Data Solutions • High Resolution Mapping
High Resolution Map Index
Global 1 km spatial raster layers for ISO 9223 corrosion rates, localized industrial emissions (LE v4), atmospheric pollutants, climate variables, and coastal terrain exposure.
Primary ISO 9223 Corrosion Layers
16 layers| Layer Name & Identifier | Description | Units | Grid | Action |
|---|---|---|---|---|
ISO9223_Steel_2020_2024_1km
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This dataset represents the modeled first-year atmospheric corrosion rate of carbon steel based on the ISO 9223 atmospheric corrosivity framework. | µm/yr | 1 km | View Map → |
ISO9223_zinc_2020_2024_1km
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This dataset represents the modeled first-year atmospheric corrosion rate of zinc based on the ISO 9223 atmospheric corrosivity framework. Corrosion rates were calculated using five-year climatological averages (2020–2024). | µm/yr | 1 km | View Map → |
ISO9223_Aluminum_2020_2024_1km
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This dataset represents the modeled first-year atmospheric corrosion rate of aluminum based on the ISO 9223 atmospheric corrosivity framework. Corrosion rates were calculated using five-year climatological averages (2020–2024). | µm/yr | 1 km | View Map → |
ISO9223_Copper_2020_2024_1km
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This dataset represents the modeled first-year atmospheric corrosion rate of copper based on the ISO 9223 atmospheric corrosivity framework. Corrosion rates were calculated using five-year climatological averages (2020–2024). | µm/yr | 1 km | View Map → |
BLDFIE_M_sl7_1km_ll
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Bulk density of the fine earth fraction (<2 mm) expressed in kg/m³, representing the oven-dry mass of soil per unit volume at standard depth intervals. This property influences soil porosity, water retention, and subsurface transport processes and is a key parameter in modeling electrical resistivity and corrosion behavior. | kg/m³ | 1 km | View Map → |
BLDFIE_M_sl1_1km_ll
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ulk density of the fine earth fraction (<2 mm) expressed in kg/m³, representing the oven-dry mass of soil per unit volume at standard depth intervals. This property influences soil porosity, water retention, and subsurface transport processes and is a key parameter in modeling electrical resistivity and corrosion behavior. | kg/m³ | 1 km | View Map → |
TAXNWRB_corrosion_risk_5class_1km
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This layer represents a global baseline classification of soil corrosivity derived from soil environment conditions using the ISRIC SoilGrids WRB Soil Taxonomy (TAXNWRB) dataset. Original WRB soil classes were reclassified into pipeline-relevant soil environment categories and further translated into a standardized corrosion risk scale (1–5). | Index 1-5 | 1 km | View Map → |
apparent_soil_resistivity_P10101
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This raster represents predicted average soil resistivity (ohm·cm) within the 0–2 meter depth interval, corresponding to typical pipeline burial depths. Values are generated using a Random Forest model trained on field measurements collected with the Wenner four-pin method, incorporating soil properties (sand, silt, clay, water capacity) and climatic variables (temperature, humidity, and time-of-wetness). The raster provides a spatially continuous estimate of subsurface resistivity for regional corrosion risk screening and engineering analysis. | ohm-cm | 1 km | View Map → |
iso9223_al_2019_2023
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In ISO 9223, the corrosion rate for Aluminum is classified based on the atmospheric corrosivity categories. These categories describe the annual loss of material thickness in micrometers per year (µm/year) for uncoated Aluminum exposed to the environment. | µm/year | 1 km | View Map → |
copper_iso9223_2019_2023
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In ISO 9223, the corrosion rate for Copper is classified based on the atmospheric corrosivity categories. These categories describe the annual loss of material thickness in micrometers per year (µm/year) for uncoated carbon steel exposed to the environment. | µm/year | 1 km | View Map → |
iso9223_steel_2019_2023
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In ISO 9223, the corrosion rate for steel is classified based on the atmospheric corrosivity categories. These categories describe the annual loss of material thickness in micrometers per year (µm/year) for uncoated carbon steel exposed to the environment. | µm/year | 1 km | View Map → |
iso9223_zinc_2019_2023
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In ISO 9223, the corrosion rate for Zinc is classified based on the atmospheric corrosivity categories. These categories describe the annual loss of material thickness in micrometers per year (µm/year) for uncoated carbon steel exposed to the environment. | µm/Year | 1 km | View Map → |
Pipeline_Hydrologic_Exposure_Score_1_100_v14_final
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The Pipeline Hydrologic Exposure Score (1–100) raster provides a continuous global assessment of hydrologic conditions relevant to buried pipeline corrosion risk. The score integrates terrain position, drainage accumulation, proximity to rivers, slope, and precipitation to estimate the likelihood of water accumulation, soil saturation, and persistent wet conditions. | Unitless (Normalizd Index 1–100) | 1 km | View Map → |
