Enhanced automatic detection of human settlements using Sentinel-1 interferometric coherence

This article presents an experiment in which multi-temporal interferometric coherence calculated from 6-days Sentinel-1A and Sentinel-1B image pairs and backscatter intensity σ° are jointly used for the extraction of built-up areas in the framework of the symbolic machine learning classification. The results obtained with the proposed approach confirm the enhanced capabilities of discriminating built-up areas when using coherence information in comparison to two available global human settlement layers derived: (1) from Landsat optical data and (2) from Sentinel-1 ground range detected data and based on backscatter intensity σ° only. The experiment carried out in The Netherlands Randstad area is expected to be indicative of the results obtainable for urban areas having similar structures and types of built-up.     

Assessing the activity of a large landslide in southern Italy by ground-monitoring and SAR interferometric techniques

Landslides are recognized as one of the most damaging natural hazards in Italy. Campania region represents a complex geological setting, where mass movements of different types are widespread, and urban expansion can be increasingly seen by the presence of buildings and infrastructure in landslide-prone areas. In such a context, monitoring of unstable slopes represents a key activity in the process of landslide risk prevention and mitigation, in order to correctly establish a cause–effect correlation and to predict the possible reactivation phases that may result in high costs for the human society. This article focuses on the application of different methods of landslide analysis and monitoring, including those developed more recently and based on data acquired by satellites and processed by synthetic aperture radar (SAR) interferometric techniques. The study area is a small town, Calitri, known worldwide for the large landslide reactivated by the 23 November 1980 earthquake that destroyed a large sector of the historical centre. The site has been investigated by two ground-monitoring campaigns, the analysis of which allowed identification of the evolution of landslide activity over time. Furthermore, differential SAR interferometry (DInSAR), based upon two different approaches, allowed us to produce point-wise and wide area deformation maps after processing data sets of Earth Resource Satellite 1/2 (ERS-1/2) images, respectively acquired in 1992–2001 and 1992–1995. The results obtained from this analysis highlighted the potentiality of remote-sensing tools in landslide hazard assessment and led to development of a research project based on the installation of corner reflectors along unstable slopes and aimed at creating a field–Earth observation monitoring system.     

林地山区滑坡遥感的最优融合方法及应用

滑坡作为造成巨大经济损失和人员伤亡的地质灾害之一,越来越引起社会的高度重视。为精确识别林地山区中的滑坡灾害,以2020年7月6日发生在湖南省常德市石门县南北镇潘坪村的雷家山滑坡为研究对象,使用不同的融合方法进行Sentinel-1A C波段干涉宽幅的地距多视产品和Sentinel-2A多光谱2A级光学影像融合,得到主成分分析融合方法对分贝化处理后的S1A VV极化影像与S2A影像融合效果最优,采用支持向量机方法分别对最优融合影像和原始S2A影像进行滑坡识别,最后使用S2A影像滑坡目视解译结果为检验标准对支持向量机滑坡识别结果进行精度评价,同时以2020年7月21日发生在湖北恩施屯堡乡马者村的沙子坝滑坡作为案例检验该方案的可推广性。结果表明：与单独使用光学影像进行研究区滑坡识别相比,使用最优融合影像滑坡识别的准确率由95.24%提升到了96.65%,滑坡提取质量也由87.18%提升到了91.84%,滑坡的漏识别和过度识别均有所降低,说明光学影像和合成孔径雷达影像融合的研究方案具有可推广性,能提高林地山区滑坡识别的准确率,可以更好地为滑坡风险评估、灾后应急调查以及灾后恢复重建等提供有价值的...     

Advanced InSAR techniques for deformation studies and for simulating the PS-assisted calibration procedure of Sentinel-1 data: case study from Thessaloniki (Greece), based on the Envisat/ASAR archive

Using state-of-the-art InSAR techniques, namely persistent scatterers (PSs) and small baseline subset (SBAS) approaches, this study contributes to open geotechnical questions in the area of Thessaloniki (Greece) from a remote-sensing perspective. It also demonstrates the potential of these techniques for calibration purposes, with reference to the new C-band synthetic aperture radar (SAR) sensor on board the Sentinel-1 mission satellites. By exploiting the historical archive of Envisat/ASAR data, as well as a pair of the first Sentinel-1A SAR images, recent (2004–2010) deformation rates up to 18 mm year^–1 are detected over the study area. These results are then compared to the findings of previous InSAR and geophysical observations, indicating for example, subsidence or tectonic activity. On the other hand, the usefulness of the PS technique is shown over the same region for external SAR calibration purposes. This process simulates the PS-assisted calibration procedure to be applied systematically to Sentinel-1 SAR products.     

