Investigation of the effect of the incidence angle on land cover classification using fully polarimetric SAR images

Incidence angle is one of the most important imaging parameters that affect polarimetric SAR (PolSAR) image classification. Several studies have examined the land cover classification capability of PolSAR images with different incidence angles. However, most of these studies provide limited physical insights into the mechanism how the variation of incidence angle affects PolSAR image classification. In the present study, land cover classification was conducted by using RADARSAT-2 Wide Fine Quad-Pol (FQ) images acquired at different incidence angles, namely, FQ8 (27.75°), FQ14 (34.20°), and FQ20 (39.95°). Land cover classification capability was examined for each single-incidence angle image and a multi-incidence angle image (i.e., the combination of single-incidence angle images). The multi-incidence angle image produced better classification results than any of the single-incidence angle images, and the different incidence angles exhibited different superiorities in land cover classification. The effect mechanisms of incidence angle variation on land cover classification were investigated by using the polarimetric decomposition theorem that decomposes radar backscatter into single-bounce scattering, double-bounce scattering and volume scattering. Impinging SAR easily penetrated crops to interact with the soil at a small incidence angle. Therefore, the difference in single-bounce scattering between trees and crops was evident in the FQ8 image, which was determined to be suitable for distinguishing between croplands and forests. The single-bounce scattering from bare lands increased with the decrease in incidence angles, whereas that from water changed slightly with the incidence angle variation. Consequently, the FQ8 image exhibited the largest difference in single-bounce scattering between bare lands and water and produced the fewest confusion between them among all the images. The single- and double-bounce scattering from urban areas and forests increased with the decrease in incidence angles. The increase in single- and double-bounce scattering from urban areas was more significant than that from forests because C-band SAR could not easily penetrate the crown layer of forests to interact with the trunks and ground. Therefore, the FQ8 image showed a slightly better performance than the other images in discriminating between urban areas and forests. Compared with other crops and trees, banana trees caused stronger single- and double-bounce scattering because of their large leaves. As a large incidence angle resulted in a long penetration path of radar waves in the crown layer of vegetation, the FQ20 image enhanced the single- and double-bounce scattering differences between banana trees and other vegetation. Thus, the FQ20 image outperformed the other images in identifying banana trees.     

Radar backscatter measurements over saline ice

Abstract

During the 1984 and 1985 winter seasons, radar backscatter measurements were performed on artificial sea ice at the U.S. Army Cold Regions Research and Engineering Laboratory (CRREL) at Hanover, New Hampshire. Radar data were collected at selected frequencies in the 4-17 GHz region for incidence angles from 0 to 60^° with like and cross polarizations. These measurements were performed on smooth, rough, bare and snow-covered saline ice and open water. Backscattering from ice increased with its thickness until the ice was about 1 cm thick and then decreased gradually with further growth. Rough ice and snow-covered ice gave similar returns at 13-6 GHz, but the scattering coefficients of snow-covered ice were lower than that of rough ice at 9-6 GHz. Depolarized scattering from smooth, thin ice and water were much lower than from rough ice and snow-covered ice.     

On the classification of melt season first-year and multi-year sea ice in the Beaufort Sea using Radarsat-2 data

Interpreting satellite microwave sea ice data during the melt season is difficult. Warm temperatures allow for a greater presence of water in the liquid phase at the surface and within the ice, resulting in similar backscattering responses for first-year ice (FYI) and multi-year ice (MYI). Differentiating these ice types is important, especially during summer, in view of the higher presence of seasonal marine traffic, functioning of the ecosystem, and the Inuit use of the marine icescape in summer. In this article, we investigate the similarities between geophysical, thermodynamic, and dielectric characteristics of the late-season MYI and FYI, and discuss how this can lead to a false detection of MYI. The study uses Radarsat-2 data for ice detection during summer. This involves an analysis of co-polarization versus cross-polarization (HH vs. HV), various incident angles (20°, 35°, and 45°), and ice types (FYI vs. MYI). Statistical analyses of the measurements obtained in 2009 identify the difficulty in differentiating ice types during summer. The results show that the physical and electromagnetic properties of the ice surfaces are virtually identical with few differences in the scattering of microwave energy. We conclude with suggestions on how a more effective differentiation of MYI and FYI types in the summer season can be accomplished.     

