The study and monitoring of active volcanic regions such as Long Valley Caldera is well served by remote sensing methods for several reasons.

• Volcanic activity occurs on time scales that are coincident with the repeat times of both airborne and spaceborne instruments.
• The inherent danger in field monitoring of active volcanoes can be avoided through remote observations.
• Many types of analyses can be made with only one or two kinds of data and with only one acquistion time period.

The Long Valley Observatory created in 1998 by the USGS has at its disposal a myriad of remotely sensed data that provides scientists with new ways to monitor hazard and study volcanic processes and phenomena.

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Background

Long Valley Caldera is a 17km x 32 km caldera located in eastern California that formed approximately 760,000 years ago. Since then, the caldera has been home to post-caldera volcanism and an extensive hydrothermal system. Beginning in 1980, the caldera entered a state of renewed restlessness. This restlessness, which has continued to the present day, is embodied by both large and small seismic swarms in and around the caldera (many of which are thought to accompany magma intrusion at depth), reinflation of the central resurgent dome at rates of 2-3cm/yr, and massive exhalation of CO2 gas at Mammoth Mountain, a small stratovolcano located on the southwestern rim of the caldera.

In order to study the volcanic activity at Long Valley, a wide array of remotely sensed data is being amassed. Below are examples of imagery used in studies of Long Valley:

LANDSAT-7 This is a Landsat Enhanced Thematic Mapper multispectral image from 1999, taken of the central Sierra Nevada mountain range. Central Valley is visible to the west, while Mono Lake and Long Valley Caldera (outlined in yellow) are seen to the east. A near-infrared treatment makes vegetation appear red. Images such as these are excellent for regional studies of geology and biology; especially those requiring a high temporal resolution. The blue rectangle shows the outline of the SPOT image below.

Dataset: Landsat ETM+        Image credit: Image courtesy USGS/Processing by Brigette Martini, UCSC Characteristics: 30m spatial resolution, 185km swath width, seven bands spanning the visible, infrared, and thermal wavelengths, revist time of 16 days Processing Shown: Georeferenced; Near-Infrared treatment

SPOT These two mosaickedSPOT images extend from the central Sierra in the west, to the White Mountains in the east. The SPOT satellite has a multispectral sensor (SPOT-XS), however the spatial resolution is 20m. The SPOT-PAN band shown to the left, has a 10m resolution and can be used to "sharpen" not only SPOT imagery, but other low spatial resolution imagery such as Landsat. The blue rectangle shows the outline of the AVIRIS image below.

Dataset: SPOT       Image credit: Image courtesy UCSB/Processing by Brigette Martini, UCSC Characteristics: 10m spatial resolution, 60x80km swath width, one panchromatic band spanning the visible wavelengths Processing Shown: Georeferenced; Two SPOT images mosaicked together; Gaussian stretch

AVIRIS This is one scene from a hyperspectral AVIRIS flightline flown north-south in 1996. The southern flank of Mammoth Mt. is visible at the top of the image, while Devil's Postpile and the Sierran front are shown to the south. Vegetation appears red, water is black, and the high albedo volcanic rocks of Mammoth are bright white (it's not snow!). The advantage of AVIRIS over satellite-borne instruments are the many bands that allow for identification of earth materials based on their spectral signatures vs. mere discrimination of materials. However, the data size, processing time, and cost for hyperspectral imagery is significantly more than multispectral data such as Landsat. It also lacks the high temporal resolution of satellite acquistions. The blue rectangle shows the outline of the next HyMap image.

Dataset: AVIRIS       Image credit: Image courtesy of JPL/Processing by Brigette Martini, UCSC Characteristics: 20m spatial resolution, 10.5km swath width, 224 bands spanning the visible and near-infrared, flown aboard the NASA ER-2 plane, SNR 400:1 Processing Shown: Atmospherically corrected; Near-Infrared treatment

HyMap This is one third of an east-west HyMap flightline extending west from the Sierran front, over Mammoth Mt., and the town of Mammoth Lakes, and out east into the Caldera. Though it's a hyperspectral instrument like AVIRIS, HyMap's advantage in this case is its superior spatial resolution (3m vs. 20m) and Signal-to-Noise Ratio (HyMap SNR >1000:1). Again, the data size and processing time for this imagery is significant. One should be sure that hyperspectral capabilities are really what is needed to address a particular problem

Dataset: HyMap       Image credit: Brigette Martini, UCSC Characteristics: 3-5m spatial resolution, 2.3km swath width, 126 bands spanning the visible and near-infrared, flown aboard a Twin Otter small aircraft, SNR 1000:1 Processing Shown: Atmospherically corrected; Georeferenced; Near-infrared treatment

DOQs This Digital Ortho-Photo Quadrangle covers one quarter of a USGS 7.5 minute topographic quadrangle. These are constructed using mosaicked and georeferenced aerial photographs. It covers Mammoth Mt. in the south and extends north along the front range of the Sierra and the western boundary of the Caldera. DOQs exist for many places in the U.S., though coverage is not complete yet. Such images are used in georectifying other forms of data or increasing spatial resolutions of data with poorer resolutions. They can also be used for any form of standard air photo analysis.

Dataset: DOQ       Image credit: Image courtesy USGS/Processing by Brigette Martini, UCSC Characteristics: 1m spatial resolution, 10.2 x 12.8km in size, panchromatic aerial photo Processing Shown: Orthorectified; Gaussian stretch