A new phase unwrapping method based on region recognition and region expansion

Phase unwrapping is a key step in retrieving digital elevation models (DEMs) from across-track interferometric synthetic aperture radar (InSAR) data. The coherence of synthetic aperture radar (SAR) data set is an effective indicator for the quality of phase unwrapping. However, the coherence of different regions usually distributes unevenly in SAR images monitoring heterogeneous areas. Errors in low-coherence areas are prone to pollute the whole image. In order to mitigate propagation error, a new phase unwrapping algorithm based on region recognition and region expansion is proposed. In the region recognition step, optical images are incorporated to recognize low-coherence regions by virtue of supervised classification technique. Low-coherence regions and the ones that are not of interest for the application are then discarded. In the region expansion step, stable pixels of high coherence are selected as growing seeds, and then phase unwrapping grows from high-quality regions to low-quality ones guided by coherence information and weighted numbers of neighbouring unwrapped pixels. The ambiguity number of a wrapped pixel is estimated from its neighbouring pixels under the criteria of pixel distance and phase gradient. Iterative examination continues until the whole image is unwrapped. Experiments on PALSAR and ASAR data demonstrate its validity and advantages over other classical methods.     

Sentinel-1 bathymetry for North Sea palaeolandscape analysis

Submerged palaeolandscapes can contain pristine underwater heritage. Regular monitoring of these areas is essential to assess and mitigate threats from development including construction, mining, and commercial trawling. While bathymetry alone may be insufficient to detect submerged palaeolandscape features, it can nonetheless recognize previously mapped structures that have a topographic expression. The Sentinel-1 constellation will provide unprecedented access to freely available, high-resolution Synthetic Aperture Radar (SAR) data, acquired systematically and with long-term continuity, and may constitute a cost-effective solution for the monitoring of submerged palaeolandscapes. The article shows the application of a recently developed bathymetric algorithm to Sentinel-1 SAR data over a region of the southern North Sea. Results show general agreement with water depth data obtained from the European Marine Observation and Data Network portal for bathymetry (EMODnet). To assess the support that SAR bathymetry can provide to the analysis of submerged palaeolandscapes, the Sentinel-1-derived water depths were compared to a palaeolandscape map of the same area produced by the North Sea Palaeolandscapes Project (NSPP). Results show a clear correspondence between certain topographic structures identified in the Sentinel-1 water depth map and features interpreted by the NSPP as early Holocene lakes, rivers, and landscape topography.     

Optimal estimation of interferometric phase for measuring surface deformation

In recent times, time-series interferometric synthetic aperture radar (InSAR) methods are developed to retrieve the deformation signal in non-urban areas from distributed scatterers (DS). Phase triangulation algorithm (PTA), an important step in these methods for filtering decorrelation noise from DS, aims at optimal estimation of the filtered wrapped interferometric phase values using InSAR data stack. The uniqueness of this research work lies in the incorporation of one such PTA only to provide an optimal set of wrapped interferometric phase values before phase unwrapping in the open source StaMPS processing environment. The proposed methodology, when adapted to measure surface deformation in Tehri reservoir rim region, Uttarakhand, India using Environmental Satellite (Envisat) C-band advanced synthetic aperture radar images, works efficiently and has enhanced the spatial coverage of measurement pixels compared to standalone PS-InSAR processing. It is also revealed from the one-dimension-line of sight velocity map that resulted velocity estimates are congruent with standalone PS-InSAR processing.     