PHIHOX_M_sl7_1km_ll
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Soil pH measured in a water solution (**pH H₂O x 10**), representing the acidity or alkalinity of the soil. This parameter is critical for understanding chemical conditions that influence nutrient availability, metal mobility, and corrosion behavior. | pH (unitless, logarithmic scale) | 1 km | View Map → |
PHIHOX_M_sl1_1km_ll
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Soil pH measured in a water solution (**pH H₂O**), representing the acidity or alkalinity of the soil. This parameter is critical for understanding chemical conditions that influence nutrient availability, metal mobility, and corrosion behavior. | pH (unitless, logarithmic scale) | 1 km | View Map → |
tow_2019_2023
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Hours per year (h/year)Explanation:Time of Wetness (TOW) refers to the duration when a surface is wet due to moisture, such as dew, rainfall, or high relative humidity (RH ≥ 80%) combined with a temperature above 0°C (32°F).TOW is an important factor in determining the corrosivity of an environment, as prolonged wetness accelerates the electrochemical processes involved in corrosion. | h/year | 1 km | View Map → |
Local Emissions (LE v4) Corrosion Layers
5 layers| Layer Name & Identifier | Description | Units | Grid | Action |
|---|---|---|---|---|
steel_ISO9223_LE_V4_Enhanced_2020_2024_1km
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This dataset represents the modeled first-year atmospheric corrosion rate of carbon steel based on the ISO 9223 atmospheric corrosivity framework enhanced through the Localized Emissions (LE V4) atmospheric chemistry model. Corrosion rates were calculated using five-year climatological averages (2020–2024). | µm/yr | 1 km | View Map → |
zinc_ISO9223_LE_V4_Enhanced_2020_2024_1km
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This dataset represents the modeled first-year atmospheric corrosion rate of zinc based on the ISO 9223 atmospheric corrosivity framework enhanced through the Localized Emissions (LE V4) atmospheric chemistry model. Corrosion rates were calculated using five-year climatological averages (2020–2024). | µm/yr | 1 km | View Map → |
aluminum_ISO9223_LE_V4_Enhanced_2020_2024_1km
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This dataset represents the modeled first-year atmospheric corrosion rate of aluminum based on the ISO 9223 atmospheric corrosivity framework enhanced through the Localized Emissions (LE V4) atmospheric chemistry model. Corrosion rates were calculated using five-year climatological averages (2020–2024). | µm/yr | 1 km | View Map → |
copper_ISO9223_LE_V4_Enhanced_2020_2024_1km
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This dataset represents the modeled first-year atmospheric corrosion rate of copper based on the ISO 9223 atmospheric corrosivity framework enhanced through the Localized Emissions (LE V4) atmospheric chemistry model. Corrosion rates were calculated using five-year climatological averages (2020–2024). | µm/yr | 1 km | View Map → |
steel_ISO9223_LE_V2_Enhanced_2020_2024_1km
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This raster represents modeled global atmospheric corrosivity for carbon steel using the ISO 9223 atmospheric corrosion framework enhanced with Localized Emissions (LE) analytics derived from EDGAR global anthropogenic atmospheric pollution datasets. | µm/yr | 1 km | View Map → |
Supporting Atmospheric & Environmental Layers
48 layers| Layer Name & Identifier | Description | Units | Grid | Action |
|---|---|---|---|---|
ISO9223_Chlorides_2020_2024_1km
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This dataset represents modeled global atmospheric chloride deposition developed to support ISO 9223 atmospheric corrosivity modeling for the period 2020–2024. | mg/m²·d | 1 km | View Map → |
ISO9223_Sulfates_2020_2024_1km
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This dataset represents modeled global atmospheric sulfate deposition developed to support ISO 9223 atmospheric corrosivity modeling for the period 2020–2024. | mg/m²·d | 1 km | View Map → |
ISO9223_Temp_2020_2024_1km
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This dataset represents modeled global mean annual atmospheric temperature developed to support ISO 9223 atmospheric corrosivity modeling for the period 2020–2024. | °C | 1 km | View Map → |
ISO9223_Humidity_2020_2024_1km
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This dataset represents modeled global mean annual relative humidity developed to support ISO 9223 atmospheric corrosivity modeling for the period 2020–2024. | % | 1 km | View Map → |
tow_global_2020_2024_ERA5
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This dataset represents the global mean annual Time of Wetness (TOW) derived from hourly ERA5 reanalysis data for the period 2020–2024. | h/year | 1 km | View Map → |
Artesian_Well_Likelihood_Class_1km_Industry_Filled_webfile
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The Artesian Well Likelihood Index (1–5) provides a simplified classified global hydrogeologic screening layer representing the relative likelihood of artesian, confined, pressurized, or groundwater emergence conditions. The index is derived from the continuous Artesian Well Likelihood Score (1–100) and is intended for rapid screening, corridor prioritization, infrastructure planning, and operational GIS workflows. | Unitless (Index 1-5) | 1 km | View Map → |
EDGAR_AcidGas_Burden_2020_2022_mean_1km
