N: 90 S: -90 E: 180 W: -180
30 Meters x 30 Meters
90 Meters x 90 Meters
The AST_L1T Version 3 data product was decommissioned on December 15, 2025. Users are encouraged to use the AST_L1T Version 4 data product.
The Terra Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) Level 1 Precision Terrain Corrected Registered At-Sensor Radiance (AST_L1T) data contains calibrated at-sensor radiance, which corresponds with the ASTER Level 1B (AST_L1B), that has been geometrically corrected and rotated to a north-up UTM projection. The AST_L1T is created from a single resampling of the corresponding ASTER L1A (AST_L1A) product. The bands available in the AST_L1T depend on the bands in the AST_L1A and can include up to three Visible and Near Infrared (VNIR) bands, six Shortwave Infrared (SWIR) bands, and five Thermal Infrared (TIR) bands. The AST_L1T dataset does not include the aft-looking VNIR band 3. The AST_L1T product has a spatial resolution of 15 meters (m) for the VNIR bands, 30 m for the SWIR bands, and 90 m for the TIR bands.
The precision terrain correction process incorporates GLS2000 digital elevation data with derived ground control points (GCPs) to achieve topographic accuracy for all daytime scenes where correlation statistics reach a minimum threshold. Alternate levels of correction are possible (systematic terrain, systematic, or precision) for scenes acquired at night or that otherwise represent a reduced quality ground image (e.g., cloud cover).
For daytime images, if the VNIR or SWIR telescope collected data and precision correction was attempted, each precision terrain corrected image will have an accompanying independent quality assessment. It will include the geometric correction available for distribution in both as a text file and a single band browse images with the valid GCPs overlaid.
This multi-file product also includes georeferenced full resolution browse images. The number of browse images and the band combinations of the images depends on the bands available in the corresponding AST_L1A dataset.
AST_L1T V3 was processed using radiometric calibration coefficients (RCC) Version 4 as a direct download.
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 |
|---|---|---|---|
| A data-driven approach to understanding the relations between geothermal exploration parameters: insights from Coso, Brady and Desert Peak, USA | Yu, Yu-Ting, Duzgun, H. Sebnem, Sabin, Andrew E. | REFLECTED INFRARED, THERMAL INFRARED, VISIBLE IMAGERY, Visible Radiance | |
| Alteration mineral information extraction based on image | Zhao, Chunyu, Xiao, Zhiqiang, Zhang, Yan, Yuan, Changjiang, Yang, Jie | REFLECTED INFRARED, THERMAL INFRARED, VISIBLE IMAGERY, Visible Radiance | |
| Habitat preference of bitter and sweet asafoetida plants, topographic, soil and climatic factors using remote sensing and statistics analysis | Jamali, Ali Akbar, Hossein Jafari, Samira, Zarekia, Sedigheh | REFLECTED INFRARED, THERMAL INFRARED, VISIBLE IMAGERY, Visible Radiance | |
| Image acquisition and processing techniques for crucial component of renewable energy technologies: mapping of rare earth element-bearing peralkaline granites | Jain, Ronak, Pandey, Ashutosh Kumar | REFLECTED INFRARED, THERMAL INFRARED, VISIBLE IMAGERY, Visible Radiance | |
| Spectral mixture analysis of intimate mixtures for lithological mapping | Ahmad, Adnan, Nair, Archana M. | REFLECTED INFRARED, THERMAL INFRARED, VISIBLE IMAGERY, Visible Radiance | |
| Thermal infrared shadow-hiding in GOES-R ABI imagery: snow and forest temperature observations from the SnowEx 2020 Grand Mesa field campaign | Pestana, Steven J., Chickadel, C. Chris, Lundquist, Jessica D. | REFLECTED INFRARED, THERMAL INFRARED, VISIBLE IMAGERY, Visible Radiance, Liquid Water Content, Snow Density, Snow Depth, Snow Grain Size, Snow/Ice Temperature, Snow Stratigraphy, Snow Water Equivalent | |
