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GeoXO Ocean Color Instrument (OCX) Spatial and Temporal Coverage Assessment

NOAA’s next generation Geostationary Extended Observations (GeoXO) satellite system will advance Earth observations from geostationary orbit. GeoXO will supply vital information supporting the U.S. weather, ocean, and climate operations. The recommended three-satellite constellation includes spacecrafts at the current GOES-East and GOES-West positions that will carry an imager, lightning mapper, and an ocean color (OCX) instrument. In this poster we describe an assessment of U.S. Exclusive Economic Zone (EEZ) availability for OCX observations, based on EEZ view geometry, solar angle range over the year, sun glint, as well as cloud climatology. The availability for observations for each EEZ region is estimated per day of the year, as function of atmospheric mass factor (AMF) and sun glint. In addition, cloud climatology – based on statistics derived from three years of GOES-16 ABI cloud mask – is considered to determine the fraction of cloud-free OCX observations for each region as function of time of day and season. The results of such assessments can be used to optimize OCX collections and potentially explore regions outside the EEZ.

Boryana Efremova↗
NASA NTRS1986

IRAS observations of comets

The moderate spatial resolution and high sensitivity of the Infrared Astronomical Satellite (IRAS), which surveyed the celestial sphere during 1983 at wavelengths of 12, 25, 60, and 100 microns, were particularly well suited to detecting extended thermal emission from cometary dust. Sources with infrared color temperatures characteristic of solar system bodies, and at the ephemerides position of known comets were selected for analysis by the IRAS Asteroid Data Analysis System (ADAS). The data base is now available for use by researchers. This paper describes the development of the data base, details its entries, and presents a statistical analysis of its contents. The IRAS survey contains multiple observations of many periodic comets. A brief description and analysis is given of the observed infrared and derived physical properties for several comets of special interest.

Walker, R. G.↗
NASA NTRS2014

NMME Monthly / Seasonal Forecasts for NASA SERVIR Applications Science

This work details use of the North American Multi-Model Ensemble (NMME) experimental forecasts as drivers for Decision Support Systems (DSSs) in the NASA / USAID initiative, SERVIR (a Spanish acronym meaning "to serve"). SERVIR integrates satellite observations, ground-based data and forecast models to monitor and forecast environmental changes and to improve response to natural disasters. Through the use of DSSs whose "front ends" are physically based models, the SERVIR activity provides a natural testbed to determine the extent to which NMME monthly to seasonal projections enable scientists, educators, project managers and policy implementers in developing countries to better use probabilistic outlooks of seasonal hydrologic anomalies in assessing agricultural / food security impacts, water availability, and risk to societal infrastructure. The multi-model NMME framework provides a "best practices" approach to probabilistic forecasting. The NMME forecasts are generated at resolution more coarse than that required to support DSS models; downscaling in both space and time is necessary. The methodology adopted here applied model output statistics where we use NMME ensemble monthly projections of sea-surface temperature (SST) and precipitation from 30 years of hindcasts with observations of precipitation and temperature for target regions. Since raw model forecasts are well-known to have structural biases, a cross-validated multivariate regression methodology (CCA) is used to link the model projected states as predictors to the predictands of the target region. The target regions include a number of basins in East and South Africa as well as the Ganges / Baramaputra / Meghna basin complex. The MOS approach used address spatial downscaling. Temporal disaggregation of monthly seasonal forecasts is achieved through use of a tercile bootstrapping approach. We interpret the results of these studies, the levels of skill by several metrics, and key uncertainties.

