Japanese Earth Resources Satellite Research Articles

Floodplain water storage in the Negro River basin estimated from microwave remote sensing of inundation area and water levels

The objective of this study is to determine spatio-temporal variations of water volume over inundated areas located in large river basins using combined observations from the Synthetic Aperture Radar (SAR) onboard the Japanese Earth Resources Satellite (JERS-1), the Topex/Poseidon (T/P) altimetry satellite, and in-situ hydrographic stations. Ultimately, the goal is to quantify the role of floodplains for partitioning water and sediment fluxes over the great fluvial basins of the world. SAR images are used to identify the type of surface (open water, inundated areas, forest) and, hence, the areas covered with water. Both radar altimetry data and in-situ hydrographic measurements yield water level time series. The basin of the Negro River, the tributary which carries the largest discharge to the Amazon River, was selected as a test site. By combining area estimates derived from radar images classification with changes in water level, variations of water volume (focusing on a seasonal cycle) have been obtained. The absence of relationship between water volume and inundated area, reflecting the diverse and widely dispersed floodplains of the basin, is one of the main result of this study.

Evaluation and Perspectives of Using Multitemporal L-Band SAR Data to Monitor Deforestation in the Brazilian AmazÔnia

Japanese Earth Resources Satellite 1 (JERS-1) synthetic aperture radar (SAR) data were evaluated to map areas of deforestation in a Brazilian Amazo/spl circ/nia test-site. The results were compared with information derived from a Landsat TM multitemporal series. Unambiguous detection of deforested areas was observed only when the entire deforestation process (slash, burning, and terrain clearing) had already occurred. This result recommends further investigations on the effectiveness of horizontal polarization SAR data to map deforestation in a consistent basis. The cross-polarized (horizontal-vertical) channel designed to be in the ALOS/PALSAR system is expected to improve the distinction between forested and recently deforested areas.

Synthetic Aperture Radar (L band) and Optical Vegetation Indices for Discriminating the Brazilian Savanna Physiognomies: A Comparative Analysis

Abstract The all-weather capability, signal independence to the solar illumination angle, and response to 3D vegetation structures are the highlights of active radar systems for natural vegetation mapping and monitoring. However, they may present significant soil background effects. This study addresses a comparative analysis of the performance of L-band synthetic aperture radar (SAR) data and optical vegetation indices (VIs) for discriminating the Brazilian cerrado physiognomies. The study area was the Brasilia National Park, Brazil, one of the test sites of the Large-Scale Biosphere–Atmosphere (LBA) experiment in Amazonia. Seasonal Japanese Earth Resources Satellite-1 (JERS-1) SAR backscatter coefficients (σ°) were compared with two vegetation indices [normalized difference vegetation index (NDVI) and enhanced vegetation index (EVI)] over the five most dominant cerrados’ physiognomies plus gallery forest. In contrast to the VIs, σ° from dry and wet seasons did not change significantly, indicating primary response to vegetation structures. Discriminant analysis and analysis of variance (ANOVA) showed an overall higher performance of radar data. However, when both SAR and VIs are combined, the discrimination capability increased significantly, indicating that the fusion of the optical and radar backscatter observations provides overall improved classifications of the cerrado types. In addition, VIs showed good performance for monitoring the cerrado dynamics.

An application of L-band synthetic aperture radar to tide height measurement

A method for measuring the tide height near the coast from L-band synthetic aperture radar (SAR) data is presented. Twenty-one coherent interferograms have been successfully constructed from Japanese Earth Resources Satellite 1 (JERS-1) SAR data obtained over oyster sea-farming structures. A coherence analysis of the 21 interferometric pairs showed that a perpendicular baseline of less than 3 km, with a temporal baseline within 500 days, are required to obtain a coherent pair, with a coherence higher than 0.25, in the study area. The coherent phases preserved in the interferograms showed a close relation with the sea level. The problem of phase unwrapping to restore an absolute tide height was overcome by introducing normalized image intensities. The radar measurements estimated by the proposed method were verified using tide gauge data, and comparison of the two datasets yielded a correlation coefficient R/sup 2/ of 0.91, with a root mean square error of 5.76 cm. The results demonstrate that radar interferometry can be applied for a tide height measurement near the coast given sufficient structures that return off-nadir radar pulses to the antenna. The multipolarized L-band SAR system will provide better results, using only double-bounced signals, in the future.

