Global geoscience data

Dates Available: April 2021 - Present Update Frequency: Twice a day Summary: Landslides are a widespread and often underestimated natural hazard, causing thousands of deaths and significant economic damage each year. They routinely block roads, destroy infrastructure, and disrupt communities worldwide. While intense or prolonged rainfall is the most common landslide trigger, earthquakes and human activities can also cause them. The global Landslide Hazard Assessment for Situational Awareness (LHASA) model provides users with a comprehensive view of landslide hazard in near real-time. Using machine learning, LHASA combines rainfall data from the Global Precipitation Measurement (GPM) satellite with antecedent soil moisture from the Soil Moisture Active Passive (SMAP) satellite to identify areas currently at risk from landslides. The model shows where and when landslides are most probable, then calculates the exposed population and road length within each administrative district, helping users understand both the hazard and potential impacts on communities and infrastructure. To learn more please visit: https://landslides.nasa.gov/ Suggested Use: LHASA 2.1 was created to enable global monitoring of landslide hazard and is not a substitute for local site investigations. Red indicates high hazard and blue indicates low hazard. LHASA nowcast Hazard: "yesterday", "today", and "tomorrow": This map shows the relative probability of landslide occurrence yesterday, today, and tomorrow; respectively, based on rainfall estimates from GPM and forecasts from GEOS-FP. Satellite/Sensor: GPM, SMAP Resolution: 30 arcseconds (~1 kilometer) Credits: NASA GSFC Users are requested to cite the following paper: Stanley, T. A., D. B. Kirschbaum, G. Benz, et al. 2021. "Data-Driven Landslide Nowcasting at the Global Scale." Frontiers in Earth Science, 9: [10.3389/feart.2021.640043]

Global summer (June/July/August) median 6-day interferometric coherence (COH06) in HH polarization from the Global Seasonal Sentinel-1 Interferometric Coherence and Backscatter Data Set. Pixel values in source rasters are the coherence value (ranging from 0 to 1) multiplied by 100. A processing template is included with the service to provide the standard coherence values (0 to 1) along with the original source raster values. The source rasters referenced in this service are available on the Registry of Open Data on AWS: https://registry.opendata.aws/ebd-sentinel-1-global-coherence-backscatter/

The NASA Making Earth System Data Records for Use in Research Environments (MEaSUREs) Combined Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) and Moderate Resolution Imaging Spectroradiometer (MODIS) Emissivity for Land (CAMEL) dataset provides monthly emissivity uncertainty at 0.05 degree (~5 kilometer) resolution (CAM5K30UC). CAM5K30UC is an estimation of total emissivity uncertainty comprising three independent components of variability: temporal, spatial, and algorithm. Each measure of uncertainty is provided for all 13 hinge points of emissivity and each latitude-longitude point. Additional details regarding the methodology are available in the User Guide and Algorithm Theoretical Basis Document (ATBD). Corresponding emissivity values can be found in the CAM5K30EM data product. Provided in the CAM5K30UC product are layers for algorithm uncertainty, spatial uncertainty, temporal uncertainty, total uncertainty, latitude, longitude, spectral wavelength, CAMEL quality, and total uncertainty quality information. Known Issues * The following granules are missing from the product: January, February, and August of 2000; June and July of 2001; March of 2002; December of 2003; July of 2010; and February of 2016.