Analysis of deformation over permafrost regions of Qinghai-Tibet plateau based on permanent scatterers

The surface displacement by seasonally freezing bulge and thawing subsidence are the main hazards for engineering construction in permafrost regions, especially for the Qinghai-Tibet railway. One of the main problems is how to monitor the frozen ground's displacement in the process of construction and protection of the Qinghai-Tibetan railway. The technology of Permanent Scatterers (PS) has been successfully used to detect the long-term subsidence at urban areas. For detecting the subsidence of the frozen earth on Qinghai-Tibet Plateau, this paper extended the capability of the technology of PS to investigate deformation phenomena in vegetated area. The paper analyses an interferometric phase model, and presents improved PS algorithms for separating different components in interferometric phase. The proposed technique is implemented using ENVISAT ASAR images to detect the deformation over permafrost region of Qinghai-Tibet Plateau. The results are in concordance with results provided by a traditional ground levelling, which encourages future development using the Permanent Scatterers method to analyse deformation of the frozen earth on Qinghai-Tibet Plateau.     

A comparison of Arctic sea ice freeboard products from Sentinel-3A and CryoSat-2 data

ABSTRACT

A number of satellite altimeters have been used to measure Arctic sea ice freeboard and to study its changes over the past decades (1992-present). In order to produce long-term time series of sea ice freeboard data set, it is essential to investigate the difference and consistency between different satellite-based sea ice freeboard data sets. Hence in this study, the comparison between ice freeboard products from altimeters on board Sentinel-3A and CryoSat-2 is constructed from February 2017 to January 2018 excluding summer months. The comparisons of echo waveform shapes and along-track radar freeboard estimates suggest that the freeboard difference between these two sensors is caused by the signal range bin number and the chosen retrackers for different surface types (leads and sea ice floes). Monthly gridded freeboard results show that mean values of two different satellite altimeters agree each other reasonably over the whole study period. In general, Sentinel-3A data set shows lower freeboard estimates than CryoSat-2 data set, this phenomenon is found in both First-Year ice (FYI) and Multi-Year ice (MYI) regions. No ice-type-related difference indicates the good consistency between Sentinel-3A and CryoSat-2 data sets. Over the whole period, mean freeboard estimates for the entire Arctic differs generally by not more than 0.07 m between Sentinel-3A and CryoSat-2. Compared to airborne Operation IceBridge (OIB) data, Sentinel-3A has closer sea ice freeboard estimates than CryoSat-2.     

Towards automated mapping and monitoring of potentially dangerous glacial lakes in Bhutan Himalaya using Sentinel-1 Synthetic Aperture Radar data

The majority of glacial lakes around the world are located in remote and hardly accessible regions. The use of remote sensing data is therefore of high importance to identify and assess their potential hazards. However, the persistence of cloud cover, particularly in high mountain areas such as the Himalayas, limits the temporal resolution of optical satellite data with which we can monitor potentially dangerous glacial lakes (PDGLs). The ability of Synthetic Aperture Radar (SAR) satellites to collect data, irrespective of weather and at day or night, facilitates monitoring of PDGLs by without compromising temporal resolution. In this study, we present a semi-automated approach, based on a radar signal intensity threshold between water and non-water feature classes followed by post-processing including elevations, slopes, vegetation and size thresholds, to delineate glacial lakes in Sentinel-1 SAR images in Bhutan Himalaya. We show the capability of our method to be used for delineating and monitoring glacial lakes in Bhutan Himalaya by comparing our results to 10 m resolution Sentinel-2 multispectral data, field survey data, meteorological data, and a time series of monthly images from January to December 2016 of two lakes. Sentinel-1 SAR data can, moreover, be used for detecting lake surface area changes and open water area variations, at temporal resolution of six days, providing substantial advantages over optical satellite data to continuously monitor PDGLs.     

Sentinel-1-based flood mapping: a fully automated processing chain

This article presents an automated Sentinel-1-based processing chain designed for flood detection and monitoring in near-real-time (NRT). Since no user intervention is required at any stage of the flood mapping procedure, the processing chain allows deriving time-critical disaster information in less than 45 min after a new data set is available on the Sentinel Data Hub of the European Space Agency (ESA). Due to the systematic acquisition strategy and high repetition rate of Sentinel-1, the processing chain can be set up as a web-based service that regularly informs users about the current flood conditions in a given area of interest. The thematic accuracy of the thematic processor has been assessed for two test sites of a flood situation at the border between Greece and Turkey with encouraging overall accuracies between 94.0% and 96.1% and Cohen’s kappa coefficients (κ) ranging from 0.879 to 0.910. The accuracy assessment, which was performed separately for the standard polarizations (VV/VH) of the interferometric wide swath (IW) mode of Sentinel-1, further indicates that under calm wind conditions, slightly higher thematic accuracies can be achieved by using VV instead of VH polarization data.     