Interlook cross-correlation function of speckle in SAR images of sea surface processed with partially overlapped subapertures

In the present paper, a general integral expression is derived and discussed for the cross-correlation function (CCF) of speckle patterns in synthetic aperture radar (SAR) images processed by using partially overlapped subapertures of arbitrary Doppler center frequencies (or equivalent azimuth times). It is shown that, under the white noise approximation for the backscattered field, the CCF of the interlook speckle intensity patterns is given by the squared modulus of the autocorrelation function of the amplitude weighting function of subapertures where the time lag is the center time difference. It is also shown that the CCF of the interlook speckle patterns is independent of the surface coherence time of sea surface. The integral expression for the intensity CCF is then evaluated for a rectangular weighting function, and comparison is made with Japanese Earth Resources Satellite-1 (JERS-1) L-band and RADARSAT-1 C-band SAR images of sea surface to test the theory. The CCFs computed from the JERS-1 SAR data show excellent agreement with the theory, and good agreement is obtained with the RADARSAT-1 data.

Plio-Quaternary extension in the Venezuelan Andes: Mapping from SAR JERS imagery

The geometry of extensional structures is described for the first time in the active setting of the Venezuelan Andes using remote sensing imagery. We favored the use of a mosaic of Synthetic Aperture Radar (SAR) scenes of the Japanese Earth Resources Satellite-1 (JERS-1) assisted by complementary remote sensing devices (Landsat TM, digital elevation models) and field observations to make a structural analysis at regional scale. Radar images are particularly efficient in the Venezuelan Andes where dense vegetation and frequent cloud covering earlier lent difficulties to remote sensing studies. We focused our analysis in the Valera–Rio Momboy and Bocono faults corner and in the Mucujun area. We show that, in an area where ongoing compression and strike–slip deformations occur, brittle extension can be detected independently from previous knowledge. Extensional structures correspond to elongated tilted blocks with dimension less than 10 km in width. Blocks are bounded by curved faults in plan view, the concavity being turned towards the axial part of the belt. The geometry and kinematics of such structures suggest that syn-orogenic extension started together with initiation of right-lateral strike–slip motion along the Bocono Fault in the Plio-Quaternary.

Long-term stability of L-band normalized radar cross section of Amazon rainforest using the JERS-1 SAR

This paper describes the long-term stability of L-band synthetic aperture radar (SAR) data observed over the Amazon and the applicability of the Amazon as a calibration reference. We evaluated 139 Japanese Earth Resources Satellite 1 (JERS-1) SAR images acquired over the southwest Amazon during six and a half years (1992–1998), including wet and dry seasons. During each season, the data appeared to be stable, with mean values of –6.81 and –7.08 dB, standard deviations of 0.20 and 0.18 dB, and a 0.27 dB difference between the two seasons. The Amazon is thus a stable reference for calibration.

A novel approach to the classification of regional-scale Radar mosaics for tropical vegetation mapping

