Monitoring leaf area of sugar beet using ERS-1 SAR data

This paper presents the results of field testing a radar model which relates leaf area index to radar backscatter for ERS-1 C-band VV polarization SAR data. Ground truth measurements of leaf area index and soil moisture content were made in selected sugar beet fields, with simultaneous acquisition of ERS-1 SAR image data. Radar backscatter coefficients were derived from the calibrated ERS-1 SAR data. The Leeuwen and Clevers expression of the water cloud model was fitted to determine the in situ relationship between radar back-scatter and leaf area index. The model can be inverted analytically to calculate leaf area index from radar backscatter. The results show considerable potential for the operational application of ERS-1 SAR data in crop monitoring.     

Classification of sea ice types in the Ross Sea,Antarctica from SAR and AVHRR imagery

ERS-2 synthetic aperture radar (SAR) and Advanced Very High Resolution Radiometer (AVHRR) imagery are used to examine spectral characteristics of late winter/early spring ice in the Ross Sea, Antarctica. The combined spectral signatures are used to distinguish six ice types: fast ice, new ice, smooth first year ice, rough first year ice, thin new ice/wind roughened open water and glacial ice. The procedure firstly involves 'picking' class boundaries from SAR imagery based on the morphology of a speckle reduced backscatter spectrum. These class boundaries are then used as input to an iterative segmentation procedure that involves the repeated application of a speckle reduction filter to the image. For an image from late September 1996 the segmentation procedure enabled separation of five general ice categories each with a characteristic backscatter range. However because of the combined contributions of ice thickness, surface roughness, salinity and water content to the SAR backscatter, further decision criteria are required to separate some physical ice types unable to be resolved individually using this method. Coincident and co-registered infrared data from the AVHRR sensor are used to extract spectral characteristics for the final ice classes. Using this procedure we were able to distinguish floating glacier ice from thin new ice/wind roughened open water and new ice from nearshore fast ice. These ice types were unable to be separated using SAR backscatter intensity alone. In addition image subtraction was also able to clearly delineate areas of shore fast ice.     

Investigating the potential for soil moisture and surface roughness monitoring in drylands using ERS SAR data

Multitemporal ERS-1 and ERS-2 SAR data were acquired for northern Jordan between 1995 and 1997 to investigate changes in the backscatter coefficients of a range of typical desert land surfaces. The changes in backscatter found were ascribed to variations in surface soil moisture, and changes in surface roughness caused by a range of natural and anthropogenic factors. Data collected from monitored sites were input into the Integral Equation Model (IEM). The model outputs were strongly correlated with observed backscatter coefficients (r ²=0.84). The results show that the successful monitoring of soil moisture in these environments is strongly dependent on the surface roughness. On surfaces with RMS height 0.5 cm, the sensitivity of the backscatter coefficient to changes in surface microtopography did not allow accurate soil moisture estimation. Microtopographic change on rougher surfaces has less influence on the backscatter coefficient, and the probability of soil moisture estimation from SAR imagery is greater. These results indicate that knowledge of the surface conditions (both in terms of surface roughness and geomorphology) is essential for accurate soil moisture monitoring, whether in a research or operational context. The potential benefits of these findings are discussed in the context of the Jordan Badia Research and Development Project.     

Motion patterns of Nabesna Glacier (Alaska) revealed by interferometric SAR techniques

