L-band HH Research Articles

Synthetic aperture radar polarised backscattering behaviour in partially inundated agricultural fields

ABSTRACT A methodology for classifying rainfed paddy fields based on their hydrological conditions is lacking. This study analysed the behaviour of synthetic aperture radar (SAR) backscatter coefficients at each polarisation and cross-polarisation ratio index in a rainfed rice paddy field with a partially waterlogged surface. The SAR polarisations used were the VH and VV of the C-band SAR Sentinel-1 and the HV and HH of the L-band SAR Palsar-2. The relationship between backscatter coefficient and terrains including topographic categories and local relative elevation, which affect waterlogging conditions in rainfed paddy fields, were evaluated. The VV of C-band, and HH and HV of L-band showed different patterns in the time series variation according to the topographic categories. We observed that the combination of L-band HH and HV could be used to assess waterlogging conditions because they differ depending on variations in local elevation. The study results suggest that future studies can evaluate the microtopography and associated local hydrological environment using the combination of L-band HH and HV backscatter coefficient.

Vegetation Effects on Soil Moisture Retrieval from Water Cloud Model Using PALSAR-2 for Oil Palm Trees

In oil palm crop, soil fertility is less important than the physical soil characteristics. It is important to have a balance and sufficient soil moisture to sustain high yields in oil palm plantations. However, conventional methods of soil moisture determination are laborious and time-consuming with limited coverage and accuracy. In this research, we evaluated synthetic aperture radar (SAR) and in-situ observations at an oil palm plantation to determine SAR signal sensitivity to oil palm crop by means of water cloud model (WCM) inversion for retrieving soil moisture from L-band HH and HV polarized data. The effects of vegetation on backscattering coefficients were evaluated by comparing Leaf Area Index (LAI), Leaf Water Area Index (LWAI) and Normalized Plant Water Content (NPWC). The results showed that HV polarization effectively simulated backscatter coefficient as compared to HH polarization where the best fit was obtained by taking the LAI as a vegetation descriptor. The HV polarization with the LAI indicator was able to retrieve soil moisture content with an accuracy of at least 80%.

Structural characterisation of mangrove forests achieved through combining multiple sources of remote sensing data

Temporal information on mangrove extent, age, structure and biomass provides an important contribution towards understanding the role of these ecosystems in terms of the services they provide (e.g., in relation to storage of carbon, conservation biodiversity), particularly given the diversity of influences of human activity and natural events and processes. Focusing on the Matang Mangrove Forest Reserve (MMFR) in Perak Province, Peninsular Malaysia, this study aimed to retrieve comprehensive information on the biophysical properties of mangroves from spaceborne optical and Synthetic Aperture Radar (SAR) to support better understanding of their dynamics in a managed setting. For the period 1988 to 2016 (29 years), forest age was estimated on at least an annual basis by combining time-series of Landsat-derived Normalised Difference Moisture Index (NDMI) and Japanese L-band Synthetic Aperture Radar (SAR) data. The NDMI was further used to retrieve canopy cover (%). Interferometric Shuttle Radar Topographic Mission (SRTM) X/C-band (2000), TanDEM-X-band (2010–2016) and stereo WorldView-2 stereo (2016) data were evaluated for their role in estimating canopy height (CH), from which above ground biomass (AGB, Mg ha−1) was derived using pre-established allometry. Whilst both L-band HH and HV data increased with AGB after about 8–10 years of growth, retrieval was compromised by mixed scattering from varying amounts of dead woody debris following clearing and wood material within regenerating forests, thinning of trees at ~15 and 20 years, and saturation of L-band SAR data after approximately 20 years of growth. Reference was made to stereo Phantom-3 DJI stereo imagery to support estimation of canopy cover (CC) and validation of satellite-derived CH. AGB estimates were compared with ground-based measurements. Using relationships with forest age, both CH and AGB were estimated for each date of Landsat or L-band SAR observation and the temporal trends in L-band SAR were shown to effectively track the sequences of clearing and regeneration. From these, four stages of the harvesting cycle were defined. The study provided new information on the biophysical properties and growth dynamics of mangrove forests in the MMFR, inputs for future monitoring activities, and methods for facilitating better characterisation and mapping of mangrove areas worldwide.