The Global Rain Forest Mapping (GRFM) radar mosaics, generated from L-band Japanese Earth Resources Satellite 1 imagery downsampled to 100-m pixel size, provide a two-season spatially continuous coverage of the humid tropical ecosystems of the world. This paper presents a novel classification approach suitable for regional-scale vegetation mapping using the GRFM datasets. The mapping system consists of: 1) an application-dependent wavelet-based edge-preserving smoothing algorithm and 2) a two-stage per-pixel hybrid learning nearest multiple-prototype (NMP) classifier, whose unsupervised first stage is a per-pixel near-optimal vector quantizer, called enhanced Linde-Buzo-Gray (ELBG), recently proposed in pattern recognition literature. Identified as ENMP (NMP with ELBG), this novel classification approach is compared against two alternative systems in the classification of forest cover disturbances located across an area in the Amazon Basin. Surface classes of interest are primary forest, degraded forest, nonforest, and water bodies. Reference maps, derived from 30-m resolution Landsat Thematic Mapper imagery, are provided by the National Aeronautics and Space Administration and the Food and Agriculture Organization of the United Nations. Abundant quantitative and qualitative evidence shows that: 1) in a forest/nonforest data-mapping task, ENMP provides a testing accuracy of 87%, in line with training accuracies, i.e., the proposed method seems capable of generalizing well over the GRFM South America dataset and 2) among three competing approaches, ENMP provides the best compromise between ease of use, mapping accuracy, and computational time. Starting from these results, ENMP is employed to generate a swamp forest map of the whole Amazon Basin from the two-season GRFM radar mosaic of South America, in the context of the Global Land Cover project (GLC 2000).

Defining approaches to settlement mapping for public health management in Kenya using medium spatial resolution satellite imagery

This paper presents an appraisal of satellite imagery types and texture measures for identifying and delineating settlements in four Districts of Kenya chosen to represent the variation in human ecology across the country. Landsat Thematic Mapper (TM) and Japanese Earth Resources Satellite-1 (JERS-1) synthetic aperture radar (SAR) imagery of the four districts were obtained and supervised per-pixel classifications of image combinations tested for their efficacy at settlement delineation. Additional data layers including human population census data, land cover, and locations of medical facilities, villages, schools and market centres were used for training site identification and validation. For each district, the most accurate approach was determined through the best correspondence with known settlement and non-settlement pixels. The resulting settlement maps will be used in combination with census data to produce medium spatial resolution population maps for improved public health planning in Kenya.

Seasonal change in the extent of inundation on floodplains detected by JERS-1 Synthetic Aperture Radar data

Two sets of JERS-1 (Japanese Earth Resource Satellite–1) Synthetic Aperture Radar (SAR) data, coupled with ancillary datasets, were analysed in an effort to find a single algorithm to study the extent of inundation and its variation on floodplains at a regional scale. The SAR data were acquired on 14 January, 1993 and 9 August, 1994. The study area was ca 14 212 km2, covering the lower portions of the Cape Fear, Lumber, Little Pee Dee and Waccamaw river basins within the states of North Carolina and South Carolina, USA. The analysis was based on the decision tree classification that classifies the study area into three aquatic categories, water, marsh and flooded forest, and two upland classes, field and non-flooded forest. From January 1993 to August 1994, the aquatic extent varied from 4872 km2 to 3496 km2, and upland 9340 km2 to 10 717 km2. The decrease of the water, marsh and flooded forest categories and the increase of the field and non-flooded forest classes were mainly caused by falls in water surface heights and discharges of the rivers and their tributaries from January 1993 to August 1994. The overall classification accuracy was near to 90%. The search for the single algorithm ended with promising results and also prompted additional research.

Evaluation of JERS-1 SAR Images From a Coastal Wind Retrieval Point of View

Wind retrieval from Japanese Earth Resources Satellite-1 (JERS-1) synthetic aperture radar (SAR) using an L-band model function in coastal regions is evaluated. It is known that JERS-1 SAR has excessive ambiguities. This paper also gives a quantitative evaluation of excessive ambiguities in coastal scenes of JERS-1 SAR. First, focusing on the cases where wind blows from the shore in Sagami Bay, we investigate phenomena of wind speed increase with offshore distance using European Remote sensing Satellite-1 (ERS-1) SAR-derived wind speeds. The relation between wind speed and offshore distance is well formulated, which indicates the transition of the atmospheric boundary layer from land to sea surface. Wind speeds derived from JERS-1 SAR should be overestimated due to the excessive ambiguity. Then, for observation time of each JERS-1 SAR capturing the cases that wind blows from the shore in Sagami Bay, the expected wind speed growth profile is derived from the wind speed growth formula and an in situ wind observation of Hiratsuka Experiment Station. We convert the wind-speed profile into the sigma-0 profile by an L-band model function. Finally, the profiles of JERS-1 SAR-observed and the estimated sigma-0 are compared, and the excessive ambiguity is estimated as the difference between them. As a result, the dynamic range of first azimuth ambiguity is as large as that of the wind-relating signal from the ocean surface. Moreover, higher order azimuth ambiguities and range ambiguity also may have a significant impact on near-shore wind retrieval.

