Estimating Area Coverage and Volume of Hot Lava by Integrating Multiple Satellite Remote Sensing Techniques

Areal Coverage ◽

Volcanic Processes ◽

Distribution Index ◽

Temporal Coverage ◽

Area And Volume

Monitoring the regions that are prone to natural hazards is essential in disaster management, since early warnings can be issued. Airborne and space-borne remote sensing techniques are cost-effective in accomplishing the task. Estimating the area and volume of erupted lava can help researchers understand the volcanic processes and impact on land use and land cover. In this study, we developed a new algorithm to estimate areal coverage and volume of exposed hot lava by integrating the space-borne Interferometric Synthetic Aperture Radar (InSAR), thermal infrared, and Normalized Vegetation Distribution Index (NDVI) techniques. We applied this algorithm to the eruption of the East Rift Zone (ERZ) of the Kilauea volcano took place between May and August 2018 and estimated the areal coverage and volume of lava erupted. We compared the results of InSAR to those derived from airborne Light Detection and Ranging (LiDAR), and found that although air-borne LiDAR provides data with higher resolution and accuracy, InSAR is almost as good as LiDAR in monitoring deformed areas and has larger spatial and temporal coverage.

Review of Satellite Interferometry for Landslide Detection in Italy

Remote Sensing ◽

10.3390/rs12081351 ◽

2020 ◽

Vol 12 (8) ◽

pp. 1351 ◽

Cited By ~ 8

Author(s):

Lorenzo Solari ◽

Matteo Del Soldato ◽

Federico Raspini ◽

Anna Barra ◽

Silvia Bianchini ◽

...

Keyword(s):

Remote Sensing ◽

Management Strategies ◽

Back Analysis ◽

Remote Sensing Data ◽

Economic Losses ◽

Monitoring Tools ◽

Average Production ◽

Landslide Mapping ◽

Remote Sensing Techniques

Landslides recurrently impact the Italian territory, producing huge economic losses and casualties. Because of this, there is a large demand for monitoring tools to support landslide management strategies. Among the variety of remote sensing techniques, Interferometric Synthetic Aperture Radar (InSAR) has become one of the most widely applied for landslide studies. This work reviews a variety of InSAR-related applications for landslide studies in Italy. More than 250 papers were analyzed in this review. The first application dates back to 1999. The average production of InSAR-related papers for landslide studies is around 12 per year, with a peak of 37 papers in 2015. Almost 70% of the papers are written by authors in academia. InSAR is used (i) for landslide back analysis (3% of the papers); (ii) for landslide characterization (40% of the papers); (iii) as input for landslide models (7% of the papers); (iv) to update landslide inventories (15% of the papers); (v) for landslide mapping (32% of the papers), and (vi) for monitoring (3% of the papers). Sixty-eight percent of the authors validated the satellite results with ground information or other remote sensing data. Although well-known limitations exist, this bibliographic overview confirms that InSAR is a consolidated tool for many landslide-related applications.

Validation of Pleiades Tri-Stereo DSM in Urban Areas

10.20944/preprints201801.0030.v1 ◽

2018 ◽

Author(s):

Manolis Panagiotakis ◽

Nektarios Chrysoulakis ◽

Vasiliki Charalampopoulou ◽

Dimitris Poursanidis

Keyword(s):

Remote Sensing ◽

Urban Areas ◽

Relevant Literature ◽

Simulation Models ◽

Cost Effective ◽

Stereo Images ◽

Cost Effective Approach ◽

Spatial Coverage ◽

Temporal Coverage

A very high-resolution DSM covering an area of 400km2 over the Athens Metropolitan Area has been produced using Pleiades 1B 0,5m panchromatic tri-stereo images. Applied Remote Sensing and Photogrammetry tools have been used resulted in a 1x1m DSM over the study area. DSM accuracy has been evaluated by comparison with measured elevations with D-GPS and a reference DSM provided by the National Cadaster & Mapping Agency S.A. In addition, different combinations of stereo images have been prepared for further exploitation of the quality of the produced DSM by stereo vs. tri-stereo images. Results show that the produced by the tri-stereo images DSM has an RMSE of 1.17m in elevation (z), which is among the best reported in the relevant literature. Stereo based DSMs from the same sensor have worst performance to this end. Satellite Remote Sensing (SRS) based DSMs over urban areas provide the best cost-effective approach in comparison to airborne-based datasets due to high spatial coverage, lower cost and high temporal coverage. Pleiades-based high-quality DSM products can serve the domains of urban planning/climate, hydrological modelling and natural hazards, as major input for simulation models and morphological analysis at local scale.

