Analysis of ERS-1 Synthetic Aperture Radar data from Nordaustlandet,Svalbard

Study of the Earth's terrestrial ice masses (glaciers, ice caps and ice sheets), especially the seasonal variation of different surface conditions such as dry snow, wet snow and bare ice, is of particular importance in relation to possible climatic change. Synoptic monitoring techniques using visible and near-infrared satellite imagery are severely limited by the prevalence of cloud cover in the polar regions, and winter observations are impossible as a result of the absence of solar radiation. Consequently, considerable attention is now being focused on the use of imaging radar in the study of large ice masses. In this paper, we present and interpret a time-series of C-band synthetic aperture radar images acquired using the ERS-1 satellite from the Austfonna ice cap in eastern Svalbard. Winter imagery shows little variability, most of the ice cap having a uniform and high (approximately – 3dB) backscatter attributed to ice lenses or to a large effective grain size. Summer imagery shows considerable topographically-related detail, and backscatter values typically 5 to l0 dB less than in winter, which can be explained on the basis of surface scattering from wet snow. However, the marginal areas of the ice cap show a clearly defined zone of high ( –5dB) backscatter in mid- to late-August. It is proposed that this corresponds to the bare ice zone, the high backscatter values being due to scattering from crevasses and meltwater channels, and that the inner boundary of the zone of enhanced backscatter indicates the position of the transient snow line.     

Bara Shigri and Chhota Shigri glacier velocity estimation in western Himalaya using Sentinel-1 SAR data

In this article, we have presented surface velocity estimation of Chhota Shigri (CS) and Bara Shigri (BS) glaciers in the Himalaya using C-band synthetic aperture radar (SAR) data from Sentinel-1 (S-1). Repeat-pass SAR image subpixel offset tracking has been used to generate velocity vectors from yearly and seasonal S-1 data sets. SAR offset tracking on the basis of maximum intensity correlation provided the two-dimensional (2-D) movement of the both CS and BS glaciers of Chandra valley in western Himalaya. Movement of the glacier has been observed in the terminus to ablation zone during 2014–2018. S-1-derived movement is compared with in-situ measurement over CS glacier, and it has shown approximately 25% deviation during 2015–2016 with respect to field measurements from 2009 to 2010. Similar to previous decade observations, S-1 offset tracking movement results of recent three years have shown a decreasing trend.     

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.     

Observations of wind and ocean wave fields using ERS Synthetic Aperture Radar imagery

The aim of the research reported here is to evaluate Synthetic Aperture Radar (SAR) capability to estimate the wind vector and associated directional wave spectrum. Two ERS–2 SAR images of the Mediterranean Sea, one over the Sicily Channel and one over the Ligurian Sea, were selected as case studies. Wind speed was estimated using SAR calibrated backscatter response, in conjunction with empirically derived ERS scatterometer models such as CMOD4 and CMOD–IFREMER. The predictions of these models were then compared with the actual sea surface wave spectra either provided by in situ measurements or resulting from the inversion of the SAR image spectrum. SAR-detected effects of both wind and wave features, induced either by atmospheric boundary layer instability or by land shadowing, were also used as reliable indicators of wind direction.     

Combination of SRTM3 and repeat ASTER data for deriving alpine glacier flow velocities in the Bhutan Himalaya

The present study evaluates the fusion of DEMs from the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) instrument and the Shuttle Radar Topography Mission (SRTM). The study area consists of high elevation glaciers draining through the rough topography of the Bhutan Himalayas. It turns out that the ASTER-derived and SRTM3 DEMs have similar accuracy over the study area, but the SRTM3 DEM contains less gross errors. However, for rough topography large sections of the SRTM3 DEM contain no data. We therefore compile a combined SRTM3-ASTER DEM. From this final composite-master DEM, we produce repeat ASTER orthoimages from which we evaluate the DEM quality and derive glacier surface velocities through image matching. The glacier tongues north of the Himalayan main ridge, which enter the Tibet plateau, show maximum surface velocities in the order of 100-200 m year⁻¹. In contrast, the ice within the glacier tongues south of the main ridge flows with a few tens of meters per year. These findings have a number of implications, among others for glacier dynamics, glacier response to climate change, glacier lake development, or glacial erosion. The study indicates that space-based remote sensing can provide new insights into the magnitude of selected surface processes and feedback mechanisms that govern mountain geodynamics.     

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.     

