Progresses on SAR Remote Sensing of Tropical Forests:Forest Biomass Retrieval and Analysis of Changing Weather Conditions

This paper is intended to report on the progresses made during the Dragon-4 project Three and Four-Dimensional Topographic Measurement and Validation(ID:32278),sub-project Multi-baseline SAR Processing for 3 D/4 D Reconstruction(ID:322782).The work here reported focuses on two important aspects of SAR remote sensing of tropical forests,namely the retrieval of forest biomass and the assessment of effects due to changing weather conditions.Recent studies have shown that by using SAR tomography the backscattered power at 30 m layer above the ground is linearly correlated to the forest Above Ground Biomass(AGB).However,the two parameters that determine this linear relationship might vary for different tropical forest sites.For purpose of solving this problem,we investigate the possibility of using Li DAR derived AGB to help training the two parameters.Experimental results obtained by processing data from the Tropi SAR campaign support the feasibility of the proposed concept.This analysis is complemented by an assessment of the impact of changing weather conditions on tomographic imaging,for which we simulate BIOMASS repeat pass tomography using ground-based Tropi SCAT data with a revisit time of 3 days and rainy days included.The resulting backscattered power variation at 30 m is within 1.5 d B.For this forest site,this error is translated into an AGB error of about 50~80 t/hm^(2),which is 20%or less of forest AGB.

Landslide monitoring with high-resolution SAR data in the Three Gorges region

Employing the well-known D-InSAR technique,we investigated landslide monitoring in the Three Gorges region using TerraSAR-X data.The experiment demonstrates that using both the amplitude and differential phase allows us to identify the precise location,deformation and time range of occurrence of certain landslides.To overcome the atmospheric effect on D-InSAR results,a time-series analysis was also carried out.The observed nonlinear relationship between the deformation and water level suggests that reservoir water level fluctuation is one of the major causes of landslides,which is significant in terms of issuing landslide warnings.In addition,the comparison of TerraSAR-X and C-band ASAR data results indicates that TerraSAR-X data provide far more reasonable deformation measurements because of their high temporal and spatial resolutions.

Absolute geolocation accuracy of high-resolution spotlight TerraSAR-X imagery–validation in Wuhan

TerraSAR-X(TSX)can acquire high-resolution SAR images and due to its high orbit precision as well as its ability to acquire data from different off-nadir viewing angles,the high-precision stereo geolocation can be obtained.In this study,we investigate the absolute geolocation accuracy of TSX high-resolution images in Wuhan,China.We present a direct stereo SAR geolocation method and analyze the 2D and 3D geoposition accuracy of two corner reflectors.The sub-meter localization accuracy was achieved using only atmospheric correction information available in the TSX metadata.

Iteration convergence condition modeling for single spaceborne SAR image direct positioning

Single SAR image direct positioning is to determine the ground coordinate for each pixel in the SAR image assisted with a reference DEM.During this procedure,an iterative procedure is essentially needed to solve the uncertainty in elevation of each pixel in the SAR image.However,such an iterative procedure may suffer from the problem of divergence in shaded and serious layover areas.To investigate this problem,we performed a theoretical analysis on the convergence conditions that has not been intensively studied till now.The Range-Doppler(RD)model was simplified and then the general surface is degenerated into a planar surface.Mathematical deduction was then carried out to derive the convergence conditions and the impact factors for the convergence speed were evaluated.The theoretical findings were validated by experiments for both simulated and real scenarios.

Decomposing and mapping different scales of land subsidence over Shanghai with X-and C-Band SAR data stacks

Land subsidence can be observed with time-series of Interferometric Synthetic Aperture Radar(InSAR)data.However,existing approaches only reveal subsidence signals that are multi-scale mixed,which is not conducive to the systematic analysis of subsidence of different mechanisms.A deformation signal decomposition(DSD)method based on spectral analysis is used to decompose the deformation extracted by time-series InSAR into three classes of deformation signals.They refer to large-scale deformation related to geological settings,medium-scale deformation caused more by group excavation,and small-scale deformation along linear infrastructures.TerraSAR-X datasets for Shanghai spanning April 2013 to September 2020,and Sentinel-1A datasets spanning January 2016 to September 2020 are used in this study.The results were cross-verified between the TerraSAR-X and Sentinel-1A datasets,and validated against levelling measurements.Subsidence signals caused by different mechanisms were automatically decomposed,which facilitates a systematic analysis for targeted diagnosis of land subsidence signals.A detailed analysis was conducted jointly at three scales of surface displacement,geological conditions,major construction activities,and subsidence mechanisms.It indicated that construction activities were the leading cause of land subsidence,and suggests that local authorities that wish to mitigate surface subsidence may benefit from primarily considering this process.