Evaluation of emission from snow-covered ground for passive microwave remote sensing

This article investigates emission behaviour at frequencies of 18.7, 36.5 and 89 GHz and an incidence angle of 55° over a snow-covered surface at the local scale observation site in Fraser, CO, USA, using both one-layer and two-layer emission models. The models employ the matrix doubling approach to implement the radiative-transfer equation based on dense media theory and the advanced integral equation model. When compared to Ground-Based Passive Microwave Radiometer (GBMR-7) observation on 21 February 2003, both the models could simulate the observed brightness temperature well, but the polarization difference between the observation and the models was smaller for the two-layer emission model than the one-layer model. In addition, we successfully interpreted the emission magnitude and polarization separation of a snow-removed surface by incorporating a Mie scattering transition layer above the soil medium. In this work, we also demonstrated the effect of snow fraction on the brightness temperature difference at 18.7 and 36.5 GHz over a snow-covered surface with the field observation. In conclusion, we demonstrate the snow impact on soil surface with snow depth (SD) and snow fraction variation through modelling and in situ data.     

Fully polarimetric airborne SAR and ERS SAR observations of snow: implications for selection of ENVISAT ASAR modes

Snow cover has a substantial impact on processes involved in the interaction between atmosphere and surface, and the knowledge of snow parameters is important in both climatology and weather forecasting. With the upcoming launch of Advanced Synthetic Aperture Radar (ASAR) instruments on Envisat, enhanced snow-mapping capabilities are foreseen. In this paper fully polarimetric C- and L-band airborne SAR data, ERS SAR and auxiliary data from various snow conditions in mountainous areas are analysed in order to determine the optimum ASAR modes for snow monitoring. The data used in this study are from the Norwegian part of the snow and ice experiment within the European Multi-sensor Airborne Campaign (EMAC'95) acquired in the Kongsfjellet area, located in Norway, 66°?N, 14°?E. Fully polarimetric C- and L-band SAR data from ElectroMagnetic Institute SAR (EMISAR), an airborne instrument operated by the Danish Center for Remote Sensing (DCR), were acquired in March, May, and July 1995. In addition, several ERS SAR, airborne photos, field and auxiliary data were acquired.

A larger separation between wet snow and bare ground in EMISAR C-VV polarisation data was found at high incidence angle (55°) compared to lower incidence angle (45°). Cross-polarized observations from bare ground, dry and wet snow in the incidence angle range 35° to 65° are below the specified Envisat ASAR noise floor of –20–22 dB. The backscattering angular dependency for wet snow and bare ground derived from EMISAR C-VV and ERS SAR data corresponds well, and agrees to some extent with volume and surface scattering model results. The C-band is more sensitive to variation in snow properties than the L-band.     

Investigation of C- and X-band backscattering signatures of Baltic Sea ice

Backscattering signatures of various Baltic Sea ice types and open water leads were measured with the helicopter-borne C- and X-band Helsinki University of Technology scatterometer (HUTSCAT) during six ice research campaigns in 1992–1997. The measurements were conducted at incidence angles of 23° and 45°. The HUTSCAT data were assigned by video imagery into various surface type categories. The ground data provided further classification of the HUTSCAT data into different snow wetness categories (dry, moist and wet snow). Various basic statistical parameters of backscattering signature data were used to study discrimination of open water leads and various ice types. The effect of various physical parameters (e.g. polarization, frequency, snow condition) on the surface type discrimination was investigated. The results from the data analysis can be used to help the development of sea ice classification algorithms for space-borne SAR data (e.g. Radarsat and Envisat). According to the results from the maximum likelihood classification it is not possible to reliably distinguish various surface types in the SAR images only by their backscatter intensity. In general, the best ice type discrimination accuracy is achieved with C-band VH-polarization σ° at an incidence angle of 45°.     

