Long term observation of crustal deformation in NE-Italy

2020 ◽  
Author(s):  
Carla Braitenberg ◽  
Barbara Grillo ◽  
Alberto Pastorutti ◽  
Tommaso Pivetta
Keyword(s):  
Time Series ◽  
Crustal Deformation ◽  
Surface Deformation ◽  
Earth Tide ◽  
Atmospheric Effects ◽  
Transfer Of Knowledge ◽  
Long Time Series ◽  
Ne Italy ◽  
Long Time

<p>The long term monitoring of crustal deformation in NE-Italy derives from tilt and strainmeter observations since 1960. The stations have been maintained by three generations of scientists starting with the geodesist Antonio Marussi, keeping the instrumentation active and up to date. The decade-long time series have given observations of rare events, as the free oscillations recorded by the largest earthquakes ever recorded (Chile 1960, Sumatra 2004, Tohoku 2011) and climatic extreme events leading to extremely intense rainfalls that generate underground flooding and surface deformation (Braitenberg et al., 2019; Braitenberg, 2018). The stations have the characteristic of being representative of geodetic monitoring in karst geologic formation, that they are placed in a seismically active area which has experienced a magnitude M 6.4 earthquake in the past (1976 Gemona), and that they are influenced by the ocean loading deformation of the Adriatic Sea. The seismic area implies that the strain accumulation is an ongoing process, presently activating the elastic energy of the next earthquake. We show some relevant observations, which could hardly have been caught without such a long time series. Between 1973 and 1976 the long base horizontal pendulums of the Grotta Gigante cave gave episodic disturbances, that seized 6 months after the Gemona main shock. The hydrology of the karst is made of an underground channel system that is completely flooded during extreme rainfall and is pressurized close to simultaneously over a distance of 30 km, leading to an observable uplift and deformation of the surface (Braitenberg et al., 2019). It has been possible to extract and model this type of deformation.</p><p>The tilt and strainmeters have high accuracies and precision in the detection of crustal deformation, with the drawback to be point measurements. InSAR acquisitions cover thousands of points on the surface, but with coarser accuracy. One major problem is in the correction of atmospheric effects in the InSAR signal, which produces apparent movement in the direction of Line of Sight, uncorrelated to the real soil movement. Our present research objective is the transfer of knowledge from the signals known in the tilt and strainmeter observations to the detection of these signals with InSAR. </p><p> </p><p>Braitenberg C. (2018). The deforming and rotating Earth - A review of the 18th International Symposium on Geodynamics and Earth Tide, Trieste 2016 , Geodesy and Geodynamics, 187-196, doi::10.1016/j.geog.2018.03.003 .</p><p>Braitenberg C., Pivetta T., Barbolla D. F., Gabrovsek F., Devoti R., Nagy I. (2019). Terrain uplift due to natural hydrologic overpressure in karstic conduits. Scientific Reports, 9:3934, 1-10, doi.:10.1038/s41598-019-38814-1.</p>

The tilt and strainmeter network of NE Italy: multi-decadal observations of crustal deformation as ground truth for DinSAR.

2021 ◽  
Author(s):  
Carla Braitenberg ◽  
Alberto Pastorutti ◽  
Barbara Grillo ◽  
Marco Bartola
Keyword(s):  
Crustal Deformation ◽  
Surface Deformation ◽  
Spatial Scales ◽  
Earth Tide ◽  
Ground Truth ◽  
Atmospheric Effects ◽  
Megathrust Earthquakes ◽  
Ne Italy ◽  
Applied Geophysics ◽  
Fluid Diffusion

