詳細な積雪分布観測 のための偏波レーダ活用技術開発
| Project/Area Number |
25820172
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| Research Category |
Grant-in-Aid for Young Scientists (B)
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| Allocation Type | Multi-year Fund |
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| Research Field |
Measurement engineering
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| Research Institution | Niigata University |
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Principal Investigator |
PARK SANGUN 新潟大学, 自然科学系, 助教 (20576392)
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| Project Period (FY) |
2013-04-01 – 2014-03-31
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| Project Status |
Discontinued (Fiscal Year 2013)
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| Budget Amount *help |
¥4,420,000 (Direct Cost: ¥3,400,000、Indirect Cost: ¥1,020,000)
Fiscal Year 2014: ¥2,210,000 (Direct Cost: ¥1,700,000、Indirect Cost: ¥510,000)
Fiscal Year 2013: ¥2,210,000 (Direct Cost: ¥1,700,000、Indirect Cost: ¥510,000)
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| Keywords | リモートセンシング / センシング情報処理 / 地球計測 / 環境計測 / 水圈環境 |
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| Research Abstract |
Since snow is a highly dynamic media in conjunction with energy fluxes, wind, moisture, water vapor, and pressure, integrated observation of snow-covered areas from multi-frequency SAR data can play an important role in mapping and monitoring snow properties and dynamics. This study aims to evaluate the capability of L-band space-borne Synthetic Aperture Radar (SAR) for detection of seasonal snow-covered areas. The seasonal change of backscattering from a snow-covered mountainous ecosystem was studied using the Japanese ALOS/PALSAR system. This study places the focus on utilization of the fully polarimetric scattering observation, maximizing information on the seasonal changes of snow-cover. The selected study site is Uonuma area in Southern Niigata Prefecture. This area is on the northern edge of the Japanese Alps and has some of the heaviest snowfall in the country due to a winter monsoon blowing from Siberia to the islands of Japan.
In this study, vector scattering information of L-band signal and its snow-induced changes have been originally investigated. The effect of topography as well as snowpack thickness on SAR signal has been newly discovered. Based on the characteristic seasonal changes of polarimetric parameters, a new method to map snow-covered areas has been developed using an information fusion approach. Snow extent can be identified successfully by combining polarimetric indices. This study has elucidated that the L-band fully polarimetric spaceborne SAR, such as ALOS-2, will provide sufficient information on seasonal snow.
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Report
(1 results)
Research Products
(3 results)
