The Hyperspectral Infrared Imager or HyspIRI mission will study the world’s ecosystems and provide critical information on natural disasters such as volcanoes, wildfires and drought. HyspIRI will be able to identify the type of vegetation that is present and whether the vegetation is healthy. The mission will provide a benchmark on the state of the worlds ecosystems against which future changes can be assessed. The mission will also assess the pre-eruptive behavior of volcanoes and the likelihood of future eruptions as well as the carbon and other gases released from wildfires.
Organization
Launch Date
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Flight Project
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The Hyperspectral Infrared Imager or HyspIRI mission will study the world’s ecosystems and provide critical information on natural disasters such as volcanoes, wildfires and drought. HyspIRI will be able to identify the type of vegetation that is present and whether the vegetation is healthy. The mission will provide a benchmark on the state of the worlds ecosystems against which future changes can be assessed. The mission will also assess the pre-eruptive behavior of volcanoes and the likelihood of future eruptions as well as the carbon and other gases released from wildfires.
Related Publications
2018.
"Using imaging spectroscopy to detect variation in terrestrial ecosystem productivity across a water‐stressed landscape.",
Ecological Applications,
28
(5):
1313-1324
[10.1002/eap.1733]
[Journal Article/Letter]
2015.
"Remotely estimating photosynthetic capacity, and its response to temperature, in vegetation canopies using imaging spectroscopy.",
Remote Sensing of Environment,
167
78-87
[10.1016/j.rse.2015.05.024]
[Journal Article/Letter]
2013.
"Disentangling the contribution of biological and physical properties of leaves and canopies in imaging spectroscopy data.",
Proceedings of the National Academy of Sciences,
110
(12):
[10.1073/pnas.1300952110]
[Journal Article/Letter]
2014.
"Spectroscopic determination of leaf morphological and biochemical traits for northern temperate and boreal tree species.",
Ecological Applications,
24
(7):
1651-1669
[10.1890/13-2110.1]
[Journal Article/Letter]
2015.
"An LUT-Based Inversion of DART Model to Estimate Forest LAI from Hyperspectral Data.",
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing,
8
(6):
3147-3160
[10.1109/jstars.2015.2401515]
[Journal Article/Letter]