Chinatsu Yonezawa

Analysis of Urban Areas Affected by the 2011 Off the Pacific Coast of Tohoku Earthquake and Tsunami With L-Band SAR Full-Polarimetric Mode

The 2011 off the Pacific coast of Tohoku earthquake was observed using phased array type L-band synthetic aperture radar (PALSAR) and polarimetric and interferometric airborne synthetic aperture radar (PiSAR) full-polarimetric data. Representative polarimetric parameters were calculated from full-polarimetric data for urban areas, where most of the buildings were destroyed by the subsequent tsunami, in order to identify the radar scattering mechanism in these areas. These parameters were compared with the ones observed before the disaster. The full-polarimetric data analysis shows that the affected areas were represented by surface scattering with high entropy, indicating that a complex scattering mechanism with nonreflection symmetry is involved. The coherence between HH and VV and that between RR and LL are the most important factors in distinguishing the disaster areas from the data. Alpha angle and anisotropy are also important factors in this respect; however, anisotropy derived from PiSAR data does not show the difference between areas with collapsed and still-standing buildings. This may be because the azimuth slope angle for the target urban area is different before and after the disaster for both PALSAR and PiSAR data. Owing to the double-bounce scattering from azimuthally rotated targets in the urban areas, the power estimated from the four-component decomposition model is distributed within a wide range not only for double-bounce scattering but also for volume and surface scatterings. Additionally, the model does not show a systematic change between before and after the disaster, and σ0 for four polarizations with 30-m resolution does not show a systematic difference.

Polarimetric Decomposition Analysis of ALOS PALSAR Observation Data before and after a Landslide Event

Radar scattering mechanisms over landslide areas were studied using representative full polarimetric parameters: Freeman–Durden decomposition, and eigenvalue–eigenvector decomposition. Full polarimetric ALOS (Advanced Land Observation Satellite) PALSAR (Phased Array type L-band Synthetic Aperture Radar) datasets were used to examine landslides caused by the 2008 Iwate-Miyagi Nairiku Earthquake in northern Japan. The Freeman–Durden decomposition indicates that areas affected by large-scale landslides show dominance of the surface scattering component in both ascending and descending orbit data. The polarimetric parameters of eigenvalue–eigenvector decomposition, such as entropy, anisotropy, and alpha angle, were also computed over the landslide areas. Unsupervised classification based on the H- plane explicitly distinguishes landslide areas from others such as forest, water, and snow-covered areas, but does not perform well for farmland. A landslide area is difficult to recognize from a single-polarization image, whereas it is clearly extracted on the full polarimetric data obtained after the earthquake. From these results, we conclude that 30-m resolution full polarimetric data are more useful than 10-m resolution single-polarization PALSAR data in classifying land coverage, and are better suited to detect landslide areas. Additional information, such as pre-landslide imagery, is needed to distinguish landslide areas from farmland or bare soil.

Growth monitoring and classification of rice fields using multitemporal RADARSAT-2 full-polarimetric data

Spaceborne synthetic aperture radar (SAR) can be used for agricultural monitoring. In this study, three single-polarimetric and four full-polarimetric observation data sets were analysed. A rice paddy field in northern Japan was used as the study site; the data for this site were obtained using RADARSAT-2, which carries a full-polarimetric C-band SAR. Soybean and grass fields were also present within the paddy fields. The temporal change in the backscattering coefficient of the rice paddy fields for the single-polarization data agreed with the temporal change obtained for a rice growth model based on radiative transfer theory. A three-component decomposition approach was applied to the full-polarimetric data. With each rice growth stage, the volume scattering component ratio increased, whereas the surface scattering component ratio generally decreased. The soybean and grass fields showed a smaller double-bounce scattering component than the rice fields for all the acquired data. The results of this study show that multitemporal observation by full-polarimetric SAR has great potential to be utilized for estimating rice-planted areas and monitoring rice growth.