Annual seasonality in Sentinel-1 signal for forest mapping and forest type classification

ABSTRACT

The Sentinel-1 satellites provide the formerly unprecedented combination of high spatial and temporal resolution of dual polarization synthetic aperture radar data. The availability of dense time series enables the derivation and analysis of temporally filtered annual backscatter signals. The study concentrates on the use of Sentinel-1 seasonal backscatter signatures for forest area estimation and forest type classification. A classification method based on time series similarity measures is introduced and tested in three test areas covered by various forest types including broadleaf temperate, boreal and montane forests. The results are compared with two European-wide Copernicus high resolution layers, namely forest type and tree cover density (TCD). The correspondence of forest/non-forest maps and TCD is high in all test areas, with overall accuracies for forest/non-forest classification between 86% and 91% and Pearson correlation coefficients for TCD between 0.68 and 0.74. The forest type classification (non-forest, coniferous and broadleaf forest classes) provides best results in temperate forests with an overall accuracy of 85%; in boreal forest, the accuracy decreases to only 65%. Generally, the method provides reliable results for forest area estimation, including regions where methods based on static parameters are often problematic (mountainous areas), and it enables forest type classification in temperate forests.     

Study on Differences between Sentinel-2A and Landsat-8 Images in Rape Identification

Rape is one of the most important crops for many countries,so it is important to obtain accurate rape area.Compared with Landsat-8 data,Sentinel-2A has many advantages,but whether the results of Sentinel-2A data in crop identification are better than Landsat-8 is still an unknown question.The study site is located in a typical agricultural region：Gaochun District in Nanjing,the capital of Jiangsu Province,China,with central coordinates of 118°52′E and 31°19′N.One Sentinel-2A and one Landsat-8 image were obtained during the flowering stage of rape,and then rape area was extracted by using different classification methods based on spectral characteristics and vegetation indices.By comparing the identification accuracy of two images under different classification conditions and methods,the results show that：(1) The difference of spectral characteristics and separability of vegetation indices of different objects in Sentinel-2A were higher than those of Landsat-8 images;(2) Under the classifier of support vector machine,the Producer’s and User’s accuracy of rape of Sentinel-2A based on spectral characteristics were 89.7% and 91.3% respectively,which were 7.0% and 6.2% higher than the identification accuracy of Landsat-8 data;(3) After adding texture information,the overall accuracy and kappa coefficient of two kinds of data were significantly improved,but there was no increase in the producer’s and user’s accuracy of rape.The result presented in this paper show that compared with Landsat-8 data,Sentinel-2A data is more suitable for extracting crop distribution information in small areas with complex planting structure,which can lay a theoretical foundation for crop identification and application of Sentinel-2A data.     

Correction of cirrus effects in Sentinel-2 type of imagery

Optical satellite images are often contaminated with cirrus clouds. Thin cirrus can be detected with a channel at 1.38 μm, and an established cirrus removal method exists for visible/near-infrared (VNIR) channels in atmospheric window regions, which was demonstrated with Moderate Resolution Imaging Spectrometer (MODIS) data. This contribution addresses open issues of cirrus correction for Sentinel-2 type of instruments, that is, future spaceborne sensors such as Sentinel-2 or similar instruments. These issues are (i) an extension of the existing technique to account for cirrus during the water vapour retrieval (channel at 0.94 μm) and surface reflectance calculation to avoid reflectance artefacts at 0.94 μm, (ii) a discussion of options concerning cirrus removal in the short-wave infrared (SWIR, channels at 1.6 and 2.2 μm) region and (iii) an analysis of channel parallax (view angle) requirements to achieve a high-quality cirrus removal.     