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This dataset represents the global EDGAR Acid Gas Atmospheric Burden, a normalized indicator of long-term anthropogenic acid gas influence derived from the Emissions Database for Global Atmospheric Research (EDGAR) v8 emissions inventory for the period 2020–2022. | Acid Gas Burden Index (0-1) | 1 km | View Map → |
EDGAR_Particulate_Burden_2020_2022_mean_1km
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This dataset represents the global EDGAR Particulate Atmospheric Burden, a normalized indicator of long-term anthropogenic particulate influence derived from the Emissions Database for Global Atmospheric Research (EDGAR) v8 emissions inventory for the period 2020–2022. | Particulate Burden Index (0-1) | 1 km | View Map → |
EDGAR_Chemistry_Burden_2020_2022_mean_1km
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This dataset represents the global EDGAR Atmospheric Chemistry Burden, a normalized indicator of long-term anthropogenic atmospheric chemistry influence derived from the Emissions Database for Global Atmospheric Research (EDGAR) v8 emissions inventory for the period 2020–2022. | Chemistry Burden Index (0-1) | 1 km | View Map → |
EDGAR_Total_Burden_2020_2022_mean_1km
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This dataset represents the global EDGAR Total Atmospheric Burden, a normalized indicator of long-term anthropogenic atmospheric pollution influence derived from the Emissions Database for Global Atmospheric Research (EDGAR) v8 emissions inventory for the period 2020–2022. | Mixed Burden Index (0-1) | 1 km | View Map → |
Climate_Wetness_Index_0_1_v14
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A normalized global climate moisture index (0–1) representing the relative intensity and persistence of wet environmental conditions derived from ERA5 climate data. | Unitless (Normalized Index: 0–1) | 1 km | View Map → |
BDRICM_M_250m_NA
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Depth to bedrock (R horizon) up to 200 cm | cm | 1 km | View Map → |
AWCtS_M_sl7_1km
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Derived saturated water content (volumetric fraction) teta-S for depth 200 cm | % | 1 km | View Map → |
Distance_To_River_20km_Geodesic
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The Distance to River raster provides the geodesic distance (in meters) from each location to the nearest mapped river channel. This metric is used to quantify hydrologic connectivity and proximity to flood-prone environments. | Meters (m) | 1 km | View Map → |
Drainage_Index_Normalized_0_1
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The Drainage Intensity Index represents the relative magnitude of upstream contributing area (flow accumulation), normalized between 0 and 1. Higher values indicate areas receiving flow from larger upstream regions, often corresponding to major drainage pathways and floodplains. | Unitless (Normalized Index: 0–1) | 1 km | View Map → |
Drainage_Position_Index_0_1
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The Drainage Position Index characterizes the relative position of each location within the landscape drainage hierarchy. Lower values correspond to ridge tops and well-drained uplands, while higher values represent valley bottoms and convergent flow zones. | Unitless (Normalized Index: 0–1) | 1 km | View Map → |
EDGAR_Dominant_Component_V4_2020_2022_1km
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This dataset represents the global EDGAR Dominant Atmospheric Component, a categorical classification layer derived from the EDGAR v8 atmospheric burden framework for the period 2020–2022. | Dominant LE Class (0-4) | 1 km | View Map → |
Freeze_Thaw_Cycle_2020_2024
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North America Freeze–Thaw Cycles raster quantifies the annual number of temperature transition events in which the daily minimum temperature falls below 0 °C and the daily maximum temperature exceeds 0 °C. | cycles/yr | 1 km | View Map → |
GLHYMPS_Hydrogeology_Constraint_1km_WGS84_UINT8
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The GLHYMPS Hydrogeology Constraint raster represents an integrated global hydrogeologic favorability framework derived from the GLHYMPS hydrogeology dataset and supporting hydrogeologic normalization workflows. | Hydrogeologic Fav Index (0–100) | 1 km | View Map → |
GLHYMPS_Porosity_1km_WGS84_UINT8
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The GLHYMPS Porosity raster represents the estimated relative porosity of near-surface geologic materials derived from the GLHYMPS global hydrogeology framework. Porosity describes the proportion of void space within geologic materials and is an important control on groundwater storage potential, aquifer capacity, groundwater persistence, and artesian system development. | Relative Porosity Index | 1 km | View Map → |
GLHYMPS_Transmissivity_1km_WGS84_UINT8_v3
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he GLHYMPS Transmissivity raster represents the relative ability of geologic materials to transmit groundwater through saturated aquifer systems at global scale. The raster was derived from the GLHYMPS global hydrogeology framework and processed into a normalized ~1 km global hydrogeologic transmissivity favorability index. | Relative Index (0–100) | 1 km | View Map → |
GLiM_Lithology_Constraint_1km_WGS84_UINT8
