metadata
language: pt
widget:
- 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.
example_title: example 1
- 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.
example_title: example 2
- 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).
example_title: example 3
inference:
parameters:
aggregation_strategy: first
satellite-instrument-bert-NER
For details, please visit the GitHub link.
Citation
Our paper has been published in the International Journal of Digital Earth :
@article{lin2022satellite,
title={Satellite and instrument entity recognition using a pre-trained language model with distant supervision},
author={Lin, Ming and Jin, Meng and Liu, Yufu and Bai, Yuqi},
journal={International Journal of Digital Earth},
volume={15},
number={1},
pages={1290--1304},
year={2022},
publisher={Taylor \& Francis}
}