N: 90 S: -90 E: 180 W: -180
30 Meters x 30 Meters
The Terra Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) Surface Reflectance VNIR and Crosstalk Corrected SWIR (AST_07XT) dataset contains measures of the fraction of incoming solar radiation reflected from the Earth’s surface to the ASTER instrument corrected for atmospheric effects and viewing geometry for both the Visible and Near Infrared (VNIR) and Shortwave Infrared (SWIR) sensors. Both the VNIR and SWIR data are atmospherically corrected and are generated using the bands of the corresponding ASTER L1B image. The AST_07XT product has a spatial resolution of 15 meters (m) for the VNIR bands and 30 m for the SWIR bands.
Known Issues
Citation is critically important for dataset documentation and discovery. This dataset is openly shared, without restriction, in accordance with the EOSDIS Data Use and Citation Guidance.
| Title | Year Sort ascending | Author | Topic |
|---|---|---|---|
| Identification and field verification of Fe-bearing rocks in the | Inal, Sedat, Kavak, Kaan Sevki | Topographical Relief Maps, Terrain Elevation, Digital Elevation/Terrain Model (DEM), Albedo, Reflectance | |
| Direct Geologic Constraints on the Timing of Late Holocene Ice Thickening in the Amundsen Sea Embayment, Antarctica | Nichols, Keir A., Adams, Jonathan R., Brown, Katie, Creel, Roger C., McKenzie, Marion A., Venturelli, Ryan A., Johnson, Joanne S., Rood, Dylan H., Wilcken, Klaus, Woodward, John, Roberts, Stephen J. | Ice Velocity, Albedo, Reflectance | |
| Mapping clay minerals using the Spectral Angle Mapper method and ASTER data, Minas do Camaqua, RS, Brazil | Balbinot, Pietro Luiz, Engelmann de Oliveira, Christie Helouise | Albedo, Reflectance | |
| Mapping mineralogy in evaporite basins through time using multispectral Landsat data: Examples from the Bonneville basin, Utah, USA | Radwin, Mark H., Bowen, Brenda B. | Albedo, Reflectance | |
| Reconnaissance assessment of the Stenian-Tonian granitoids of southern Tanzania for metal resources by using geological remote sensing and geochemical techniques | Kazimoto, Emmanuel O., Mshiu, Elisante E. | Albedo, Reflectance | |
| Assessing 50 Years of Mangrove Forest Loss Along the Pacific Coast of Ecuador: A Remote Sensing Synthesis | Hamilton, Stuart E. | Albedo, Reflectance | |
| Processing and analysis of ASTER and Landsat 8 scenes to aid in geological mappingA case study of murchison greenstone belt area, South Africa | Thomas, Abraham | Terrain Elevation, Digital Elevation/Terrain Model (DEM), Topographical Relief Maps, Albedo, Reflectance | |
| The application of day and night time ASTER satellite imagery for geothermal and mineral mapping in East Africa | Hewson, Rob, Mshiu, Elisante, Hecker, Chris, van der Werff, Harald, van Ruitenbeek, Frank, Alkema, Dinand, van der Meer, Freek | Land Surface Temperature, Sea Surface Temperature, Albedo, Reflectance | |
| Spectral characteristics of talc and mineral abundance mapping in the Jahazpur Belt of Rajasthan, India using AVIRIS-NG data | Bhadra, B. K., Pathak, Suparn, Nanda, Dhruv, Gupta, Ankit, Rao, S. Srinivasa | REFLECTED INFRARED, THERMAL INFRARED, VISIBLE IMAGERY, Visible Radiance, Albedo, Reflectance | |
| Integration and visualization of mineralogical and topographical information derived from ASTER and DEM data | Kurata, Kana, Yamaguchi, Yasushi | Emissivity, Albedo, Reflectance | |
| Mapping hydrothermally altered minerals with AST_07XT, AST_05 and Hyperion datasets using a voting-based extreme learning machine algorithm | Hu, Bin, Wan, Bo, Xu, Yongyang, Tao, Liufeng, Wu, Xincai, Qiu, Qinjun, Wu, Yehui, Deng, Hui | REFLECTED INFRARED, THERMAL INFRARED, VISIBLE IMAGERY, Visible Radiance, Emissivity, Albedo, Reflectance | |