Robertson, Franklin R.↗
NASA NTRS2019

Evaluation Analysis of NASA SMAP L3 and L4 and SPoRT-LIS Soil Moisture Data in the United States

Soil moisture has a critical role in the development, frequency and persistence of climatic and hydrologic extremes such as drought, heat wave and flooding events. In situ soil moisture data are uneven and sparse in time and space. This highlights the need to utilize other soil moisture sources to fill this spatiotemporal gap. The goal of this study is to validate one satellite-based and two model-based soil moisture datasets with in situ data across the United States. Soil moisture information from the Soil Moisture Active Passive (SMAP) enhanced level 3 (L3) (SMAP L3) and modeled level 4 (L4) (SMAP L4) data at 9-km resolution and Short-term Prediction Research and Transition-Land Information System (SPoRT-LIS) modeled at 3-km resolution were selected for evaluation. SPoRT-LIS is a near real-time, high resolution operational land analysis data. Ground-based data were obtained from the North American Soil Moisture Database (NASMD) for 362 stations. Seven statistical indicators including anomaly, Spearman, and Pearson correlation coefficients, the systematic error (Bias), root mean square error (RMSE), unbiased root mean square error (ubRMSE), and normalized standard deviation (SDV) were used to evaluate the satellite- and model-derived soil moisture data. In addition, the triple collocation (TC) error model was used to measure the error among SMAP L4, SPoRT-LIS and ground-based data. This study assesses which satellite or modeled dataset is most appropriate for specific times and locations to use as a surrogate for in situ observations. Temporal and spatial analysis demonstrated that, overall, SMAP L4 performed better than SMAP L3 and SPoRT-LIS. Strong agreement was observed between SMAP L4 and in situ observations (ρ = 0.53, Bias = −0.006) in all seasons and most regions with various land covers, especially in winter and in the central regions of the United States. For croplands, SMAP L4 presented the best agreement with in situ data, analyzing all period (ρ = 0.60) and non-winter period (ρ = 0.61) separately.

Tavakol, Ameneh↗
NASA NTRS1990

A statistical study of Pc 3-5 pulsations observed by the AMPTE/CCE magnetic fields experiment. I - Occurrence distributions

A classification system based on dynamic power spectra of AMPTE/CCE magnetic field data has been developed which allows semiquantitative specification of pulsation activity at all times. Fifteen months of 6.24-s AMPTE/CCE magnetic field data have been analyzed using this scheme to generate a comprehensive data base of all pulsation activity observed from L = 5 to L = 9 at all local times in the frequency range 0-80 mHz. The pulsation divide naturally into five basic categories: toroidal fundamental mode resonances, toroidal harmonic resonances, compressional low-frequency waves, radially polarized waves, and disturbed intervals. Additional distinctions among members of these classes are made to arrive at 14 categories which describe 95 percent of the pulsations observed. Normal spatial distributions in local time and L shell are determined for each category. Magnetic latitude distributions are determined for four coherent categories of activity.

Anderson, B. J.↗
NASA NTRS1993

The tropopause cold trap in the Australian Monsoon during STEP/AMEX 1987

The relationship between deep convection and tropopause cold trap conditions is examined for the tropical northern Australia region during the 1986-87 summer monsoon season, emphasizing the Australia Monsoon Experiment (AMEX) period when the NASA Stratosphere-Troposphere Exchange Project (STEP) was being conducted. The factors related to the spatial and temporal variability of the cold point potential temperature (CPPT) are investigated. A framework is developed for describing the relationships among surface average equivalent potential temperature in the surface layer (AEPTSL) the height of deep convection, and stratosphere-troposphere exchange. The time-mean pattern of convection, large-scale circulation, and surface AEPTSL in the Australian monsoon and the evolution of the convective environment during the monsoon period and the extended transition season which preceded it are described. The time-mean fields of cold point level variables are examined and the statistical relationships between mean CPPT, surface AEPTSL, and deep convection are described. Day-to-day variations of CPPT are examined in terms of these time mean relationships.