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The GLiM Lithology Constraint raster represents a global lithologic favorability layer derived from the GLiM global lithology database. The raster classifies surface lithology into relative hydrogeologic favorability values based on the likelihood that mapped geologic materials support groundwater storage, groundwater transmission, confined aquifer development, or artesian-style hydrogeologic conditions. | dimensionless Index (0-100) | 1 km | View Map → |
global_drainage_2020_2024_ERA5
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Global drainage intensity raster derived from MERIT Hydro flow accumulation data. Values represent log10-transformed upstream contributing area, resampled to ~1 km resolution for integration with climate and environmental datasets. Higher values indicate major drainage pathways and river systems. | unitless | 1 km | View Map → |
Freeze_Thaw_2020_2024_ERA5
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This raster represents the mean annual number of freeze–thaw cycles over the period 2020–2024, derived from ERA5 reanalysis data. A freeze–thaw cycle is defined as a day in which the daily minimum air temperature falls below 0 °C (273.15 K) and the daily maximum air temperature exceeds 0 °C. | cycles/yr | 1 km | View Map → |
GMSR_v1_Global_Ground_Movement_Susceptibility_0_100
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The Global Ground Movement Susceptibility Raster (GMSR) is a global geospatial dataset representing relative susceptibility to long-term ground movement hazards. | Index Score (0–100) | 1 km | View Map → |
GMSR_v1_Global_Ground_Movement_Susceptibility_Class_7
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The Global Ground Movement Susceptibility Raster (GMSR) is a global geospatial dataset representing relative susceptibility to long-term ground movement hazards. | Index (1-7) | 1 km | View Map → |
GMSR_Landslide_Susceptibility_0_100
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The Global Landslide Susceptibility Raster (GMSR-LS) is a global geospatial dataset representing relative susceptibility to gravitational slope failure and landslide occurrence. | Score (1-100) | 1 km | View Map → |
emag2
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Magnetic anomaly maps provide insight into the subsurface structure and composition of the Earth's crust. Anomalies trending parallel to the isochrons (lines of equal age) in the oceans reveal the temporal evolution of oceanic crust. Magnetic maps are widely used in the geological sciences and in resource exploration. Furthermore, the global magnetic map is useful in science education to illustrate various aspects of Earth evolution such as plate tectonics and crustal interaction with the deep mantle. Distinct patterns and magnetic signatures can be attributed to the formation (seafloor spreading) and destruction (subduction zones) of oceanic crust, the formation of continental crust by accretion of various terranes to cratonic areas and large scale volcanism (both on continents and oceans). | nanoTesla (nT) | 1 km | View Map → |
mean_annual_precip_2020_2024
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This raster represents the spatial distribution of mean annual precipitation across the globe, expressed in millimeters per year (mm/year), averaged over the period 2020 through 2024. The dataset was derived from the ERA5 reanalysis provided by the European Centre for Medium-Range Weather Forecasts (ECMWF), using monthly averaged total precipitation fields. | mm/yr | 1 km | View Map → |
mean_annual_temp_2020_2024
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This raster represents the mean annual near-surface air temperature at 2 meters above ground level, derived from ERA5 reanalysis data for the period 2020 through 2024. Monthly averaged temperature values were obtained from the ERA5 dataset and converted from Kelvin to degrees Celsius. For each year, monthly values were averaged to produce annual mean temperature rasters. A five-year mean was then calculated by averaging the annual rasters across the full period. | °C | 1 km | View Map → |
global_annual_rainfall_2020_2024
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This raster dataset represents the mean annual number of rainy days across the globe for the period 2020 through 2024, derived from the ERA5 reanalysis dataset provided by the European Centre for Medium-Range Weather Forecasts (ECMWF). | days/year | 1 km | View Map → |
GMSR_Seismic_Amplification_0_100
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The Global Seismic Amplification Raster (GMSR-SA) is a global geospatial dataset representing relative susceptibility to amplification of seismic ground motions resulting from local geological, geomorphic, and seismic hazard conditions. | Score (1-100) | 1 km | View Map → |
wet_dry_cycles_2020_2024_ERA5
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This raster represents the average annual number of dry-to-wet transitions derived from daily total precipitation. A dry day is defined as precipitation < 1 mm, and a wet day is defined as precipitation ≥ 1 mm. A wet–dry cycle is counted when a dry day is immediately followed by a wet day. | cycles/yr | 1 km | View Map → |
global_lightning
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Global lightning strikes per km^2 per decade. | strokes/km^2/decade | 1 km | View Map → |
RH_Mean_2020_2024_30arcsec_GCS_WGS84_tileview
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This dataset represents the global mean annual near-surface relative humidity (RH) in percent (%), derived from ERA5 reanalysis data for the period 2020–2024. | % | 1 km | View Map → |