Multi-incidence angle RISAT-1 Hybrid Polarimetric SAR data for large area mapping of maize crop – a case study in Khagaria district,Bihar, India

Analysis of hybrid polarimetric synthetic aperture radar data has gained importance in the last couple of years with the availability of spaceborne data from Radar Imaging Satellite-1 (RISAT-1). RISAT-1 provides right circular transmit and linear receive data in Fine Resolution Stripmap-1 (FRS-1) mode with a swath of 25 km approximately covering 625 km² areas. But an administrative unit, like a district, in India cannot be covered in single FRS-1 acquisition. In this article, the possibility of acquisition of multi-incidence angle FRS-1 data to cover a larger area in three consecutive days over Khagaria district of Bihar State, India, for maize crop discrimination and mapping was investigated. It was assumed that the difference of 3 days in imaging does not affect the backscatter response from maize crop as there will not be much change in the maize crop characteristics in 3 days. The backscatter response of maize crop, which is in maximum vegetative stage, was studied at three incidence angles (viz. 28°, 42°, and 52°). The analysis was carried out for the discrimination of maize crop at each incidence angle in Raney derived hybrid decomposition parameters viz. Odd bounce, Double bounce, and Volume scattering mechanisms. The result shows that there is a slight difference in the backscatter response from maize crop due to the changes in incidence angle from 28° to 42° and has not shown any significant difference from 42° to 52°. However, the maize crop got well discriminated in the scatter plots of volume and double bounce scattering at both 28° and 42° and with odd and volume scattering combinations at 52°. The classification of the multi-incidence angle data resulted in 47,732 ha of maize cropped area in Khagaria district during rabi (winter season), 2014–15 with the producer’s accuracy of 92.00%.     

C-band radar backscatter of Baltic sea ice: theoretical predictions compared with calibrated SAR measurements

Abstract

Airborne Synthetic Aperture Radar (SAR) data have been analysed together with in situ measurements of sea ice during the Bothnian Experiment in Preparation for ERS-1 (BEPERS) in March 1988. Based on the physical properties of the snow-covered level ice, a scattering model is used to predict the C-band like-polarization backscattering coefficient in an experiment area. Both the average backscattering coefficient and the SAR image texture were found to be in good agreement with the scattering model predictions. The backscatter signature of the level ice was found to be dominated by the ice surface r.m.s. height and autocorrelation function. These parameters were determined from profiles of the ice surface height, which were measured using a laser profiler device with sub-mm accuracy. The present model is expected to be accurate when the backscattering is dominated by scattering from the cm-scale snow or ice surface roughness.     

Controls on Eurasian coastal sea ice formation,melt onset and decay from ERS scatterometry: regional contrasts and effects of river influx

Regional and local patterns in the formation, melt onset and disappearance of coastal first-year sea ice (FYI) are observed in the Eurasian Arctic using the C-band (5.3 GHz) European Remote Sensing Satellite (ERS) radar scatterometers. Near-daily time-series (1991–1999) of the radar backscatter coefficient normalized to an incident angle of 40° (σ ⁰ ₄₀ ) and the backscatter- incident angle relationship (B) are examined for test sites near the Severnaya Dvina, Mezen, Pechora, Ob’, Yenisei, Khatanga, Lena, Indigirka and Kolyma rivers. Melt onset of the sea ice surface is associated with abrupt changes in σ ⁰ ₄₀ , with values converging towards ～–17dB. As such, whether backscatter increases or decreases at melt onset is largely determined by contrast with pre-melt backscatter levels. The presence or absence of FYI is designated from low or high values of B, respectively, whereas the addition of an anisotropy criterion further improves discrimination of FYI from open water. A strong regional pattern is seen in the daily temporal variability of both melt onset and ice cover, with maximum variability in the Barents and Kara seas and decreasing variability eastward. Similarly, significant contrasts in the seasonal duration of ice cover are found between western and eastern sites. Seasonal ice cover persists ～144 days for sites in the Barents Sea, but ～293 days for sites farther east in the East Siberian Sea. We speculate that our observed west-east contrasts are due to North Atlantic modulation of salinity, air temperature and cyclone density. Rivers also exert a local effect on ice cover, causing earlier formation (～4 days) and earlier disappearance (～17 days) near river mouths. The hydrological influence of rivers is potentially strong in the Kara, Laptev and East Siberian seas, but weak or absent in the Barents Sea.     