| Soil Erosion Assessment and Mitigation Scenarios Based on Geopedology in Northwestern Patagonia, Argentina | Frugoni, M. C., Gonzalez Musso, R. F., Falbo, G. | REFLECTED INFRARED, THERMAL INFRARED, VISIBLE IMAGERY, Visible Radiance | |
| A comparative study of convolutional neural networks and conventional machine learning models for lithological mapping using remote sensing data | Shirmard, Hojat, Farahbakhsh, Ehsan, Heidari, Elnaz, Beiranvand Pour, Amin, Pradhan, Biswajeet, Muller, Dietmar, Chandra, Rohitash | REFLECTED INFRARED, THERMAL INFRARED, VISIBLE IMAGERY, Visible Radiance | |
| A high-resolution fuel type mapping procedure based on satellite imagery and neural networks: Updating fuel maps for wildfire simulators | Lopez-De-Castro, Marcos, Prieto-Herraez, Diego, Asensio-Sevilla, Maria Isabel, Pagnini, Gianni | Land Surface Temperature, Emissivity, REFLECTED INFRARED, THERMAL INFRARED, VISIBLE IMAGERY, Visible Radiance, Terrain Elevation, RADAR IMAGERY, Topographical Relief Maps | |
| Application of ASTER data for differentiating carbonate minerals and evaluating MgO content of magnesite in the Jiao-Liao-Ji Belt, North China Craton | Son, Young-Sun, Lee, Gilljae, Lee, Bum Han, Kim, Namhoon, Koh, Sang-Mo, Kim, Kwang-Eun, Cho, Seong-Jun | REFLECTED INFRARED, THERMAL INFRARED, VISIBLE IMAGERY, Visible Radiance | |
| Application of per-pixel and sub-pixel unmixing methods on ASTER images to map hydrothermal alterations in a highly metamorphosed terrainA case of the Musina copper deposit field | Muavhi, Nndanduleni | REFLECTED INFRARED, THERMAL INFRARED, VISIBLE IMAGERY, Visible Radiance | |
| Hydrothermal alteration mapping using ASTER data, Takab-Baneh area, NW IranA key for further exploration of polymetal deposits | Saed, Shima, Azizi, Hossein, Daneshvar, Narges, Afzal, Peyman, Whattam, Scott A., Mohammad, Yousif O. | REFLECTED INFRARED, THERMAL INFRARED, VISIBLE IMAGERY, Visible Radiance | |
| Geochemical and hydrothermal alteration patterns of the Abrisham-Rud Porphyry Copper District, Semnan Province, Iran | Timkin, Timofey, Abedini, Mahnaz, Ziaii, Mansour, Ghasemi, Mohammad Reza | REFLECTED INFRARED, THERMAL INFRARED, VISIBLE IMAGERY, Visible Radiance | |
| Mapping sequences and mineral deposits in poorly exposed lithologies of inaccessible regions in Azad Jammu and Kashmir using SVM with ASTER satellite data | Imran, Muhammad, Ahmad, Sultan, Sattar, Amir, Tariq, Aqil | REFLECTED INFRARED, THERMAL INFRARED, VISIBLE IMAGERY, Visible Radiance | |
| Mapping vegetation species succession in a mountainous grassland | Adagbasa, Efosa Gbenga, Mukwada, Geofrey | REFLECTED INFRARED, THERMAL INFRARED, VISIBLE IMAGERY, Visible Radiance | |
| Integration of multi-sensor remote sensing, geological and geochemical data for delineation of PbZn bearing carbonates of Middle Aravalli group in Zawar ... | Jain, Ronak, Bhu, Harsh, Kumar, Hrishikesh, Purohit, Ritesh | REFLECTED INFRARED, THERMAL INFRARED, VISIBLE IMAGERY, Visible Radiance | |
| Integration of multispectral and hyperspectral remote sensing data for lithological mapping in Zhob Ophiolite, Western Pakistan | Qasim, Muhammad, Khan, Shuhab D., Haider, Rashid, Rasheed, Mehboob ur | REFLECTED INFRARED, THERMAL INFRARED, VISIBLE IMAGERY, Visible Radiance | |
| Offset of MODIS land surface temperatures from in situ air temperatures in the upper Kaskawulsh Glacier region (St. Elias Mountains) indicates near-surface ... | Kindstedt, Ingalise, Schild, Kristin M., Winski, Dominic, Kreutz, Karl, Copland, Luke, Campbell, Seth, McConnell, Erin | Land Surface Temperature, Sea Surface Temperature, Emissivity, REFLECTED INFRARED, THERMAL INFRARED, VISIBLE IMAGERY, Visible Radiance, Albedo | |