<p>Decade-long series of tilt- and strain-meter observations in NE Italy allow monitoring the crustal deformation from short transient to long-term phenomena. These recordings, some of them started in 1960, are generated by sources spanning a wide spectrum of spatial scales, such as sudden underground flooding due to extreme rainfall [1, 2], years-long fluid diffusion transients due to fault behavior [3], the free oscillation arising from megathrust earthquakes (e.g. Chile 1960, Sumatra 2004, Tohoku 2011).<br>The instrumental sites lie on karst formations, in an area of continental collision and active seismicity, the northeastern portion of the Adria microplate, where the south-directed thrusts of the Alpine system merge with the NW-SE transpressive regime of the External Dinarides. Measurements include the ongoing interseismic strain accumulation processes, including the peculiar observation of episodic disturbances and southward tilting in the three years preceding the 1976 Mw6.4 Friuli earthquake [4].<br><br>The channel systems of Karst hydrology, which undergo complete flooding and overpressure buildup in extremely short time spans (e.g. near-simultaneous flooding over a distance of 30 km) result in observable surface deformation and a change in the gravity field. Tilt time series allow to extract and model this type of hydrology-forced uplift and associated deformation [2,5].<br><br>Tilt- and strain-meters allow for accuracy and precision in measuring crustal deformation, to a level which space-borne geodesy cannot provide. The main drawback, however, is that only point measurements are provided, in locations where stations could be set up.<br>On the other hand, the thousands of points on the surface that DInSAR can provide are affected by coarser accuracy and influenced by atmospheric effects - resulting in LoS displacements uncorrelated to the actual surface deformations. We aim at enabling the transfer of knowledge from tilt- and strain-meters observations to DInSAR-derived data, thus allowing a first assessment of ground-truth constrained displacement models.<br><br>[1] Braitenberg C. (2018). The deforming and rotating Earth - A review of the 18th International Symposium on Geodynamics and Earth Tide, Trieste 2016 , Geodesy and Geodynamics, 187-196, doi::10.1016/j.geog.2018.03.003</p><p>[2] Braitenberg C., Pivetta T., Barbolla D. F., Gabrovsek F., Devoti R., Nagy I. (2019). Terrain uplift due to natural hydrologic overpressure in karstic conduits. Scientific Reports, 9:3934, 1-10, doi.:10.1038/s41598-019-38814-1</p><p>[3] Rossi, G., Fabris, P. & Zuliani, D. Overpressure and Fluid Diffusion Causing Non-hydrological Transient GNSS Displacements. Pure Appl. Geophys. 175, 1869–1888 (2018). https://doi.org/10.1007/s00024-017-1712-x</p><p>[4] Dragoni M., Bonafede M., and Boschi E. (1985). On the interpretation of slow ground deformation precursory to the 1976 Friuli earthquake. Pure and Applied Geophysics 122, 781–792. doi:10.1007/978-3-0348-6245-5_3</p><p>[5] Grillo B., Braitenberg C., Nagy I., Devoti R., Zuliani D., Fabris P. (2018). Cansiglio Karst-Plateau: 10 years of geodetic-hydrological observations in seismically active northeast Italy. Pure and Applied Geophysics, 175, 5, 1765-1781, doi:10.1007/s00024-018-1860-7.</p><p> </p>

scholarly journals Sea Ice Concentration Products over Polar Regions with Chinese FY3C/MWRI Data

2021 ◽  
Vol 13 (11) ◽  
pp. 2174
Author(s):  
Lijian Shi ◽  
Sen Liu ◽  
Yingni Shi ◽  
Xue Ao ◽  
Bin Zou ◽  
...  
Keyword(s):  
Time Series ◽  
Sea Ice ◽  
Ocean Circulation ◽  
The Arctic ◽  
Retrieval Algorithm ◽  
Atmospheric Effects ◽  
Observation Data ◽  
Long Time Series ◽  
Ice Concentration ◽  
Long Time