The Earth Surface Mineral Dust Source Investigation (EMIT) is an Earth Ventures-Instrument (EVI-4) Mission aboard the International Space Station (ISS). EMIT’s prime mission was designed to map surface mineralogy of arid dust source regions using imaging spectroscopy in the visible and short-wave infrared (VSWIR). EMIT uses imaging spectroscopy to take mineralogical measurements of sunlit regions of interest between 52° N latitude and 52° S latitude. During the prime mission, the EMIT team focused on using surface reflectance to resolve absorption features of iron oxides, clays, sulfates, carbonates, and other dust-forming minerals in Earth's dust source regions. In the extended mission, EMIT’s core measurements remain the same, but acquisitions expand to sample all regions observable from the ISS orbit, supporting efforts across the atmosphere, biosphere, cryosphere, geosphere, hydrosphere, and more. An interactive map showing the regions being investigated, current and forecasted data coverage, and additional data resources can be found on the VSWIR Imaging Spectroscopy Interface for Open Science (VISIONS) EMIT Open Data Portal. The EMIT Level 2B Estimated Mineral Identification and Band Depth and Uncertainty (EMITL2BMIN) Version 2 data product provides estimated mineral identification and band depths in a spatially raw, non-orthocorrected format. Each EMITL2BMIN granule contains two Network Common Data Format 4 (NetCDF4) files at a spatial resolution of 60 meters (m): Mineral Identification (EMIT_L2B_MIN) and Mineral Uncertainty (EMIT_L2B_MINUNCERT). The EMIT_L2B_MIN file contains the band depth (the depth of the identified spectral feature) and the identified mineral for each pixel. Two spectral groups, which correspond to different regions of the spectrum, are identified independently and often co-occur. These estimates are generated using the Tetracorder system (code) and are based on (EMITL2ARFL) reflectance values. The EMIT_L2B_MINUNCERT file provides band depth uncertainty estimates calculated using surface Reflectance Uncertainty values from the EMITL2ARFL data product. The band depth uncertainties are presented as standard deviations. The fit score for each mineral identification is also provided as the coefficient of determination (r-squared) of the match between the continuum normalized library reference and the continuum normalized observed spectrum. Associated metadata indicates the name and reference information for each identified mineral, and additional information about aggregating minerals into different categories is available in the emit-sds-l2b GitHub repository and will be available as subsequent data products. The EMITL2BMIN granules include eight core variables: Mineral Identification, Band Depth, Band Depth Uncertainty, and Fit Score for each of the Spectral Groups (Group 1 and Group 2). Additional variables contain geolocation information (geometric lookup table (GLT)-x values, GLT-y values, latitude, longitude, and elevation), as well as reference tables with spectral library records, spectral library sample names, mapped mineral names, spectral group, spectral library, and spectral group index. A browse image that contains Group 1 Band Depth, Group 2 Band Depth, Group 1 Band Depth Uncertainty, and Group 2 Band Depth Uncertainty is included with each granule. Each granule is approximately 75 kilometers (km) by 75 km, nominal at the equator, with some granules at the end of an orbit segment reaching 150 km in length. Disclaimer This product is generated to support the EMIT mission objectives of constraining the sign of dust related radiative forcing. Ten mineral types are the core focus of this work: calcite, chlorite, dolomite, goethite, gypsum, hematite, illite+muscovite, kaolinite, montmorillonite, and vermiculite. A future product will aggregate these results for use in Earth System Models. Additional minerals are included in this product for transparency but were not the focus of this product. Further validation is required to use these additional mineral maps, particularly in the case of resource exploration. Similarly, the separation of minerals with similar spectral features, such as fine-grained goethite and hematite, is an area of active research. The results presented here are an initial offering, but the precise categorization is likely to evolve over time, and the limits of what can and cannot be separated on the global scale is still being explored. The user is encouraged to read the Algorithm Theoretical Basis Document (ATBD) for more details. Known Issues * Data acquisition gap: From September 13, 2022, through January 6, 2023, a power issue outside of EMIT caused a pause in operations. Due to this shutdown, no data were acquired during that timeframe. Outside of this period, regular short-term gaps in coverage are expected depending on the solar and sensor geometry.

Mineral depletion is the ratio of the value of the stock of mineral resources to the remaining reserve lifetime (capped at 25 years). It covers tin, gold, lead, zinc, iron, copper, nickel, silver, bauxite, and phosphate. This indicator is expressed in current prices, meaning no adjustment has been made to account for price changes over time. This indicator is expressed in United States dollars.

The Earth Surface Mineral Dust Source Investigation (EMIT) instrument measures surface mineralogy, targeting the Earth’s arid dust source regions. EMIT is installed on the International Space Station (ISS) and uses imaging spectroscopy to take measurements of the sunlit regions of interest between 52° N latitude and 52° S latitude. An interactive map showing the regions being investigated, current and forecasted data coverage, and additional data resources can be found on the VSWIR Imaging Spectroscopy Interface for Open Science (VISIONS) EMIT Open Data Portal. The EMIT Level 3 Aggregated Mineral Spectral Abundance and Uncertainty (EMITL3ASA) Version 2 data product provides an aggregated mineral spectral abundance of the 10 minerals that are the focus of the EMIT mission. These minerals, referred to as the EMIT-10 minerals, are calcite, chlorite, dolomite, goethite, gypsum, hematite, illite+muscovite, kaolinite, montmorillonite, and vermiculite. The EMITL3ASA granule consists of one Network Common Data Format 4 (netCDF-4) file at a spatial resolution of 0.5 degrees. The data in EMITL3ASA relies heavily on the EMIT L2B Estimated Mineral Identification and Band Depth and Uncertainty (EMITL2BMIN) data. Using the EMITL2BMIN data, aggregated spectral abundance (ASA) and uncertainty is calculated within each 0.5 degree grid cell in the EMITL3ASA product for each of the EMIT-10 minerals. Grainsize was determined to be the strongest contributor to abundance variation, and as such layers calculated using the 2.5 and 97.5 percentile confidence interval of the grainsize are provided for use in uncertainty quantification. The EMITL3ASA data product contains 30 Science Dataset (SDS) layers. There are three layers for each of the EMIT-10 minerals: one layer containing mineral spectral abundance and two layers for uncertainty quantification containing mineral spectral abundance at 2.5 and 97.5 percentile confidence intervals of grainsize. The latitude and longitude layers contain the coordinates for the upper left corner of each pixel. Known Issues * Minor Abundance Estimate Discrepancy. A transcription error in the grain-size median prediction caused a minor discrepancy in the EMITL3ASA Version 2 mineral spectral abundance estimates. The issue caused deviations well within the uncertainty estimates, typically far below 1%. The most affected estimate is calcite, with maximum deviations reaching 2% for a very small number of pixels. Iron oxides are virtually unaffected.