temp_2019_2023
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Used in creation of ISO 9223 raster map | °C | 1 km | View Map → |
Mean_Temp_2020_2024
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North American Arithmetic mean of daily average air temperature calculated from Daymet v4 minimum and maximum temperature fields, expressed in degrees Celsius per grid cell per year. | °C | 1 km | View Map → |
cl_iso9223_2019_2023
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Used in creation of ISO 9223 raster map | mg/m²·d | 1 km | View Map → |
so2_2019_2023
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Used in creation of ISO 9223 raster map | mg/m²·d | 1 km | View Map → |
Pipeline_Hydrologic_Exposure_Index_1_7_v14_INT_websafe
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The Pipeline Hydrologic Exposure Index (1–7) raster provides a classified representation of hydrologic exposure conditions derived from the continuous 1–100 exposure score. The index simplifies interpretation by grouping areas into seven discrete exposure classes for rapid visualization, decision-making, and web-based applications. | Unitless (Normalizd Index 1–) | 1 km | View Map → |
Rainfall_Raster_2020_2024_1km
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This raster represents the average number of days per year where daily precipitation was ≥ 1 mm. Unit of measure: days/year (5-year average). | days/year | 1 km | View Map → |
River_Influence_20km
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The River Influence raster represents the relative influence of major river systems based on proximity. Values decrease with increasing distance from rivers, reflecting reduced hydrologic connectivity and floodplain influence. | Influence (dimensionless, 0-1) | 1 km | View Map → |
tceq_calcium_carbonate_equal
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Global high-resolution spatial environmental raster layer. | g/kg | 1 km | View Map → |
TOW_2020_2024_1km
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The Web GeoTIFF is a 30 arc-second (~1 km) EPSG:4326 raster representing annual Time of Wetness (hours/year) across North America for 2020–2024, analytically derived from NASA ORNL DAAC Daymet v4 daily climate data in accordance with ISO 9223 exposure criteria. | hours/year | 1 km | View Map → |
Precip_2020_2024_1km
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North American Annual cumulative precipitation derived from Daymet v4 daily precipitation data, representing the total millimeters of precipitation received per grid cell per year. | mm/yr | 1 km | View Map → |
so2_concentrations_2019_2023
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Global high-resolution spatial environmental raster layer. | — | 1 km | View Map → |
wet_dry_cycles_1km
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This raster represents the average number of dry-to-wet transitions per year (precipitation ≥ 1 mm threshold). In other words, it counts how often conditions shift from dry to wet on a daily basis. Unit of measure: cycles/year (5-year average). | cycles/year | 1 km | View Map → |
GLWD_v2_0_area_pct
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The Global Wetland Area Percentage Raster provides spatially continuous estimates of wetland and inland water coverage as a percentage of each grid cell. | % | 1 km | View Map → |
Coastal, Wind & Terrain Layers
53 layers| Layer Name & Identifier | Description | Units | Grid | Action |
|---|---|---|---|---|
Distance_to_Coast_2013_1km
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This dataset represents the modeled global distance from each raster cell to the nearest marine coastline. | Distance (km) | 1 km | View Map → |
Bathymetry_2024_1km
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This dataset represents a continuous global terrain surface combining both land elevation and ocean bathymetry derived from the GEBCO_2024 Grid. | Elevation (m) | 1 km | View Map → |
windrix_style_2020_2024_ERA5
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This dataset represents the global WindRIX-Style Terrain–Wind Exposure Index, a continuous environmental exposure raster derived from the combined influence of terrain ruggedness, prevailing wind speed, and directional wind exposure for the period 2020–2024. | Unitless (0–100 index) | 1 km | View Map → |
Wind_Degree_Direction_2020_2024_ERA5
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This dataset represents the global mean resultant wind direction at 10 meters above ground level derived from ERA5 reanalysis data for the period 2020–2024. | 0–360° (azimuth) | 1 km | View Map → |
wind_speed_2020_2024_ERA5
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This dataset represents the global mean near-surface wind speed derived from ERA5 reanalysis data for the period 2020–2024. | m/s | 1 km | View Map → |
air_temperature_2m_c_2020_2024_web_1km
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Average near-surface air temperature measured at 2 meters above ground level. Critical for solar panel efficiency modeling. | °C | 1 km | View Map → |
BDTICM_M_250m
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Absolute depth from the soil surface to the **R horizon (continuous bedrock)**, expressed in centimeters. This represents the total thickness of unconsolidated soil material above consolidated rock. | cm | 1 km | View Map → |
Artesian_Well_Likelihood_1km_Industry_Filled_webfile