Nabesna Glacier is one of the longest land-terminus mountain glaciers in North America. However, its flow has never been studied. We derived detailed motion patterns of Nabesna Glacier in winter and spring 1994–1996 from the synthetic aperture radar (SAR) images acquired by the European Remote Sensing satellites (ERS-1 and ERS-2) using interferometric SAR (InSAR) techniques. Special effort was made to assess the accuracy of the motion estimates, and remove data points with high uncertainty from the motion profiles, enabling us to obtain reliable glacier flow patterns along the highly curved main course of Nabesna Glacier. The results, covering 80 km of the 87 km main course of the glacier, were used to delineate four distinctive sections in terms of spatial and temporal variability of the glacier speed: (1) the upper section where glacier flow was apparently random both temporally and spatially presumably due to development of crevasses; (2) the upper-middle section with relatively steady flow around 0.27 to 0.4 m/day; (3) the middle section with a stable pattern of acceleration from 0.27–0.3 m/day to the maximum about 0.67–0.73 m/day, followed by a general deceleration to 0.17–0.33 m/day before reaching (4) the lower section where the glacier motion was generally slow yet highly variable although uncertainty in the estimation is high. Occurrence of the flow maximum, as well as many local maxima and minima at consistent locations over different periods suggests that the valley geometry affect the overall flow pattern. On top of this general trend, many small-scale temporal/spatial variations in the glacier flow patterns were observed along the glacier, especially in the lower sections. On average, the flow speeds were in the range of 0.3 to 0.7 m/day; however this lacks any measurements of summer flow speeds which are expected to be significantly higher.     

Orbital effects on ERS-1 SAR temporal backscatter profiles of agricultural crops

Multi-temporal radar backscatter characteristics of crops and their underlying soils were analysed for an agricultural area in south-western Ontario, Canada using nine dates of ERS-1 SAR imagery acquired during the 1993 growing season. From the calibrated data, SAR temporal backscatter profiles were generated for each crop type. The results indicate that small changes in incidence-angle can have strong impacts on radar backscatter. Thus, attention must be given to local incidence-angle effects when using ERS-1 SAR data,especially when comparing backscatter coefficients of the same area from different scenes or different areas within the same scene.     

Short contributions

Studies of ERS-1 synthetic aperture radar (SAR) imagery have shown that fire scars in Alaskan forests are significantly brighter (3–6 dB) than surrounding unburned forest. The signature varies seasonally and changes as vegetation re-establishes on the site over longer time periods (>5years). Additionally, it is known that soil water content typically increases following forest fires due to changes in evapotranspiration rates and melting of the permafrost.

The objective of this study was to understand the relation between soil water content and the ERS-1 SAR signature at fire-disturbed sites. To accomplish this objective, we compared soil water in six burned black spruce (Picea mariana (Mill.) B.S.P.) forest sites in interior Alaska to ERS-1 SAR backscalter measurements. The six sites are of various age since burn. Soil water was periodically measured at each site during the summer of 1992 and at one site in 1993 and 1994 when the ERS-1 imaging radar was scheduled to pass overhead. Results indicate that a positive linear relation exists between soil water content and the SAR backscatter coefficient in young burns ( < ～4years). Older burns do not show this relation, a result of vegetation establishment following the burn. This interaction between soil moisture condition and ERS-1 SAR backscatter shows great potential for measuring soil water content and monitoring seasonal variations in soil water content in black spruce sites recently disturbed by wildfire.     

Delineation of glacial zones of Gangotri and other glaciers of Central Himalaya using RISAT-1 C-band dual-pol SAR

The Himalayan glaciers, being unique in nature, need more detailed study over their evolution in the Himalayan glacial zones. A methodology has been developed using two-dimensional signatures from synthetic aperture radar (SAR) C-band dual-polarized data. A linear decision rule-based model has been generated using the signatures and the result further filtered by the use of a digital elevation model (DEM) to delineate glacial zones in the Himalayas. The advantage of using cross-polarized data is the addition of extra information from the volume of the glacial mass. Some important prerequisites for the analysis are SAR image ortho-rectification and calibration, glacier boundary delineation, and the development of sites for collecting SAR backscattering signatures from glaciers along the profile. The study deals with the evolution of glacial snow cover and glacial zones/facies in the Himalayan region under a subtropical humid climate from the ablation to the accumulation season. SAR images from 15 July 2012 to 30 June 2013 over the Gangotri and Mana glaciers were evaluated with the developed model. The identification of a superimposed zone during the ablation season is among the key results. The identified snowlines and other boundaries of glacial facies are studied on a temporal scale. The highest snowline altitude of Mana was recorded at 5768 and 5194 m for the Gangotri glacier in 2012. SAR data are also important in identifying glacial zones buried under winter snow cover. The results obtained are useful in regard to further glaciological studies of the Himalayan glaciers.     