雷达遥感考古机理、应用与展望

面对雷达遥感多模式、多极化和高分辨率等发展趋势,结合考古学对空间技术的迫切需求,从雷达遥感工作特性出发,阐述了雷达遥感考古的机理。在回顾雷达遥感考古取得成就的基础上,围绕考古目标探测与发现、监测与诊断等现实需求,提出了一种适应于考古研究的雷达遥感实施框架;并对当前所面临的科学问题及研究内容进行了深入探索与分析。应用实践认为以项目实施为牵引,建立典型示范案例地,开展雷达遥感机理、方法与模型等考古适应性研究刻不容缓,并可着实推进我国文明探源与遗产地可持续化发展。     

An automated scheme for glacial lake dynamics mapping using Landsat imagery and digital elevation models: a case study in the Himalayas

Glacial lakes in alpine regions are sensitive to climate change. Mapping and monitoring these lakes would improve our understanding of regional climate change and glacier-related hazards. However, glacial lake mapping over large areas using remote sensing remains a challenge because of various disturbing factors in glacial and periglacial environments. This article presents an automated mapping algorithm based on hierarchical image segmentation and terrain analysis to delineate glacial lake extents. In this algorithm, each glacial lake is delineated with a local segmentation value, and the topographic features derived from digital elevation models (DEMs) are also used to separate mountain shadows from glacial lakes. About 100 scenes of Landsat Thematic Mapper/Enhanced Thematic Mapper Plus (TM/ETM+) images from circa 1990, circa 2000 and 2009 were used to map the glacial lakes and their changes over the entire Himalayas. The results show that the algorithm can map the glacial lakes effectively and efficiently. Mountain shadows or melting glaciers can be differentiated from glacial lakes automatically, and those lakes with mountain shadows can also be identified. Area changes of more than 1000 glacial lakes show that the glacial lakes in the Himalayas have experienced mixed directions of change, while the overall lake areas are expanding at an accelerated rate in the past two decades, indicating great changes to the glacial lakes in the Himalayas.     

Airborne and spaceborne Synthetic Aperture Radar (SAR) integration with Landsat TM and gamma ray spectrometry for geological mapping in a tropical rainforest environment,the Carajas Mineral Province,Brazil

This research focuses on the integration of Synthetic Aperture Radar (SAR) (C-HH airborne, JERS-1, ERS-1) with Landsat TM and airborne gamma ray (total count, uranium, and thorium) data for geological mapping in Carajas Province, Brazil. The area is related to an Archean shear belt, with metasediments, metavolcanics, gneisses, and granulites. Anorogenic granites with Middle Proterozoic ages are scattered throughout the study area. The vegetation is typical of tropical upland rain forest. Radar and Landsat TM produce enhanced images closely related to geobotanical associations. Radar and gamma channels show the relationships between terrain morphology and bedrock radioactivity, good indicators of structures, lithological units, rock types, and hydrothermal metasomatism processes. The research emphasizes the practical importance of using SAR integrated products for geological mapping in the Amazon Region when airborne geophysical data are available.     

Lineament mapping for groundwater resource assessment: A comparison of digital Synthetic Aperture Radar (SAR) imagery and stereoscopic Large Format Camera (LFC) photographs in the Red Sea Hills,Sudan

The results of a comparative investigation of lineament mapping from stereoscopic Large Format Camera (LFC) photographs and from SIR-C L- and C-band Synthetic Aperture Radar (SAR) data are described. The lineament patterns are used to test a model developed by Koch (1993) of groundwater flow in the arid Red Sea Hills area of Sudan. Initial results show that the LFC imagery is most useful for mapping detailed fracture patterns while the combination of the L- and C-bands of the SIR-C Synthetic Aperture Radar is helpful in the location of major deep-seated fracture zones. The lineament patterns derived from LFC and SIR-C show strong N-S and E-W orientations, which correspond to the current tectonic configuration of the Red Sea rift system. The longer E-W trending features may be important from a regional hydro-geological point of view, whereas the shorter features are significant in that they interconnect the major faults.     

As-built data acquisition and its use in production monitoring and automated layout of civil infrastructure: A survey

The collection and analysis of data on the three-dimensional (3D) as-built status of large-scale civil infrastructure – whether under construction, newly put into service, or in operation – has been receiving increasing attention on the part of researchers and practitioners in the civil engineering field. Such collection and analysis of data is essential for the active monitoring of production during the construction phase of a project and for the automatic 3D layout of built assets during their service lives. This review outlines recent research efforts in this field and technological developments that aim to facilitate the analysis of 3D data acquired from as-built civil infrastructure and applications of such data, not only to the construction process per se but also to facility management – in particular, to production monitoring and automated layout. This review also considers prospects for improvement and addresses challenges that can be expected in future research and development. It is hoped that the suggestions and recommendations made in this review will serve as a basis for future work and as motivation for ongoing research and development.     