Change detection, risk assessment and mass balance of mobile dune fields near Dunhuang Oasis with optical imagery and global terrain datasets

Quantifying the kinematic evolution patterns of dune migration plays a major role in resisting the sand-dust disasters and evaluating the desertification process.With the increment of optical observations,measuring the dune migration with dense spatial and temporal density has become possible.In this study,with the open-accessible Landsat-8(L8)/Sentinel-2(S2)imagery and global terrain datasets,we designed a complete workflow of inverting the dune displacement time series and velocity,identifying the potential encroachment risk,and evaluating the sediment balance of mobilized dune fields near Dunhuang Oasis.After the performance of time-series inversion,the standard deviation(STD)of measurements in stable area of raw correlation results was improved by above 40%.The displacement time series and velocity revealed out the spatial heterogeneity and seasonal/inter-annual dynamic evolution of dune migration.Furthermore,dune encroachment risk in the immediate vicinity of local landscapes was evaluated to highlight the unstable dune fields,and the workability of existent sand-control facilities.Additionally,the mass budget of around−0.001±0.025 m/yr shows the stable sediment transport in Mingsha mountain.This study case can be exemplified to lead the risk monitoring and sustainable conservation of Dunhuang region and other places controlled by similar climatic conditions.

Potential loess landslide deformation monitoring using L-band SAR interferometry

Multi-temporal InSAR technique can implement continuous earth surface deformation detection with long time scale and wide geographical coverage.In this paper,we first employ the Small Baseline Subset method to survey potential landslides in Guide County,Qinghai Province,which is identified as a loess landslide prone area for geological and climate conditions.Two anomalous deformation regions are detected by L-band Phased Array and L-band Synthetic Aperture Radar stacks.Then,qualitative and quantitative evaluations of the measuring points are given for understanding the distribution regularity of deformation.Finally,preliminary correlation between the time-series deformation and triggering factors is analyzed to explore the driving mechanism for landslide movement.The results demonstrate that L-band SAR has high potential in landslide monitoring applications and can be used as the basis for landslide recognizing,precursory information extracting,and early warning.

Elevation change around Dome A region of Antarctica from EnviSat satellite radar altimetry during 2002–2012

The expected responses of ice sheets to climate warming are growth in the thickness of the inland ice areas and thinning near the margins.In recent decades,researchers have identified glacier acceleration along Antarctic ice sheet coastal margins.However,the study of ice sheet interiors where seasonal accumulation eventually balances ice wastage at the lower elevation is poorly understood.In this paper,the ice sheet elevation change around Dome A region is analyzed from 2002 to 2012 using two million elevation change measurements from EnviSat satellite radar altimeter data covering an area of about 7000 km2.A declining trend of 0.572±1.31 mm/year which means that the Dome A region was in balance during the last decade can be captured.In addition,two obvious changes in accumulation which divide elevation change time series into three independent equilibration stages are also extracted.In order to explain this phenomenon,two speculations related to snowfall and firn compaction are proposed in this paper.

Monitoring the built-up environment of Shanghai on the street-block level using SAR and volunteered geographic information

In this geo-statistical analysis of change detection,we illustrate the evolution of the built-up environment in Shanghai at the street-block level.Based on two TerraSAR-X image stacks with 36 and 15 images,covering the city centre of Shanghai for the time period from 2008 to 2015,a set of coherence images was created using a small baseline approach.The road network from Open Street Map,a volunteered geographic information product,serves as the input dataset to create street-blocks.A street-block is surrounded by roads and resembles a ground parcel,a real estate property–a cadastral unit.The coherence information is aggregated to these street-blocks for each observation and the variation is analysed over time.An analysis of spatial autocorrelation reveals clusters of similar behaviours.The result is a detailed map of Shanghai highlighting areas of change.We argue that the aggregation and grouping of synthetic aperture radar coherence image information to real-world entities(street-blocks)is comprehensible and relevant to the urban planning process.Therefore,this research is a contribution to the community of urban planners,designers,and government agencies who want to monitor the development of the urban landscape.