Estimation of Level and Deformed First-Year Sea Ice Surface Roughness in the Canadian Arctic Archipelago from C- and L-Band Synthetic Aperture Radar

Utilizing synthetic aperture radar (SAR) data to understand and map sea ice roughness is an active area of research. An object-based image analysis is here used to quantitatively link the winter first-year sea ice surface roughness to C-band RADARSAT-2 and L-band ALOS-2 PALSAR-2 SAR backscatter measured in the Canadian Arctic. Results indicate: (1) C-band HH-polarization backscatter is correlated with roughness (r = 0.86) at a shallow incidence angle; and (2) L-band HH- and VV-polarization backscatter is correlated with roughness (r = 0.82) at a shallow incidence angle. Retrieval models for surface roughness are developed and applied to the imagery to demonstrate the potential of SAR for mapping deformation with a best case RMSE of 5 mm. Additionally, strong correlations between C- and L-band SAR backscatter acquired during the advanced melt period, and the winter measured surface roughness, are observed. These results are discussed in the context of SAR potentially providing significant sea ice structural information despite the occurrence of melt and presence of surface melt ponds.

Comparative flood area analysis of C-band VH, VV, and L-band HH polarizations SAR data

ABSTRACTThe role of synthetic aperture radar (SAR)-image-based flood area mapping is proved beyond the doubts. It is also well known that different wavelength, polarization SAR reacts in varying ways over the same land-use/land-cover region. In line to this, this article mainly brings out the significance of comparing and analysing different wavelength, polarization SAR data of the same inundated region against the land-use classes of the study area. The C-band ENVISAT advanced synthetic aperture radar data of vertically transmitted horizontally received (VH), vertically transmitted vertically received (VV) polarizations data, and L-band ALOS-1 PALSAR data of horizontally transmitted horizontally received (HH) polarization data has been obtained as both these satellites captured the same flood event of Andhra Pradesh state of India. Initially, the SAR images are classified with the help of digital elevation model of the disaster region which supports in mapping the fully submerged, partially submerged and non-flooded pixels of disaster region. The fully submerged regions includes the natural waterbodies, adjacent flood plain regions which are completely submerged, as well as not accessible, whereas the partially submerged regions are spatially discontinuous and scattered regions which are inundated due to recent disaster but accessible. In this study, much emphasis has been given in comparing and analysing the fully submerged, partially submerged, and non-flooded regions of classified SAR images against each land use of the disaster region by which the response of individual land-use units of the disaster region at different wavelength, polarization has been brought out. From this comparative assessment, it has been observed that the areal extent of fully submerged regions is considerably more in L-band HH image than in the C-band polarization images. It is also been noticed that C-band VH polarization image is able to map and quantify considerable part of the land-use classes as partially submerged regions than the L-band HH polarization image. In addition to this, the proposed technique is able to rectify in classifying mangrove regions as non-flooded regions due to the land-use/land-cover-based approach.

L-band Synthetic Aperture Radar imagery performs better than optical datasets at retrieving woody fractional cover in deciduous, dry savannahs

Woody canopy cover (CC) is the simplest two dimensional metric for assessing the presence of the woody component in savannahs, but detailed validated maps are not currently available in southern African savannahs. A number of international EO programs (including in savannah landscapes) advocate and use optical LandSAT imagery for regional to country-wide mapping of woody canopy cover. However, previous research has shown that L-band Synthetic Aperture Radar (SAR) provides good performance at retrieving woody canopy cover in southern African savannahs. This study’s objective was to evaluate, compare and use in combination L-band ALOS PALSAR and LandSAT-5 TM, in a Random Forest environment, to assess the benefits of using LandSAT compared to ALOS PALSAR. Additional objectives saw the testing of LandSAT-5 image seasonality, spectral vegetation indices and image textures for improved CC modelling. Results showed that LandSAT-5 imagery acquired in the summer and autumn seasons yielded the highest single season modelling accuracies (R2 between 0.47 and 0.65), depending on the year but the combination of multi-seasonal images yielded higher accuracies (R2 between 0.57 and 0.72). The derivation of spectral vegetation indices and image textures and their combinations with optical reflectance bands provided minimal improvement with no optical-only result exceeding the winter SAR L-band backscatter alone results (R2 of ∼0.8). The integration of seasonally appropriate LandSAT-5 image reflectance and L-band HH and HV backscatter data does provide a significant improvement for CC modelling at the higher end of the model performance (R2 between 0.83 and 0.88), but we conclude that L-band only based CC modelling be recommended for South African regions.