Selkirk, Henry B.↗
NASA NTRS1994

Interaction of ring current and radiation belt protons with ducted plasmaspheric hiss. 1: Diffusion coefficients and timescales

Protons that are convected into the inner magnetosphere in response to enhanced magnetic activity can resonate with ducted plasmaspheric hiss in the outer plasmasphere via an anomalous Doppler-shifted cyclotron resonance. Plasmaspheric hiss is a right-hand-polarized electromagnetic emission that is observed to fill the plasmasphere on a routine basis. When plasmaspheric hiss is confined within field-aligned ducts or guided along density gradients, wave normal angles remain largely below 45 deg. This allows resonant interactions with ions at typical ring current and radiation belt energies to take place. Such field-aligned ducts have been observed both within the plasmasphere and in regions outside of the plasmasphere. Wave intensities are estimated using statistical information from studies of detached plasma regions. Diffusion coefficients are presented for a range of L shells and proton energies for a fixed wave distribution. Harmonic resonances in the range N = +/-100 are considered in order to include interactions between hiss at 100 Hz to 2 kHz frequencies, and protons in the energy range between approximately 10 keV and 1000 keV. Diffusion timescales are estimated to be of the order of tens of days and comparable to or shorter than lifetimes for Coulomb decay and charge exchange losses over most of the energy and spatial ranges of interest.

Kozyra, J. U.↗
NASA NTRS1998

Direct Numerical Simulation of a Coolant Jet in a Periodic Crossflow

A Direct Numerical Simulation of a coolant jet injected normally into a periodic crossflow is presented. The physical situation simulated represents a periodic module in a coolant hole array with a heated crossflow. A collocated finite difference scheme is used which is fifth-order accurate spatially and second-order accurate temporally. The scheme is based on a fractional step approach and requires the solution of a pressure-Poisson equation. The simulations are obtained for a blowing ratio of 0.25 and a channel Reynolds number of 5600. The simulations reveal the dynamics of several large scale structures including the Counter-rotating Vortex Pair (CVP), the horse-shoe vortex, the shear layer vortex, the wall vortex and the wake vortex. The origins and the interactions of these vortical structures are identified and explored. Also presented are the turbulence statistics and how they relate to the flow structures.

Sharma, Chirdeep↗
NASA NTRS2013

Re-Greening Sahel: 30 Years of Remote Sensing Data and Field Observations (Mali, Niger)

Desertification of the Sahel region has been debated for decades, while the concept of a "re-greening" Sahel appeared with satellite remote sensing data that allowed vegetation monitoring across wide regions and over increasingly long series of years (nowadays 30 years with the GIMMS-3g dataset). However, the scarcity of long-term field observations of vegetation in the Sahel prevents ground validation and deeper analysis of such trends. After assessing the consistency of the new GIMMS-3g NDVI product by comparison to three other AVHRR-NDVI datasets and MODIS NDVI, regional GIMMS-3g NDVI trends over 1981-2011 are analyzed. Trends are found positive and statistically significant almost everywhere in Sahel over the 1981-2011 period. Long-term field observations of the aboveground herbaceous layer mass have been collected within the Gourma region in Mali (1984-2011) and within the Fakara region in western Niger (1994-2011). These observations sample ecosystem and soil diversity, thus enabling estimation of averaged values representative of the Gourma and Fakara. NDVI measurements are found in good agreement with field observations, both over the Gourma and Fakara regions where re-greening and negative trends are observed respectively. A linear regression analysis performed between spatially averaged seasonal NDVI and a weighted average of field measurements explains 59% of the variability for the Gourma region over 1984-2011, and 38% for the Fakara region over 1994-2011. In the Gourma, which is a pastoral region, the re-greening trend is mainly observed over sandy soils, and attests for the ecosystem's resilience to the 1980s' drought, able to react to the more favorable rainfall of the 1990s and 2000s. However, contrasted changes in the landscape's functioning have occurred locally. An increase in erosion and run-off processes in association with decreasing or stable vegetation cover was observed over shallow soils, which occupy 30% of the area. In the agro-pastoral Fakara, the decreasing trends observed both from satellite NDVI and field assessments of herbaceous mass are hardly explained by rainfall. These results give confidence in the dominant positive trends in Sahelian greenness, but indicate that degradation trends can also be observed, both in situ and from satellite time series.