Polar sea ice affects atmospheric and ocean circulation and plays an important role in global climate change. Long time series sea ice concentrations (SIC) are an important parameter for climate research. This study presents an SIC retrieval algorithm based on brightness temperature (Tb) data from the FY3C Microwave Radiation Imager (MWRI) over the polar region. With the Tb data of Special Sensor Microwave Imager/Sounder (SSMIS) as a reference, monthly calibration models were established based on time–space matching and linear regression. After calibration, the correlation between the Tb of F17/SSMIS and FY3C/MWRI at different channels was improved. Then, SIC products over the Arctic and Antarctic in 2016–2019 were retrieved with the NASA team (NT) method. Atmospheric effects were reduced using two weather filters and a sea ice mask. A minimum ice concentration array used in the procedure reduced the land-to-ocean spillover effect. Compared with the SIC product of National Snow and Ice Data Center (NSIDC), the average relative difference of sea ice extent of the Arctic and Antarctic was found to be acceptable, with values of −0.27 ± 1.85 and 0.53 ± 1.50, respectively. To decrease the SIC error with fixed tie points (FTPs), the SIC was retrieved by the NT method with dynamic tie points (DTPs) based on the original Tb of FY3C/MWRI. The different SIC products were evaluated with ship observation data, synthetic aperture radar (SAR) sea ice cover products, and the Round Robin Data Package (RRDP). In comparison with the ship observation data, the SIC bias of FY3C with DTP is 4% and is much better than that of FY3C with FTP (9%). Evaluation results with SAR SIC data and closed ice data from RRDP show a similar trend between FY3C SIC with FTPs and FY3C SIC with DTPs. Using DTPs to present the Tb seasonal change of different types of sea ice improved the SIC accuracy, especially for the sea ice melting season. This study lays a foundation for the release of long time series operational SIC products with Chinese FY3 series satellites.

scholarly journals Long Time Series Land Cover Classification in China from 1982 to 2015 Based on Bi-LSTM Deep Learning

2019 ◽  
Vol 11 (14) ◽  
pp. 1639 ◽  
Author(s):  
Haoyu Wang ◽  
Xiang Zhao ◽  
Xin Zhang ◽  
Donghai Wu ◽  
Xiaozheng Du
Keyword(s):  
Remote Sensing ◽  
Time Series ◽  
Land Cover ◽  
Land Cover Classification ◽  
Series Data ◽  
Long Time Series ◽  
Quantitative Remote Sensing ◽  
Long Time ◽  
Year 2000

Land cover classification data have a very important practical application value, and long time series land cover classification datasets are of great significance studying environmental changes, urban changes, land resource surveys, hydrology and ecology. At present, the starting point of continuous land cover classification products for many years is mostly after the year 2000, and there is a lack of long-term continuously annual land cover classification products before 2000. In this study, a long time series classification data extraction model is established using a bidirectional long-term and short-term memory network (Bi-LSTM). In the model, quantitative remote sensing products combined with DEM, nighttime lighting data, and latitude and longitude elevation data were used. We applied this model in China and obtained China’s 1982–2017 0.05° land cover classification product. The accuracy assessment results of the test data show that the overall accuracy is 84.2% and that the accuracies of wetland, water, glacier, tundra, city and bare soil reach 92.1%, 92.0%, 94.3%, 94.6% and 92.4%, respectively. For the first time, this study used a variety of long time series data, especially quantitative remote sensing products, for the classification of features. At the same time, it also acquired long time series land cover classification products, including those from the year 2000. This study provides new ideas for the establishment of higher-resolution long time series land cover classification products.

scholarly journals Long Time-Series Mapping and Change Detection of Coastal Zone Land Use Based on Google Earth Engine and Multi-Source Data Fusion

2021 ◽  
Vol 14 (1) ◽  
pp. 1 ◽  
Author(s):  
Dong Chen ◽  
Yafei Wang ◽  
Zhenyu Shen ◽  
Jinfeng Liao ◽  
Jiezhi Chen ◽  
...  
Keyword(s):  
Land Use ◽  
Time Series ◽  
Change Detection ◽  
Coastal Zone ◽  
Google Earth ◽  
Coastal Zones ◽  
Long Time Series ◽  
Coastal Aquaculture ◽  
Long Time

