ALOS-2 launch and initial checkout result

Arikawa, Yasuyoshi; Kankaku, Yukihiro; Saruwatari, Hideki; Hatooka, Yasushi; Suzuki, Shuichi

doi:10.1117/12.2067157

Cited by 2 publications

(1 citation statement)

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“…RISAT-1, the first radar satellite with CP measurement capability, was successfully launched in April 2012 [ 8 ]. ALOS-2, launched in 2014, also includes CP as in the experimental imaging model in 2014 [ 9 ]. Moreover, in near future the RADARSAT Constellation Mission (RCM) of Canada will launch a C-band CP SAR satellite as well [ 10 ].…”

Section: Introductionmentioning

confidence: 99%

Inversion of Rice Biophysical Parameters Using Simulated Compact Polarimetric SAR C-Band Data

Guo

Shao

et al. 2018

Sensors

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Timely and accurate estimation of rice parameters plays a significant role in rice monitoring and yield forecasting for ensuring food security. Compact-polarimetric (CP) synthetic aperture radar (SAR), a good compromise between the dual- and quad-polarized SARs, is an important part of the new generation of Earth observation systems. In this paper, the ability of CP SAR data to retrieve rice biophysical parameters was explored using a modified water cloud model. The results showed that S1 was superior to other CP variables in rice height inversion with a coefficient of determination (R2) of 0.92 and a root-mean-square error (RMSE) of 5.81 cm. RL was the most suitable for inverting the volumetric water content of the rice canopy, with an R2 of 0.95 and a RMSE of 0.31 kg/m3. The m-χ decomposition produced the highest accuracies for the ear biomass: R2 was 0.89 and RMSE was 0.17 kg/m2. The highest accuracy of leaf area index (LAI) retrieval was obtained for RH (right circular transmit and horizontal linear receive) with an R2 of 0.79 and a RMSE of 0.33. This study illustrated the capability of CP SAR data with respect to retrieval of rice biophysical parameters, especially for height, volumetric water content of the rice canopy, and ear biomass, and this mode may offer the best option for rice-monitoring applications because of swath coverage.

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Section: Introductionmentioning

confidence: 99%

Inversion of Rice Biophysical Parameters Using Simulated Compact Polarimetric SAR C-Band Data

Guo

Shao

et al. 2018

Sensors

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Comparative Study on Potential Landslide Identification with ALOS-2 and Sentinel-1A Data in Heavy Forest Reach, Upstream of the Jinsha River

et al. 2022

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Many SAR satellites such as the ALOS-2 satellite and Sentinel-1A satellite can be used in Interferometric Synthetic Aperture Radar (InSAR) to identify landslides. As their wavelengths are different, they can perform differently in the same area. In this study, we selected the alpine canyon heavy forest area of the Baishugong–Shangjiangxiang section of the Jinsha River with a strong uplift of faults and folds as the study area. The Small Baseline Subset (SBAS)–InSAR was used for landslide identification to compare the reliability and applicability of L-band ALOS-2 data and C-band Sentinel-1A data. In total, 13 potential landslides were identified, of which 12 potential landslides were identified by ALOS-2 data, two landslides were identified by Sentinel-1A data, and the Kongzhigong (KZG) landslide was identified by both datasets. Then, the field investigation was used to verify the identification results and analyze the genetic mechanism of four typical landslides. Both the Duila (DL) and KZG landslides are bedding slip, while the Jirenhe (JRH) and Maopo (MP) landslides are creep–pull failure. Then, the difference between ALOS-2 and Sentinel-1A data on KZG landslide was compared. A total of 35,961 deformation points on the KZG landslide were obtained using ALOS-2 data, which are relatively dense. Meanwhile, a total of 7715 deformation points were obtained by Sentinel-1A data, which are relatively scattered and seriously lacking, especially in areas with dense vegetation coverage. Comparing the advantages of ALOS-2 and Sentinel-1A data and the identification results of potential landslides, the reliability and applicability of ALOS-2 data in the identification of potential landslides in areas with dense vegetation cover and complex geological conditions were confirmed from the aspects of vegetation cover, topography, field investigation, and comparative analysis of typical landslides.

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ALOS-2 launch and initial checkout result

Cited by 2 publications

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Inversion of Rice Biophysical Parameters Using Simulated Compact Polarimetric SAR C-Band Data

Inversion of Rice Biophysical Parameters Using Simulated Compact Polarimetric SAR C-Band Data

Comparative Study on Potential Landslide Identification with ALOS-2 and Sentinel-1A Data in Heavy Forest Reach, Upstream of the Jinsha River

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