Sahel↗
NASA NTRS2008

Statistical Evaluation of Combined Daily Gauge Observations and Rainfall Satellite Estimations over Continental South America

This paper describes a comprehensive assessment of a new high-resolution, high-quality gauge-satellite based analysis of daily precipitation over continental South America during 2004. This methodology is based on a combination of additive and multiplicative bias correction schemes in order to get the lowest bias when compared with the observed values. Inter-comparisons and cross-validations tests have been carried out for the control algorithm (TMPA real-time algorithm) and different merging schemes: additive bias correction (ADD), ratio bias correction (RAT) and TMPA research version, for different months belonging to different seasons and for different network densities. All compared merging schemes produce better results than the control algorithm, but when finer temporal (daily) and spatial scale (regional networks) gauge datasets is included in the analysis, the improvement is remarkable. The Combined Scheme (CoSch) presents consistently the best performance among the five techniques. This is also true when a degraded daily gauge network is used instead of full dataset. This technique appears a suitable tool to produce real-time, high-resolution, high-quality gauge-satellite based analyses of daily precipitation over land in regional domains.

Vila, Daniel↗
NASA NTRS1991

Effects of satellite data resolution on measuring the space/time variations of surfaces and clouds

The correlated distributions of satellite-measured visible and infrared radiances, caused by spatial and temporal variations in clouds and surfaces, have been found to be characteristic of the major climate regimes and can be described by the attributes of bidimensional and monodimensional histograms and time-composite images. Most of the variability of both the surfaces and clouds is found to occur at scales larger than the minimum resolved by satellite imagery. Since satellite imaging data sets are difficult to analyze because of their large volumes, many studies reduce the volume by various sampling or averaging schemes. The effects of data resolution and sampling on the radiance histogram statistics and on the time-composite image characteristics are examined. In particular, the sampling strategy used by the International Satellite Cloud Climatology Project is tested. This sampling strategy is found to preserve the statistics of smaller cloud variations for most regions, with the exception of very rare events, if they are accumulated over large enough areas (at least 500 km in dimension) and long enough time periods (at least one month).

Seze, Genevieve↗
NASA NTRS1994

On the bimodal distribution of gamma-ray bursts

Kouveliotou et al. recently confirmed that gamma-ray bursts are bimodal in duration. In this paper we compute the statistical properties of the short (less than or = 2 s) and long (greater than 2 s) bursts using a method of analysis that makes no assumption regarding the location of the bursts, whether in the Galaxy or at a cosmological distance. We find the 64 ms channel on Burst and Transient Source Experiment (BATSE) to be more sensitive to short bursts and the 1024 ms channel to be more sensitive to long bursts. We show that all the currently available data are consistent with the simple hypothesis that both short and long bursts have the same spatial distribution and that within each population the sources are standard candles. The rate of short bursts per unit volume is about 40% of the rate of long bursts. Although the durations of short and long gamma-ray bursts span several orders of magnitude and the total energy of a typical short burst is smaller than that of a typical long burst by a factor of about 20, surprisingly the peak luminosities of the two kinds of bursts are equal to within a factor of about 2.