Classification of low-salinity sea ice types by ranging scatterometer

Abstract

A helicopter-borne 8-channel ranging scatterometer HUTSCAT (Helsinki University of Technology Scatterometer) was used to investigate the backscattering behaviour of low-salinity sea ice at 5-4GHz and 9-8 GHz. The measurements were conducted during the BEPERS-88 Sea Ice Campaign in the Gulf of Bothnia, 6-12 March 1988. The backscattering properties of several sea ice types were examined at the two frequencies, using HH, VV, HV, and VH polarization modes. An incidence angle of 23° off nadir was used in order to investigate the feasibility of the ESA ERS-I (launched in July 1991) SAR for sea ice mapping. The capability of the new scatterometer to identify sea ice types was examined using the following radar output products at 8 channels: (a) the backscattering coefficient and (b) the characteristics of the radar return versus range spectrum (range resolution 65 cm).     

The effect of anisotropic reflectance on imaging spectroscopy of snow properties

How does snow's anisotropic directional reflectance affect the mapping of snow properties from imaging spectrometer data? This sensitivity study applies two spectroscopy models to synthetic images of the spectral hemispherical-directional reflectance factor (HDRF) with prescribed snow-covered area and snow grain size. The MEMSCAG model determines both sub-pixel snow-covered area and the grain size of the fractional snow cover. The Nolin/Dozier model analyzes the ice absorption feature that spans wavelength λ≅1.03 μm to estimate snow grain radius when the pixel is fully snow-covered. Retrievals of subpixel snow-covered area with MEMSCAG are progressively more sensitive to the HDRF as grain size decreases, solar zenith angle increases, and fractional snow cover increases. The model overestimates snow cover in the forward reflectance angles by up to +20% and underestimates it in the backward reflectance angles by as much as −15%. Grain size retrievals from both MEMSCAG and Nolin/Dozier are more sensitive to anisotropy as grain size and solar zenith angle increase. MEMSCAG retrievals of grain size are insensitive to snow-covered area. The largest inferred grain sizes occur around a peak in the backward reflectance angles and the smallest generally occur at the largest view angles in the forward direction. Retrievals of albedo from MEMSCAG and Nolin/Dozier are similarly sensitive to anisotropy, with albedo errors up to 5% for a 30° solar zenith angle and up to 10% at 60°. The albedo differences between the two models are less than 0.015 for all grain sizes and solar zenith angles.     

Assessing relationships between Radarsat-2 C-band and structural parameters of a degraded mangrove forest

Relationships were assessed between mangrove structural data (leaf area index (LAI), stem density, basal area, diameter at breast height (DBH)) collected from 61 stands located in a black mangrove (Avicennia germinans)-dominated forest and both single polarized ultra-fine (3 m) and multipolarized fine beam (8 m) Radarsat-2 C-band synthetic aperture radar (SAR) data. The stands examined included representatives from the four types of mangroves that typify this degraded system, specifically: predominantly dead mangrove, poor-condition mangrove, healthy dwarf mangrove, and tall healthy mangrove. The results indicate that the selection of the spatial resolution (3 m vs. 8 m) of the incidence angle (27–39°) and the polarimetric mode greatly influence the relationship between the SAR and mangrove structural data. Moreover, the extent of degradation, i.e. whether dead stands are considered, also determines the strength of the relationships between the various SAR and mangrove parameters.

When dead stands are included, the strongest overall relationships between the ultra-fine backscatter (incidence angle of ～32°) and the various structural parameters were found using the horizontal-horizontal (HH) polarization/horizontal-vertical (HV) polarization ratio. However, if the dead stands are not included, then significant relationships with the ultra-fine data were only calculated with the HH data. Similar results were observed using the corresponding incidence angle (～33°) of the fine beam data. When a shallower incidence angle was considered (～39°), fewer and weaker relationships were calculated. Moreover, no significant relationships were observed if the dead stands were excluded from the sample at this incidence angle. The highest correlation coefficients using the steepest incidence (～27°) were found with the co-polarized (HH, vertical-vertical (VV) polarization) modes. Several polarimetric parameters (entropy, pedestal height, surface roughness, alpha angle) based on the decomposition of the scattering matrix of the fine beam mode at this incidence angle were also found to be significantly correlated to mangrove structural data. The highest correlation (R = 0.71) was recorded for entropy and LAI. When the dead stands were excluded, volume scattering was found to be the most significant polarimetric parameter. Finally, multiple regression models, based on texture measures derived from both the grey level co-occurrence matrix (GLCM) and the sum and difference histogram (SADH) of the ultra-fine data, were developed to estimate mangrove parameters. The results indicate that only models derived from the HH data are significant and that several of these were strong predictors of all but stem density.     