The Earth Surface Mineral Dust Source Investigation (EMIT) instrument measures surface mineralogy, targeting the Earth’s arid dust source regions. EMIT is installed on the International Space Station (ISS) and uses imaging spectroscopy to take mineralogical measurements of the sunlit regions of interest between 52° N latitude and 52° S latitude. An interactive map showing the regions being investigated, current and forecasted data coverage, and additional data resources can be found on the VSWIR Imaging Spectroscopy Interface for Open Science (VISIONS) EMIT Open Data Portal. The EMIT Level 2B Estimated Mineral Identification and Band Depth and Uncertainty (EMITL2BMIN) Version 1 data product provides estimated mineral identification and band depths in a spatially raw, non-orthocorrected format. Each EMITL2BMIN granule contains two Network Common Data Format 4 (NetCDF4) files at a spatial resolution of 60 meters (m): Mineral Identification (EMIT_L2B_MIN) and Mineral Uncertainty (EMIT_L2B_MINUNCERT). The EMIT_L2B_MIN file contains the band depth (the depth of the identified spectral feature) and the identified mineral for each pixel. Two spectral groups, which correspond to different regions of the spectra, are identified independently and often co-occur. These estimates are generated using the Tetracorder system (code) and are based on EMITL2ARFL reflectance values. The EMIT_L2B_MINUNCERT file provides band depth uncertainty estimates calculated using surface Reflectance Uncertainty values from the EMITL2ARFL data product. The band depth uncertainties are presented as standard deviations. The fit score for each mineral identification is also provided as the coefficient of determination (r-squared) of the match between the continuum normalized library reference and the continuum normalized observed spectrum. Associated metadata indicates the name and reference information for each identified mineral, and additional information about aggregating minerals into different categories is available in the emit-sds-l2b repository and will be available as subsequent data products. The EMITL2BMIN data product includes a total of 19 Science Dataset (SDS) layers. There are four layers for each of the Spectral Groups (Group 1 and Group 2): Mineral Identification, Band Depth, Band Depth Uncertainties, and Fit Score. Additional layers consist of geometric lookup table (GLT) x values, GLT y values, latitude, longitude, elevation, associated spectral library record, mineral name, URL for the spectral library description, spectral group, spectral library, and spectral group index. A browse image with Group 1 Band Depth, Group 2 Band Depth, Group 1 Band Depth Uncertainty, and Group 2 Band Depth Uncertainty is also included. Each granule is approximately 75 kilometers (km) by 75 km, nominal at the equator, with some granules at the end of an orbit segment reaching 150 km in length. Disclaimer This product is generated to support the EMIT mission objectives of constraining the sign of dust related radiative forcing. Ten mineral types are the core focus of this work: calcite, chlorite, dolomite, goethite, gypsum, hematite, illite+muscovite, kaolinite, montmorillonite, and vermiculite. A future product will aggregate these results for use in Earth System Models. Additional minerals are included in this product for transparency but were not the focus of this product. Further validation is required to use these additional mineral maps, particularly in the case of resource exploration. Similarly, the separation of minerals with similar spectral features, such as a fine-grained goethite and hematite, is an area of active research. The results presented here are an initial offering, but the precise categorization is likely to evolve over time, and the limits of what can and cannot be separated on the global scale is still being explored. The user is encouraged to read the Algorithm Theoretical Basis Document (ATBD) for more details. Known Issues * Data acquisition gap: From September 13, 2022, through January 6, 2023, a power issue outside of EMIT caused a pause in operations. Due to this shutdown, no data were acquired during that timeframe.

The Earth Surface Mineral Dust Source Investigation (EMIT) instrument measures surface mineralogy, targeting the Earth’s arid dust source regions. EMIT is installed on the International Space Station (ISS) and uses imaging spectroscopy to take mineralogical measurements of the sunlit regions of interest between 52° N latitude and 52° S latitude. An interactive map showing the regions being investigated, current and forecasted data coverage, and additional data resources can be found on the VSWIR Imaging Spectroscopy Interface for Open Science (VISIONS) EMIT Open Data Portal. The EMIT Level 3 Aggregated Mineral Spectral Abundance and Uncertainty (EMITL3ASA) Version 1 data product provides an aggregated mineral spectral abundance of the 10 minerals that are the focus of the EMIT mission. These minerals, referred to as the EMIT-10 minerals, are calcite, chlorite, dolomite, goethite, gypsum, hematite, illite+muscovite, kaolinite, montmorillonite, and vermiculite. The EMITL3ASA granule consists of one network Common Data Format 4 (netCDF-4) file at a spatial resolution of 0.5 degrees. The data in EMITL3ASA relies heavily on the EMIT L2B Estimated Mineral Identification and Band Depth and Uncertainty (EMITL2BMIN) data. Using the EMITL2BMIN data, aggregated spectral abundance (ASA) is calculated for each of the EMIT-10 minerals as the simple average of relevant 60 m pixels within each 0.5 degree grid cell in the EMITL3ASA product, after controlling for the estimated fractional cover of bare soil within the pixel. The EMITL3ASA data product contains 22 Science Dataset (SDS) layers. There are two layers for each of the EMIT-10 minerals: mineral spectral abundance and mineral spectral abundance uncertainty. The latitude and longitude layers contain the coordinates for the upper left corner of each pixel. Known Issues * The current version of the spectral unmixing algorithm may retrieve spuriously high non-photosynthetic vegetation values over bare playas. Algorithmic fixes are underway and will be integrated during the first data reprocessing cycle. As such, some bare playas are excluded from the current L3 aggregation. * Spectral abundance is a measure of optical abundance, not of mass fraction. Conversion to mass or volume fraction requires leverage on particle grain size, which is not incorporated into the current model. Given this limitation, this product should not be used directly as a measure of mass fraction.