Mao, Shude↗
NASA NTRS2012

Multiscale Studies of the Three-Dimensional Dayside X-Line

We review recent experience from the Cluster, Double Star, and THEMIS missions for lessons that apply to the upcoming Magnetospheric Multiscale Mission (MMS) being developed for launch in 2014. On global scales, simulation and statistical studies lead to mean congurations of dayside reconnection, implying specific relative alignments of the inflow magnetic fields and X-line, with implications for MMS operations designed to maximize the number of close encounters with the diffusion region. At intermediate MHD-to-ion scales, reconstruction of features created by one or two X-lines have developed to the point where data from a cluster of spacecraft can determine their temporal trends and the approximate three-dimensional X-line structure. Recent petascale particle-in-cell (PIC) simulations of reconnection encompass three spatial dimensions with excellent resolution, and make striking predictions of electron scale physics that creates complex interacting flux ropes under component reconnection. High time resolution measurements from MMS will determine the detailed electron scale kinetics embedded within the global and MHDion scale contexts. These developments will lead to the refinement of our three-dimensional multiscale picture of reconnection, yielding improved understanding of the global, MHD, and local physics controlling the onset or quenching, variability, and mean rate of reconnection. This in turn will enable improved predictability of the structural features created by transient reconnection, and their space weather consequences.

Reconnection↗
NASA NTRS2020

Monitoring Water-Related Ecosystems with Earth Observation Data in Support of Sustainable Development Goal (SDG) 6 Reporting

Lack of national data on water-related ecosystems is a major challenge to achieving the Sustainable Development Goal (SDG) 6 targets by 2030. Monitoring surface water extent, wetlands, and water quality from space can be an important asset for many countries in support of SDG 6reporting. We demonstrate the potential for Earth observation (EO) data to support country reporting for SDG Indicator 6.6.1, ‘Change in the extent of water-related ecosystems over time’ and identify important considerations for countries using these data for SDG reporting. The spatial extent of water-related ecosystems, and the partial quality of water within these ecosystems is investigated for seven countries. Data from the Moderate Resolution Imaging Spectroradiometer (MODIS) and Landsat 5, 7, and 8 with Shuttle Radar Topography Mission (SRTM) are used to measure surface water extent at 250 m and 30 m spatial resolution, respectively, in Cambodia, Jamaica, Peru, the Philippines, Senegal, Uganda, and Zambia. The extent of mangroves is mapped at 30 m spatial resolution using Landsat 8 Operational Land Imager (OLI), Sentinel-1, and SRTM data for Jamaica, Peru, and Senegal. Using Landsat 8 and Sentinel 2A imagery, total suspended solids and chlorophyll-a are mapped overtime for a select number of large surface water bodies in Peru, Senegal, and Zambia. All of the EO datasets used are of global coverage and publicly available at no cost. The temporal consistency and long time-series of many of the datasets enable replicability over time, making reporting of change from baseline values consistent and systematic. We find that statistical comparisons between different surface water data products can help provide some degree of confidence for countries during their validation process and highlight the need for accuracy assessments when using EO-based land change data for SDG reporting. We also raise concern that EO data in the context of SDG Indicator 6.6.1reporting may be more challenging for some countries, such as small island nations, than others to use in assessing the extent of water-related ecosystems due to scale limitations and climate variability. Country-driven validation of the EO data products remains a priority to ensure successful data integration in support of SDG Indicator 6.6.1 reporting. Multi-country studies such as this one can be valuable tools for helping to guide the evolution of SDG monitoring methodologies and provide a useful resource for countries reporting on water-related ecosystems. The EO data analyses and statistical methods used in this study can be easily replicated for country-driven validation of EO data products in the future.

Raha Hakimdavar↗
NASA NTRS2000

Applications of Fractal Analytical Techniques in the Estimation of Operational Scale