A water index for rapid mapping of shoreline changes of five East African Rift Valley lakes: an empirical analysis using Landsat TM and ETM+ data

Because of the complicated shorelines, inaccessibility and vast spread of some lakes, information on changing shorelines is difficult to acquire. A new water index (WI) has been applied to quantify changes in five saline and non‐saline Rift Valley lakes in Kenya using Landsat Thematic Mapper (TM) and Enhanced Thematic Mapper (ETM+) data. The WI is based on a logical combination of the Tasseled Cap Wetness (TCW) index and the Normalized Difference Water Index (NDWI). Using regression analysis with estimated shoreline coordinates, the WI detected the shorelines with an accuracy of 98.4%, which was 22.3% higher than the TCW, and 43.2% more accurate than the NDWI. Change detection was derived using image differencing followed by density slicing and unsupervised classification. The saline lakes (Bogoria, Nakuru and Elementaita) changed more with respect to the ratio of the change in the original surface areas than the non‐saline lakes (Baringo and Naivasha).     

Tree and building detection in dense urban environments using automated processing of IKONOS image and LiDAR data

The automated detection and reconstruction of artificial structures, larger than 10 m² in area using high resolution satellite images and Light Detection and Ranging (LiDAR) data through 3-dimensional shapes and/or 2-dimensional boundaries is described here. Additionally, it is demonstrated how individual tree crowns have been detected with more than 90% accuracy in very dense urban environments from very high-resolution images and range data. Pre-existing machine vision algorithms and techniques were modified and updated for this particular application to building detection within dense urban areas. All products from such procedures have not only been demonstrated with a significant areal coverage but have also been quantitatively assessed against manually obtained and third party mapping data. Accuracies of around 85% have been achieved for building detection and almost 95% for tree crown detection.     

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 km² 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 m³/ha, accuracies of over 80% are achieved for over a hundred ERS frames at a spatial resolution of 50 m.     

Shrinking lake basins in the proximity of the Indus Suture Zone of northwestern Himalaya: A case study of Tso Kar and Startsapuk Tso,using 1RS-1C data

The study of active tectonics in Himalaya is important as this helps to understand the style of evolutionary process of this gigantic mountain system in more specific terms. The formation of lakes, regarded as the crown stage development of an orogenic belt, is an impressive geomorphic feature that adorns the Himalayan belt end to end. Tso Kar and Startsapuk Tso are the two ancient lakes that lie south of the Indus Suture Zone in the northwestern Himalaya. An attempt has been made to map the former extent of these lakes, using remote sensing techniques, for providing vital clues in elucidating the paleoenvironmental conditions under which these water bodies were developed. It is observed that the dimension of these lakes has constantly fluctuated in time due to ongoing compression in the collision regime and possible climatic influences that have been recorded on a large scale globally. An added advantage of this study has been to evaluate the high spatial resolution data of the Indian Remote Sensing Satellite (IRS-1C) for geomorphological, lithological and structural inferences in the arid, inaccessible and complex terrain like the northwestern Trans Himalaya.     

Evolution of urban monitoring with radar interferometry in Madrid City: performance of ERS-1/ERS-2, ENVISAT,COSMO-SkyMed,and Sentinel-1 products

During the last decades, synthetic aperture radar (SAR) image exploitation has matured with the launch of different satellite missions and the development of different techniques, which allow exploiting the capabilities of the radar images. Among these techniques, persistent scatterer interferometry (PSI) has proven to be a powerful tool to derive terrain deformations over urban areas. It is based on the use of a large number of images over wide areas in order to obtain terrain displacements time series. The imagery from the different SAR missions has led to an archive with data that covers up to 30 years in the past. Moreover, different methods and algorithms have been proposed in order to perform this complex task. In this line, this work aims at identifying if data from different missions and processed by different techniques can be combined in order to study the evolution of urban monitoring. Three different PSI techniques are used in order to process data from four SAR missions: European Remote Sensing (ERS)-1/2, Environmental Satellite, COSMO-SkyMed, and the recent Sentinel-1 A/B. The rapidly evolving urban area of Madrid, where numerous undergrounding works have been carried out in the last decade, has been chosen as the testing environment. The density of persistent scatterers, the deformation accuracy validated with GPS displacements and deformation trends are used as the key performance items for the assessment.     

