Phased Array Type L-band Synthetic Aperture Radar Research Articles

The Penetration Depth Derived from the Synthesis of ALOS/PALSAR InSAR Data and ASTER GDEM for the Mapping of Forest Biomass

The Global Digital Elevation Model produced from stereo images of Advanced Spaceborne Thermal Emission and Reflection Radiometer data (ASTER GDEM) covers land surfaces between latitudes of 83°N and 83°S. The Phased Array type L-band Synthetic Aperture Radar (PALSAR) onboard Advanced Land Observing Satellite (ALOS) collected many SAR images since it was launched on 24 January 2006. The combination of ALOS/PALSAR interferometric data and ASTER GDEM should provide the penetration depth of SAR data assuming ASTER GDEM was the elevation of vegetation canopy top. It would be correlated with forest biomass because penetration depth could be affected by forest density and forest canopy height. Their combination held great promises for the forest biomass mapping over large area. The feasibility of forest biomass mapping through the data synthesis of ALOS/PALSAR InSAR data and ASTER GDEM was investigated in this study. A procedure for the extraction of penetration depth was firstly proposed. Then three models were built for biomass estimation: (I) model only using backscattering coefficients of ALOS/PALSAR data; (II) model only using penetration depth; (III) model using both of them. The biomass estimated from Lidar data was taken as reference data to evaluate the three different models. The results showed that the combination of backscattering coefficients and penetration depth gave the best accuracy. The forest disturbance has to be considered in forest biomass estimation because of the long time span of ASTER data for generating ASTER GDEM. The spatial homogeneity could be used to improve estimation accuracy.

Structural mapping using PALSAR data in the Central Gold Belt, Peninsular Malaysia

The Central Gold Belt (CGB) of Peninsular Malaysia has been investigated to map structural elements associated with gold mineralization using the Phased Array type L-band Synthetic Aperture Radar (PALSAR) satellite remote sensing data. Gold mineralization in this belt is structurally controlled and associated with steeply dipping faults and fold hinges. Adaptive local sigma and directional filters were applied to PALSAR data for tracing structural elements associated with gold mineralization. Structural features along the Bentong–Raub Suture Zone have been identified as highly potential areas for gold prospecting. Four sets of lineaments trending N–S, NE–SW, NNW–SSE and ESE–WNW were identified. Results of this study demonstrate the applicability of PALSAR remote sensing data to assist gold exploration in the CGB particularly in reducing costs related to exploration for epithermal and polymetallic vein-type mineralization in tropical environments.

SAR-derived wind fields at the coastal region in the East/Japan Sea and relation to coastal upwelling

The relationship between the modification of synthetic aperture radar (SAR) wind field and coastal upwelling was investigated using high-resolution wind fields from Advanced Land Observing Satellite (ALOS) Phased Array type L-band synthetic aperture radar (PALSAR) imagery and sea-surface temperature (SST) from National Oceanic and Atmospheric Administration/Advanced Very-High-Resolution Radiometer (NOAA/AVHRR) data. The retrieved SAR wind speeds seem to agree well with in situ buoy measurements with only a relatively small error of 0.7 m s−1. The SAR wind fields retrieved from the east coast of Korea in August 2007 revealed a spatial distinction between near and offshore regions. Low wind speeds of less than 3 m s−1 were associated with cold water regions with dominant coastal upwelling. Time series of in situ measurements of both wind speed and water temperature indicated that the upwelling was induced by the wind field. The low wind field from SAR was mainly induced by changes in atmospheric stability due to air–sea temperature differences. In addition, wind speed magnitude showed a positive correlation with the difference between SST and air temperature (R2 = 0.63). The dependence of viscosity of water on radar backscattering at the present upwelling region was negligible since SAR data showed a relatively large backscattering attenuation to an SST ratio of 1.2 dB °C−1. This study also addressed the important role of coastal upwelling on biological bloom under oligotrophic environments during summer.