The observational scale and the resolution of remotely sensed imagery are essential considerations in the interpretation process. Many atmospheric, hydrologic, and other natural and human-influenced spatial phenomena are inherently scale dependent and are governed by different physical processes at different spatial domains. This spatial and operational heterogeneity constrains the ability to compare interpretations of phenomena and processes observed in higher spatial resolution imagery to similar interpretations obtained from lower resolution imagery. This is a particularly acute problem, since longterm global change investigations will require high spatial resolution Earth Observing System (EOS), Landsat 7, or commercial satellite data to be combined with lower resolution imagery from older sensors such as Landsat TM and MSS. Fractal analysis is a useful technique for identifying the effects of scale changes on remotely sensed imagery. The fractal dimension of an image is a non-integer value between two and three which indicates the degree of complexity in the texture and shapes depicted in the image. A true fractal surface exhibits self-similarity, a property of curves or surfaces where each part is indistinguishable from the whole, or where the form of the curve or surface is invariant with respect to scale. Theoretically, if the digital numbers of a remotely sensed image resemble an ideal fractal surface, then due to the self-similarity property, the fractal dimension of the image will not vary with scale and resolution, and the slope of the fractal dimension-resolution relationship would be zero. Most geographical phenomena, however, are not self-similar at all scales, but they can be modeled by a stochastic fractal in which the scaling properties of the image exhibit patterns that can be described by statistics such as area-perimeter ratios and autocovariances. Stochastic fractal sets relax the self-similarity assumption and measure many scales and resolutions to represent the varying form of a phenomenon as the pixel size is increased in a convolution process. We have observed that for images of homogeneous land covers, the fractal dimension varies linearly with changes in resolution or pixel size over the range of past, current, and planned space-borne sensors. This relationship differs significantly in images of agricultural, urban, and forest land covers, with urban areas retaining the same level of complexity, forested areas growing smoother, and agricultural areas growing more complex as small pixels are aggregated into larger, mixed pixels. Images of scenes having a mixture of land covers have fractal dimensions that exhibit a non-linear, complex relationship to pixel size. Measuring the fractal dimension of a difference image derived from two images of the same area obtained on different dates showed that the fractal dimension increased steadily, then exhibited a sharp decrease at increasing levels of pixel aggregation. This breakpoint of the fractal dimension/resolution plot is related to the spatial domain or operational scale of the phenomenon exhibiting the predominant visible difference between the two images (in this case, mountain snow cover). The degree to which an image departs from a theoretical ideal fractal surface provides clues as to how much information is altered or lost in the processes of rescaling and rectification. The measured fractal dimension of complex, composite land covers such as urban areas also provides a useful textural index that can assist image classification of complex scenes.

Emerson, Charles W.↗
NASA NTRS1989

Non-LTE CO, revisited

A more extensive and detailed non-LTE simulation of the Delta v = 1 bands of CO than attempted previously is reported. The equations of statistical equilibrium are formulated for a model molecule containing 10 bound vibrational levels, each split into 121 rotational substates and connected by more than 1000 radiative transitions. Solutions are obtained for self-consistent populations and radiation fields by iterative application of the 'Lambda-operator' to an initial LTE distribution. The formalism is used to illustrate models of the sun and Arcturus. For the sun, negligible departures from LTE are found in either a theoretical radiative-equilibrium photosphere with outwardly falling temperatures in its highest layers or in a semiempirical hot chromosphere that reproduces the spatially averaged emission cores of Ca II H and K. The simulations demonstrate that the puzzling 'cool cores' of the CO Delta V = 1 bands observed in limb spectra of the sun and in flux spectra of Arcturus cannot be explained simply by non-LTE scattering effects.

Ayres, Thomas R.↗
NASA NTRS2018

Constraining the Thickness of Polar Ice Deposits on Mercury Using the Mercury Laser Altimeter and Small Craters in Permanently Shadowed Regions