Human activities along with climate change have unsustainably changed the land use in coastal zones. This has increased demands and challenges in mapping and change detection of coastal zone land use over long-term periods. Taking the Bohai rim coastal area of China as an example, in this study we proposed a method for the long time-series mapping and change detection of coastal zone land use based on Google Earth Engine (GEE) and multi-source data fusion. To fully consider the characteristics of the coastal zone, we established a land-use function classification system, consisting of cropland, coastal aquaculture ponds (saltern), urban land, rural settlement, other construction lands, forest, grassland, seawater, inland fresh-waters, tidal flats, and unused land. We then applied the random forest algorithm, the optimal classification method using spatial morphology and temporal change logic to map the long-term annual time series and detect changes in the Bohai rim coastal area from 1987 to 2020. Validation shows an overall acceptable average accuracy of 82.30% (76.70–85.60%). Results show that cropland in this region decreased sharply from 1987 (53.97%) to 2020 (37.41%). The lost cropland was mainly transformed into rural settlements, cities, and construction land (port infrastructure). We observed a continuous increase in the reclamation with a stable increase at the beginning followed by a rapid increase from 2003 and a stable intermediate level increase from 2013. We also observed a significant increase in coastal aquaculture ponds (saltern) starting from 1995. Through this case study, we demonstrated the strength of the proposed methods for long time-series mapping and change detection for coastal zones, and these methods support the sustainable monitoring and management of the coastal zone.

scholarly journals Performance stability of the MODIS and VIIRS LAI algorithms inferred from analysis of long time series of products

2021 ◽  
Vol 260 ◽  
pp. 112438
Author(s):  
Kai Yan ◽  
Jiabin Pu ◽  
Taejin Park ◽  
Baodong Xu ◽  
Yelu Zeng ◽  
...  
Keyword(s):  
Time Series ◽  
Long Time Series ◽  
Long Time

Cloud Properties over the North Slope of Alaska: Identifying the Prevailing Meteorological Regimes

2012 ◽  
Vol 25 (23) ◽  
pp. 8238-8258 ◽  
Author(s):  
Johannes Mülmenstädt ◽  
Dan Lubin ◽  
Lynn M. Russell ◽  
Andrew M. Vogelmann
Keyword(s):  
Time Series ◽  
Climate Model ◽  
North Slope ◽  
Test Cases ◽  
Synoptic Scale ◽  
Long Time Series ◽  
The North ◽  
Cloud Properties ◽  
North Slope Of Alaska ◽  
Long Time

Abstract Long time series of Arctic atmospheric measurements are assembled into meteorological categories that can serve as test cases for climate model evaluation. The meteorological categories are established by applying an objective k-means clustering algorithm to 11 years of standard surface-meteorological observations collected from 1 January 2000 to 31 December 2010 at the North Slope of Alaska (NSA) site of the U.S. Department of Energy Atmospheric Radiation Measurement Program (ARM). Four meteorological categories emerge. These meteorological categories constitute the first classification by meteorological regime of a long time series of Arctic meteorological conditions. The synoptic-scale patterns associated with each category, which include well-known synoptic features such as the Aleutian low and Beaufort Sea high, are used to explain the conditions at the NSA site. Cloud properties, which are not used as inputs to the k-means clustering, are found to differ significantly between the regimes and are also well explained by the synoptic-scale influences in each regime. Since the data available at the ARM NSA site include a wealth of cloud observations, this classification is well suited for model–observation comparison studies. Each category comprises an ensemble of test cases covering a representative range in variables describing atmospheric structure, moisture content, and cloud properties. This classification is offered as a complement to standard case-study evaluation of climate model parameterizations, in which models are compared against limited realizations of the Earth–atmosphere system (e.g., from detailed aircraft measurements).

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