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A continuous global artesian groundwater likelihood score (1–100) representing the relative probability of artesian, confined, pressurized, or groundwater emergence conditions based on integrated terrain hydrology, hydrogeology, climate wetness, lithology, and groundwater system characteristics. | Index Score (0–100) | 1 km | View Map → |
WWP_M_sl7_1km
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Derived available soil water capacity (volumetric fraction) until wilting point for depth 200 cm | Capacity/% | 1 km | View Map → |
AWCh1_M_sl7_1km_ll.tif
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Available water capacity is the maximum amount of plant available water a soil can provide. It is an indicator of a soil's ability to retain water and make it sufficiently available for plant use. Available water capacity is the water held in soil between its field capacity and permanent wilting point. | cmol/kg | 1 km | View Map → |
direct_horizontal_2020_2024_web_1km
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Description: Direct beam solar radiation received on a horizontal surface. This excludes diffuse radiation and represents only the direct component of sunlight. | W/m² | 1 km | View Map → |
CECSOL_M_sl4_1km
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Cation-exchange capacity is a measure of how many cations can be retained on soil particle surfaces. Negative charges on the surfaces of soil particles bind positively-charged atoms or molecules, but allow these to exchange with other positively charged particles in the surrounding soil water. | cmol/kg | 1 km | View Map → |
CECSOL_M_sl1_1km_ll
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Cation Exchange Capacity (CEC) represents the soil’s ability to retain and exchange positively charged ions (cations) such as calcium (Ca²⁺), magnesium (Mg²⁺), potassium (K⁺), sodium (Na⁺), and hydrogen (H⁺). | cmol(c)/kg | 1 km | View Map → |
CECSOL_M_sl7_1km_ll
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Cation Exchange Capacity (CEC) represents the soil’s ability to retain and exchange positively charged ions (cations) such as calcium (Ca²⁺), magnesium (Mg²⁺), potassium (K⁺), sodium (Na⁺), and hydrogen (H⁺). | cmol(c)/kg | 1 km | View Map → |
CLYPPT_M_sl1_1km_ll
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Percentage of **clay-sized particles (< 0.002 mm)** in the soil by weight. Clay content is a major component of soil texture and strongly influences water retention, permeability, cation exchange capacity, shrink-swell behavior, and electrical conductivity. | % (Weight Percentage) | 1 km | View Map → |
CLYPPT_M_sl7_1km_ll
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Percentage of **clay-sized particles (< 0.002 mm)** in the soil by weight. Clay content is a key component of soil texture and strongly influences water retention, permeability, chemical reactivity, and electrical properties. | % (percent by weight) | 1 km | View Map → |
clear_sky_direct_horizontal_2020_2024_web_1km
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This dataset represents mean daily direct solar radiation under cloud-free conditions. CDIR quantifies the maximum direct beam irradiance absent cloud attenuation. | W/m² | 1 km | View Map → |
clear_sky_ghi_2020_2024_web_1km
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Global horizontal irradiance under cloud-free (clear-sky) conditions, representing the theoretical maximum solar radiation at the surface. | W/m² | 1 km | View Map → |
CRFVOL_M_sl1_1km_ll
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Percentage of **coarse fragments (> 2 mm)** in the soil by volume, including gravel, stones, and rock fragments. This represents the proportion of soil volume occupied by non-fine-earth material. | % (percent by volume) | 1 km | View Map → |
CRFVOL_M_sl7_1km_ll
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Percentage of **coarse fragments (> 2 mm)** in the soil by volume, including gravel, stones, and rock fragments. This represents the proportion of soil volume occupied by non-fine-earth material. | % (percent by volume) | 1 km | View Map → |
WWP_M_sl7_250m_NA
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Derived available soil water capacity (volumetric) until wilting point 2.0m depth (ISRIC WWP_M_sl7_250m) | Capacity/% | 1 km | View Map → |
soil_moisture_root_zone_2020_2024_ERA5
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This raster represents the mean annual root-zone soil moisture for the period 2020–2024, derived from the ERA5-Land climate reanalysis dataset. Soil moisture is expressed as volumetric water content (m³/m³) and represents a depth-weighted average across the upper 0–100 cm of the soil profile. | m³/m³ | 1 km | View Map → |
soil_temp_rootzone_2020_2024_ERA5
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The Global Root-Zone Soil Temperature Raster (0–100 cm) represents the mean annual soil temperature across the upper 1 meter of the soil profile, derived from ERA5-Land reanalysis data for the period 2020–2024. This raster reflects subsurface thermal conditions that are less sensitive to short-term atmospheric variability and more representative of long-term thermal stability relevant to buried infrastructure and soil processes. | °C | 1 km | View Map → |
aerobic_index_1km