Updated repeat orbit interferometry package released

RO1_PAC V2.3, a Repeat Orbit Interferometry package that allows topographic and surface change researchers to apply Interferometric Synthetic Aperture Radar (InSAR) methods, is now freely available to the community InSAR is the synthesis of conventional SAR and interferometry techniques that have been developed over several decades in radio astronomy and radar remote sensing. In recent years, it has opened entirely new application areas for radar in the Earth system sciences, including topographic mapping and geodesy.RO1_PAC, developed primarily to work with European Remote Sensing (ERS) satellite radar data, currently supports ERS‐1, ERS‐2, and Japanese Earth Resources Satellite (JERS) radar data, and is configurable to work with “strip‐mode” data from all existing satellite radar instruments. The first release of RO1_ PAC (V1.0) was made quietly in 2000, and roughly 30 groups in the academic and research community currently use it.

Radar remote sensing for monitoring of dynamic ecosystem processes related to biogeochemical exchanges in tropical peatlands

Peatlands are an important multipurpose ecosystem, supporting huge quantities of biomass and peat soil carbon. A time series of Japanese Earth Resource Satellite-1 (JERS-1) L-band Synthetic Aperture Radar (SAR) data was employed to monitor two dynamic ecosystem processes; deforestation and inundation patterns. Using a change detection analysis for three images acquired during dry seasons of 1994, 1997 and 1998, we detected the deforestation that has occurred in the region due to the anthropogenic and natural causes. At a threshold of ±2 dB change in backscattering response, an area of about 98 km2 of these forests was found to have been cleared during 1994–1997 for conversion to cultivatable lands. However, the agricultural crops miserably failed to grow on these cleared lands because of the adverse water and soil chemistry conditions. The deliberate draining of these lands, by laying and extension of a huge network of canals, created congenial ecological conditions for the spread of forest fires, particularly during the 1997 El Nino period. An area of 250 km2 of forests was thus detected to have been destroyed by these fires between September 1997 and January 1998. These deforested lands are rapidly regenerating since their abandonment and the regenerating carbon stocks were simulated using the CENTURY ecosystem dynamics model. Furthermore, the L-band SAR was able to detect the pixel-wise seasonal and spatial inundation information for particular forest types where the transmissivity of the L-band SAR signals was quite significant. These forest types corresponded to comparatively low biomass areas. The SAR derived information about these two important dynamic processes would be useful for improving the accuracy of modelling the spatial and temporal distribution of the carbon and other trace gases in these ecosystems.

Dual-season mapping of wetland inundation and vegetation for the central Amazon basin

Wetland extent was mapped for the central Amazon region, using mosaicked L-band synthetic aperture radar (SAR) imagery acquired by the Japanese Earth Resources Satellite-1. For the wetland portion of the 18×8° study area, dual-season radar mosaics were used to map inundation extent and vegetation under both low-water and high-water conditions at 100-m resolution, producing the first high-resolution wetlands map for the region. Thematic accuracy of the mapping was assessed using high-resolution digital videography acquired during two aerial surveys of the Brazilian Amazon. A polygon-based segmentation and clustering was used to delineate wetland extent with an accuracy of 95%. A pixel-based classifier was used to map wetland vegetation and flooding state based on backscattering coefficients of two-season class combinations. Producer's accuracy for flooded and nonflooded forest classes ranged from 78% to 91%, with lower accuracy (63–65%) for flooded herbaceous vegetation. Seventeen percent of the study quadrat was occupied by wetlands, which were 96% inundated at high water and 26% inundated at low water. Flooded forest constituted nearly 70% of the entire wetland area at high water, but there are large regional variations in the proportions of wetland habitats. The SAR-based mapping provides a basis for improved estimates of the contribution of wetlands to biogeochemical and hydrological processes in the Amazon basin, a key question in the Large-Scale Biosphere–Atmosphere Experiment in Amazônia.

