"Satellite Imagery" is a descriptor in the National Library of Medicine's controlled vocabulary thesaurus,
MeSH (Medical Subject Headings). Descriptors are arranged in a hierarchical structure,
which enables searching at various levels of specificity.
Composition of images of EARTH or other planets from data collected during SPACE FLIGHT by remote sensing instruments onboard SPACECRAFT. The satellite sensor systems measure and record absorbed, emitted, or reflected energy across the spectra, as well as global position and time.
| Descriptor ID |
D063809
|
| MeSH Number(s) |
E05.925.500.500 L01.178.847.550.500 L01.178.847.675.500.500
|
| Concept/Terms |
Satellite Imagery- Satellite Imagery
- Imageries, Satellite
- Imagery, Satellite
- Satellite Imageries
|
Below are MeSH descriptors whose meaning is more general than "Satellite Imagery".
Below are MeSH descriptors whose meaning is more specific than "Satellite Imagery".
This graph shows the total number of publications written about "Satellite Imagery" by people in this website by year, and whether "Satellite Imagery" was a major or minor topic of these publications.
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| Year | Major Topic | Minor Topic | Total |
|---|
| 2013 | 1 | 0 | 1 |
| 2015 | 1 | 0 | 1 |
| 2016 | 2 | 1 | 3 |
| 2019 | 1 | 0 | 1 |
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Below are the most recent publications written about "Satellite Imagery" by people in Profiles.
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TROPOMI reveals dry-season increase of solar-induced chlorophyll fluorescence in the Amazon forest. Proc Natl Acad Sci U S A. 2019 10 29; 116(44):22393-22398.
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Spatiotemporal patterns of paddy rice croplands in China and India from 2000 to 2015. Sci Total Environ. 2017 Feb 01; 579:82-92.
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Assessing agricultural drought in summer over Oklahoma Mesonet sites using the water-related vegetation index from MODIS. Int J Biometeorol. 2017 Feb; 61(2):377-390.
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Mapping forests in monsoon Asia with ALOS PALSAR 50-m mosaic images and MODIS imagery in 2010. Sci Rep. 2016 Feb 11; 6:20880.
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Insect-inspired navigation algorithm for an aerial agent using satellite imagery. PLoS One. 2015; 10(4):e0122077.
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Rivers and flooded areas identified by medium-resolution remote sensing improve risk prediction of the highly pathogenic avian influenza H5N1 in Thailand. Geospat Health. 2013 Nov; 8(1):193-201.