Mapping forest growth and degradation stage in the Brigalow Belt Bioregion of Australia through integration of ALOS PALSAR and Landsat-derived foliage projective cover data

Differentiation of forest growth stages through classification of single date or time-series of Landsat sensor data is limited because of insensitivity to their three-dimensional structure. This study therefore evaluated the benefits of integrating the Advanced Land Observing Satellite (ALOS) Phased Array L-band Synthetic Aperture Radar (PALSAR) L-band HH and HV polarisation response from the woody components of vegetation with Landsat-derived foliage projective cover (FPC). Focus was on 12 regional ecosystems (REs) distributed across the Brigalow Belt Bioregion (BRB) of Queensland, Australia, where different stages of growth dominated by brigalow (Acacia harpophylla) were widespread. From remnant areas of brigalow-dominated forests mapped previously for each RE by the Queensland Herbarium through field visits and interpretations of aerial imagery, frequency distributions of all three channels were extracted and compared to those of image segments generated using FPC and PALSAR data. For woody vegetation (with an FPC threshold of ≥9%) outside of the remnant areas, mature (non-remnant) forests were associated with segments where the HH and HV backscatter thresholds were within one standard deviation of the mean extracted for remnant forest. Early-stage regrowth was differentiated using an L-band HH threshold of <−14dB, common for all REs because of similarities in structure at this stage. The early-stage included forests regrowing over several decades and often occurred in areas recovering from recent clearing events. Objects falling between the early and mature stages were considered to be intermediate regrowth and/or degraded forest. All areas with an FPC <9% were mapped as non-forest.Within the BRB, the Queensland Herbarium established that forests with brigalow as a dominant or subdominant component originally occupied over 7.3 million ha but were reduced to 586,364ha by 2009, with 460,499ha (78.5%) having brigalow as the dominant component. Using the Landsat FPC and ALOS PALSAR data, an additional 722,686ha of brigalow-dominated regrowth forest were identified giving a total forested area (brigalow-dominated remnant and secondary forest) of 1,183,185ha or 17.2% of the area of the 12 REs. Within this area, the greater proportion of regrowth (368,473ha or 31.1%) was mapped as early stage primarily because of recovery following recent clearance events. 230,551 (19.5%) ha and 123,662ha (10.5%) were mapped as intermediate and mature (non-remnant) stages respectively and the remainder (38.9%) was remnant forest. Users’ and producers’ accuracies were, respectively, 81% and 69% for early regrowth and 71% and 89% for mature and intermediate stage forests combined. The mapping, which used Queensland Herbarium’s RE data to delineate brigalow extent, provided a structural, rather than age-based classification of growth stage, as is typically retrieved using time-series comparison of optical imagery. The regional estimates of growth/degradation stage generated for the BRB provide a basis for optimising the use and recovery of these threatened brigalow ecosystems with benefits for biodiversity and carbon sequestration.

New global forest/non-forest maps from ALOS PALSAR data (2007–2010)

Four global mosaics of Advanced Land Observing Satellite (ALOS) Phased Arrayed L-band Synthetic Aperture Radar (SAR) HH and HV polarization data were generated at 25m spatial resolution using data acquired annually from 2007 to 2010. Variability in L-band HH and HV gamma-naught (γ0) for forests was observed between regions, with this attributed to differences in forest structure and vegetation/surface moisture conditions. Region-specific backscatter thresholds were therefore applied to produce from each annual mosaic, a global map of forest and non-forest cover from which maps of forest losses and gain were generated. The overall agreement with forest/non-forest assessments using the Degree Confluence Project, the Forest Resource Assessment and Google Earth images was 85%, 91% and 95% respectively. Using 2007 as a baseline, decreases of 0.040 and 0.028dB (with a 0.006dB 99% confidence level) were observed in the HH and HV γ0 respectively over the same areas suggesting a decrease in forest area and/or increased smoothing of the global surface at the L-band radar observation over the four-year period. The maps provide a new global resource for documenting the changing extent of forests and offer opportunities for quantifying historical and future dynamics through comparison with historical (1992–1998) Japanese Earth Resources Satellite (JERS-1) SAR and the forthcoming (from 2014) ALOS-2 PALSAR-2 data. Four year PALSAR mosaics and the forest/non-forest data, which were generated and analyzed in this paper, are opened to the public for free downloading albeit with coarser resolutions (WWW1). Future distribution of the higher (original) resolution datasets from PALSAR as well as the ALOS-2/PALSAR-2 is planned.