ALOS/PALSAR full polarimetric observations of the Iwate–Miyagi Nairiku earthquake of 2008

We analysed Advanced Land Observing Satellite (ALOS) Phased Array type L-band Synthetic Aperture Radar (PALSAR) data on the areas damaged by the Iwate–Miyagi Nairiku earthquake that struck Japan in 2008. The observations before and after the earthquake have been carried out in the full polarimetric mode. We observed the dominance of surface scattering of the three-component scattering model in the landslide areas and identified 11 of the 13 landslide areas. However, we also detected vacant pieces of land, pastures and other land bodies. The possible landslide areas are estimated for 102 patch areas, of which 36 correspond to the actual landslide areas. This method is useful to detect the landslide area when the land classification map or optical image taken before a disaster is available. We propose the use of σ0 VH information to distinguish the landslide areas from the other areas. Since σ0 VH is sensitive to the surface roughness of an area, vacant pieces of land and pastures, which have a relatively low surface roughness, can be distinguished from the landslide areas, which have a high surface roughness. By combining the surface scattering and the σ0 VH filter, the number of possible landslide areas is reduced from 102 to 54, which include the actual landslide areas except for some small patch areas.

Urban damage detection using decorrelation of SAR interferometric data

We investigate decreasing interferometric correlation of SAR data caused by building damages in urban area. We analyze JERS-1 SAR data pairs straddling the occurrence of the 1995 Hyogoken-nanbu earthquake. The distribution patterns of the pixels which indicated interferometric decorrelation correspond well with the building damaged area reported by the ground survey. The degree of decorrelation shows obvious correlation with the damaged building ratio on the area in each block and measured seismic intensity from strong motion data. The result of this study indicates a fact that the building damage causes the interferometric decorrelation. We also try to extract the urban area damaged by the 2001 Gujrat (western India) earthquake using Radarsat data. For practical use of interferometric decorrelation to detect the urban damage, effect of building type and urban concentration should be examined. These results show the applicability for interferometric analysis of SAR data to urban disaster management.

Effect of clouds on ERS SAR interferograms applied to land subsidence detection

We analysed ERS-1, 2 Synthetic Aperture Radar (SAR) interferometric data pairs from the Kanto Plains, which includes Tokyo, Japan. Fringe features that were independent of actual land deformations were found from the interferograms obtained. A SPOT HRV image acquired 18 min after the SAR data provides strong evidence for cloud perturbation of SAR data, because it reveals patterns of cloud distribution that are similar to the fringe features in the interferograms. GMS-5 visible-channel images indicate the direction of cloud movement, which supports the presence of cloud-induced phase delays, but the spatial resolution of GMS-5 data is not fine enough for comparison with the SAR data. Other interferograms indicate the land subsidence patterns that agree with known levelling processes. The extraction of information on land subsidence is possible from the area where the atmospheric effects are small. The results of this study suggest that optical sensor imagery with a spatial resolution equivalent to that of the SAR imagery is required for the evaluation of cloud-induced perturbations in radar signals.

Multitemporal Fluctuations in L-Band Backscatter From a Japanese Forest

The temporal variations (diurnal and annual) in arboreal (ε_Tree) and bare soil (ε_Soil) dielectric constants and their correlation with precipitation were examined for several trees in Japan. A significant (1 σ (standard deviation) and 2 σ) ε_Tree increase is observed after rainfall at 89.8% and 90.5% probability. However, rainfall does not always induce significant ε_Tree increases. Rainfall of more than 5 mm/day can induce 1 σ ε_Tree Tree increase at a 59.6% probability. In order to examine whether the increase in εTree affects the L-band σ⁰ variation in a forest, the four-year temporal variation of the L-band backscattering coefficient (σ⁰) was estimated from observations by the Advanced Land Observing Satellite Phased Array type L-band Synthetic Aperture Radar. Observed maximum absolute deviations from the mean over the forest area were 1.0 and 1.2 dB for σ_HH⁰ and σ_HV⁰, respectively, and 4.0 and 3.0 dB over open land. σ⁰ and rainfall correlations show that ε_Tree and σ_Forest⁰ are proportional to precipitation integrated over seven or eight days; ε_Soil and σ_{Open land}⁰ are proportional to precipitation integrated over three days. This finding indicates that ε_Tree variations influence σ_{Forest areas}⁰. A stronger correlation between σ_HV⁰ and precipitation is observed in several sites with low σ_HV⁰, where less biomass is expected, and several sites with high σ_HV⁰, where more biomass is expected. A weaker correlation between σ_HV⁰ and precipitation is observed for several sites with high σ_HV⁰. These differences may be explained by the different contributions of double bounce scattering and potential transpiration, which is a measure of the ability of the atmosphere to remove water from the surface through the processes of transpiration. The two other results were as follows: 1) The functional relation between aboveground biomass and σ⁰ showed dependence on precipitation data, this being an effect connected with seasonal changes of the ε_Tree. This experiment reinforces the fact that the dry season is preferable for retrieval of woody biomass from inversion of the functional dependence of SAR backscatter and for avoiding the influence of rainfall. 2) The complex dielectric constant for a tree trunk, which is measured between 0.2 and 6 GHz, indicates that free water is dominant in the measured tree.