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This project produces a spatially continuous **Aerobic Index Raster** used to classify global soils based on their relative oxygenation potential. Rather than directly estimating soil oxygen concentration, the model computes a composite environmental proxy derived from soil, climatic, hydrologic, and lithological variables. :contentReference[oaicite:0]{index=0} | Dimensionless index (range: 0–1) | 1 km | View Map → |
GMSR_Soil_Creep_Potential_0_100
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The Global Soil Creep Potential Raster (GMSR-SC) is a global geospatial dataset representing the relative susceptibility of soils and surficial materials to long-term downslope movement driven by gravity, moisture fluctuations, freeze–thaw activity, and gradual deformation processes. | Score (1-100) | 1 km | View Map → |
soil_moisture_surface_2020_2024_ERA5
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This raster represents the mean annual surface soil moisture for the period 2020–2024, derived from the ERA5-Land climate reanalysis dataset. Soil moisture is expressed as volumetric water content (m³/m³) and corresponds to the upper 0–7 cm soil layer. | m³/m³ | 1 km | View Map → |
soil_temp_surface_2020_2024_ERA5
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The Global Surface Soil Temperature Raster (0–7 cm) represents the mean annual soil temperature at the near-surface layer, derived from ERA5-Land reanalysis data for the period 2020–2024. This raster reflects the thermal conditions of the uppermost soil layer, which is strongly influenced by atmospheric temperature, solar radiation, precipitation, and surface energy balance. | °C | 1 km | View Map → |
GMSR_Shrink_Swell_v2_0_100
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The Global Shrink–Swell Potential Raster (GMSR-SS) v2 is a global geospatial dataset representing the relative susceptibility of soils to volumetric expansion and contraction resulting from moisture fluctuations. | Score (1-100) | 1 km | View Map → |
GMSR_Subsidence_Susceptibility_v2_0_100
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The Global Subsidence Susceptibility Raster (GMSR-SUB) is a global geospatial dataset representing relative susceptibility to long-term ground subsidence resulting from consolidation, compaction, settlement, and deformation of soils and sediments. | Score (1-100) | 1 km | View Map → |
HAND_Height_Above_Nearest_Drainage_m
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The Height Above Nearest Drainage (HAND) raster represents the vertical distance (in meters) between each land surface location and the nearest hydrologically connected drainage channel. Lower values indicate areas closer to river systems and floodplains, while higher values represent elevated terrain. | Meters (m) | 1 km | View Map → |
HAND_Low_Lying_Index_0_1
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The HAND Low-Lying Index is a normalized representation of terrain position derived from the HAND dataset. Values range from 0 to 1, where higher values indicate lower-lying terrain more closely connected to drainage systems and floodplains. | Unitless (Normalized Index: 0–1) | 1 km | View Map → |
ghi_2020_2024_web_1km
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Total incoming solar radiation on a horizontal surface, including both direct and diffuse components. | W/m² | 1 km | View Map → |
Sl7_nitrogen_100_200cm_mean_100_1km0
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This raster represents the mean total nitrogen content in soils at a depth of 100–200 cm, expressed in centigrams per kilogram (cg/kg). This unit reflects the mass of nitrogen per unit mass of soil, where 1 cg/kg is equivalent to 10 mg/kg (ppm). | cg/kg | 1 km | View Map → |
OCDENS_M_sl1_1km_ll
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Organic Carbon Density represents the estimated mass of soil organic carbon stored within a given soil volume and depth interval. | kg/m³ | 1 km | View Map → |
OCDENS_M_sl7_1km_ll
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Organic Carbon Density represents the estimated mass of soil organic carbon stored within a given soil volume and depth interval. | kg/m³ | 1 km | View Map → |
SNDPPT_M_sl1_1km_ll
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Percentage of **sand particles** in the soil fine earth fraction. Sand particles are mineral particles with diameters typically between **0.05 mm and 2.0 mm**. | % fine earth | 1 km | View Map → |
SNDPPT_M_sl7_1km_ll
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Percentage of **sand particles** in the soil fine earth fraction. Sand particles are mineral particles with diameters typically between **0.05 mm and 2.0 mm**. | % fine earth | 1 km | View Map → |
AWCtS_M_sl1_1km_ll
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Saturated water content of the soil, expressed as a volumetric fraction (m³/m³ or %), representing the maximum amount of water the fine earth fraction can retain when all pore spaces are fully filled. This parameter characterizes the soil’s total pore volume and is a key factor influencing water storage capacity, hydraulic behavior, and subsurface transport processes within the integrated 0-5 cm soil profile. | mm/m | 1 km | View Map → |
AWCtS_M_sl7_1km_ll
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Saturated water content of the soil, expressed as a volumetric fraction (m³/m³ or %), representing the maximum amount of water the fine earth fraction can retain when all pore spaces are fully filled. This parameter characterizes the soil’s total pore volume and is a key factor influencing water storage capacity, hydraulic behavior, and subsurface transport processes within the integrated 100–200 cm soil profile. | mm/m | 1 km | View Map → |
