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--- |
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language: "pt" |
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widget: |
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- text: "Poised for launch in mid-2021, the joint NASA-USGS Landsat 9 mission will continue this important data record. In many respects Landsat 9 is a clone of Landsat-8. The Operational Land Imager-2 (OLI-2) is largely identical to Landsat 8 OLI, providing calibrated imagery covering the solar reflected wavelengths. The Thermal Infrared Sensor-2 (TIRS-2) improves upon Landsat 8 TIRS, addressing known issues including stray light incursion and a malfunction of the instrument scene select mirror. In addition, Landsat 9 adds redundancy to TIRS-2, thus upgrading the instrument to a 5-year design life commensurate with other elements of the mission. Initial performance testing of OLI-2 and TIRS-2 indicate that the instruments are of excellent quality and expected to match or improve on Landsat 8 data quality. " |
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example_title: "example 1" |
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- text: "Compared to its predecessor, Jason-3, the two AMR-C radiometer instruments have an external calibration system which enables higher radiometric stability accomplished by moving the secondary mirror between well-defined targets. Sentinel-6 allows continuing the study of the ocean circulation, climate change, and sea-level rise for at least another decade. Besides the external calibration for the AMR heritage radiometer (18.7, 23.8, and 34 GHz channels), the AMR-C contains a high-resolution microwave radiometer (HRMR) with radiometer channels at 90, 130, and 168 GHz. This subsystem allows for a factor of 5× higher spatial resolution at coastal transitions. This article presents a brief description of the instrument and the measured performance of the completed AMR-C-A and AMR-C-B instruments." |
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example_title: "example 2" |
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- text: "Landsat 9 will continue the Landsat data record into its fifth decade with a near-copy build of Landsat 8 with launch scheduled for December 2020. The two instruments on Landsat 9 are Thermal Infrared Sensor-2 (TIRS-2) and Operational Land Imager-2 (OLI-2)." |
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example_title: "example 3" |
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inference: |
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parameters: |
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aggregation_strategy: "first" |
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--- |
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# satellite-instrument-bert-NER |
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For details, please visit the [GitHub link](https://github.com/THU-EarthInformationScienceLab/Satellite-Instrument-NER). |
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## Citation |
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Our [paper](https://www.tandfonline.com/doi/full/10.1080/17538947.2022.2107098) has been published in the International Journal of Digital Earth : |
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```bibtex |
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@article{lin2022satellite, |
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title={Satellite and instrument entity recognition using a pre-trained language model with distant supervision}, |
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author={Lin, Ming and Jin, Meng and Liu, Yufu and Bai, Yuqi}, |
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journal={International Journal of Digital Earth}, |
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volume={15}, |
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number={1}, |
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pages={1290--1304}, |
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year={2022}, |
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publisher={Taylor \& Francis} |
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} |
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``` |