Estimation of Arctic glacier motion with satellite L-band SAR data

Offset fields between pairs of JERS-1 satellite SAR data acquired in winter with 44 days time interval were employed for the estimation of Arctic glacier motion over Svalbard, Novaya Zemlya and Franz-Josef Land. The displacement maps show that the ice caps are divided into a number of clearly defined fast-flowing units with displacement larger than about 6 m in 44 days (i.e. 50 m/year). The estimated error of the JERS-1 offset tracking derived displacement is on the order of 20 m/year. Occasionally, azimuth streaks related to auroral zone ionospheric disturbances were detected and dedicated processing steps were applied to minimize their influence on the estimated motion pattern. Our analysis demonstrated that offset tracking of L-band SAR images is a robust and direct estimation technique of glacier motion. The method is particularly useful when differential SAR interferometry is limited by loss of coherence, i.e. for rapid and incoherent flow and large acquisition time intervals between the two SAR images. The JERS-1 results, obtained using SAR data acquired by a satellite operated until 1998, raise expectations of L-band SAR data from the ALOS satellite launched in early 2006.     

Aspect and incidence angle sensitivity in ERS-1 SAR data

Large variations in backscattering coefficients were observed on ERS-1 SAR images acquired from ascending and descending orbits, within 36 hours, over an agricultural area and under stable winter conditions. Three possible causes were investigated: (1) environmental factors; (2) SAR processor instability; and (3) aspect and incidence angle sensitivity. The look direction (aspect angle) accounted for a 1.5dB difference in backscattering coefficients. The remaining variations were related to the incidence angle. A correction model is proposed.     

A test of detecting spring leaf flush within the Alaskan boreal forest using ERS-2 and Radarsat SAR data

This study tests whether ERS-2 and Radarsat Standard Beam SAR data could be used to detect spring green-up of broadleaf forests on floodplains in interior Alaska. SAR data were acquired for pre- and post-budburst dates during the spring of 1997, 1998 and 1999. The images were radiometrically calibrated to dB and then geometrically co-registered to a colour infrared Landsat TM image. Ten broadleaf and ten conifer floodplain forest polygons were then delineated from the Landsat TM image for the extent of each SAR image. The mean dB from each broadleaf and conifer stand was computed from each SAR image to test whether there was a consistent change in mean dB associated with spring leaf-out of broadleaf trees. There was no evidence that the 1997 or 1998 ERS-2 dB SAR data were useful for detecting spring leaf flush. The 1998 Radarsat broadleaf stands all increased in dB after budburst, but this was attributed to an increase in surface moisture from rain, rather than due to spring leaf flush. The 1999 Radarsat stands all decreased in SAR dB after budburst, while control conifer stands increased and decreased in dB during the same time period. Confounding factors such as changing surface moisture, and possibly freezing/ thawing effects may mask any change in ERS-2 or Radarsat SAR dB due to spring leaf flush.     

A novel approach for the characterization of tundra wetland regions with C-band SAR satellite data