Landslide detection in La Paz City (Bolivia) based on time series analysis of InSAR data

Geologically, La Paz City is located in an unstable area. During the history of La Paz city, many landslides have destroyed houses and valuable infrastructures. In the last decades, time series Interferometric Synthetic Aperture Radar (InSAR) technologies have demonstrated a great capacity for detecting slow ground displacement, achieving an accuracy of millimetre-level. In order to have a better landslide monitoring of La Paz city, in this study, the Sentinel-1 SAR images have been processed by Persistent Scatterer Interferometry (PSI) and the Small Baseline Subset (SBAS) techniques. The time span of the datasets is from March 2015 to August 2016. Both ascending and descending Synthetic Aperture Radar (SAR) images have been processed to obtain the line of sight (LOS) ground velocity, and then the results have been combined to estimate the up-down and east-west displacement. Several active movement areas have been identified, showing a surface velocity up to 158 mm year^?1 westward and 49 mm year^?1 eastward. Furthermore, two important findings have been discovered. First, the InSAR result has detected movement in Auquisamaa hill before the area collapsed (15 February 2017), where five houses are buried. Second, the InSAR result has identified that there are still some unstable sites in Callapa area, where a mega-landslide has destroyed more than a thousand of houses in February 2011. In conclusion, we have verified that the InSAR technology could be a very useful tool to help La Paz public institutions for a better management of urban planning, landslide areas delimitation and landslide risk mitigation.     

Using sentinel-1A SAR wind retrievals for enhancing scatterometer and radiometer regional wind analyses

Scatterometer surface wind speed and direction observations in combination with radiometer wind speeds allow to generate surface wind analyses with high space and time resolutions over global as well as at regional scales. Regarding scatterometer sampling schemes and physics, the resulting surface wind analyses suffer from lack of accuracy in areas near coasts. The use of the synthetic aperture radar (SAR) onboard the Sentinel-1A satellite attempts to address the enhancement of surface wind analyses issues. In this study, SAR wind speeds and directions retrieved from backscatter coefficients acquired in interferometric wide (IW) swath mode are used. Their accuracy is determined through comprehensive comparisons with moored buoy wind measurements. SAR and buoy winds agree well at offshore and nearshore locations. The statistics characterizing the comparison of SAR and buoy wind speeds and directions are of the same order as those obtained from scatterometer (Advanced SCATterometer (ASCAT) and RapidScat) and buoy wind comparisons. The main discrepancy between SAR and buoy data are found for high wind speeds. SAR wind speeds exceeding 10 m s^–1 tend to be underestimated. A similar conclusion is drawn from SAR and scatterometer wind speed comparisons. It is based on the underestimation of SAR backscatter coefficient (σ°) with respect to σ° estimated from scatterometer winds and the geophysical model function (GMF) named CMOD-IFR2 (Ifremer C band MODel). New SAR wind speeds are retrieved using CMOD-IFR2. The corrected SAR retrievals allow better determination of the spatial characteristics of surface wind speeds and of the related wind components in near-coast areas. They are used for enhancing the determination of the spatial structure function required for the estimation of wind fields gridded in space and time at the regional scale. The resulting wind fields are only determined from scatterometer wind observations in combination with radiometer retrievals. Their qualities are determined through comparisons with SAR wind speeds and directions, and through their application for determination of wind power off Brittany coasts.     

Testing two methods for mapping water hyacinth (Eichhornia crassipes) in the Greater Letaba river system,South Africa: discrimination and mapping potential of the polar-orbiting Sentinel-2 MSI and Landsat 8 OLI sensors

ABSTRACT

Early detection and mapping of the spatio-temporal distribution of invasive water hyacinth (Eichhornia crassipes) in inland hydrological systems are vital for a number of water resource management-related reasons. Field surveys and current climate change projections (associated with longer dry spells, and shortened rain seasons) have shown that climate change and the rapid spread of aquatic invasive species are increasingly affecting inland surface water availability in semi-arid regions of Southern Africa. It is upon this premise that accurate, reliable, and timely information on the spatio-temporal distribution and configuration of water hyacinth is required in tracing their evolution and propagation in affected areas as well as in potential vulnerable areas. This work, therefore, attempts to test two robust push-broom multispectral sensors: Landsat 8 Operational Land Imager (OLI) and Sentinel-2 MultiSpectral Instrument (MSI) in identifying, detecting, and mapping the spatial distribution and configuration of invasive water hyacinth in a river system. The results of the study show that water hyacinth in small reservoirs can be mapped with an overall accuracy of 68.44% and 77.56% using Landsat 8 and Sentinel-2 data, respectively. The results further demonstrated the blue, red, red edge (RE) 1, short-wavelength infrared (SWIR)-1, and SWIR-2 of both satellite data sets as the critical and outstanding spectral regions in detecting and mapping water hyacinth from other land-cover types. Overall, the study highlights the unexploited prospects of the new noncommercial multispectral sensors in monitoring invasive species infestation from inland surface waterbodies in semi-arid regions (i.e. smaller reservoirs).     