Analysis of TerraSAR-X data and their sensitivity to soil surface parameters over bare agricultural fields

The sensitivity of TerraSAR-X radar signals to surface soil parameters has been examined over agricultural fields, using HH polarization and various incidence angles (26°, 28°, 50°, 52°). The results show that the radar signal is slightly more sensitive to surface roughness at high incidence (50°–52°) than at low incidence (26°–28°). The difference observed in the X-band, between radar signals reflected by the roughest and smoothest areas, reaches a maximum of the order of 5.5 dB at 50°–52°, and 4 dB at 26°–28°. This sensitivity increases in the L-band with PALSAR/ALOS data, for which the dynamics of the return radar signal as a function of soil roughness reach 8 dB at HH38°. In the C-band, ASAR/ENVISAT data (HH and VV polarizations at an incidence angle of 23°) are characterised by a difference of about 4 dB between the signals backscattered by smooth and rough areas.Our results also show that the sensitivity of TerraSAR-X signal to surface roughness decreases in very wet and frozen soil conditions. Moreover, the difference in backscattered signal between smooth and rough fields is greater at high incidence angles. The low-to-high incidence signal ratio (Δσ° = σ_26°–28°/σ_50°–52°) decreases with surface roughness, and has a dynamic range, as a function of surface roughness, smaller than that of the backscattering coefficients at low and high incidences alone. Under very wet soil conditions (for soil moistures between 32% and 41%), the radar signal decreases by about 4 dB. This decrease appears to be independent of incidence angle, and the ratio Δσ° is found to be independent of soil moisture.     

An extended multiple-component scattering model for PolSAR images

An extended multiple-component scattering model (MCSM) is proposed for polarimetric synthetic aperture radar (PolSAR) image decomposition. The MCSM is an extension of the three-component scattering model (TCSM), and it describes single-bounce, double-bounce, volume, helix and wire scattering as elementary scattering mechanisms in the analysis of PolSAR images. The proposed MCSM is demonstrated with German Aerospace Centre (DLR) experimental SAR (ESAR) L-band fully polarized images of the Oberpfaffenhofen Test Site Area (DE), Germany. Double-bounce, helix and wire scattering are found to be predominant in urban areas and the results confirm that the MCSM is effective for analysis of buildings in urban areas. A comparison of the TCSM and its extended models is also implemented.     

Radar detection of flooding beneath the forest canopy: a review

Abstract

Synthetic aperture radar remote sensing is a promising tool for detection of flooding on forested floodplains. The bright appearance of flooded forests on radar images results from double-bounce reflections between smooth water surfaces and tree trunks or branches. Enhanced back scattering at L-band has been shown to occur in a wide variety of forest types, including cypress-tupelo swamps, temperate bottomland hardwoods, spruce bogs, mangroves and tropical floodplain forests. Lack of enhancement is a function of both stand density and branching structure. According to models and measurements, the magnitude of the enhancement is about 3 to 10 dB. Steep incidence angles (20^°-30^°) are optimal for detection of flooding, since some forest types exhibit bright returns only at steeper angles. P-band should prove useful for floodwater mapping in dense stands, and multifrequency polarimetric analysis should allow flooded forests to be distinguished from marshes.     

Analysis of ERS-1 Synthetic Aperture Radar data from Nordaustlandet,Svalbard

Study of the Earth's terrestrial ice masses (glaciers, ice caps and ice sheets), especially the seasonal variation of different surface conditions such as dry snow, wet snow and bare ice, is of particular importance in relation to possible climatic change. Synoptic monitoring techniques using visible and near-infrared satellite imagery are severely limited by the prevalence of cloud cover in the polar regions, and winter observations are impossible as a result of the absence of solar radiation. Consequently, considerable attention is now being focused on the use of imaging radar in the study of large ice masses. In this paper, we present and interpret a time-series of C-band synthetic aperture radar images acquired using the ERS-1 satellite from the Austfonna ice cap in eastern Svalbard. Winter imagery shows little variability, most of the ice cap having a uniform and high (approximately – 3dB) backscatter attributed to ice lenses or to a large effective grain size. Summer imagery shows considerable topographically-related detail, and backscatter values typically 5 to l0 dB less than in winter, which can be explained on the basis of surface scattering from wet snow. However, the marginal areas of the ice cap show a clearly defined zone of high ( –5dB) backscatter in mid- to late-August. It is proposed that this corresponds to the bare ice zone, the high backscatter values being due to scattering from crevasses and meltwater channels, and that the inner boundary of the zone of enhanced backscatter indicates the position of the transient snow line.     