Agricultural field observation by space and airborne polarimetric L-band SAR data

Full polarimetric space- and air-borne L-band SAR data acquired on the same day were analyzed. The target areas were agricultural fields, including paddy in the maturation stage, that were severely damaged by a tsunami three years earlier. Lodging of paddy was found in some fields. Three-and four-component decomposition and eigenvalue-eigenvector decomposition analysis were performed. On paddy fields, the dominant component was double-bounce scattering. Paddy fields including lodged paddy showed larger volume scattering ratio than paddy fields without lodged paddy in Pi-SAR-L2 data. On soybean, weed, and bare-soil fields, surface scattering was dominant in a four-component decomposition. Paddy field and other fields were separated by a threshold of alpha angle in the eigenvalue-eigenvector decomposition. Subtle differences were found although PALSAR-2 and Pi-SAR-L2 data behaved almost similarly. L-band SAR is suitable for rice field extraction during this season.

COSMO-SkyMed data observation of reconstruction process in agricultural fields damaged by the March 11 2011 tsunami

To extract annual changes in paddy field areas, we analyzed COSMO-SkyMed observation data relating to an area damaged by the 2011 Tohoku earthquake. Backscattering coefficient (gamma naught: γ0) values were calculated for images obtained on June 4 2011, June 2 2012, and June 9 2013. Mean backscattering coefficients were calculated for each agricultural parcel using vector boundary data. Areas of relatively low backscattering coefficients correspond with fields that were flooded in relation to rice planting, or fields that have not been repaired. The area of low backscattering coefficients expanded annually between the inland area and the coastal area, showing the progress of paddy field reconstruction. The spatial distribution of COSMO-SkyMed data backscattering coefficient patterns in 2011 were similar to that of TerraSAR-X data obtained 1 day after the COSMO-SkyMed data.

Detection of Ice-Jam Floods Using PALSAR Full-Polarimetry Data

The Lena River in Russia at its intersection with the Arctic Ocean is subject to spring floods such as those caused by ice jams. In such cases, snowmelt occurs at lower latitudes and river water freezes at higher latitudes. That snowmelt is blocked by the frozen river water, which induces ice-jam floods every year. Full-polarimetric parameters obtained from the Phased Array Type L-band Synthetic Aperture Radar (PALSAR) were used to determine the most suitable ones for detecting ice-jam floods. Representative full-polarimetric parameters were calculated, including σ0, entropy/α/anisotropy, the four-component decomposition model, and coherence. The PALSAR mosaic image helped to identify two large-scale floods, at Ytyk Kiuel on May 18, 2007, and at Berdigestiakh on July 15, 2007. These flood events were confirmed by articles published in the local newspaper and by optical sensor images. The optimum detectability for the flooding area was derived by the difference of polarimetric coherence, γ(HH + VV) − (HH − VV), obtained with and without the consideration of flooding. Total accuracy was 92.9%, and user and producer accuracies for detection of the flooded areas were 53.5% and 72.8%, respectively. The four-component decomposition analysis indicated that flood detection using γ(HH + VV) − (HH − VV) is applicable to low-height vegetation areas and urban regions.