Mapping invasive Phragmites australis in the coastal Great Lakes with ALOS PALSAR satellite imagery for decision support

The invasive variety of Phragmites australis (common reed) forms dense stands that can cause negative impacts on coastal Great Lakes wetlands including habitat degradation and reduced biological diversity. Early treatment is key to controlling Phragmites, therefore a map of the current distribution is needed. ALOS PALSAR imagery was used to produce the first basin-wide distribution map showing the extent of large, dense invasive Phragmites-dominated habitats in wetlands and other coastal ecosystems along the U.S. shore of the Great Lakes. PALSAR is a satellite imaging radar sensor that is sensitive to differences in plant biomass and inundation patterns, allowing for the detection and delineation of these tall (up to 5m), high density, high biomass invasive Phragmites stands. Classification was based on multi-season ALOS PALSAR L-band (23cm wavelength) HH and HV polarization data. Seasonal (spring, summer, and fall) datasets were used to improve discrimination of Phragmites by taking advantage of phenological changes in vegetation and inundation patterns over the seasons. Extensive field collections of training and randomly selected validation data were conducted in 2010–2011 to aid in mapping and for accuracy assessments. Overall basin-wide map accuracy was 87%, with 86% producer's accuracy and 43% user's accuracy for invasive Phragmites. The invasive Phragmites maps are being used to identify major environmental drivers of this invader's distribution, to assess areas vulnerable to new invasion, and to provide information to regional stakeholders through a decision support tool.

QUANTATAIVE ANALYSIS OF RELATIONSHIP BETWEEN ALOS PALSAR BACKSCATTER AND FOREST STAND VOLUME

To estimate forest stand volume, topographic effects should be considered in Synthetic Aperture Radar (SAR) data processing, because most forests are located on mountainous areas in Korea. This paper shows how the effects on the ALOS Phased-Array L-Band SAR (PALSAR) backscatter in Kwangneung Experiment Forest can be reduced by gamma-nought γ^0.Regardless of coniferous and deciduous forests, the gamma-nought γ^0 values are always lower compared to the sigma-nought σ^0 values at HH and HV polarization for 58 standwise tree volume of the fore-slope (here, the west-facing slope) and are always higher in case of far-slope (here, east-facing slope).Comparison of the fore-slope with the far-slope, relating to the stand volume of the γ^0 and σ^0 values, demonstrates that the σ^0 values are significantly remarkable, while the γ^0 values are not. This means that the topographic normalized backscattering coefficient γ^0 can be used to estimate tree volume, independent of fore-slope and far-slope.Though the aforementioned two backscattering coefficients of γ^0 and σ^0 indicate L-band HH and HV saturations with tree volume observed at around 310 m^3ha^(-1), they increase with increasing trend with forest stand volume.These results show that stand volume retrieval of mountain forests can be improved by using topographic normalized backscattering coefficient of ALOS PALSAR data.

An Approach to Mapping Forest Growth Stages in Queensland, Australia through Integration of ALOS PALSAR and Landsat Sensor Data

Whilst extensive clearance of forests in the eastern Australian Brigalow Belt Bioregion (BBB) has occurred since European settlement, appropriate management of those that are regenerating can facilitate restoration of biomass (carbon) and biodiversity to levels typical of relatively undisturbed or remnant formations. However, maps of forests are different stages of regeneration are needed to facilitate restoration planning, including prevention of further re-clearing. Focusing on the Tara Downs subregion of the BBB and on forests with brigalow (Acacia harpophylla) as a component, this research establishes a method for differentiating and mapping early, intermediate and remnant growth stages from Japan Aerospace Exploration Agency (JAXA) Advanced Land Observing Satellite (ALOS) Phased-Array L-band Synthetic Aperture Radar (PALSAR) Fine Beam Dual (FBD) L-band HH- and HV-polarisation backscatter and Landsat-derived Foliage Projective Cover (FPC). Using inventory data collected from 74 plots, located in the Tara Downs subregion, forests were assigned to one of three regrowth stages based on their height and cover relative to that of undisturbed stands. The image data were then segmented into objects with each assigned to a growth stage by comparing the distributions of L-band HV and HH polarisation backscatter and FPC to that of reference distributions using a z-test. Comparison with independent assessments of growth stage, based on time-series analysis of aerial photography and SPOT images, established an overall accuracy of &gt; 70%, with this increasing to 90% when intermediate regrowth was excluded and only early-stage regrowth and remnant classes were considered. The proposed method can be adapted to respond to amendments to user-definitions of growth stage and, as regional mosaics of ALOS PALSAR and Landsat FPC are available for Queensland, has application across the state.

