constellation studies are designed to establish initial international agreements, develop preliminary standards for a mid-resolution land surface imaging constellation, and contribute data to a global forest assessment.

Conference Paper↗

USGSDate not supplied

Simulation of the long term radiometric responses of the Terra MODIS and EO-1 ALI using Hyperion spectral responses over Railroad Valley Playa in Nevada (RVPN)

The Earth Observing-1 (EO-1) Hyperion instrument provides 220 spectral bands with wavelengths between 400 and 2500 nm at 30 m spatial resolution, which covers a 7.5 km by 100 km area on the ground. The EO-1 spacecraft has another multispectral sensor called the Advanced Land Imager (ALI), which has 10 spectral bands with wavelengths between 400 and 2350 nm at 30 m spatial resolution. The Moderate Resolution Imaging Spectroradiometer (MODIS) sensor onboard the Terra spacecraft was launched in Dec., 1999, and flies approximately 30 minutes behind EO-1. Nearsimultaneous observations from Terra MODIS, EO-1 ALI and Hyperion over a well characterized Railroad Valley Playa in Nevada (RVPN) target are chosen for this study. A uniform region of interest (ROI) within the playa within latitudes and longitudes of 38.48 and -115.71 to 38.53 and -115.66 was chosen for this analysis. A representation of the ground spectra during every near-simultaneous acquisition of MODIS and ALI is obtained using EO-1 Hyperion data. Using the EO-1 Hyperion derived top-of-atmosphere (TOA) reflectance profile along with the ALI and MODIS relative spectral responses (RSR), simulated reflectance for the matching band pairs is calculated. The Hyperion simulated TOA reflectance results are compared to the measured TOA reflectance trends of ALI and MODIS. The long-term measured versus simulated reflectance results are used to examine the relationships and calibration differences between the ALI and MODIS sensors.

Conference Paper↗