| Mineral discrimination by combination of multispectral image and surrounding hyperspectral image | Hirai, Akihiro | Albedo, Reflectance | |
| Associations of greenness, greyness and air pollution exposure with children's health: a cross-sectional study in Southern Italy | Cilluffo, Giovanna, Ferrante, Giuliana, Fasola, Salvatore, Montalbano, Laura, Malizia, Velia, Piscini, Alessandro, Romaniello, Vito, Silvestri, Malvina, Stramondo, Salvatore, Stafoggia, Massimo, Ranzi, Andrea, Viegi, Giovanni, La Grutta, Stefania | Albedo, Reflectance | |
| Evaluation and aggregation properties of thermal Infra-Red-based evapotranspiration algorithms from 100 m to the km scale over a semi-arid irrigated agricultural area | Bahir, Malik, Boulet, Gilles, Olioso, Albert, Rivalland, Vincent, Gallego-Elvira, Belen, Mira, Maria, Rodriguez, Julio-Cesar, Jarlan, Lionel, Merlin, Olivier | Vegetation Index, Normalized Difference Vegetation Index (NDVI), Enhanced Vegetation Index (EVI), Emissivity, Land Surface Temperature, Albedo, Reflectance, Leaf Area Index (LAI), Fraction Of Absorbed Photosynthetically Active Radiation (fapar), Sea Surface Temperature | |
| Processing methodology based on ASTER data for mapping mine waste dumps in a semiarid polysulphide mine district | Rodriguez-Hernandez, Alejandro, Briones-Gallardo, Roberto, Razo, Israel, Noyola-Medrano, Cristina, Lazaro, Isabel | Emissivity, Albedo, Reflectance |
The table below lists the variables contained within a single granule for this dataset. Variables often contain observed or derived geophysical measurements collected from a variety of sources, including remote sensing instruments on satellite and airborne platforms, field campaigns, in situ measurements, and model outputs. The terms variable, parameter, scientific data set, layer, and band have been used across NASA’s Earth science disciplines; however, variable is the designated nomenclature in NASA’s Common Metadata Repository (CMR). Variable metadata attributes such as Name, Description, Units, Data Type, Fill Value, Valid Range, and Scale Factor allow users to efficiently process and analyze the data. The full range of attributes may not be applicable to all variables. Additional information on variable attributes is typically available in the data, user guide, and/or other product documentation.
For questions on a specific variable, please use the Earthdata Forum.
| Name Sort descending | Description | Units | Data Type | Fill Value | Valid Range | Scale Factor | Offset |
|---|---|---|---|---|---|---|---|
| SWIR_Band4 | 30 meter resolution SWIR Band 4 (1.600 to 1.700 µm) | N/A | int16 | N/A | 0 to 1000 | 0.001 | N/A |
| SWIR_Band5 | 30 meter resolution SWIR Band 5 (2.145 to 2.185 µm) | N/A | int16 | N/A | 0 to 1000 | 0.001 | N/A |
| SWIR_Band6 | 30 meter resolution SWIR Band 6 (2.185 to 2.225 µm) | N/A | int16 | N/A | 0 to 1000 | 0.001 | N/A |
| SWIR_Band 7 | 30 meter resolution SWIR Band 7 (2.235 to 2.285 µm) | N/A | int16 | N/A | 0 to 1000 | 0.001 | N/A |
| SWIR_Band 8 | 30 meter resolution SWIR Band 8 (2.295 to 2.365 µm) | N/A | int16 | N/A | 0 to 1000 | 0.001 | N/A |
| SWIR_Band 9 | 30 meter resolution SWIR Band 9 (2.360 to 2.430 µm) | N/A | int16 | N/A | 0 to 1000 | 0.001 | N/A |
| VNIR_Band 1 | 15 meter resolution VNIR Band 1 (0.52 to 0.60 µm) | N/A | int16 | N/A | 0 to 1000 | 0.001 | N/A |
| VNIR_Band2 | 15 meter resolution VNIR Band 2 (0.63 to 0.69 µm) | N/A | int16 | N/A | 0 to 1000 | 0.001 | N/A |
| VNIR_Band3N | 15 meter resolution VNIR Band 3 (0.78 to 0.86 µm) | N/A | int16 | N/A | 0 to 1000 | 0.001 | N/A |