FOREST RESOURCES STUDY IN MONGOLIA USING ADVANCED SPATIAL TECHNOLOGIES

Abstract. The aim of this study is to conduct a forest resources study using optical and synthetic aperture radar (SAR) satellite images. For this purpose, a forest-dominated site around the Lake Khuvsgul located in northern Mongolia is selected. As remote sensing (RS) data sources, panchromatic and multispectral Landsat 7 images as well as ALOS PALSAR L-band HH polarization data are used. To produce a reliable land cover map from the multisensor images, a novel refined maximum likelihood classification based on the spectral and spatial thresholds are applied and for the accuracy assessment an overall accuracy is used. Overall, the research demonstrates that advanced spatial technologies based on optical and microwave RS are reliable tools for different forest studies.

Mapping forest aboveground biomass in the Northeastern United States with ALOS PALSAR dual-polarization L-band

A method for regional scale mapping of aboveground forest biomass with Advanced Land Observing Satellite (ALOS) Phased Array type L-band Synthetic Aperture Radar (PALSAR) data is presented. A fully automated algorithm, exploiting the synergy of SAR and optical remote sensing for the calibration of a semi-empirical model (Santoro et al., 2011; Cartus et al., 2011), was adopted to map forest aboveground biomass with L-band HH and HV intensity in the northeastern United States. In the retrieval algorithm, a semi-empirical model is calibrated and inverted for each HH and HV image to estimate biomass at the pixel level. Where possible, biomass estimates for single images in a multi-temporal stack were combined in a weighted manner. A comparison with the National Biomass and Carbon Dataset, NBCD 2000 (Kellndorfer et al., in preparation), at different spatial scales indicated the feasibility of the automated biomass retrieval approach and confirmed previous findings that the retrieval accuracy for HV intensity is consistently better than that for HH intensity and depends on the imaging conditions. The weighted combination of the biomass estimates from each intensity image in a multi-temporal stack significantly improved the retrieval performance. Because of regional differences in the multi-temporal coverage with ALOS PALSAR dual polarization data (1–5 images for 2007/08) and the pronounced dependence of the retrieval for single images on the imaging conditions, the possibility of producing maps with consistent accuracy at high resolution was found to be limited. Accurate biomass estimates were obtained when aggregating the ALOS biomass maps at county scale and comparing the estimates to Forest Inventory and Analysis (FIA) county statistics (RMSE=12.9t/ha, R2=0.86).

Using Diurnal Variation in Backscatter to Detect Vegetation Water Stress

A difference has been detected between the C-band wind scatterometer measurements from the morning (descending) and evening (ascending) passes of the European Remote Sensing (ERS) 1/2 satellite. In the West African savanna, for example, these differences correspond to the onset of vegetation water stress. A literature review of the current state of knowledge regarding the diurnal variation in vegetation dielectric properties and its influence on observed backscatter is presented. A numerical sensitivity study using the Michigan microwave canopy scattering model was performed to investigate whether this difference might be explained by diurnal variation in the dielectric properties of the canopy. For vertically copolarized backscatter, as in the case of the ERS wind scatterometer, the greatest sensitivity is to leaf moisture (and, hence, dielectric constant), but the trunk moisture is significant at low values of leaf moisture content. This suggests that the ERS wind scatterometer may well detect changes in vegetation water status. The impact of leaf, branch, trunk, and soil moisture contents on L-band HH, VV, and HV backscatter was also investigated to explore the implications for the National Aeronautics and Space Administration's upcoming Soil Moisture Active Passive (SMAP) mission. Results suggest that combining the morning and evening passes of the SMAP radar observations might yield valuable insight into water stress in areas otherwise considered too densely vegetated for traditional soil moisture retrieval.