Change detection of boreal forest using bi-temporal ALOS PALSAR backscatter data

Long-wavelength Synthetic Aperture Radar (SAR) satellite systems have the potential to increase the efficiency of forest mapping and monitoring, which today are based primarily on optical satellite systems. Here, we evaluate the effectiveness of using L-band SAR satellite images to detect and delineate clear-cuts in Swedish boreal forest. A set of computationally efficient techniques are combined in a fully automated unsupervised bi-temporal change detection approach that detects changes in SAR backscatter intensities. For radiometric normalization and initial change classification, we propose an iterative procedure consisting of successive polynomial based histogram matching and thresholding. Recently proposed methods for automatic SAR amplitude ratio thresholding and final change classification are adopted. The latter is a Markov random field based change detection method that exploits both spectral and spatial information from one or multiple SAR polarization channels. The change detection approach was applied to SAR images from the Japanese Advanced Land Observing Satellite (ALOS) Phased Array type L-band Synthetic Aperture Radar (PALSAR) acquired in Fine Beam Dual (FBD) mode (HH- and HV-polarizations) with a pixel size of 20m (path data). Clear-cuts that took place between image acquisitions were clearly detected, and most errors were due to imperfect delineations of clear-cut edges. Pixel-wise clear-cut detection accuracies above 90% could be reached, with false alarm rates of approximately 10% or less. The results indicate that ALOS PALSAR path data are well suited for operational clear-cut detection in Swedish boreal forest.

Analyses of optical images and radar data reveal structural features and predict groundwater accumulations in the central Eastern Desert of Egypt

The North African Sahara is currently dominated by arid to hyperarid climate. In the central part of the Eastern Desert of Egypt, Wadi Matula is a dry stream course much like those in the rest of the Sahara. It covers an area of about 7,500 km2. Radarsat-1 images, Shuttle Radar Topography Mission (SRTM), and Advanced Land Observing Satellite (ALOS)/Phased Array type L-band Synthetic Aperture Radar (PALSAR) data revealed paleodrainage systems and fault/fracture zones. Its trends display cross-cutting relationships. Interrupted surface runoff connections are inferred from block movements, tectonic capture processes, diverted valleys, and paleodrainage. The movements of the blocks led to newly formed drainage and caused disturbances in drainage orientations, topography, fractures, and stream density. Paleodrainage and the more recent drainage lines are superposed on weakness zones of major fractures and faults. These zones facilitated the hydrologic processes that caused erosion and downcutting. The intersection points of paleochannel courses, fracture/fault systems, and active streams must have increased the possibilities of groundwater accumulations. Accordingly, several exploration wells are suggested, which they represent the best abstraction sites of groundwater potentials. These predicted sites are consistent with the high potential zone of the groundwater prospect map. Thick fluvial deposits support that past pluvial events recharged the underlying aquifers. It is concluded that locations of paleodrainage, fractures/faults, and stream intersections are the best sites for groundwater resources; thus, radar images are powerful tools for mapping multi-temporal near-surface features in arid regions.

Correction of Atmospheric Phase Screen in Time Series InSAR Using WRF Model for Monitoring Volcanic Activities

One of the main limitations in measuring ground deformation using synthetic aperture radar interferometry (InSAR) is atmospheric phase delay effects. In volcanic regions, the atmospheric phase delay effects can cause serious problems in detecting volcanic unrest because atmospheric thickness is inversely related with the elevation of a volcanic mountain. It is commonly known that the atmospheric phase screen (APS) can be decomposed spatially into stratified and turbulent components. In this paper, the stratified and turbulent atmospheric conditions of a volcanic area were simulated using weather research and forecasting (WRF) model, and the simulated atmospheric conditions were compared with in situ radiosonde data. The comparison results proved that the stratified APS from the WRF model could reflect the reasonable patterns of seasonal changes and vertical profiles with dependable quality. We also found that the stratified APS was significantly correlated with time and sometimes severely contaminated the quality of volcanic deformation estimation. These results indicate that the temporal high-pass (HP) filtering, which has been usually applied in time series InSAR analysis for extracting and removing APS, cannot work properly in volcanic area. Thus, we propose a new method that employs the stratified APS obtained from the WRF model by correlating with topography and the (residual) turbulent APS that can be effectively eliminated by temporal HP filtering in persistent scatterer interferometry (PSI). We applied the proposed method (atmosphere-corrected PSI) to Advanced Land Observing Satellite Phased Array type L-band SAR data that cover Shinmoedake volcano, Japan, and found that the estimated surface deformation and APS agreed well with those measured from GPS and Moderate-Resolution Imaging Spectroradiometer data, respectively.