A circumpolar representative and consistent wetland map is required for a range of applications ranging from upscaling of carbon fluxes and pools to climate modelling and wildlife habitat assessment. Currently available data sets lack sufficient accuracy and/or thematic detail in many regions of the Arctic. Synthetic aperture radar (SAR) data from satellites have already been shown to be suitable for wetland mapping. Envisat Advanced SAR (ASAR) provides global medium-resolution data which are examined with particular focus on spatial wetness patterns in this study. It was found that winter minimum backscatter values as well as their differences to summer minimum values reflect vegetation physiognomy units of certain wetness regimes. Low winter backscatter values are mostly found in areas vegetated by plant communities typically for wet regions in the tundra biome, due to low roughness and low volume scattering caused by the predominant vegetation. Summer to winter difference backscatter values, which in contrast to the winter values depend almost solely on soil moisture content, show expected higher values for wet regions. While the approach using difference values would seem more reasonable in order to delineate wetness patterns considering its direct link to soil moisture, it was found that a classification of winter minimum backscatter values is more applicable in tundra regions due to its better separability into wetness classes. Previous approaches for wetland detection have investigated the impact of liquid water in the soil on backscatter conditions. In this study the absence of liquid water is utilized.

Owing to a lack of comparable regional to circumpolar data with respect to thematic detail, a potential wetland map cannot directly be validated; however, one might claim the validity of such a product by comparison with vegetation maps, which hold some information on the wetness status of certain classes. It was shown that the Envisat ASAR-derived classes are related to wetland classes of conventional vegetation maps, indicating its applicability; 30% of the land area north of the treeline was identified as wetland while conventional maps recorded 1–7%.     

Correlation Analysis between L-band SAR and ForestStem Volume in Northeast China

Because Synthetic Aperture Radar(SAR)can penetrate into forest canopy and interact with the primary stem volume contents of the trees (trunk and branch),SAR data are widely used for forest stem volume estimation.This paper investigated the correlation between SAR data and forest stem volume in Xunke,Heilongjiang using the stand-wise forest inventory data in 2003 and ALOS PALSAR data for five dates in 2007.The influences of season and polarizations on the relationship between stem volume and SAR data were studied by analyzing the scatterplots;that was followed by interpretation of the mechanisms primarily based on a forest radar backscattering model-water cloud model.The results showed that the relationship between HV polarization backscatter and stem volume is better than HH polarization,and SAR data in summer dry conditions are more correlated to stem volume than the data acquired in other conditions.The interferometric coherence with 46-day temporal baseline is negatively correlated to the stem volume.The correlation coefficients from winter coherence are higher than those from summer coherence and backscatter.The study results suggest using the interferometric coherence in winter as the best choice for forest stem volume estimation with L-band SAR data.     

Movement estimate of the Dongkemadi Glacier on the Qinghai–Tibetan Plateau using L-band and C-band spaceborne SAR data

We measured the complex motion of the Dongkemadi Glacier on Tanggula Mountain, Qinghai–Tibetan Plateau, using two-pass differential synthetic aperture radar interferometry (InSAR) with satellite L-band and C-band SAR data. We derived detailed motion patterns of the Dongkemadi Glacier for the winter seasons of 1996, 2007 and 2008 using a European Remote sensing Satellite-1/2 (ERS-1/2) tandem InSAR pair acquired from descending orbit and a 46-day-separation Advanced Land Observing Satellite (ALOS) InSAR pair acquired from ascending orbit. In this article, we focus on an analysis of the glacier's surface motion features and a validation of the results from the InSAR using Global Positioning System (GPS) survey data. The experimental results show that the glacier flow distribution displays strong spatial variations depending on elevation. The glacier is divided into four clearly defined fast-flowing units in terms of spatial variability of the glacier speed, with evidence from both ERS and ALOS/PALSAR InSAR pairs (palsar – Phased Array type L-band Synthetic Aperture Radar). Among the four fast-flowing units, three are on the Dadongkemadi Glacier (DDG) and one on the Xiaodongkemadi Glacier (XDG). The flow patterns are generally characterized by terrain complexity for both glacier branches. The upper central area of the DDG shows slow movement, maybe due to the convergent and uptaking effect of ice from steep slope areas with opposite flow directions.     