레이더 산란계 후방산란계수를 이용한 토양수분함량 추정

다편파 레이더 산란계 시스템 (L, C, X-밴드 안테나)에서 얻어진 편파별 후방산란계수와 토양수분함량과의 상관성을 분석하고 후방산란계수를 이용 토양수분함량을 추정하고자 하였다. 콩 생육시기에 따른 밴드별 후방산란계수 변화 관측 결과 L-밴드 후방산란계수가 C-, X-밴드후방산란계수보다 높게 나타났고, 모든 안테나 밴드에서 콩 생육초기에는 VV-편파가 HH, HV-편파보다 후방산란계수가 높게 나타났다. HH-편파가 VV-편파보다 후방산란계수가 높게 나타나는 시기는 밴드에 따라 차이를 보였다. L-밴드의 경우 7월 20일 (DOY 200), C, X-밴드는 7월 30일 (DOY 210)부터 HH-편파가 다른 편파들 보다 후방산란계수가 높게 나타났다. 모든 안테나 편파별 후방산란계수가 9월 29일 (DOY 271)에 최대값을 보였고, 그 이후 수확기 (DOY 294) 까지 감소하였다. L-밴드 HH-편파와 VV-편파 간의 차이는 꼬투리가 생성되는 착협기 (R3, DOY 228) 부터 다른 밴드에 비해 크게 나타났고, 반면에 C-밴드 HH-편파와 VV-편파 간의 차이는 착협성기 (R4, DOY 242) 이후 증가폭이 크게 나타났다. 후방산란계수와 토양수분함량과의 변화를 분석한 결과 생육기간동안 토양수분함량 변이가 컸고, 전체 생육기간에서는 모든 밴드별 후방산란계수와 토양수분함량 간에 상관성이 나타나지 않았다. 하지만 엽면적지수가 2 이하 (R2, DOY 224) 일 때 후방산란계수가 증가함에 따라 토양수분함량도 증가하는 경향을 보였다. 밴드별 후방산란계수와 토양수분함량과의 상관관계를 분석하였다. 전체 생육기간에서는 모든 밴드에서 두 변수간의 상관계수가 낮게 나타났다 (<TEX>$r{\leq}0.50$</TEX>). 반면에 엽면적지수 2 이하 일 때 모든 밴드에서 후방산란계수와 토양수분함량과의 상관계수가 전체 생육단계에서 조사한 것 보다 높게 나타났다. L-밴드 후방산란계수가 C-, X-밴드 후방산란계수 보다 토양수분함량과의 상관성이 높게 나타났고 (<TEX>$r{\geq}0.84$</TEX>), L-밴드 HH-편파가 상관계수가 가장 높았다 (r=0.90). X-밴드 후방산란계수는 L-, C-밴드 후방산란계수보다 상관계수가 낮게 나타났다 (<TEX>$r{\leq}0.71$</TEX>). 후방산란계수를 이용하여 토양수분함량 추정 모형식을 작성하였다. L-밴드 HH-편파 후방산란계수와 토양수분함량과의 관계를 비교해 본 결과 결정계수가 높게 나타났다(<TEX>$R^2=0.92$</TEX>). 본 연구를 통해 레이더 산란계 시스템에서 얻어진 후방산란계수를 이용하여 토양수분함량을 추정할 수 있음을 확인하였다. Microwave remote sensing can help monitor the land surface water cycle, crop growth and soil moisture. A ground-based polarimetric scatterometer has an advantage for continuous crop using multi-polarization and multi-frequencies and various incident angles have been used extensively in a frequency range expanding from L-band to Ka-band. In this study, we analyzed the relationships between L-, C- and X-band signatures and soil moisture content over the whole soybean growth period. Polarimetric backscatter data at L-, C- and X-bands were acquired every 10 minutes. L-band backscattering coefficients were higher than those observed using C- or X-band over the period. Backscattering coefficients for all frequencies and polarizations increased until Day Of Year (DOY) 271 and then decreased until harvesting stage (DOY 294). Time serious of soil moisture content was not a corresponding with backscattering over the whole growth stage, although it increased relatively until early August (R2, DOY 224). We conducted the relationship between the backscattering coefficients of each band and soil moisture content. Backscattering coefficients for all frequencies were not correlated with soil moisture content when considered over the entire stage (<TEX>$r{\leq}0.50$</TEX>). However, we found that L-band HH polarization was correlated with soil moisture content (r=0.90) when Leaf Area Index (LAI)<2. Retrieval equations were developed for estimating soil moisture content using L-band HH polarization. Relation between L-HH and soil moisture shows exponential pattern and highly related with soil moisture content (<TEX>$R^2=0.92$</TEX>). Results from this study show that backscattering coefficients of radar scatterometer appear effective to estimate soil moisture content.