Global Seasonal Sentinel-1 Interferometric Coherence and Backscatter: mean amplitude of radiometrically terrain-corrected gamma-0 backscatter (AMP) values for September/October/November in HH polarization. Pixel values in source rasters are stored as digital numbers (DN). Processing templates are included with the service to provide the power and dB values along with the original DN values. The power value is calculated using the formula DN ^ 2 / 199526231, and the dB value is calculated using the formula 20 x log10(DN) - 83. The source rasters referenced in this service are available on the Registry of Open Data on AWS: https://registry.opendata.aws/ebd-sentinel-1-global-coherence-backscatter/

Global Seasonal Sentinel-1 Interferometric Coherence and Backscatter: mean amplitude of radiometrically terrain-corrected gamma-0 backscatter (AMP) values for March/April/May in VV polarization. Pixel values in source rasters are stored as digital numbers (DN). Processing templates are included with the service to provide the power and dB values along with the original DN values. The power value is calculated using the formula DN ^ 2 / 199526231, and the dB value is calculated using the formula 20 x log10(DN) - 83. The source rasters referenced in this service are available on the Registry of Open Data on AWS: https://registry.opendata.aws/ebd-sentinel-1-global-coherence-backscatter/

The Global Assessment of Land Degradation and Improvement (GLADA) project (2006–2009) was part of the GEF–UNEP–FAO program Land Degradation in Drylands. It utilized remote sensing data to identify areas experiencing land degradation as well as regions where degradation had been halted or reversed. The study relied on analyses of vegetation greenness using the Normalized Difference Vegetation Index (NDVI) as a proxy for net primary productivity, adjusted for the effects of climate variability on biomass through rain-use efficiency and energy-use efficiency. Biomass represents an integrated measure of biological productivity, and deviations from the local norm can serve as indicators of land degradation or improvement. Changes in biomass can be monitored via remote sensing of NDVI—the difference between reflected near-infrared and visible wavebands divided by their sum. NDVI is strongly and linearly correlated with the fraction of photosynthetically active radiation absorbed by vegetation, as well as with vegetation cover and above-ground net primary productivity. Baseline norms can be established by stratifying land areas based on climate, soil, terrain, and land use or vegetation type. Deviations from these norms may then be assessed regionally and aggregated globally to enable universal comparisons. Although the GLADA project concluded in 2009, its datasets and maps have been periodically updated as new remote sensing and climate data have become available, extending coverage to approximately 2021. The GLADA dataset comprises two primary raster layers presented in percentage: (1) global land degradation 1981-2021 and (2) global land improvement 1981-2021. Further details about the data can be found in the associated metadata and project documentation.

Global Seasonal Sentinel-1 Interferometric Coherence and Backscatter: 12-day median coherence for September/October/November in HH polarization. Pixel values in source rasters are the coherence value (ranging from 0 to 1) multiplied by 100. A processing template is included with the service to provide the standard coherence values (0 to 1) along with the original source raster values. The source rasters referenced in this service are available on the Registry of Open Data on AWS: https://registry.opendata.aws/ebd-sentinel-1-global-coherence-backscatter/

Tectonic plates divide up the Earth’s crust. Earthquakes and volcanic activity are mostly concentrated along the boundaries of these plates. Many earthquakes happen around the mid-ocean ridges and the major faults that occur at the plates’ boundaries.

Global summer (June/July/August) median 6-day interferometric coherence (COH06) in VV polarization from the Global Seasonal Sentinel-1 Interferometric Coherence and Backscatter Data Set. Pixel values in source rasters are the coherence value (ranging from 0 to 1) multiplied by 100. A processing template is included with the service to provide the standard coherence values (0 to 1) along with the original source raster values. The source rasters referenced in this service are available on the Registry of Open Data on AWS: https://registry.opendata.aws/ebd-sentinel-1-global-coherence-backscatter/

Global spring (March/April/May) median 6-day interferometric coherence (COH06) in HH polarization from the Global Seasonal Sentinel-1 Interferometric Coherence and Backscatter Data Set. Pixel values in source rasters are the coherence value (ranging from 0 to 1) multiplied by 100. A processing template is included with the service to provide the standard coherence values (0 to 1) along with the original source raster values. The source rasters referenced in this service are available on the Registry of Open Data on AWS: https://registry.opendata.aws/ebd-sentinel-1-global-coherence-backscatter/

- This data set delineates peatlands and other organic soils globally using five layers. Miettinen et al. 2016 was used for Indonesia and Malaysia, Hastie et al. 2022 was used in lowland Peru, Crezee et al. 2022 was used in the Congo basin, and Gumbricht et al. 2017 was used for all land between 40 degrees north and 60 degrees south (including areas covered by the aforementioned data sets). Xu et al. 2018 was used for all land above 40 degrees north. Miettinen et al. 2016 and Xu et al. 2018 were rasterized to ~30x30 m resolution while Gumbricht et al. 2017, Crezee et al. 2022, and Hastie et al. 2022 were resampled from their native resolutions to ~30x30 m resolution in order to align with the Global Forest Change maps from Hansen et al. 2013. All layers were combined, i.e. Gumbricht et al. 2017 was also used in Indonesia/Malaysia, the Peruvian Amazon, and the Congo basin. All data sources have different methods for peatland delineation, which are described in their original publications. - Crezee, B. et al. Mapping peat thickness and carbon stocks of the central Congo Basin using field data. Nature Geoscience 15: 639-644 (2022). https://www.nature.com/articles/s41561-022-00966-7. Data downloaded from https://congopeat.net/maps/, using classes 4 and 5 only (peat classes). - Gumbricht, T. et al. An expert system model for mapping tropical wetlands and peatlands reveals South America as the largest contributor. Glob. Change Biol. 23, 3581–3599 (2017). https://onlinelibrary.wiley.com/doi/full/10.1111/gcb.13689 - Hastie, A. et al. Risks to carbon storage from land-use change revealed by peat thickness maps of Peru. Nature Geoscience 15: 369-374 (2022). https://www.nature.com/articles/s41561-022-00923-4 - Miettinen, J., Shi, C. & Liew, S. C. Land cover distribution in the peatlands of Peninsular Malaysia, Sumatra and Borneo in 2015 with changes since 1990. Glob. Ecol. Conserv. 6, 67– 78 (2016). https://www.sciencedirect.com/science/article/pii/S2351989415300470 - Xu et al. PEATMAP: Refining estimates of global peatland distribution based on a meta-analysis. CATENA 160: 134-140 (2018). https://www.sciencedirect.com/science/article/pii/S0341816217303004 Delineates extent of peatlands