The physical,radiative and microwave scattering characteristics of melt ponds on Arctic landfast sea ice

Melt ponds are an important characteristic of Arctic sea ice because of their control on the surface radiation balance. Little is known about the physical nature of these features and to date there is no operational method for detection of their formation or estimation of their aerial fraction. Coincident in situ observations, aerial surveys and synthetic aperture radar data from a field site in Arctic Canada are compared in an evaluation of the physical, radiative and electrical properties of melt ponds on first-year and multiyear sea ice. Results show that the interrelationships between the thermal diffusivity and conductivity of the snow cover control the mechanisms of snow ablation. Aerial fractions of snow patches, and light and dark coloured melt ponds, show considerable variation both as a function of proximity to land and due to ice type. First-year sea ice is shown to have a water background with discrete snow patches distributed throughout. Multiyear sea ice consists of discrete 'particles' within a snow background. Morphological measurements indicate that snow patches range in size with average areas of from 5 to 20m2 . Pond sizes over multiyear sea ice are also highly variable with averages ranging from 15 to 20m2. The integrated shortwave albedo was measured in the field and averaged to: snow patches (0.64 0.07); light melt ponds (0.29 0.04); and dark melt ponds (0.14 0.03). Snow patch size statistics explained a statistically significant proportion of the surface shortwave albedo. We found that microwave scattering could be used to obtain a measure of the onset ofmelt and had utility in detecting subtle details ofthe thermodynamic transition from winter through early melt into pond formation. We formalized a statistical relationship between microwave scattering and surface climatological albedo (sigma-alpha relationship). We found the relationship valid only for landfast firstyear sea ice under windy conditions. We conclude with a discussion of the role of surface wind stress and diurnal cycling in specification of the sigma-alpha relationship.     

Modelling temporal variations in microwave backscattering from reed marshes

A full understanding of radar backscattering characteristics and their seasonal variations is one of the important ways to analyse the growth conditions in wetlands. This research simulated seasonal C-band and L-band synthetic aperture radar (SAR) backscattering from reed marshes using a refined version of the electromagnetic (REM) model, which was first validated by time series of multimode SAR observations at the experimental site used. Then, two factors including sensor parameters and vegetation structure, which influence the temporal evolution of the radar response from reed marshes, were assessed. The results demonstrate that the radar response is closely related to growth processes in the reed marsh. At the early growth stage when reed marshes are sparse, the double-bounce mechanism was dominant at all the incidence angles of C-band radar, but for L-band radar, strong specular reflection was produced from the smooth water if the incidence angle is lower than 25°. It was also found that the sensitivity to the density and height of reed marshes is greater for L-band radar than at the C-band, indicating that L-band backscattering may be useful for reed marsh biomass retrieval.     

Multi‐frequency scatterometer measurements on water surfaces agitated by artificial and natural rain

Images of rain events over the ocean acquired by a multi‐frequency/multi‐polarization Synthetic Aperture Radar (SAR) show different radar contrasts at different frequencies and polarizations. In order to better understand these effects, field and laboratory experiments were performed at different rain rates and wind speeds with scatterometers working at different radar frequencies, polarizations, and incidence angles. Our results show that the dominant scattering mechanism on a rain‐roughened water surface, observed at VV polarization, at all incidence angles is Bragg scattering from ring waves. At HH polarization the radar backscatter is caused by both ring waves and non‐propagating splash products, with the dominating effect depending on incidence angle. The reduction and enhancement of the surface roughness by ring waves and sub‐surface phenomena, respectively, result in a transition wavenumber between reduction of the radar backscattering and its enhancement of about 100 rad m^?1. We assume that this transition wavenumber depends on the drop‐size distribution of the rain. Taking into consideration the different dependencies of the radar backscatter at different frequencies and polarizations on rain rate, we suggest a method to estimate rain rates by calculating the ratio of the radar cross‐sections at L band, VV polarization and at C band, HV polarization. Provided an availability of SAR data at the respective frequency–polarization combinations, this method allows for investigating the nature of small‐scale (convective) rain events over the ocean.     

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.