| Satellite multi-sensor data fusion for soil clay mapping based on the spectral index and spectral bands approaches | Gasmi, Anis, Gomez, Cecile, Chehbouni, Abdelghani, Dhiba, Driss, Elfil, Hamza | REFLECTED INFRARED, THERMAL INFRARED, VISIBLE IMAGERY, Visible Radiance | |
| Multispectral discrimination of spectrally similar hydrothermal minerals in mafic crust: A 5000 km2 ASTER alteration map of the OmanUAE ophiolite | Belgrano, Thomas M., Diamond, Larryn W., Novakovic, Nevena, Hewson, Robert D., Hecker, Christoph A., Wolf, Robin C., de Doliwa Zielinski, Ludwik, Kuhn, Raphael, Gilgen, Samuel A. | REFLECTED INFRARED, THERMAL INFRARED, VISIBLE IMAGERY, Visible Radiance | |
| Multispectral remote sensing for determination the Ultra-mafic complexes distribution and their applications in reducing the equivalent dose from the radioactive wastes | Libeesh, N. K., Naseer, K. A., Arivazhagan, S., Mahmoud, K. A., Sayyed, M. I., Alqahtani, Mohammed S., Yousef, El Sayed | REFLECTED INFRARED, THERMAL INFRARED, VISIBLE IMAGERY, Visible Radiance | |
| Slope streaks in the Yingxiong Range, the western Qaidam Basin and implications for Mars | Cheng, Rui-Lin, He, Hongping, Michalski, Joseph R., Li, Yi-Liang, Li, Long | REFLECTED INFRARED, THERMAL INFRARED, VISIBLE IMAGERY, Visible Radiance | |
| A simple approach for monitoring vegetation change using time series remote sensing analysis: A case study from the Thathe Vondo Area in Limpopo Province, South Africa | Muavhi, Nndanduleni | REFLECTED INFRARED, THERMAL INFRARED, VISIBLE IMAGERY, Visible Radiance | |
| A new hybrid method for epithermal gold exploration using multi-sensor satellite data in Sistan and Baluchestan Province (Iran) | Seifi, Aliyeh, Esmaeily, Ali, Mokhtari, Zahra | REFLECTED INFRARED, THERMAL INFRARED, VISIBLE IMAGERY, Visible Radiance | |
| Application of dirichlet process and support vector machine techniques for mapping alteration zones associated with porphyry copper deposit using ASTER remote sensing imagery | Yousefi, Mastoureh, Tabatabaei, Seyed Hassan, Rikhtehgaran, Reyhaneh, Pour, Amin Beiranvand, Pradhan, Biswajeet | REFLECTED INFRARED, THERMAL INFRARED, VISIBLE IMAGERY, Visible Radiance |
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) | W/m²/sr/μm | uint8 | N/A | 0 to 255 | N/A | N/A |
| SWIR_Band5 | 30 meter resolution SWIR Band 5 (2.145 to 2.185 µm) | W/m²/sr/μm | uint8 | N/A | 0 to 255 | N/A | N/A |
| SWIR_Band6 | 30 meter resolution SWIR Band 6 (2.185 to 2.225 µm) | W/m²/sr/μm | uint8 | N/A | 0 to 255 | N/A | N/A |
| SWIR_Band7 | 30 meter resolution SWIR Band 7 (2.235 to 2.285 µm) | W/m²/sr/μm | uint8 | N/A | 0 to 255 | N/A | N/A |
| SWIR_Band8 | 30 meter resolution SWIR Band 8 (2.295 to 2.365 µm) | W/m²/sr/μm | uint8 | N/A | 0 to 255 | N/A | N/A |
| SWIR_Band9 | 30 meter resolution SWIR Band 9 (2.360 to 2.430 µm) | W/m²/sr/μm | uint8 | N/A | 0 to 255 | N/A | N/A |
| TIR_Band10 | 90 meter resolution TIR Band 10 (8.125 to 8.475 µm) | W/m²/sr/μm | uint16 | N/A | 0 to 65535 | N/A | N/A |
| TIR_Band11 | 90 meter resolution TIR Band 11 (8.475 to 8.825 µm) | W/m²/sr/μm | uint16 | N/A | 0 to 65535 | N/A | N/A |
| TIR_Band12 | 90 meter resolution TIR Band 12 (8.925 to 9.275 µm) | W/m²/sr/μm | uint16 | N/A | 0 to 65535 | N/A | N/A |
| TIR_Band13 | 90 meter resolution TIR Band 13 (10.25 to 10.95 µm) | W/m²/sr/μm | uint16 | N/A | 0 to 65535 | N/A | N/A |
| TIR_Band14 | 90 meter resolution TIR Band 14 (10.95 to 11.65 µm) | W/m²/sr/μm | uint16 | N/A | 0 to 65535 | N/A | N/A |
| VNIR_Band1 | 15 meter resolution VNIR Band 1(0.52 to 0.60 µm) | W/m²/sr/μm | uint8 | N/A | 0 to 255 | N/A | N/A |
| VNIR_Band2 | 15 meter resolution VNIR Band 2 (0.63 to 0.69 µm) | W/m²/sr/μm | uint8 | N/A | 0 to 255 | N/A | N/A |
| VNIR_Band3N | 15 meter resolution VNIR Band 3N (0.78 to 0.86 µm) | W/m²/sr/μm | uint8 | N/A | 0 to 255 | N/A | N/A |