Assessing the Impact of Precipitation on L-band SAR Forest Observation: An ALOS-2 Big Data Case Study in the Tropics

被引：0
|
作者：
Koyama, Christian N. [1 ]
Watanabe, Manabu [1 ]
Tadono, Takeo [2 ]
Shimada, Masanobu [1 ,2 ]
机构：
[1] Tokyo Denki Univ, Hatoyama, Saitama 3500394, Japan
[2] JAXA, Sengen 2-1-1, Tsukuba, Ibaraki 3058505, Japan
来源：
13TH EUROPEAN CONFERENCE ON SYNTHETIC APERTURE RADAR, EUSAR 2021 | 2021年
关键词：
D O I：
暂无
中图分类号：
TP7 [遥感技术];
学科分类号：
081102 ; 0816 ; 081602 ; 083002 ; 1404 ;
摘要：
Forest monitoring is a prime mission for SAR earth observation. However, the reliability of applications like biomass estimation and deforestation detection is largely hampered by spatial-temporal backscatter fluctuations. In the tropics, these variabilities are mainly driven by the rainfall regime. In preparation for the golden age of L-band SAR, this paper presents the first comprehensive study on the impact of rainfall on L-band EO data. Based on a big data analysis using 300 TB of ALOS-2 images together with 1.5 billion rainfall datasets, pantropic gamma(0)/rainfall correlation maps were produced which provide all-new information on the precipitation effects in SAR imaging.
引用
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页码：10 / 15
页数：6
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