Combining ALOS and ERS-2 SAR data for the characterization of tidal flats. Case study from the Baie des Veys, Normandy, France

To better understand the SAR backscattering of tidal flats’ sediments, a study was conducted in the framework of the ALOS Data European Node. The approach is mainly based on the analysis of a time series of ALOS data acquired from April to June 2008. The emphasis is on the spatial statistics of the underlying random surface of the tidal flat. Three ALOS cycles with interesting adjacent swath configurations were considered. The study comprised field work to establish the ground truth, and then the analysis of radar data. For this purpose combined PALSAR L-band HH and ERS-2 C-band VV data were explored, because dual-frequency data acquisition is needed for geophysical parameters retrieval. Co-polarized data are more relevant for the study of the tidal flat itself, whereas the HV polarization is suitable for identifying the presence of halophytic plants growing in the upper part of the tidal flat. Quad-polarization L-band data could be of great interest, but experiments could not be set up due to lack of suitable acquisitions. The C-band is more accurate for sensing the roughness of the finer sediments, whereas the L-band is more relevant for drawing the instantaneous limit of the sea. This paper briefly discusses the role of the local mean time for the study of areas experiencing high tidal range. For the test site located in Normandy, the ALOS acquisition time does not allow more than 55 per cent of the tidal flat to be exposed.

An Evaluation of the ALOS PALSAR L-Band Backscatter—Above Ground Biomass Relationship Queensland, Australia: Impacts of Surface Moisture Condition and Vegetation Structure

Focusing on woody vegetation in Queensland, Australia, the study aimed to establish whether the relationship between Advanced Land Observing Satellite (ALOS) Phased Array L-band SAR (PALSAR) HH and HV backscattering coefficients and above ground biomass (AGB) was consistent within and between structural formations (forests, woodlands and open woodlands, including scrub). Across these formations, 2781 plot-based measurements (from 1139 sites) of tree diameters by species were collated, from which AGB was estimated using generic allometric equations. For Queensland, PALSAR fine beam dual (FBD) 50 m strip data for 2007 were provided through the Japanese Space Exploration Agency's (JAXA) Kyoto and Carbon (K&C) Initiative, with up to 3 acquisitions available for each Reference System for Planning (RSP) paths. When individual strips acquired over Queensland were combined, `banding' was evident within the resulting mosaics, with this attributed to enhanced L-band backscatter following rainfall events in some areas. Reference to Advanced Microwave Scanning Radiometer-EOS (AMSR-E) data indicated that strips with enhanced L-band backscatter corresponded to areas with increased effective vegetation water content (kg m <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">-2</sup> ) and, to a lesser extent, soil moisture (g cm <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">-3</sup> ). Regardless of moisture conditions, L-band HV topographically normalized backscattering intensities backscatter (σ <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">f</sub> <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">o</sup> ) increased asymptotically with AGB, with the saturation level being greatest for forests and least for open woodlands. However, under conditions of relative maximum surface moisture, L-band HV and HH σ <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">f</sub> <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">o</sup> was enhanced by as much as 2.5 and 4.0 dB respectively, particularly for forests of lower AGB, with this resulting in an overall reduction in dynamic range. The saturation level also reduced at L-band HH for forests and woodlands but remained similar for open woodlands. Differences in the rate of increase in both L-band HH and HV σ <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">f</sub> <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">o</sup> with AGB were observed between forests and the woodland categories (for both relatively wet and dry conditions) with these attributed, in part, to differences in the size class distribution and stem density between non-remnant (secondary) forests and remnant woodlands of lower AGB. The study concludes that PALSAR data acquired when surface moisture and rainfall are minimal allow better estimation of the AGB of woody vegetation and that retrieval algorithms ideally need to consider differences in surface moisture conditions and vegetation structure.