The NASA Making Earth System Data Records for Use in Research Environments (MEaSUREs) Combined Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) and Moderate Resolution Imaging Spectroradiometer (MODIS) Emissivity for Land (CAMEL) data suite has been expanded to include a monthly global coefficient climatology product (CAM5K30CFCLIM). The product is provided at 0.05 degree (~5 kilometer) resolution. The CAMEL Principal Components Analysis (PCA) input coefficients utilized in the CAMEL high spectral resolution (HSR) algorithm are provided in the CAM5K30CFCLIM data product. This HSR algorithm is accessible in both MATLAB and FORTRAN programming languages, and it corresponds with the temporally equivalent CAM5K30EMCLIM emissivity data product. The HSR emissivity spectra for the same month each year and each unique combination of lab dataset version and number of Principal Components (PC)s are first computed independently and then combined via a weighted average. The weighted average over 2003 through 2021 (19 years) defines the weights by the number of samples from each unique combination. Additional details regarding the methodology are available in the User Guide and Algorithm Theoretical Basis Document (ATBD). Provided in the CAM5K30CFCLIM product are variables for PCA coefficients, the weights and sample numbers of the climatology coefficients used in the average calculation, sets of the number of PCA coefficients, laboratory version numbers, latitude, longitude, and land flag information. PCA coefficients depend on the lab PC data version and the number of PCs used.

The Earth Surface Mineral Dust Source Investigation (EMIT) instrument measures surface mineralogy, targeting the Earth’s arid dust source regions. EMIT is installed on the International Space Station (ISS). EMIT uses imaging spectroscopy to take mineralogical measurements of the sunlit regions of interest between 52° N latitude and 52° S latitude. An interactive map showing the regions being investigated, current and forecasted data coverage, and additional data resources can be found on the VSWIR Imaging Spectroscopy Interface for Open Science (VISIONS): EMIT Open Data Portal. The EMIT Level 1B Corrected Spacecraft Attitude and Ephemeris (EMITL1BATT) Version 1 data product provides both corrected and uncorrected attitude quaternions and spacecraft ephemeris data obtained from the ISS, including Earth-centered inertial (ECI) position and velocity, and associated time elements. The data are provided in 1 second intervals, and each product file contains vectors from the duration of the orbit. The time elements are copied from the ISS raw data. The data for each EMITL1BATT granule are delivered in a single Network Common Data Format 4 (netCDF-4) file. Known Issues * Data acquisition gap: From September 13, 2022, through January 6, 2023, a power issue outside of EMIT caused a pause in operations. Due to this shutdown, no data were acquired during that timeframe.

Global Seasonal Sentinel-1 Interferometric Coherence and Backscatter: mean amplitude of radiometrically terrain-corrected gamma-0 backscatter (AMP) values for March/April/May in HH polarization. Pixel values in source rasters are stored as digital numbers (DN). Processing templates are included with the service to provide the power and dB values along with the original DN values. The power value is calculated using the formula DN ^ 2 / 199526231, and the dB value is calculated using the formula 20 x log10(DN) - 83. The source rasters referenced in this service are available on the Registry of Open Data on AWS: https://registry.opendata.aws/ebd-sentinel-1-global-coherence-backscatter/

“Mining concession” refers to an area allocated by a government or other body for the extraction of minerals. The terminology for these areas varies from country to country. “Concession” is used as a general term for licenses, permits, or other contracts that confer rights to private companies to manage and extract minerals from public lands; terminology varies at the national level, however, and includes mineral or mining "permits," "tenures," "licenses," and other terms. This data set displays mining concessions as a single layer assembled by aggregating concession data for multiple countries. The data may come from government agencies, NGOs, or other organizations and vary by date and source. Only active or available concessions are included in this layer. Inactive or expired concessions are excluded as defined by the dataset source. As available, additional data source information is linked below: - Brazil - Cameroon - Cambodia - Colombia - Democratic Republic of the Congo - Malaysia - Peru - Suriname - [Zambia](www.znsdi.net) If you are aware of concession data for additional countries, please email us [here](mailto:gnw@wri.org).  Displays boundaries of areas allocated by governments to companies for extraction of minerals

The NASA Making Earth System Data Records for Use in Research Environments (MEaSUREs) Combined Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) and Moderate Resolution Imaging Spectroradiometer (MODIS) Emissivity for Land (CAMEL) dataset provides monthly emissivity uncertainty at 0.05 degree (~5 kilometer) resolution (CAM5K30UC). CAM5K30UC is an estimation of total emissivity uncertainty, comprising 3 independent components of variability: temporal, spatial, and algorithm. Each measure of uncertainty is provided for all 13 hinge points of emissivity and each latitude-longitude point. Additional details regarding the methodology are available in the User Guide and Algorithm Theoretical Basis Document (ATBD). Corresponding emissivity values can be found in the CAM5K30EM data product. Provided in the CAM5K30UC product are layers for algorithm uncertainty, spatial uncertainty, temporal uncertainty, total uncertainty, latitude, longitude, spectral wavelength, CAMEL quality, and total uncertainty quality information.