Using time series PALSAR gamma nought mosaics for automatic detection of tropical deforestation: A test study in Riau, Indonesia

This study intended to demonstrate the effectiveness of phased array type L-band synthetic aperture radar (PALSAR) time series mosaics for automatic detection of tropical deforestation in Riau province, Indonesia. Using six time series PALSAR mosaics, the characteristics of HH and HV gamma nought (γ0) in natural forests and deforested areas from 2007 to 2010 and the accuracy of deforestation detection by using a threshold were investigated. We obtained the following results: (1) Applying a simple thresholding method to time series differences of γ0HV was effective for fully automatic detection of deforestation areas. When we used a fixed threshold, the accuracy ranged from 72% to 96% (average of 87%). (2) γ0HH did not always show systematic changes after deforestation. (3) The temporal variation of γ0 for deforested areas was larger than that for natural forests. These variations in γ0 were correlated with 10-day accumulated precipitation. High accumulated precipitation decreased the γ0 difference between deforested areas and natural forests, causing decreased accuracy of deforestation detection. (4) Integration of the results from two different dates in a given year can reduce the detection error due to time variations and provide highly accurate results (average accuracy of 91%, minimum of 82%). The accuracy values quoted except hilly areas, shadow, and lay-over. The proposed method is effective for detection of deforestation larger than 1ha. The deforestation mapping method proposed in the study can be utilized for assessment of yearly changes in forested areas and is useful for tracking changes in forest cover on large scales.

3-D movement mapping of the alpine glacier in Qinghai-Tibetan Plateau by integrating D-InSAR, MAI and Offset-Tracking: Case study of the Dongkemadi Glacier

Three-dimensional (3-D) movements of the Dongkemadi Glacier in the Qinghai-Tibetan Plateau over 2007–2010 are fully determined by using L-band Advanced Land Observing Satellite (ALOS) Phased Array type L-band Synthetic Aperture Radar (PALSAR) ascending and C-band Environmental Satellite (ENVISAT) Advanced Synthetic Aperture Radar (ASAR) descending acquisitions. In order to yield an optimal 3-D solution, a variance component estimation (VCE) algorithm is applied to weigh the D-InSAR and MAI measurements derived from PALSAR data and the Offset-Tracking measurements from ASAR data under the scheme of weighted least squares adjustment. By exploiting the InSAR measurements themselves to determine the weights iteratively, the presented approach results in an accuracy of centimeter to decimeter per year for all the three velocity vectors. The horizontal component shows that the four main tributary streams in the Dongkemadi Glacier are all flowing from the central area of the glacier to its surroundings, along the steepest slope descent direction and with a rate up to about 5m/yr. The glacier thickening or thinning is resolved from the vertical component by subtracting the down-slope movement. A number of interesting accumulation and ablation areas are also detected, with vertical variations of 1–2m/yr, as a result of the horizontal glacier movement or the existence of concave terrain. This can be used as a good indication of the ice dynamics and the location of the subglacial water in the alpine glacier.