Measurements of soil compaction rate by using JERS-1 SAR and a prediction model

The soil compaction rate in a reclaimed land has been estimated by using the Japanese Earth Resources Satellite 1 (JERS-1) synthetic aperture radar (SAR) two-pass differential interferometry (DInSAR) and magnetic probe extensometer (an accuracy of /spl plusmn/1 mm) from 42 ground stations. Twelve JERS-1 SAR interferometric pairs were acquired in the study area. We applied a soil compaction prediction model based on a hyperbolic method using the ground truth data and the DInSAR measurements. The hyperbolic model fitted well to the ground measurements with an rms error of 1.65 cm. The rms error of the model driven by DInSAR measurements was 2.24 cm. The two model results agreed well, showing a difference of 8.1% (12.9 cm) in permanent settlement that is defined as the amount of vertical subsidence as time goes to infinity. A two-dimensional (2-D) subsidence map was constructed from five qualified pairs. The correlation coefficient R between the radar measurements and the ground truth data was 0.87 with an rms error of 1.44 cm. The results demonstrate that the L-band DInSAR combined with a prediction model is useful for geotechnical applications.

Multitemporal repeat-pass sar interferometry of boreal forests

Multitemporal European Remote Sensing satellites 1 and 2 (ERS-1/2) and the Japanese Earth Resources Satellite 1 (JERS-1) interferometric synthetic aperture radar (InSAR) data from a boreal forest test site in Sweden (stem volumes up to 335 m/sup 3//ha, equivalent to above-ground dry biomass of /spl sim/200 tons/ha) are studied in order to estimate stem volume using coherence and backscatter. The changes of JERS-1 backscatter and ERS-1/2 tandem coherence between images are consistent over the area studied, in contrast to ERS-1/2 backscatter. A model-based regression analysis has been performed, and the use of the model for inversion is discussed and compared with other approaches found in the literature. The model parameters are discussed in terms of their relation to wind speed and temperature. Results from the different acquisitions are combined to improve the stem volume estimation. The accuracy in terms of rms error (RMSE) for standwise estimated stem volume is /spl ap/10 m/sup 3//ha using ERS-1/2 coherence. Using backscatter and coherence from JERS-1 we obtain an RMSE of /spl ap/30-35 m/sup 3//ha. Finally, conditions for accurate retrieval of stem volume using multitemporal InSAR observations are discussed. We conclude that C- and L-band repeat-pass InSAR can provide stem volume estimates in boreal forests with accuracies similar to those of standard in situ measurements.

JERS SAR interferometry for land subsidence monitoring

In this paper, the potential of L-band repeat-pass differential synthetic aperture radar (SAR) interferometry for land subsidence monitoring is evaluated using Japanese Earth Resources Satellite (JERS) SAR data. Bologna, Mexico City, and the Ruhrgebiet are selected as application sites representing slow to fast deformation velocities. The investigation includes feasibility aspects such as data availability, the temporal decorrelation over different landcover classes and the range of useful spatial baselines, an analysis of the achieved deformation accuracy, and considerations on the complementarity to European Remote Sensing satellite (ERS) SAR interferometry and leveling surveys. In spite of the rather limited data availability, land subsidence maps could be generated for the three selected application sites. In contrast to ERS C-band SAR data, JERS L-band interferometry permitted the retrieval of subsidence values over vegetated areas and forest when using interferograms of less than one year acquisition time interval and short baseline. In addition, the longer L-band wavelength was found to be superior in the case of large deformation gradients that lead to phase-unwrapping problems in C-band interferometry.