The Earth Surface Mineral Dust Source Investigation (EMIT) is an Earth Ventures-Instrument (EVI-4) Mission aboard the International Space Station (ISS). EMIT’s prime mission was designed to map surface mineralogy of arid dust source regions using imaging spectroscopy in the visible and short-wave infrared (VSWIR) range. EMIT uses imaging spectroscopy to take mineralogical measurements of sunlit regions of interest between 52° N latitude and 52° S latitude. During the prime mission, the EMIT team focused on using surface reflectance to resolve absorption features of iron oxides, clays, sulfates, carbonates, and other dust-forming minerals in Earth's dust source regions. In the extended mission, EMIT’s core measurements remain the same, but acquisitions expand to sample all regions observable from the ISS orbit, supporting efforts across the atmosphere, biosphere, cryosphere, geosphere, hydrosphere, and more. An interactive map showing the regions being investigated, current and forecasted data coverage, and additional data resources can be found on the VSWIR Imaging Spectroscopy Interface for Open Science (VISIONS) EMIT Open Data Portal. The EMIT L2A Masks 60 m (EMITL2AMASK) Version 3 data product provides a series of masks designed to facilitate the identification of clear and reliable observations of the Earth’s surface in a spatially raw, non-orthocorrected format. Each EMITL2AMASK granule consists of one Network Common Data Format Version 4 (netCDF-4) file at a spatial resolution of 60 meters (m), along with a corresponding browse image. The data file (EMIT_L2A_MASK) contains seven mask bands: five binary flag bands and two data bands. The binary flag bands identify the presence of clouds, dense cirrus clouds, and water bodies, which indicate if a pixel should be excluded from analysis. The data bands provide values that describe the probability of cloud presence and the distance to the nearest cloud pixel. The netCDF-4 file holds a location group containing geometric lookup tables (GLT) which are orthorectified images that provide relative x- and y-reference locations from the raw scene, enabling projection of the data. In addition to the GLT layers, the file also contains latitude, longitude, and elevation variables. The latitude and longitude coordinates are based on the World Geodetic System 84 (WGS-84) ellipsoid. Elevation data included in each granule are sourced from Shuttle Radar Topography Mission (SRTM) v3 data and resampled to match EMIT’s 60 m spatial resolution. Each granule is approximately 75 kilometers (km) by 75 km nominal at the equator with some reaching 150 km in length at the end of an orbit segment. Known Issues * Data acquisition gap: From September 13, 2022, through January 6, 2023, a power issue on the ISS caused a pause in EMIT operations. Due to this shutdown, no data were acquired during that timeframe. Outside of this period, regular short-term gaps in coverage are expected depending on the solar and sensor geometry.

The Terra Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) Global Emissivity Dataset (GED) land surface temperature and emissivity (LST&E) data products are generated using the ASTER Temperature Emissivity Separation (TES) algorithm with a Water Vapor Scaling (WVS) atmospheric correction method using Moderate Resolution Imaging Spectroradiometer (MODIS) MOD07_L2 atmospheric profiles and the MODerate Spectral resolution TRANsmittance (MODTRAN 5.2) radiative transfer model. This dataset is computed from all clear-sky pixels of ASTER scenes acquired from 2000 through 2008. The National Aeronautics and Space Administration’s (NASA) Jet Propulsion Laboratory (JPL), California Institute of Technology, developed the ASTER GED product. When using this data product in a publication, please include the citations listed under the Publications header on the Documents and Resources tab in addition to the data product citation provided below. Known Issues * Known issues are provided in Section 4 of the User Guide.

Global Seasonal Sentinel-1 Interferometric Coherence and Backscatter: 12-day median coherence for June/July/August in HH polarization. Pixel values in source rasters are the coherence value (ranging from 0 to 1) multiplied by 100. A processing template is included with the service to provide the standard coherence values (0 to 1) along with the original source raster values. The source rasters referenced in this service are available on the Registry of Open Data on AWS: https://registry.opendata.aws/ebd-sentinel-1-global-coherence-backscatter/