Landslide observation and volume estimation in central Georgia based on L-band InSAR

Abstract. The republic of Georgia is a mountainous and tectonically active area that is vulnerable to landslides. Because landslides are one of the most devastating natural hazards, their detection and monitoring is of great importance. In this study we report on a previously unknown landslide in central Georgia near the town of Sachkhere. We used a set of Advanced Land Observation Satellite (ALOS) Phased Array type L-band Synthetic Aperture Radar (PALSAR) data to generate displacement maps using interferometric synthetic aperture radar (InSAR). We detected a sliding zone of dimensions 2 km north–south by 0.6 km east–west that threatens four villages. We estimated surface displacement of up to ∼30 cm/yr over the sliding body in the satellite line-of-sight (LOS) direction, with the largest displacement occurring after a local tectonic earthquake. We mapped the morphology of the landslide mass by aerial photography and field surveying. We found a complex set of interacting processes, including surface fracturing, shear and normal faults at both the headwall and the sides of the landslide, local landslide velocity changes, earthquake-induced velocity peaks, and loss in toe support due to mining activity. Important implications that are applicable elsewhere can be drawn from this study of coupled processes. We used inverse dislocation modelling to find a possible dislocation plane resembling the landslide basal décollement, and we used that plane to calculate the volume of the landslide. The results suggest a décollement at ∼120 m depth, dipping at ∼10° sub-parallel to the surface, which is indicative of a translational-type landslide.

Analysis of Land Deformation on Slope Area using PS InSAR. Case Study: Malang Area

The geographical position of Indonesia located between two continents and oceans is strategic, but at large risk of experiencing various disasters. Climate change and vulnerable location (surrounded by plates and geological faults in the Earth's crust) creates an earthquake-prone region and causes land/mudslides. In this paper, PS InSAR method (Persistent Scatterer Interferometric Synthetic Aperture Radar) is implemented to Phased Array type L-band Synthetic Aperture Radar (PALSAR) data to study the potential damage caused by the earthquake or volcanic eruption in Malang vicinity. By comparing the amplitude images periodically, shifting soil can be determined using precise orbital information. The analysis showed a significant decrease of land deformation on slope area in Klojen district in Malang city, reached up to −7.128 mm/year.

Structural geology mapping using PALSAR data in the Bau gold mining district, Sarawak, Malaysia

The application of optical remote sensing data for geological mapping is difficult in the tropical environment. The persistent cloud coverage, dominated vegetation in the landscape and limited bedrock exposures are constraints imposed by the tropical climate. Structural geology investigations that are searching for epithermal or polymetallic vein-type ore deposits can be developed using Synthetic Aperture Radar (SAR) remote sensing data in tropical/sub-tropical regions. The Bau gold mining district in the State of Sarawak, East Malaysia, on the island of Borneo has been selected for this study. The Bau is a gold field similar to Carlin style gold deposits, but gold mineralization at Bau is much more structurally controlled. Geological analyses coupled with the Phased Array type L-band Synthetic Aperture Radar (PALSAR) remote sensing data were used to detect structural elements associated with gold mineralization. The PALSAR data were used to perform lithological-structural mapping of mineralized zones in the study area and surrounding terrain. Structural elements were detected along the SSW to NNE trend of the Tuban fault zone and Tai Parit fault that corresponds to the areas of occurrence of the gold mineralization in the Bau Limestone. Most of quartz-gold bearing veins occur in high-angle faults, fractures and joints within massive units of the Bau Limestone. The results show that four deformation events (D1–D4) in the structures of the Bau district and structurally controlled gold mineralization indicators, including faults, joints and fractures are detectable using PALSAR data at both regional and district scales. The approach used in this study can be more broadly applicable to provide preliminary information for exploration potentially interesting areas of epithermal or polymetallic vein-type mineralization using the PALSAR data in the tropical/sub-tropical regions.