Multitemporal jers repeat-pass coherence for growing-stock volume estimation of siberian forest

Multitemporal radar data from the Japanese Earth Resources Satellite (JERS) satellite from the period 1993 to 1998 have been used to investigate if L-band interferometric coherence with a 44-day temporal baseline is suitable for estimations of growing-stock volume in boreal forest. Two forest regions north of Krasnoyarsk in Siberia have been used as test areas. Seasonal variations in the repeat-pass coherence have been studied, and a comparison with C-band coherence from the European Remote sensing Satellite 1 and 2 (ERS-1/2) tandem missions in 1997 and 1998 has been done. JERS coherence from the winter shows a clear correlation with the forest growing-stock volume. For the summer scenes, the spread in the values is too large to give reliable results. Acquisitions from the spring and fall show large problems with decorrelation caused by temporal changes. The results indicate potential of repeat-pass interferometric L-band coherence in winter, as will be provided by the forthcoming Advanced Land Observing Satellite/Phased Array type L-band Synthetic Aperture Radar (ALOS/PALSAR) to map growing-stock volume in Siberia and boreal forests.

An L-band geophysical model function for SAR wind retrieval using JERS-1 SAR

An L-band geophysical model function is developed using Japanese Earth Resources Satellite-1 (JERS-1) synthetic aperture radar (SAR) data. First, we estimate the SAR system noise, which has been a serious problem peculiar to the JERS-1 SAR. It is found that the system noise has a feature common in all the SAR images and that the azimuth-averaged profile of noise can be expressed as a parabolic function of range. By subtracting the estimated noise from the SAR images, we can extract the relatively calibrated ocean signals. Second, using the noise-removed SAR data and wind vector data from the NASA Scatterometer and buoys operated by the Japan Meteorological Agency, we generate a match-up dataset, which consists of the SAR sigma-0, the incidence angle, the surface wind speed, and wind direction. Third, we investigate the sigma-0 dependence on incidence angle, wind speed, and wind direction. While the incidence angle dependence is negligible in the present results, we can derive distinct sigma-0 dependence on wind speed and direction. For wind speeds below 8 m/s, the wind direction dependence is not significant. However, for higher wind speeds, the upwind-downwind asymmetry becomes very large. Finally, taking into account these characteristics, a new L-band-HH geophysical model function is produced for the SAR wind retrieval using a third-order harmonics formula. Resultant estimates of SAR-derived wind speed have an rms error of 2.09 m/s with a negligible bias against the truth wind speed. This result enables us to convert JERS-1 SAR images into the reliable wind-speed maps.

Large-scale mapping of boreal forest in SIBERIA using ERS tandem coherence and JERS backscatter data

Siberia's boreal forests represent an economically and ecologically precious resource, a significant part of which is not monitored on a regular basis. Synthetic aperture radars (SARs), with their sensitivity to forest biomass, offer mapping capabilities that could provide valuable up-to-date information, for example about fire damage or logging activity. The European Commission SIBERIA project had the aim of mapping an area of approximately 1 million km 2 in Siberia using SAR data from two satellite sources: the tandem mission of the European Remote Sensing Satellites ERS-1/2 and the Japanese Earth Resource Satellite JERS-1. Mosaics of ERS tandem interferometric coherence and JERS backscattering coefficient show the wealth of information contained in these data but they also show large differences in radar response between neighbouring images. To create one homogeneous forest map, adaptive methods which are able to account for brightness changes due to environmental effects were required. In this paper an adaptive empirical model to determine growing stock volume classes using the ERS tandem coherence and the JERS backscatter data is described. For growing stock volume classes up to 80 m 3/ha, accuracies of over 80% are achieved for over a hundred ERS frames at a spatial resolution of 50 m.