Relationship between green leaf biomass volumetric density and ERS-2 SAR backscatter of four vegetation formations in the semi-arid zone of Israel

Relationships between ERS-2 SAR backscatter and the biophysical properties of four Mediterranean vegetation formations (forest, shrubs, dwarf shrubs and herbaceous vegetation) were assessed. Low correlation was found between ERS-2 SAR backscatter and both aboveground biomass and LAI. However, significantly higher correlation (r =0.92) was found between ERS-2 SAR backscatter and a new index of Green leaf biomass Volumetric Density (GVD). These results stress the dominant influence of leaves in the uppermost part of the vegetation layer on ERS-2 SAR backscatter.     

Feasibility of multi-temporal interferometric SAR data for stand-level estimation of boreal forest stem volume

The feasibility of interferometric SAR (INSAR) coherence observations for stem volume (biomass) retrieval is investigated by applying coherence data determined from 14 ERS-1 and ERS-2 C-band SAR image pairs. The image set covers a single forested test area in Finland, and both summer (snow-free) and winter conditions are represented. The data set enabled (a) the study of stem volume retrieval performance under varying conditions, (b) the analysis of the seasonal behavior of interferometric coherence, and (c) the determination of the accuracy characteristics of empirical (nonlinear) coherence modeling. Additionally, a new technique to estimate forest stem volume from INSAR data was developed based on constrained iterative inversion of the applied empirical model. The results indicate that the usability of winter images with snow-covered terrain is superior to that of images obtained under summer conditions. The applied empirical model appears to be adequate for describing the stand-wise coherence of boreal forest. Hence, a practical stem volume estimation method can be established based on it. The highest correlation coefficient between the estimated stem volume and the ground truth stem volume showed values as high as r=0.9 and a relative RMSE level of 48% was obtained, respectively.     

Multi-temporal JERS SAR data in boreal forest biomass mapping

Multi-temporal JERS SAR data were studied for forest biomass mapping. The study site was located in South-eastern Finland in Ruokolahti. Pre-processing of JERS SAR data included ortho-rectification and radiometric normalization of topographic effects.In single-date regression analysis between backscatter amplitude and stem volume, summer scenes from July to October produced correlation coefficients (r) between 0.63 and 0.81. Backscatter level and the slope of the (linear) regression line were stable from scene to scene. Winter scenes acquired in very cold and dry winter conditions had a very low correlation. One winter scene acquired in conditions where snow is not completely frozen produced a correlation coefficient similar to summer scenes.Multivariate regression analysis with a 6-date JERS SAR dataset produced correlation coefficient of 0.85. A combined JERS-optical regression analysis improved the correlation coefficient to 0.89 and also alleviated the saturation, which affects both SAR and optical data.The stability of the regression results in summer scenes suggests that a simple constant model could be used in wide-area forest biomass mapping if accuracy requirements are low and if biomass estimates are aggregated to large areal units.     

Airborne line scanner measurements for ERS-1 SAR interpretation of sea ice

A new method is presented for interpretation of Synthetic Aperture Radar (SAR) images recorded with the first European Remote Sensing Satellite (ERS-1) with respect to classification of sea ice. Conventional interpretation of spaceborne radar images is often based on subjective classification of radar signatures. Themost promising approach is a region-based segmentation with subsequent interpretation of the segments. The definition of regions with common properties enables a characterisation by texture parameters besides backscatter coefficients. The major drawback of this method is the subjective selection and characterisation of the training segments on which the classification is based. To avoid this subjective influence, an attempt is made of an independent classification by the use of two airborne line scanner systems, one for the visible and the other for the infrared spectral range. The systems were installed on research aircraft (aeroplane and helicopter) during an experiment covering the marginal ice zone north of Spitsbergen in late winter 1993 and in the North East Water Polynya in summer 1993. Several underflights of ERS-1 were carried out during the SAR mode. Typical areal coverage of the line scanner images during a flight is 1.5% of a SAR scene. The line scanner images are classified using a two-dimensional feature space. By this procedure various ice types are identified. After matching the locations of the line scanner and the segmented SAR images, it is then possible to derive the characteristics of different ice types with respect to radar signatures. Backscatter coefficient and texture parameters are used for the discrimination of ice types. Texture parameters used are moments of the grey-level distribution and values of the co-occurrence matrices. The results of this work show, that the common method of a subjective characterisation of training regions runs into difficulties. SAR signatures are essentially dependent on the conditions during ice development. Regions with different ice types can have the same SAR signatures and different SAR signatures may be found for the same ice type. With the presented method it is possible to achieve classification accuracies up to 78% with a discrimination of young ice, first-year ice and old ice during winter situations. In summer, it is difficult to discriminate wind exposed water and sea ice. In this case, the classification of SAR images is derived exclusively by means of texture parameters since the backscatter coefficient is of little use. With the discrimination of water, snow-covered ice, and brash ice an accuracy of 73% is achieved under summer conditions.     