Saturation_Potential_Index_0_1
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The Saturation Potential Index represents the relative likelihood of soil moisture accumulation based on terrain position, drainage characteristics, and precipitation inputs. Higher values indicate areas where water is more likely to persist, resulting in reduced soil aeration and increased potential for anaerobic conditions. | Unitless (Normalized Index: 0–1) | 1 km | View Map → |
SLTPPT_M_sl1_1km_ll
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Percentage of **silt-sized particles (0.002–0.05 mm)** in the soil by weight. Silt content is a key component of soil texture and strongly influences moisture retention, permeability, capillary transport, erosion susceptibility, and soil aeration behavior. | % (percent by weight) | 1 km | View Map → |
SLTPPT_M_sl7_1km_ll
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Percentage of **silt-sized particles (0.002–0.05 mm)** in the soil by weight. Silt content is a key component of soil texture and strongly influences moisture retention, permeability, capillary transport, erosion susceptibility, and soil aeration behavior. | % (percent by weight) | 1 km | View Map → |
soil-cgr-romanoff-north-america
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Global high-resolution spatial environmental raster layer. | mil/year | 1 km | View Map → |
ORCDRC_M_sl1_1km_ll
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Soil organic carbon content represents the amount of organic carbon contained in the fine earth fraction of the soil. Organic carbon is a key soil property influencing nutrient cycling, water retention, microbial activity, redox behavior, soil structure, and long-term carbon storage. | g/kg | 1 km | View Map → |
ORCDRC_M_sl7_1km_ll
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Soil organic carbon content represents the amount of organic carbon contained in the fine earth fraction of the soil. Organic carbon is a key soil property influencing nutrient cycling, water retention, microbial activity, redox behavior, and soil structure. | g/kg | 1 km | View Map → |
soil_resistivity_barnes_ohm-cm_P10108
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The Predictive Soil Resistivity Raster is a global, high-resolution geospatial data product developed by Engineering Director, Inc., leveraging advanced machine-learning techniques to estimate Barnes Layer soil resistivity (Ω·cm). Built on a rigorously validated Random Forest modeling framework and calibrated and validated against field-measured resistivity data obtained using standardized Wenner four-pin methods, the raster integrates environmental, geochemical, terrain, and climatic predictors to deliver continuous, physically consistent resistivity values at 250-meter resolution. | ohm-cm | 1 km | View Map → |
solar_suitability_index_2020_2024_master_1km_class
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A classified global solar suitability index (1-7) dividing conditions into seven discrete levels for simplified interpretation and decision-making. The Solar Suitability Index closely aligns with independent estimates of solar energy performance, indicating strong reliability as a global screening metric. | SSI™ Class Index (1–7) | 1 km | View Map → |
solar_suitability_index_2020_2024_master_1km_class_Clip
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A classified continental solar suitability index (1-7) dividing conditions into seven discrete levels for simplified interpretation and decision-making. The Solar Suitability Index closely aligns with independent estimates of solar energy performance, indicating strong reliability as a global screening metric. | SSI™ Class Index (1–7) | 1 km | View Map → |
solar_suitability_index_2020_2024_web_1km
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A continuous global solar suitability score (0–100) representing the relative favorability of locations for solar energy development based on multi-parameter climatological conditions. The Solar Suitability Index closely aligns with independent estimates of solar energy performance, indicating strong reliability as a global screening metric. | SSI™ Score (1-100) | 1 km | View Map → |
surface_pressure_2020_2024_web_1km
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Average atmospheric pressure at the Earth's surface, influencing air mass and solar attenuation characteristics. | Pa | 1 km | View Map → |
total_cloud_cover_2020_2024_web_1km
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his dataset represents mean cloud cover fraction, ranging from 0 (clear sky) to 1 (fully overcast). Cloud cover strongly influences solar attenuation and variability. | Fraction (0–1) | 1 km | View Map → |
total_column_water_vapour_2020_2024_web_1km
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Total atmospheric water vapor content integrated through the vertical column, influencing atmospheric attenuation of solar radiation. | kg/m² | 1 km | View Map → |
Wind_Resultant_Direction_1km_Clip
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Worldwide Wind Resultant (°) Direction is a single, averaged wind direction derived from a wind rose. It represents the net or dominant direction toward which the wind tends to blow, taking into account both the frequency and magnitude of wind from all directions. It is typically calculated using vector components of wind data and expressed in degrees from true north (0°–360°). | Degrees (°) | 1 km | View Map → |