Fusion of Sentinel-1 and Sentinel-2 image time series for permanent and temporary surface water mapping

ABSTRACT

Monitoring the spatial and temporal extents of permanent and temporary bodies of surface water is important for various applications such as water resource management, climate modelling, and biodiversity conservation. Satellite remote sensing is an effective source of information to detect surface water over large areas and document their evolution in time. Recently, the European Space Agency (ESA) launched freely available SAR (Synthetic Aperture Radar) and optical sensors (Sentinel-1 & 2) with high revisiting time and spatial resolution. The objective of this paper is to explore the contribution of multi-temporal and multi-source (passive and active) Sentinel observations for improving the detection and mapping of surface waters by applying decision-level image fusion techniques. The approach is tested over Central Ireland using a time series of 16 Sentinel-1 images and a few Sentinel-2 images for the period 2015–2016. Compared to a mono-date approach, the combination of Sentinel-1 & 2 observations provides better accuracy for mapping permanent surface water. Decision level fusion technique allows mapping temporary surface water (such as flooding) with a high accuracy. It also gives the possibility to monitor their dynamics by providing the probability of occurrence of flooded areas at the pixel level.     

Using C/X-band SAR interferometry and GNSS measurements for the Assisi landslide analysis

This work presents an analysis of the applicability of synthetic aperture radar (SAR) interferometry to landslide monitoring. This analysis was carried out by using different interferometric approaches, different spaceborne SAR data (both in the C-band and in the X-band), and in situ global navigation satellite system (GNSS) measurements. In particular, we investigated both the reliability of displacement monitoring and the issues of the cross-comparison and validation of the interferometric synthetic aperture radar (InSAR) results. The work was focused on the slow-moving landslide that affects a relevant part of the urban area of the historical town of Assisi (Italy).

A C-band ENVISAT advanced synthetic aperture radar (ENVISAT ASAR) dataset acquired between 2003 and 2010 was processed by using two different interferometric techniques, to allow cross-comparison of the obtained displacement maps. Good correspondence between the results was found, and a deeper analysis of the movement field was possible. Results were further compared to a set of GNSS measurements with a 7 year overlap with SAR data. A comparison was made for each GNSS marker with the surrounding SAR scatterers, trying to take into account local topological effects, when possible.

Further, the high-resolution X-band acquired on both ascending and descending tracks by the COSMO-SkyMed (CSK) constellation was processed. The resultant displacement fields show good agreement with C-band and GNSS measurements and a sensible increase in the density of measurements.     

Sensitivity of Sentinel-1 backscatter to characteristics of buildings

In this study, Sentinel-1 interferometric wide swath (IW) mode backscatter is analysed with respect to physical parameters of buildings in Tallinn, Estonia. Dependence on height, alignment, density, shape, and material is shown and discussed. Distribution of backscatter was estimated with respect to each of the parameters, and a correlation matrix of all physical parameters and backscatter values was computed. Height has the strongest effect on backscatter values for both polarization bands, while shape and alignment to orbit has weaker effect on the backscatter. Relationship of co-polarized and cross-polarized backscatter with how a building is aligned with respect to the satellite’s look angle indicates that double bounce from wall–ground interactions is still the dominant scattering mechanism detected by Sentinel-1 in IW mode with 20 m resolution. In order to establish possible detection problems related to specifically oriented buildings at different latitudes, dihedral backscatter is modelled for buildings of oblong and square shapes. Results from this study should be used to improve existing and develop new urban area detection methods based on Sentinel-1 data.