Bridge monitoring and deformation time-series analysis by high-resolution Multi-Temporal SAR Interferometry (MT-InSAR)

10.5194/egusphere-egu21-15147 ◽

2021 ◽

Author(s):

Valerio Gagliardi ◽

Luca Bianchini Ciampoli ◽

Amir Alani ◽

Fabio Tosti ◽

Andrea Benedetto

Keyword(s):

Remote Sensing ◽

Time Series ◽

High Resolution ◽

Health Monitoring ◽

Space Agency ◽

Multi Temporal ◽

Italian Space Agency ◽

Non Destructive

Multi-temporal Interferometric Synthetic Aperture Radar (InSAR) is a space-borne monitoring technique capable of detecting cumulative surface displacements with millimeter accuracy in the Line of Sight (LOS) of the radar sensor [1-3]. Several developments in the processing methods and the increasing availability of SAR datasets from different satellite missions, have proven the viability of this technique in the near-real-time assessment of bridges and the health monitoring of transport infrastructures [2-4].This research aims to demonstrate the potential of satellite-based remote sensing techniques as an innovative health-monitoring method for structural assessment of bridges and the prevention of damages by structural subsidence, using high-resolution SAR datasets integrated with complementary Ground-Based (GB) Non-Destructive Testing (NDT) techniques. To this purpose, high-resolution COSMO&#8208;SkyMed (CSK) products provided by the Italian Space Agency (ASI) were acquired and processed.In particular, a multi-temporal InSAR analysis was developed to identify and monitor the structural displacements of the Rochester Bridge, located in Rochester, Kent, UK. To this extent, a clustering operation is realised to collect the identified Persistent Scatterers (PSs) over the structural elements of the bridge (i.e., bridge piers and arcs). Furthermore, several sub-clusters with a comparable deformation trend were identified and located over the bridge elements. This operation paves the way for an automatisation of the process through a Machine Learning (ML) clustering algorithms to assign each PS data-point to specific groups, based on the structural element type and the trend of seasonal deformation time-series.The outcomes of this study demonstrate how multi-temporal InSAR remote sensing techniques can be synergistically applied to complement non-destructive ground-based analyses, paving the way for future integrated methodologies in the monitoring of infrastructure assets.Acknowledgments: The authors want to acknowledge the Italian Space Agency (ASI) for providing the COSMO-SkyMed Products&#174; (&#169;ASI, 2017-2019),&#160; in the framework of the ASI-Open Call Project &#8220;MoTIB, ID 742&#8221; accepted by ASI. In addition, the authors would like to acknowledge the Rochester Bridge Trust for facilitating and supporting this research. This research is supported by the Italian Ministry of Education, University and Research under the National Project &#8220;EXTRA TN&#8221;, PRIN 2017, Prot. 20179BP4SM.References[1] Alani A. M., Tosti F., Bianchini Ciampoli L., Gagliardi V., Benedetto A., Integration of GPR and InSAR methods for the health monitoring of masonry arch bridges. NDT&E International. (2020)[2] Gagliardi V., Bianchini Ciampoli L., D'Amico F., Alani A. M., Tosti F., Battagliere M. L., Benedetto A., Bridge monitoring and assessment by high-resolution satellite remote sensing technologies, Proc. SPIE 11525, SPIE Future Sensing Technologies. 2020. doi: 10.1117/12.2579700[3] Selvakumaran, S., Plank, S., Gei&#223;, C., Rossi, C., Middleton, C. (2018). Remote monitoring to predict bridge scour failure using Interferometric Synthetic Aperture Radar (InSAR) stacking techniques, Int. J. .Appl. Earth Obs. and Geoinf. 73, 463-470.[4] Qin X, Liao M., Zhang L., & Yang M., Structural Health and Stability Assessment of High-Speed Railways via Thermal Dilation Mapping with Time-Series InSAR Analysis. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing

Linking Remote Sensing and Geodiversity and Their Traits Relevant to Biodiversity—Part I: Soil Characteristics

Remote Sensing ◽

10.3390/rs11202356 ◽

2019 ◽

Vol 11 (20) ◽

pp. 2356 ◽

Cited By ~ 11

Author(s):

Angela Lausch ◽

Jussi Baade ◽

Lutz Bannehr ◽

Erik Borg ◽

Jan Bumberger ◽

...

Keyword(s):

Remote Sensing ◽

Soil Moisture ◽

Cost Effective ◽

Global Scale ◽

Soil Characteristics ◽

Monitoring Methods ◽

In Situ Techniques ◽

The Face ◽

Remote Sensing Techniques

In the face of rapid global change it is imperative to preserve geodiversity for the overall conservation of biodiversity. Geodiversity is important for understanding complex biogeochemical and physical processes and is directly and indirectly linked to biodiversity on all scales of ecosystem organization. Despite the great importance of geodiversity, there is a lack of suitable monitoring methods. Compared to conventional in-situ techniques, remote sensing (RS) techniques provide a pathway towards cost-effective, increasingly more available, comprehensive, and repeatable, as well as standardized monitoring of continuous geodiversity on the local to global scale. This paper gives an overview of the state-of-the-art approaches for monitoring soil characteristics and soil moisture with unmanned aerial vehicles (UAV) and air- and spaceborne remote sensing techniques. Initially, the definitions for geodiversity along with its five essential characteristics are provided, with an explanation for the latter. Then, the approaches of spectral traits (ST) and spectral trait variations (STV) to record geodiversity using RS are defined. LiDAR (light detection and ranging), thermal and microwave sensors, multispectral, and hyperspectral RS technologies to monitor soil characteristics and soil moisture are also presented. Furthermore, the paper discusses current and future satellite-borne sensors and missions as well as existing data products. Due to the prospects and limitations of the characteristics of different RS sensors, only specific geotraits and geodiversity characteristics can be recorded. The paper provides an overview of those geotraits.

Rapid Land Subsidence in Tianjin, China Derived from Continuous GPS Observations (2010–2019)

Proceedings of the International Association of Hydrological Sciences ◽

10.5194/piahs-382-241-2020 ◽

2020 ◽

Vol 382 ◽

pp. 241-247

Author(s):

Ruibin Zhao ◽

Guoquan Wang ◽

Xiao Yu ◽

Xiaohan Sun ◽

Yan Bao ◽

...

Keyword(s):

Remote Sensing ◽

Land Subsidence ◽

Ground Truth ◽

Hebei Province ◽

Synthetic Aperture ◽

Continuous Gps ◽

Gps Observations ◽

Regional Reference

Abstract. We have delineated ten years of urban subsidence derived from continuous GPS stations operated by the Crustal Movement Observational Network of China (CMONOC) within and adjacent to the municipality of Tianjin. A method for obtaining accurate site velocities with respect to a stable regional reference frame is described. CMONOC stations in Jizhou (JIXN) and Baodi (TJBD) districts recorded minor subsidence of approximately 1 to 2 mm yr−1 during the period from 2010 to 2019. One station in Wuqing (TJWQ) district and one station in Binhai (TJBH) district recorded steady subsidence of approximately 5 and 2 cm yr−1 from 2010 to 2019, respectively. One station in Cangzhou (HECX) of Hebei Province, adjacent to Tianjin, recorded steady subsidence of approximately 2.4 cm yr−1 during 2010–2014 and more rapid subsidence of 4 cm yr−1 since 2015. TJWQ recorded the most rapid land subsidence and the most significant seasonal ground oscillations (uplift and subsidence) among these five stations. This study indicates that subsidence rates in Tianjin vary significantly in space and time. Particular attention should be paid, therefore, to extrapolate or infer a rate of subsidence for an area on the basis of a subsidence rate obtained from previous GPS observations or proximal GPS sites. The subsidence time series presented in this study provide reliable “ground truth” and constraints for calibrating or validating subsidence estimations from numerical modeling and repeated surveys using other remote sensing techniques, such as Interferometric Synthetic Aperture Radar (InSAR).