A 50-m Forest Cover Map in Southeast Asia from ALOS/PALSAR and Its Application on Forest Fragmentation Assessment

Southeast Asia experienced higher rates of deforestation than other continents in the 1990s and still was a hotspot of forest change in the 2000s. Biodiversity conservation planning and accurate estimation of forest carbon fluxes and pools need more accurate information about forest area, spatial distribution and fragmentation. However, the recent forest maps of Southeast Asia were generated from optical images at spatial resolutions of several hundreds of meters, and they do not capture well the exceptionally complex and dynamic environments in Southeast Asia. The forest area estimates from those maps vary substantially, ranging from 1.73×106 km2 (GlobCover) to 2.69×106 km2 (MCD12Q1) in 2009; and their uncertainty is constrained by frequent cloud cover and coarse spatial resolution. Recently, cloud-free imagery from the Phased Array Type L-band Synthetic Aperture Radar (PALSAR) onboard the Advanced Land Observing Satellite (ALOS) became available. We used the PALSAR 50-m orthorectified mosaic imagery in 2009 to generate a forest cover map of Southeast Asia at 50-m spatial resolution. The validation, using ground-reference data collected from the Geo-Referenced Field Photo Library and high-resolution images in Google Earth, showed that our forest map has a reasonably high accuracy (producer's accuracy 86% and user's accuracy 93%). The PALSAR-based forest area estimates in 2009 are significantly correlated with those from GlobCover and MCD12Q1 at national and subnational scales but differ in some regions at the pixel scale due to different spatial resolutions, forest definitions, and algorithms. The resultant 50-m forest map was used to quantify forest fragmentation and it revealed substantial details of forest fragmentation. This new 50-m map of tropical forests could serve as a baseline map for forest resource inventory, deforestation monitoring, reducing emissions from deforestation and forest degradation (REDD+) implementation, and biodiversity.

Multi-frequency, polarimetric SAR analysis for archaeological prospection

The aim of this study is to assess the sensitivity to buried archaeological structures of C- and L-band Synthetic Aperture Radar (SAR) in various polarisations. In particular, single and dual polarised data from the Phased Array type L-band SAR (PALSAR) sensor on-board the Advanced Land Observing Satellite (ALOS) is used, together with quadruple polarised (quad pol) data from the SAR sensor on Radarsat-2. The study region includes an isolated area of open fields in the eastern outskirts of Rome where buried structures are documented to exist. Processing of the SAR data involved multitemporal averaging, analysis of target decompositions, study of the polarimetric signatures over areas of suspected buried structures and changes of the polarimetric bases in an attempt to enhance their visibility. Various ancillary datasets were obtained for the analysis, including geological and lithological charts, meteorological data, Digital Elevation Models (DEMs), optical imagery and an archaeological chart.For the Radarsat-2 data analysis, results show that the technique of identifying the polarimetric bases that yield greatest backscatter over anomaly features, and subsequently changing the polarimetric bases of the time series, succeeded in highlighting features of interest in the study area. It appeared possible that some of the features could correspond with structures documented on the reference archaeological chart, but there was not a clear match between the chart and the results of the Radarsat-2 analysis. A similar conclusion was reached for the PALSAR data analysis. For the PALSAR data, the volcanic nature of the soil may have hindered the visibility of traces of buried features. Given the limitations of the accuracy of the archaeological chart and the spatial resolution of both the SAR datasets, further validation would be required to draw any precise conclusions on the sensitivity of the SAR data to buried structures. Such a validation could include geophysical prospection or excavation.

Integration of Polarimetric PALSAR Attributes and Local Geomorphometric Variables Derived from SRTM for Forest Biomass Modeling in Central Amazonia

. The objective of this work is to generate a predictive model for biomass estimation in a forested area of central Amazonia based on the integration of incoherent target scattering decomposition polarimetric attributes extracted from Phased Array type L-band Synthetic Aperture Radar (PALSAR) data and geomorphometric variables derived from Shuttle Radar Topography Mission (SRTM). In addition to their incorporation as variables of ecophysiological nature in biomass modeling, the geomorphometrics variables were also evaluated with regard to the possibility of minimization of topographic effects that affect the acquisition of PALSAR data. Based on the processed data, three biomass models were generated. The first model involves independent parameters extracted from polarimetric PALSAR data, the second includes the same polarimetric variables, which are additionally adjusted for the cosine factor effect. The third model integrates both the polarimetric parameters extracted from PALSAR and the geomorphometric variables derived from SRTM. The latter model showed the best results of biomass estimation among the models generated. Our results confirm the importance of geomorphometric variables as additional input in prognostic biomass models that use radar remote sensing, in this case L band, because of their causal relationship with ecophysiological aspects that condition the growth of forest communities and because of minimization of the terrain effects on the radar signal.