Date of Image: 2/10/2023 Date of Next Image: Unknown Summary: 2/10/2023 (ARIA, Copernicus Sentinel-1) The Advanced Rapid Imaging and Analysis (ARIA) team at NASA's Jet Propulsion Laboratory and California Institute of Technology in Southern California created this Damage Proxy Map (DPM) depicting areas that are likely damaged by the large earthquakes (Feb. 06, 2023) in Turkiye (Turkey) and Syria. The map was derived from synthetic aperture radar (SAR) images on Feb. 10, 2023 by the Copernicus Sentinel-1 satellites operated by the European Space Agency (ESA). The pre-event images were taken from Sep. 19, 2022 to Jan. 29, 2022). Suggested Use: Standard Version: The color variation from pale yellow to red indicates increasingly more significant surface change (drop in radar reflection coherence). Preliminary validation was done by comparing with high-resolution optical imagery and media reports. NOTE: This damage proxy map could be used as a guidance to identify damaged areas, and may be less reliable over vegetated and mountainous areas. Scattered pixels over vegetated areas may be false positives, and a lack of colored pixels over vegetated areas may not mean no damage. Satellite/Sensor: Copernicus Sentinel-1 Synthetic Aperture Radar (SAR) Resolution: 30 meters Credits: Sentinel-1 data were accessed through the Copernicus Open Hub and the Alaska Satellite Facility server. The product contains modified Copernicus Sentinel data (2022-2023), processed by ESA and analyzed by the NASA-JPL/Caltech ARIA team in collaboration with Earth Observatory of Singapore - Remote Sensing Lab (EOS-RS). Part of the funding was provided by NASA's Earth Applied Sciences Disasters Program. Service URL: WMS Endpoint: Data Download: https://aria-share.jpl.nasa.gov/20230206_Turkey_EQ/DPM/

Global Seasonal Sentinel-1 Interferometric Coherence and Backscatter: 12-day median coherence for March/April/May in HH polarization. Pixel values in source rasters are the coherence value (ranging from 0 to 1) multiplied by 100. A processing template is included with the service to provide the standard coherence values (0 to 1) along with the original source raster values. The source rasters referenced in this service are available on the Registry of Open Data on AWS: https://registry.opendata.aws/ebd-sentinel-1-global-coherence-backscatter/

202611_nisar_LOSDisplacement

Dates of Images: 5/11/2024 Summary: The NASA GSFC landslides team produced this landslide proxy heatmap from Sentinel-1 imagery. Potential landslides were detected by calculating the change in the backscatter coefficient before and after the triggering event using the log ratio approach (Iratio). The Iratio is generated by subtracting median pre- and post-event Radiometrically Terrain Corrected (RTC) gamma0 backscatter in decibel scale at 10 m resolution obtained from the Alaska Sar Facility’s Hybrid Pluggable Processing Pipeline (HyP3). The likely landslide pixels are identified using 99th percentile Iratio threshold considering areas greater than 10-degree in slope and not affected by radar shadow and layover effects. A heatmap is generated using identified landslide pixels for visualization ease. Pre-event imagery = median imagery generated using images from 09/14/2023, 09/26/2023 Post-event imagery = 05/11/2024 This map should be used as a guide to identify areas likely affected by landslides. This is a rapid response product. We have not done any form of manual verification or corrections to remove false positives. Please see the slope and shadow layover mask item for areas not considered in this analysis. Suggested Use: The red and yellow areas indicate potential zones of dense landsliding. False positives related to natural and human-made ground surface change, including but not limited to deformation from mining, construction, deforestation, agriculture, flooding, snow cover, and changes in reservoir water levels can also be within the red and yellow areas. Satellite/Sensor/Resolution: Synthetic Aperture Radar on European Space Agency's (ESA) Copernicus Sentinel-1 satellite, 10 meters Credits: NASA GSFC landslides team, Copernicus Sentinel-1 data Esri REST Endpoint: See URL to the right. WMS Endpoint: https://gis.earthdata.nasa.gov/portal/services/DISASTERS_EX2602_202405_FLOOD_BRAZIL/ex2602_sentinel1_landslide_heatmap/ImageServer/WMSServer

Global winter (December/January/February) median 6-day interferometric coherence (COH06) in HH polarization from the Global Seasonal Sentinel-1 Interferometric Coherence and Backscatter Data Set. Pixel values in source rasters are the coherence value (ranging from 0 to 1) multiplied by 100. A processing template is included with the service to provide the standard coherence values (0 to 1) along with the original source raster values. The source rasters referenced in this service are available on the Registry of Open Data on AWS: https://registry.opendata.aws/ebd-sentinel-1-global-coherence-backscatter/

Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) Global Emissivity Dataset (GED) land surface temperature and emissivity (LST&E) data products are generated using the ASTER Temperature Emissivity Separation (TES) algorithm with a Water Vapor Scaling (WVS) atmospheric correction method using Moderate Resolution Imaging Spectroradiometer (MODIS) MOD07_L2 atmospheric profiles and the MODerate spectral resolution TRANsmittance (MODTRAN 5.2 radiative transfer model). This dataset is computed from all clear-sky pixels of ASTER scenes acquired from 2000 through 2008. AG100 data are available globally at spatial resolution of 100 meters. The National Aeronautics and Space Administration’s (NASA) Jet Propulsion Laboratory (JPL), California Institute of Technology, developed the ASTER GED product. When using this data product in a publication, please include the citations listed under the Publications header on the Documents and Resources tab in addition to the data product citation provided below. Known Issues * Known issues are provided in Section 4, starting on page 8 of the User Guide.

Mineral rents are the difference between the value of production for a stock of minerals at world prices and their total costs of production. Minerals included in the calculation are tin, gold, lead, zinc, iron, copper, nickel, silver, bauxite, and phosphate.