SAR observations of Arctic freeze-up compared to SSM/I during ARCTIC'91

Ice concentration in the Arctic derived from ERS-1 Synthetic Aperture Radar (SAR) and Special Scanning Microwave/Imager (SSM/I) images are compared. The satellite data are compared to video images and in situ measurements. The data were acquired during the freeze-up period of the ARCTIC'91 expedition. The studied areas were characterized by melting conditions and new ice formation with frost flowers. The ERS-1 SAR images are classified by a local averaging method and a segmentation method. Parameters for the methods are derived from the backscattering distributions. Temporal sequences and meteorological information are used for consistent results. Ice concentration derived from SAR are compared with the SSM/I ice concentration (NASA team algorithm) and ship observations. SSM/I may underestimate the ice concentration by 20 per cent due to thin ice formation and melting conditions while SAR may overestimate. However, by using the SAR estimate of the different ice classes we believe it is possible to increase the accuracy of the NASA team algorithm. We conclude that it is important to compare results from different sensors and methods.     

Patterns of irrigated rice growth and malaria vector breeding in Mali using multi-temporal ERS-2 synthetic aperture radar

We explored the use of the European Remote Sensing Satellite 2 Synthetic Aperture Radar (ERS-2 SAR) to trace the development of rice plants in an irrigated area near Niono, Mali and relate that to the density of anopheline mosquitoes, especially An. gambiae. This is important because such mosquitoes are the major vectors of malaria in sub-Saharan Africa, and their development is often coupled to the cycle of rice development. We collected larval samples, mapped rice fields using GPS and recorded rice growth stages simultaneously with eight ERS-2 SAR acquisitions. We were able to discriminate among rice growth stages using ERS-2 SAR backscatter data, especially among the early stages of rice growth, which produce the largest numbers of larvae. We could also distinguish between basins that produced high and low numbers of anophelines within the stage of peak production. After the peak, larval numbers dropped as rice plants grew taller and thicker, reducing the amount of light reaching the water surface. ERS-2 SAR backscatter increased concomitantly. Our data support the belief that ERS-2 SAR data may be helpful for mapping the spatial patterns of rice growth, distinguishing different agricultural practices, and monitoring the abundance of vectors in nearby villages.     

高分辨率SAR影像提取冰川面积与冰面河

冰川面积变化是冰川积累与消融的直接体现，与气候变化密切相关。遥感的方法可以为冰川的轮廓及面积监测提供可靠手段，但常用的光学遥感容易受到冰川区多变气象条件的影响。合成孔径雷达（SAR）不受天气影响，尤其是高分辨率SAR影像能够提供冰川表面丰富的细节特征，更好地监测冰川变化。应用相位一致性方法和快速行进法相结合的方法提取冰川轮廓和表面纹理。依据提取的冰川轮廓计算的冰川面积误差在5%以下，表明该方法能够准确地提取冰川面积。同时，在高分辨率SAR图像上，利用提取的冰川表面纹理信息可以有效监测到光学图像上难以识别的冰面河，而冰面河与冰川中长期消融密切相关，提取的冰面河信息将为冰川监测提供一种新的视角。