陸域観測技術衛星２号「だいち２号」（ALOS-２）の現状

The Advanced Land Observing Satellite-2 “Daichi-2” (ALOS-2) was successfully launched by the H-IIA launch vehicle No. 24 at 12:05:14 p.m. on May 24 2014 (Japan Standard Time). And critical operation phase was successfully completed on May 27 2014. PALSAR-2 (Phased Array type L-band Synthetic Aperture Radar-2) is the main mission instrument, have a spotlight mode (1 to 3m res.), a high resolution mode (3 to 10m res.) and a wide swath “ScanSAR” mode (60 to 100m res.). ALOS-2 will conducted (1) Disaster monitoring, (2) Archiving national land and infrastructure information related data, (3) Monitoring of cultivated area, and (4) Global monitoring.

A Heuristic Approach to Reduce Atmospheric Effects in InSAR Data for the Derivation of Digital Terrain Models or for the Characterization of Forest Vertical Structure

The differences of two digital terrain models (DTMs) derived from airborne interferometric synthetic aperture radar (InSAR) data of short and long wavelengths are utilized for the estimation of vertical forest structures. However, when the spaceborne repeat-pass InSAR data are used, atmospheric effects must be considered. A simple method for the reduction of atmospheric effects in spaceborne repeat-pass interferometry is proposed in this letter. By subtracting a simulated interferogram using the Shuttle Radar Topography Mission (SRTM) DTM from the interferogram of a pair of Phased Array Type L-Band Synthetic Aperture Radar (PALSAR) InSAR data, the remaining phase includes the phase caused by the height differences of scattering phase centers (SPC) at C- and L-bands and the phases caused by atmospheric effects and other changes during the PALSAR repeat-pass period. A low-pass spatial filtering can reveal the atmospheric effect in the phase image because of the low spatial frequency of the atmospheric effects. The proper size of the filtering window can be determined by the changes of standard deviation of filtered phase images as the window size increases. The changes of the standard deviations of the filtered phase images should be almost constant when only the atmospheric effect remains. After reducing the atmospheric effects, the difference between the SRTM-DTM and the PALSAR-DTM was reduced from 60.17 m±16.2 m to near 0 m (0.52 m±4.3 m) at bare surfaces, and the correlation (R <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> ) between the mean forest height and the difference between the SRTM-DTM and the PALSAR-DTM was significantly increased from 0.021 to 0.608.

A Study on Tropical Land Cover Classification Using ALOS PALSAR 50 m Ortho-Rectified Mosaic Data

The main objective of this study is to find better classifier of mapping tropical land covers using Synthetic Aperture Radar (SAR) imagery. The data used are Advanced Land Observing Satellite (ALOS) Phased Array type L-band Synthetic Aperture Radar (PALSAR) 50 m ortho-rectified mosaic data. Training data for forest, herbaceous, agriculture, urban and water body in the test area located in Kalimantan were collected. To achieve more accurate classification, a modified slope correction formula was created to calibrate the intensity distortions of SAR data. The accuracy of two classifiers called Sequential Minimal Optimization (SMO) and Random Forest (RF) were applied and compared in this study. We focused on object-based approach due to its capability of providing both spatial and spectral information. Optimal combination of features was selected from 32 sets of features based on layer value, texture and geometry. The overall accuracy of land cover classification using RF classifier and SMO classifier was 46.8% and 55.6% respectively, and that of forest and non-forest classification was 74.4% and 79.4% respectively. This indicates that RF classifier has better performance than SMO classifier.