Reduced rate of land subsidence since 2016 in Beijing,China: evidence from Tomo-PSInSAR using RadarSAT-2 and Sentinel-1 datasets

ABSTRACT

Land subsidence associated with groundwater extraction in the city of Beijing, China, has been a problem for decades. Remote sensing has been used extensively in prior studies to monitor subsidence in Beijing. However, given recent changes in precipitation and groundwater management, there is an urgent need to update the subsidence record and to evaluate whether the long-term spatiotemporal patterns of subsidence have changed. This study therefore investigates the recent spatiotemporal patterns of land subsidence in Beijing by tomography-based persistent scatterer interferometry SAR (Tomo-PSInSAR) technology, using 39 RadarSAT-2 images from 2012 to 2015 and 33 Sentinel-1 images from 2016 to May-2018, and drawing upon Geographic Information System (GIS) spatial analysis methods. Vertical ground deformation rates in Beijing were found to range from ?176.2 to +12.3 mm year^?1 from 2012 to 2015, but subsequently decreased to ?119 to +8 mm year^?1 from 2016 to May 2018. Three spatial scale of subsidences are evident: At the metropolitan regional-scale, the total area of subsidence area is about 1235.2 km², and comprises four main subsiding regions, located in the northern and eastern parts of the city. More than 85% of the subsiding area is located between the Fifth and Sixth Ring Roads. At a more local scale, eight main subsidence bowls are characterized by different patterns of subsidence. Some of the subsidence bowls are separated by active faults. Time-series data of the displacement show that the decreasing subsidence rate after 2016 could be due to the 1 m rise in mean groundwater level from the end of 2014 to mid-2018. This change in groundwater level is likely due to an increase in precipitation since 2016, and water transfers, which reached 2.3 × 10⁹ m³ by 2017 from the South-North Water Transfer Project. At the scale of individual infrastructure projects, the Beijing subway, main roads and the Capital Airport all show severe uneven subsidence, which is a cause for concern. To our knowledge, this research is the first study using satellite SAR remote sensing methods to document the change in the land subsidence rate of Beijing. Starting in 2016, the rate notably declined, suggesting that subsidence mitigation strategies are beginning to have an effect.     

Modelling and mapping of above ground biomass (AGB) of oil palm plantations in Malaysia using remotely-sensed data

Estimating accurate above ground biomass (AGB) of oil palm plantation in Malaysia is crucial as it serves as an important indicator to assess the role of oil palm plantations in the global carbon cycle, particularly whether it serves as carbon source or sink. Research on oil palm AGB in Malaysia using remote sensing is almost insignificant and it has known that remote sensing provides easy, inexpensive and less time consuming over larger areas. Therefore, this study focuses on evaluating the potential of Landsat Thematic Mapper (TM) data with combination of field data survey to predict AGB estimates and mapping the oil palm plantations. The relationships of AGB with individual TM bands and various selected vegetation indices were examined. In addition, various possibilities of data transform were explored in statistical analysis. The potential models selected were obtained using backward elimination method where R², adjusted R² (R²_adj), standard error of estimate (SE_E), root mean squared error (RMSE) and Mallows’s C_p criterion were examined in model development and validation. It was found that the most promising model provides moderately good prediction of about 62% of the variability of the AGB with RMSE value of 3.68 tonnes (t) ha^-1. In conclusion, Landsat TM offers the low cost AGB estimates and mapping of oil palm plantations with moderate accuracy in Malaysia.     

Mapping and monitoring of degraded lands in part of Jaunpur district of Uttar Pradesh using temporal spaceborne multispectral data

Apart from soil erosion by wind and water, the major land degradation processes operating in irrigated commands in arid and semi-arid regions are waterlogging and subsequent salinization/alkalinization. Remote sensing data have been used successfully in studies of the spatial extent, magnitude and temporal behaviour of lands affected by such processes. In this work we interpreted Landsat Multispectral Scanner images acquired during 1975 and Landsat Thematic Mapper data acquired during 1993, in conjunction with ancillary information and adequate ground data, to derive information on the extent and spatial distribution of various degraded lands, namely salt-affected soils, waterlogged areas and eroded lands in part of the Jaunpur district of Uttar Pradesh. The results indicate a significant shrinkage in the spatial extent of salt-affected soils (of the order of 49.76%) over the period 1975 to 1993. A similar trend was observed in the temporal behaviour of waterlogged areas, but an increase (6.45%) was found in the spatial extent of eroded lands. The methodology employed and the observations made are described here in detail.