The NASA Making Earth System Data Records for Use in Research Environments (MEaSUREs) Combined Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) and Moderate Resolution Imaging Spectroradiometer (MODIS) Emissivity for Land (CAMEL) dataset provides monthly coefficients at 0.05 degree (~5 kilometer) resolution (CAM5K30CF). The CAMEL Principal Components Analysis (PCA) input coefficients utilized in the CAMEL high spectral resolution (HSR) algorithm are provided in the CAM5K30CF data product and are congruent to the temporally equivalent CAM5K30EM emissivity data product. Additional details regarding the methodology are available in the User Guide and Algorithm Theoretical Basis Document (ATBD). Provided in the CAM5K30CF product are layers for PCA coefficients, number of PCA coefficients, laboratory version, snow fraction derived from MODIS Snow Cover data (MOD10), latitude, longitude, and the CAMEL quality information. PCA coefficients are dependent on the version of lab Principal Component (PC) data and the number of PCs used. Known Issues * The following granules are missing from the product: January, February, and August of 2000; June and July of 2001; March of 2002; December of 2003; July of 2010; and February of 2016.

Global Seasonal Sentinel-1 Interferometric Coherence and Backscatter: mean amplitude of radiometrically terrain-corrected gamma-0 backscatter (AMP) values for June/July/August in HV polarization. Pixel values in source rasters are stored as digital numbers (DN). Processing templates are included with the service to provide the power and dB values along with the original DN values. The power value is calculated using the formula DN ^ 2 / 199526231, and the dB value is calculated using the formula 20 x log10(DN) - 83. The source rasters referenced in this service are available on the Registry of Open Data on AWS: https://registry.opendata.aws/ebd-sentinel-1-global-coherence-backscatter/

The Earth Surface Mineral Dust Source Investigation (EMIT) is an Earth Ventures-Instrument (EVI-4) Mission aboard the International Space Station (ISS). EMIT’s prime mission was designed to map surface mineralogy of arid dust source regions using imaging spectroscopy in the visible and short-wave infrared (VSWIR) range. EMIT uses imaging spectroscopy to take mineralogical measurements of sunlit regions of interest between 52° N latitude and 52° S latitude. During the prime mission, the EMIT team focused on using surface reflectance to resolve absorption features of iron oxides, clays, sulfates, carbonates, and other dust-forming minerals in Earth's dust source regions. In the extended mission, EMIT’s core measurements remain the same, but acquisitions expand to sample all regions observable from the ISS orbit, supporting efforts across the atmosphere, biosphere, cryosphere, geosphere, hydrosphere, and more. An interactive map showing the regions being investigated, current and forecasted data coverage, and additional data resources can be found on the VSWIR Imaging Spectroscopy Interface for Open Science (VISIONS) EMIT Open Data Portal. The EMIT Level 2A Surface Reflectance and Uncertainty (EMITL2ARFL) Version 2 data product provides surface reflectance data in a spatially raw, non-orthocorrected format. Each EMITL2ARFL granule consists of two Network Common Data Format Version 4 (netCDF-4) files at a spatial resolution of 60 meters (m): Reflectance (EMIT_L2A_RFL) and Reflectance Uncertainty (EMIT_L2A_RFLUNCERT). The Reflectance file contains surface reflectance maps of 285 bands with a spectral range of 381-2493 nanometers (nm) at a spectral resolution of ~7.5 nm. These are all contained within a single science dataset layer/variable. Aerosol optical thickness and water vapor values are also included within their own separate variables. The Reflectance Uncertainty file contains uncertainty estimates captured as per-pixel, per-band, posterior standard deviations. Each netCDF-4 file holds a location group containing geometric lookup tables (GLT) which are orthorectified images that provide relative x- and y-reference locations from the raw scene, enabling projection of the data. In addition to the GLT layers, the file also contains latitude, longitude, and elevation variables. The latitude and longitude coordinates are based on the World Geodetic System 84 (WGS-84) ellipsoid. Elevation data included in each granule are sourced from Shuttle Radar Topography Mission (SRTM) v3 data and resampled to match EMIT’s 60 m spatial resolution. Each granule is approximately 75 kilometers (km) by 75 km, nominal at the equator, with some reaching approximately 150 km in length at the end of an orbit segment. Known Issues: * Data acquisition gap: From September 13, 2022, through January 6, 2023, a power issue on the ISS caused a pause in EMIT operations. Due to this shutdown, no data were acquired during that timeframe. Outside of this period, regular short-term gaps in coverage are expected depending on the solar and sensor geometry.

Global Seasonal Sentinel-1 Interferometric Coherence and Backscatter: 12-day median coherence for December/January/February in HH polarization. Pixel values in source rasters are the coherence value (ranging from 0 to 1) multiplied by 100. A processing template is included with the service to provide the standard coherence values (0 to 1) along with the original source raster values. The source rasters referenced in this service are available on the Registry of Open Data on AWS: https://registry.opendata.aws/ebd-sentinel-1-global-coherence-backscatter/

Global Seasonal Sentinel-1 Interferometric Coherence and Backscatter: mean amplitude of radiometrically terrain-corrected gamma-0 backscatter (AMP) values for September/October/November in VV polarization. Pixel values in source rasters are stored as digital numbers (DN). Processing templates are included with the service to provide the power and dB values along with the original DN values. The power value is calculated using the formula DN ^ 2 / 199526231, and the dB value is calculated using the formula 20 x log10(DN) - 83. The source rasters referenced in this service are available on the Registry of Open Data on AWS: https://registry.opendata.aws/ebd-sentinel-1-global-coherence-backscatter/