Water Quality Analysis of Lake Hachiroko, Japan, using ALOS PALSAR Data

In recent years, remote sensing data have been used for water quality analyses. Such data have favorable features, including instantaneousness, wide area of coverage and periodicity. In our previous studies, we analyzed the data collected from an Advanced Visible and Near Infrared Radiometer type-2 (AVNIR-2) optical sensor of the Advanced Land Observing Satellite (ALOS), and an active sensor of JERS-1 Synthetic Aperture Radar (SAR), using a fuzzy regression model with one input and one output. In this paper, to examine the usefulness of the fuzzy regression model for a water quality analysis, data from ALOS Phased Array type L-band Synthetic Aperture Radar (PALSAR) are used. A fuzzy regression analysis was performed using the Min and Max problems, and through fuzzy-level slice processing, maps of the estimated water quality were obtained from the ALSO PALSAR data. Furthermore, by comparing the results obtained using data collected from both ALOS AVNIR-2 and JERS-1 SAR, we examine the differences in the classification resulting from the differences in the sensors and resolutions.

Carbon Stock Calculating and Forest Change Assessment Toward REDD+ Activities for The Mangrove Forest in Vietnam

Mangrove forests are one of the main forest types in Vietnam. However, during the last decades, a lot of mangrove forest area has been converted to other land-use types. The objectives of this study are to assess the changes that occurred in the mangrove forests from 1990 to 2010 and to determine a method for carbon-stock calculating for the forests that can be used as the input data for a Reference Emission Levels (REL) calculation. The study was conducted in two different research areas; one was the Quang Ninh province in the north of Vietnam, and the other took place in the Ca Mau and Kien Giang provinces in the south. In this research, the maps of mangrove forests for the periods of 1990, 2000, and 2010 were created by using optical satellite-imagery data. The change matrix was then calculated by overlaying maps of different periods in the forests for analyzing the changes and assessment. Field trips were also taken to each study area in order to verify/adjust the latest classified mangrove forest maps and interview/identify the main causes of land-use changes taking place during these periods. During the fieldwork, a number of sample points were surveyed to collect the number of parameters of mangrove trees. These data are then used for analyzing the relationship between tree height and the HH and HV values of ALOS PALSAR (Advanced Land Observing Satellite Phased Array type L-band Synthetic Aperture Radar) data. An allometric relationship between biomass and tree height was also applied for investigating the relationship between aboveground biomass and ALOS PALSAR polarimetric data. Finally, the change in the carbon stock of the forests through all periods was estimated for living biomass, fuel-wood gathering, and other losses by applying the stock-change method. The results of this study were the mangrove forest maps and biomass maps for the years 1990, 2000, and 2010; the changes analysis showed that the forest area is decreasing and that the main cause is the conversion of the forests to aquaculture land, according to the equations/models of biomass estimation for biomass mapping based on ALOS PALSAR data.

The Temporal-Spatial Distribution of Shule River Alluvial Fan Units in China Based on SAR Data and OSL Dating

Alluvial fans in arid and semi-arid regions can provide important evidence of geomorphic and climatic changes, which reveal the evolution of the regional tectonic activity and environment. Synthetic aperture radar (SAR) remote sensing technology, which is sensitive to geomorphic features, plays an important role in quickly mapping alluvial fan units of different ages. In this paper, RADARSAT-2 (Canada’s C-band new-generation radar satellite) and ALOS-PALSAR (Japan’s advanced land observing satellite, phased array type L-band SAR sensor) data, acquired over the Shule River Alluvial Fan (SRAF), are used to extract backscattering coefficients, scattering mechanism-related information, and polarimetric characteristic parameters. The correlation between these SAR characteristic parameters and fan units of the SRAF of different ages was studied, and the spatial distribution of fan units, since the Late Pleistocene, was extracted based on the Maximum Likelihood classification method. The results prove that (1) some C-band SAR parameters can describe the geomorphic characteristics of alluvial fan units of different ages in the SRAF; (2) SAR data can be used to map the SRAF’s surface between the Late Pleistocene and the Holocene and to extract the spatial distribution of fan units; and (3) the time-spatial distribution of the SRAF can provide valuable information for tectonic and paleoenvironmental research of the study area.