Radar-bright deposits at the poles of Mercury are located in permanently shadowed regions, which pro- vide thermally stable environments for hosting and retaining water ice on the surface or in the near sub- surface for geologic timescales. While the areal distribution of these radar-bright deposits is well characterized, their thickness, and thus their total mass and volume, remain poorly constrained. Here we derive thickness estimates for selected water-ice deposits using small, simple craters visible within the permanently shadowed, radar-bright deposits. We examine two endmember scenarios: in Case I, these craters predate the emplacement of the ice, and in Case II, these craters postdate the emplacement of the ice. In Case I, we find the difference between estimated depths of the original unfilled craters and the measured depths of the craters to find the estimated infill of material. The average estimated infilled material for 9 craters assumed to be overlain with water ice is ∼41 +30 −14 m, where 1 −σ standard error of the mean is reported as uncertainty. Reported uncertainties are for statistical errors only. Additional systematic uncertainty may stem from georeferencing the images and topographic datasets, from the radial accuracy of the altimeter measurements, or from assumptions in our models including (1) ice is flat in the bowl- shaped crater and (2) there is negligible ice at the crater rims. In Case II, we derive crater excavation depths to investigate the thickness of the ice layer that may have been penetrated by the impact. While the absence of excavated regolith associated with the small craters observed suggests that impacts generally do not penetrate through the ice deposit, the spatial resolution and complex illumination geometry of images may limit the observations. Therefore, it is not possible to conclude whether the small craters in this study penetrate through the ice deposit, and thus Case II does not provide a constraint on the ice thickness. For Mercury’s polar deposits, we argue that Case I of the small craters predating the emplacement of the ice deposits is more likely, given other geologic evidence that suggests that these ice deposits are relatively young. Using the ice thickness estimates from Case I to calculate the total amount of water ice currently contained in Mercury’s polar deposits results in a value of ∼10 14 –10 15 kg. This is equivalent to ∼100–1000 km 3 ice in volume. This volume of water ice is consistent with delivery via micrometeorite bombardment, Jupiter-family comets, or potentially a single impactor.

Deutsch, Ariel N.↗
NASA NTRS2020

Monitoring Water-Related Ecosystems with Earth Observation Data in Support of Sustainable Development Goal (SDG) 6 Reporting

Lack of national data on water-related ecosystems is a major challenge to achieving the Sustainable Development Goal (SDG) 6 targets by 2030. Monitoring surface water extent, wetlands, and water quality from space can be an important asset for many countries in support of SDG 6 reporting. We demonstrate the potential for Earth observation (EO) data to support country reporting for SDG Indicator 6.6.1, ‘Change in the extent of water-related ecosystems over time’ and identify important considerations for countries using these data for SDG reporting. The spatial extent of water-related ecosystems, and the partial quality of water within these ecosystems is investigated for seven countries. Data from the Moderate Resolution Imaging Spectroradiometer (MODIS) and Landsat 5, 7, and 8 with Shuttle Radar Topography Mission (SRTM) are used to measure surface water extent at 250 m and 30 m spatial resolution, respectively, in Cambodia, Jamaica, Peru, the Philippines, Senegal, Uganda, and Zambia. The extent of mangroves is mapped at 30 m spatial resolution using Landsat 8 Operational Land Imager (OLI), Sentinel-1, and SRTM data for Jamaica, Peru, and Senegal. Using Landsat 8 and Sentinel 2A imagery, total suspended solids and chlorophyll-a are mapped over time for a select number of large surface water bodies in Peru, Senegal, and Zambia. All of the EO datasets used are of global coverage and publicly available at no cost. The temporal consistency and long time-series of many of the datasets enable replicability over time, making reporting of change from baseline values consistent and systematic. We find that statistical comparisons between different surface water data products can help provide some degree of confidence for countries during their validation process and highlight the need for accuracy assessments when using EO-based land change data for SDG reporting. We also raise concern that EO data in the context of SDG Indicator 6.6.1 reporting may be more challenging for some countries, such as small island nations, than others to use in assessing the extent of water-related ecosystems due to scale limitations and climate variability. Country-driven validation of the EO data products remains a priority to ensure successful data integration in support of SDG Indicator 6.6.1 reporting. Multi-country studies such as this one can be valuable tools for helping to guide the evolution of SDG monitoring methodologies and provide a useful resource for countries reporting on water-related ecosystems. The EO data analyses and statistical methods used in this study can be easily replicated for country-driven validation of EO data products in the future.

water-related ecosystems; surface water extent; ma↗