Passive and Active L-Band Microwave Observations and Modeling of Ocean Surface Winds

L-band microwave backscatter and brightness temperature of sea surfaces acquired using the Passive/Active L-band Sensor during the High Ocean Wind campaign are reported in terms of their dependence on ocean surface wind speed and direction. We find that the L-band VV, HH, and HV radar backscatter data increase by 6-7 dB from 5 to 25 m/s wind speed at a 45° incidence angle. The data suggest the validity of Phased Array type L-band Synthetic Aperture Radar (PALSAR) HH model function between 5 and 15 m/s wind speeds, but show that the extrapolation of PALSAR model at above 20 m/s wind speeds overpredicts <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">A</i> <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">0</sub> and <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">a</i> <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">1</sub> coefficients. There is wind direction dependence in the radar backscatter with about 4 dB differences between upwind and crosswind observations at 24 m/s wind speed for VV and HH. The passive brightness temperatures show about a 5-K change for <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">T</i> <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">V</sub> and a 7-K change for <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">T</i> <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">H</sub> for a wind speed increasing from 5 to 25 m/s. Circle flight data suggest a wind direction response of about 1-2 K in <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">T</i> <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">V</sub> and <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">T</i> <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">H</sub> at 14 and 24 m/s wind speeds. The L-band microwave data show excellent linear correlation with the surface wind speed with a correlation better than 0.95. The results support the use of L-band radar data for estimating the wind-driven excess brightness temperature of sea surfaces. The data also support the applications of L-band microwave signals for high-resolution (kilometer scale) observation of ocean surface winds under high wind conditions (10-28 m/s).

An L-Band Ocean Geophysical Model Function Derived From PALSAR

This paper examines L-band normalized radar cross section (NRCS) dependence on ocean surface wind. More than 90 000 match-ups, each consisting of the L-band HH NRCS, incidence angles, wind speeds, and wind directions, were collected from the Phased-Array L-Band Synthetic Aperture Radar (PALSAR) and scatterometer wind vectors. Based on the match-ups, the L-band HH NRCS dependence on incidence angle and wind vector is modeled for 0-20-m/s wind speeds and 17deg-43deg incidence angles. The derived relation indicates that the wind sensitivity of the L-band NRCS is less than that of the C-band at moderate winds and large incidence angles, whereas comparable at stronger winds ((>10 m/s) and small incidence angles. The upwind-crosswind difference is amplified in the 10-15-m/s range followed by an almost zero amplitude from 4 to 8 m/s, which represents a clear phase shift with the C-band VV and Ku-band HH models. Wind speeds are then estimated from the match-ups, based on the derived model function. A comparison with the reference scatterometer winds reveals a 0.05-m/s bias and a 1.85-m/s root mean square error, where crosswind data give rise to large errors due to low wind sensitivity at wind speeds of around 10 m/s, particularly at large incidence angles. The L-band NRCS behavior in strong winds (>20 m/s), at which the C-band is saturated, was not determined in the current model due to the limited number of the match-ups.

Characterizing L-Band Scattering of Paddy Rice in Southeast China With Radiative Transfer Model and Multitemporal ALOS/PALSAR Imagery

Rice is a major food supply in southeast China. With increased population and urbanization, reliable rice mapping is critical in this region. Because of frequent cloud cover and precipitation during the rice-growing season, it is difficult to conduct large-area rice monitoring with optical remote sensing techniques. L-band synthetic aperture radar (SAR), with its all-weather day and night imaging and canopy penetration capabilities, provides a unique alternative. In this study, a first-order radiative transfer model was developed to simulate L-band scattering properties of paddy rice. Three Advanced Land Observing Satellite (ALOS)/Phased-Array-Type L-band Synthetic Aperture Radar (PALSAR) images in dual-polarization mode (HH and HV) acquired in early tillering (June 28, 2007), tillering (August 13, 2007), and heading (September 28, 2007) stages were processed to test the temporal variation of rice backscatter. It was found that plant height and leaf mass amount were the two major structural parameters that contributed to rice backscatter in PALSAR images. The variation of the simulated HH backscatter matched with PALSAR observations in sample fields, although the simulated backscatter coefficients were around 3 dB lower than image-extracted values. Leaf volume scattering and leaf-ground double bounce were found as the two major scattering components in L-band HH polarization and increased with leaf layer height and density. This paper demonstrated that L-band HH backscatter was more sensitive to rice's structural variation than the VV backscatter and may therefore be more useful in rice mapping and modeling studies.