Remote Sensing Techniques for Soil Organic Carbon Estimation: A Review

Remote Sensing ◽

10.3390/rs11060676 ◽

2019 ◽

Vol 11 (6) ◽

pp. 676 ◽

Cited By ~ 31

Author(s):

Theodora Angelopoulou ◽

Nikolaos Tziolas ◽

Athanasios Balafoutis ◽

George Zalidis ◽

Dionysis Bochtis

Keyword(s):

Remote Sensing ◽

Organic Carbon ◽

Soil Organic Carbon ◽

Near Infrared ◽

Cost Effective ◽

Machine Learning Techniques ◽

Unmanned Aerial Systems ◽

Advantages And Disadvantages ◽

Aerial Systems

Towards the need for sustainable development, remote sensing (RS) techniques in the Visible-Near Infrared–Shortwave Infrared (VNIR–SWIR, 400–2500 nm) region could assist in a more direct, cost-effective and rapid manner to estimate important indicators for soil monitoring purposes. Soil reflectance spectroscopy has been applied in various domains apart from laboratory conditions, e.g., sensors mounted on satellites, aircrafts and Unmanned Aerial Systems. The aim of this review is to illustrate the research made for soil organic carbon estimation, with the use of RS techniques, reporting the methodology and results of each study. It also aims to provide a comprehensive introduction in soil spectroscopy for those who are less conversant with the subject. In total, 28 journal articles were selected and further analysed. It was observed that prediction accuracy reduces from Unmanned Aerial Systems (UASs) to satellite platforms, though advances in machine learning techniques could further assist in the generation of better calibration models. There are some challenges concerning atmospheric, radiometric and geometric corrections, vegetation cover, soil moisture and roughness that still need to be addressed. The advantages and disadvantages of each approach are highlighted and future considerations are also discussed at the end.

Vegetation indices mapping for Bhiwani district of Haryana (India) through LANDSAT-7ETM+ and remote sensing techniques

Journal of Applied and Natural Science ◽

10.31018/jans.v7i2.699 ◽

2015 ◽

Vol 7 (2) ◽

pp. 874-879 ◽

Cited By ~ 5

Author(s):

A. Bala ◽

K. S. Rawat ◽

A. Misra ◽

A. Srivastava

Keyword(s):

Remote Sensing ◽

Vegetation Indices ◽

Condition Index ◽

Wheat Crop ◽

Agricultural Planning ◽

Vegetation Condition Index ◽

Regional Basis ◽

Vegetation Health ◽

Temporal Coverage

This study describes the VIs Vegetation Condition Index in term of vegetation health of wheat crop; with help of LANDSAT-7ETM+ data based NDVI and LAI for Bhiwani District of Haryana states (India) and gave the spatial development pattern of wheat crop in year 2005 over the study area of India. NDVI is found to vary from 0.3 to 0.8. In northern and southern parts of study area NDVI varied from 0.6 to 0.7 but in western part of Bhiwani showed NDVI 0.2 to 0.4 due to fertility of soil and well canal destitution. LAI showed variation from 1 to 6 accordingto the health of crop as the same manner of NDVI because LAI VI is NDVI dependent only change the manner of representation of vegetation health, due to this fact relation curve (r2=) between NDVI and LAI of four different growing date of sates are in successively increasing order 0.509, 0.563, 0.577 and 0.719. The study reveals that VIs can be mapped with LANDSAT-7ETM+ through remote sensing, which can be further used for many studies like crop yield or estimating evaptranspiration on regional basis for water management because satellite observations provide better spatial and temporal coverage, the VIs based system will provide efficient tools for monitoring health of crop for improvement of agricultural planning. VIs based monitoring will serve as a prototype in the other parts of the world where ground observations are limited or not available.